THE EFFECT OF MARKET RISK MANAGEMENT ON COMPANY VALUE AMONG THE FIRMS LISTED AT THE NAIROBI SECURITIES EXCHANGE

By JOSEPHINE ACHIENG ABIERO

A RESEARCH PROJECT SUBMITTED IN PARTIAL FULIFILMENT OF THE REQUIREMENTS FOR THE AWARD OF MASTER OF BUSINESS ADMINISTRATION DEGREE, SCHOOL OF BUSINESS, UNIVERSITY OF NAIROBI

NOVEMBER, 2012 I DECLARATION

I declare that the work presented here is my original work and has not been presented for a degree or any other examination in any University except where acknowledged.

\V-v\' . Signed: Date:------

Josephine Achieng Abiero D61/61067/2011

This project has been submitted for examination with my approval as a university supervisor.

Signed: Date:......

Mr. Otieno Luther Odhiambo Lecturer, Department of Finance and Accounting University of Nairobi

11 DEDICATION

I dedicate this project to my family for their support and encouragement throughout the period. Their love, care and encouragement inspired me to achieve this.

u ACKNOWLEDGEMENTS

First and foremost I thank the almighty God for giving the grace for sound health to complete my studies.

I appreciate and thank my husband Alfred for being there for me, encouraging and pushing me to exploit my potential whereas meeting my financial needs for the MBA program. 1 must appreciate my children Tina, Lydia, Emily, Marvin, Eddie and Mich for their sacrifice and patience in the whole period I was undertaking this course.

Finally I wish to thank my supervisor Luther Otieno who has been the ideal supervisor. His astute advice, insightful criticisms, and patient encouragement aided the writing of this thesis in innumerable ways.

While I may not be able to mention and recognize the effort of others who contributed in a way or the other I take this opportunity to thank you all. May the Lord bless you in abundance.

IV ABSTRACT

This paper investigates the effect of market risk management on firm value with specific reference to those listed at the NSE. Management of market risk is of essence at the NSE as investors have put huge sums of their capital to get value in return. Some of the components of market risk are foreign exchange risk, commodity risk and exchange rate risk.

Theories based on market imperfection imply that hedging should increase the firm’s market value. To test this, views have been sought from CEOS who are charged with the responsibility of initiating risk management in their respective companies.

The study sought to know from the CEOs of the listed companies their view of the effect of market risk management on firm value with use of questionnaires as a research instrument. Questionnaires were designed to test on usage and effectiveness of the various market risk instruments used to hedge.

The objective of the study was to determine the effect of market risk management on the value of the firm among companies listed at the NSE.

The findings revealed the CEOs used commodity risk, foreign exchange and interest rate instruments to hedge risk and reported their effectiveness to an extent but the value added to firms on their usage could not be determined except for foreign exchange instruments usage.

The researcher recommends that CEOs and the board should infuse a risk culture in the organization and this integrated in performance goals and compensation decisions to achieve value from risk management activities.

vi TABLE OF CONTENTS

DECLARATION...... ii DEDICATION...... ii ACKNOWLEDGEMENTS...... iv ABSTRACT...... vi TABLE OF CONTENTS...... vii LIST OF TABLES...... x LIST OF FIGURES...... xi

CHAPTER O N E...... 2 INTRODUCTION...... 2 1.1 Background to the Study...... 2 1.1.1 Market Risk Management and Company Value...... 3 1.1.2 Risk Management...... 4 1.1.3 Corporate Managers Challenge...... 5 1.1.4 Nairobi Securities Exchange...... 6 1.2 Research problem...... 7 1.3 Objective of the Study...... 8 1.4 Value of the Study...... 9

CHAPTER T W O ...... 10 LITERATURE REVIEW ...... 10 2.1 Introduction...... 10 2.2 Corporate financial risk management...... 10 2.2.1 CEO and Risk Management...... 11 2.2.2 Risk Irrelevance Proposition...... 12 2.2.3 Risk Relevance Proposition...... 13 2.3 Market risk types and Management Approaches...... 15 2.3.1 Equity price risk...... 15 2.3.2 Interest rate risk...... 16 2.3.3 Commodity price risk...... 16

vii 2.3.4 Foreign exchange risk...... 18 2.4 Conceptual Model...... 20

2.5 Summary...... 21

CHAPTER THREE...... 22 RESEARCH METHODOLOGY...... 22 3.1 Introduction...... 22 3.2 Research design...... 22 3.3 Population...... 22 3.4 Data collection Method...... 22 3.5 Data Analysis...... 23

CHAPTER FOUR...... 24 DATA ANALYSIS AND INTERPRETATION OF RESULTS...... 24 4.1 Introduction...... 24 4.2 Commodity Risk Instruments Usage...... 25 4.3 Effectiveness in hedging price risks...... 27 4.4 Foreign exchange risk instruments usage...... 28 4.5 Effectiveness in hedging foreign exchange risks...... 29 4.6 Interest rate risk instruments usage in your firm...... 31 4.7 Effectiveness in hedging interest rate risks...... 32 4.8 Conclusions...... 33

CHAPTER FIVE...... 35 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS...... 35 5.1 Introduction...... 35 5.2 Summary...... 35 5.2 Conclusions...... 36 5.3 Recommendations...... 37 5.4 Suggestion for further studies...... 38 5.5 Limitations of the study...... 38

viii REFERENCES...... 39

APPENDICES...... 45 APPENDIX I: COMPANIES LISTED AT THE NSE...... 45 APPENDIX II: QUESTIONNAIRE...... 49 APPENDIX III...... 55 APPENDIX IV...... 69 APPENDIX V ...... 75 APPENDIX VI...... 85 APPENDIX V II...... 87

IX LIST OF TABLES

Table 4.1: Firm categorization at the NSE...... 24 Table 4.2: Level of usage of the following commodity risk instruments in your firm 25 Table 4.3: Level of agreement in their effectiveness in hedging price risks...... 27 Table 4.4: Level of usage of the following Foreign Exchange Risk Instruments in the Firm...... 28 Table 4.5: The level of agreement in the effectiveness of these instruments in hedging foreign exchange risks...... 29 Table 4.7: Level of agreement in their effectiveness in hedging interest rate risks.... 32 Table 4.6: Level Of Usage of the following Interest rate risk instruments in your firm ...... 31

x LIST OF FIGURES

Figure 2.1: Conceptual Model 20

xi ABBREVIATIONS

CAPM - Capital Assets Pricing Model CEOs - Chief Executive Officers CFO - Chief Finance Officer E&P - Energy and power ERM - Enterprise Risk Management FCDs - Foreign cash deposits FX - Foreign exchange ISDA - International Swaps Dealers Association NPV - Net present value OTC - Over the counter

SEC - Securities Exchange Commission

Xll CHAPTER ONE INTRODUCTION

1.1 Background to the Study As the concept of risk management gains prominence globally, Kenyan companies and regulators must not been left behind in this drive to enhance risk management practices in companies through the implementation of risk management. For example, in 2007, the Central Bank of Kenya introduced regulation requiring all banks to develop and implement an Enterprise Risk Management Framework in their institutions and in 2010, the Insurance Regulatory Authority also introduced similar regulations for insurance companies (CMA Website).From a regulator point of view, the main aim of requiring companies to implement ERM is mainly to protect stakeholders’ investments in such companies (Waweru & Kisaka, 2011). Some companies at the NSE practice some form of risk management and this is demonstrated in the companies’ by establishment of the Risk Manager and Risk officers’ positions who report directly to the Chief executive officers.

Market risk is generally managed with a short term focus where the effort to minimize losses if employed on a day to day basis. A number of metrics are used to help managers assess and manage their exposures. The metrics may include duration and convexity measures, value at risk etc.

Global financial markets have been very volatile in recent decades with large changes in commodity, foreign exchange, interest rates, and capital flows. Many developing countries Kenya being among them have had large exposures to these market risks. Depending on exports of commodities that are primary in nature to generate foreign exchange and importation of manufactured products has affected the foreign exchange reserves. The adverse movement in international commodity prices have affected the Kenyan economy greatly and therefore calls for market risk management. All these risks have played a role in raising the debt burdens and negatively affecting economic performance of the economy of many developing countries.

2 The challenge is that it gets harder to monitor market risk and to be totally transparent at the level of portfolio risk exposure. Evaluating the impact of market movements with respect to investment decisions is a real challenge in the investment management industry, but it's vital to keep investors' confidence in the market by the Chief executives of firms taking precautionary measures of managing risks.

1.1.1 Market Risk Management and Company Value Finance theory suggests that risk management can increase the value of the firm by addressing the so-called corporate “underinvestment problem.” The basic idea is that, by hedging financial risks with derivatives, companies reduce the variability of their cash flow, thereby ensuring they will have sufficient funds to undertake all promising projects. This idea is supported by a leading theoretical paper, Froot, Scharfstein, and Stein (1993), which demonstrated that when the costs of external capital include deadweight costs, companies that require outside financing will under invest when internal operating cash flows are low.

According to Pandey (2009), in the current financial theories, the value of a firm can be calculated by several methods. One of the most-used, most acclaimed methods is the Net Present Value (NPV) method. This method discounts the present and future cash flows of the company to a present value. The discount rate is defined as the rate of return of an average investment in the market with the same risk profile as the investment that is subject of the NPV method.

The Capital Asset Pricing Model (CAPM) can explain the height of the discount rate (see Treynor 1961,1962; Sharpe 1964; Lintner 1965; Mossin 1966). This model and the theory that comes along predicts that the expected return on a company’s stock or any other investment is dependent on two things: the difference between the (average) premium of the market as a whole and a risk-free investment and the investment’s Beta; the relationship between the return on the market and the return on the investment. Under this theory, risky investments should generate a higher expected return, to compensate for the riskiness.

3 From a NPV perspective, risk management theory indicates that risk management might enlarge the value of the firm in two ways: Free Cash Flows can become larger or the discount rate becomes lower.

The rise of the amount of free cash flows can occur in several ways: more money can be led to those investments that generate the highest return. Stability in cash flows due to risk management makes it possible to keep investments in place, instead of having to abandon these in case money is needed.

From the discussion thus far, we postulate that management of market risks will increase shareholders value through enhanced business performance and the reduction of the firms’ cost of capital. We further theorize that in the event of corporations successfully managing its market risks the benefits received from such effective execution will have a long-term positive impact in creating value for the corporations’ shareholders.

1.1.2 Risk Management The standard finance theory is that a firm should take on a project when it increases the wealth of shareholder in the firm; further more firms exist to take projects that shareholders could not do for themselves at the same cost. The finance theory allows us to find out when homemade risk management is not equivalent to risk management by the firm. This is the case whenever risk management by a firm affects firm value in a way that investors cannot mimic. For risk management to increase firm value, it must be more expensive to take a risk within the firm than to pay the capital markets to take it. Therefore, managers add value whenever the firm can earn a higher return than shareholders can earn for themselves. Financial risk management is the practice of creating economic value in a business by using financial instruments to manage exposure to risk. Examples of financial risks are credit risk, market risk, and their components such as foreign exchange risk, interest rate risk and inflation risk. Financial risk management requires identifying its sources, measuring it, and plans to address them. Management of financial risk management focuses on when and how to reduce a business risk exposure by using financial instruments.

4 In this study, the focus is market risk. Market risk is the risk that the value of an asset or portfolio will decrease due to the change in value of the market risk factors. The four standard market risk factors are stock prices, interest rates, foreign exchange rates, and commodity prices. The associated market risk includes equity risk, the risk that the share or stock index prices and/or their volatility will change; interest rate risk, the risk that interest rates and/or their volatility will change. The other components of market risk include currency risk, the risk that foreign exchange rates and/or their implied volatility will change; and commodity risk, the risk that the commodity prices and/or their implied volatility will change. Crouhy, Galai & Mark (2001). Volatility risk is the risk of a change of price of a portfolio as a result of changes in the volatility of a risk factor. It usually applies to portfolios of derivatives instruments, where the volatility of its underlying is a major influence of prices.

These risks are managed using appropriate financial instruments (derivatives) whose price depends on the volatility of a given financial asset, such as stock, currency, a commodity and interest rate. Examples of instruments useful in managing market risk include forward and futures contracts for commodities such as oil; options contracts for equities; and caps, floor and swaps for interest rates (Hull, 2005).

1.1.3 Corporate Managers Challenge Business is characteristically risky. The manager needs to identify the risks and make sure the identified risks are managed. A corporate manager major challenge is the need to deliver ever-increasing returns and value to their shareholders in the face of increasing risk. Corporations risk taking is based on two factors: the probability an adverse circumstance will come about and the cost of such adverse circumstance. A company’s performance is adversely affected by recessions, changes in commodity prices, interest rates and exchange rates, or adverse political developments influence negatively a company’s performance. The business is to decide whether the firm should protect itself against these risks. The evidence from developed economies is that senior management believe that superior risk management can create value for shareholders; though many of them are not sure how (The Economist Intelligence, 2001). The typical financial executive's view of the value of risk management in their

5 financial institution is based on the belief that risk management focuses on loss avoidance.

Risk management has evolved to address the strategic issue of optimization of return on risk. This is accompanied by statistical, mathematical, and financial techniques which-when actively applied-can aid an institution in producing disproportionately high returns on risk. Given that companies will have to make significant investments in their risk management system it is important determining whether such investment on risk management add value (David, 2004).

1.1.4 Nairobi Securities Exchange NSE was founded in 1954. Over the years the number of companies at the NSE has experienced slow growth over its entire existence since it was founded. The number stands at a 60 of which some have since been de-listed or suspended for non- compliance with the requirements of the exchange. Only 48 quoted companies have been in operation for a long time (Kobonyo & Ongore, 2011). The NSE is a forum for trading in stocks and bonds. Here, companies from across the spectrum of industry gather to raise the public capital that will allow them to fund their businesses so that they expand. The Nairobi Stock Exchange plays an important role in the economy of bringing the borrowers and lenders of money together at a low cost. Besides stocks, the Nairobi Securities Exchange (NSE) offers a platform for the issuance and trading of debt securities. The NSE is also growing its portfolio of information products and services. Kobonyo & Ongore (2011) asserts that the typical ownership identities at the NSE are by the government, foreigners, institutions, individual and diverse ownership forms. Firm performance is measured using; return on assets, return on equity and dividend yield.

In each of the listed companies, capital structure overrides company specific activities like capital budgeting decisions and dividend policy. Similarly accounting procedures apply to all the listed companies and management prudence is observed by all the quoted companies as it is one of the major requirements by CMA before a company is quoted and as long as a company remains quoted (Chebii, Kipchumba, & Wasike 2010). 6 The companies at the NSE are exposed to market risk and as reported by the NSE’s Chairman’s annual report of 2012, the NSE suffered a blow courtesy of global downturn caused by high international oil prices, fluctuations in exchange rate, inadequate rainfall and rising global prices.

NSE 20 share index reported a 27.7 percent decline and the all share index (NASI) reported a 30.6 percent decline from 98 points in 2010 to 68.03 points end of 2011.

Like in any other security market, investors’ at NSE want the manager to increase the value of the company and its current stock price and this can be done by risk managers taking care of the downside of risk through risk management.

As managers devise strategies of risk management they have to bear in mind that investors require a higher return for their investment for taking higher risks and they can eliminate most of their risk associated with a single stock by holding a well diversified portfolio. So they require a risk premium only for the risk they cannot eliminate through diversification. The managers can therefore only increase the value of the firm only if they can do something individual investors cannot do.

1.2 Research problem Appreciating risks and measuring performance is a crucial step to better managing and improving the performance of firms. Market risk has its components of foreign exchange risk, interest rate risk and inflation risk. The goal market risk management is to maximize shareholder value. Finance theory suggests that businesses facing large exposures to interest rates, exchange rates, or commodity prices can increase their market values by using derivative securities to manage their risk exposures. Such theory emphasize on the role of derivatives in reducing the variability of business cash flows and, subsequent reduction in costs associated with financial distress (Stulz, 1996). However, the corporate use of derivatives does not seem to correspond closely to the theory and is criticized. However, using derivatives is not always beneficial; a hedged position can become un-hedged at the worst times, inflicting substantial losses on those who mistakenly believe that their risk exposure is covered (Rajan, 2006).

7 In Kenya, market risk exposure is a real issue. An examination of annual reports of companies listed at NSE show that a number of them have had their value eroded because of market risk. Diffu (2011) in her study of the relationship between FX risk management and financial performance reports that the Kenya airways suffered losses end of 2009 financial year for failing to hedge its FX risk. It is therefore important to accumulate evidence that risk management increases firm value. Smithson (2005) add that one study provides fairly compelling evidence that the use of commodity price derivatives by commodity users increases share values; but studies of hedging by commodity producers provide no clear support for the argument that risk management adds value. At a minimum, whether hedging add value appears to depend on the types of risk to which a firm is exposed (Smithson, 2005). Modigliani and Miller (1958) prove through the arbitrage process that in a frictionless setting, risk is irrelevant and have no impact on the value of the firm. The invariance result proposition stands in sharp contrast to the prominence of risk management in practice, and the rapid growth in financial innovation (Feland 1998, Miller, 1986; Tufano, 2003). This study therefore seeks an answer to the question: Does the market risk management add value?

Whereas previous local studies have enumerated the various risk management strategies adopted by firms no study has focused on market risk and firm value. Mwangi (2003) conducted a survey on hedging practices against interest risk of commercial banks in Kenya, Muthinja (2008) carried out a survey of the hedging strategies adopted by Kenyan firms in managing transaction risk exposure in international trade and Kathure (2011) conducted a case study on Kenya Airways on the relationship between hedging strategies and financial performance. Hence one major gap identified is that of linking firm value and market risk management of firms at the NSE as value is of significance to the shareholders.

1.3 Objective of the Study To determine the effect of market risk management on the value of the firm among companies listed at the NSE.

8 1.4 Value of the Study This study adds to the existing literature and provides a better understanding on what value risk management is to firms as they flock the NSE to raise both debt and equity. CEO’s who have never viewed financial risk management as a tool for having an edge over their competitors will understand how these products and strategies work to reduce market risk within the context of the organization’s risk tolerance and objectives.

To the investors it will give information of the relation between management of market risk and firm value and since value is tied to the value of the share it will give them a chance to evaluate every aspect of a company before putting their stake in it. Regulators have an important role in assessing risk management systems and practices in organizations. The failure by institutions to appropriately identify, measure, and manage their risks has raised questions not only much about corporate governance but also about the adequacy of regulatory oversight of risk management systems and how the regulators oversee risk management at these institutions.

9 CHAPTER TWO LITERATURE REVIEW

2.1 Introduction This chapter presents a review of related literature. The specific areas covered in this chapter are risk management relevance proposition, risk management irrelevance proposition and risk management approaches.

2.2 Corporate financial risk management Many empirical studies have attempted to find support for different theories of corporate financial risk management. However most of them have failed to determine which theories are supported by empirical observation of corporate hedging and which are not (Karol, 2008).

If the market is perfect, managing market risk would have no value. In real world the financial market is imperfect and managing risk can directly affect the cash flow of the firm. Lookman (2004) classifies his oil price risk into primary risk and secondary risk to examine the relationship between firm value and risk management. He finds that energy and power companies who hedge primary risk are associated with higher firm value, in contrast with diversified companies with an E&P segment are associated with higher firm value. Jin and Jorion (2006) study the relation between hedging and firm value based on 119 U.S oil and gas producers from 1998 to 2001. Thinking about the endogeneity problem, they choose oil and gas industry in which firms differ in the hedging ratios. Contrary to previous research, they find that hedging does not affect market values.

The study of Dan, Gu and Xu (2005) is the first research aimed to uncover the relationship between hedging and firm value with oil and gas data in large Canadian oil and gas companies. In their nonlinear models , they use Tobin’s Q be proxy of firm value, use oil/gas deltas and hedge dummy to be proxy hedging, and like Allayaniss and Weston (2001) and Jin and Jorion (2006), they include five control variables. The evidence is that gas production hedging has significantly negative impact while gas reserve hedging has a significant positive impact. Nain (2004) 10 conducted a research with a sample of U.S. firms (548 derivatives users and 2,711 non-derivative users) with ex ante FX exposure (1997-99); and he concluded that FX risk management increases firm value as measured by Tobin’s Q if many competitors hedge. Allayannis, Lei and Miller (2009) researched on use of FX derivatives on firm value (Tobin’s Q) for 379 firms (1990-99) and found a significant positive premium for users of derivatives with FX exposures (positive but insignificant for firms with no exposure).

Macharia (2011) in his study of risk management strategies and returns by pension fund concludes that the use of the strategies have a positive impact on financial performance. A case study undertaken by Kathure (2011) on financial strategies adopted at Kenya airways concluded the company managed to tackle and reduce commodity risk, interest rate risk and volatility because of usage of risk instruments.

2.2.1 CEO and Risk Management The role of CEOs is must be risk compliant. Threats like contagions, terrorism, and scarce resources and competitive markets means that many companies face a more complex risk environment than ever before. Business risk environment has changed a lot in recent years. The effort to get more efficient in manufacturing, and how business operate overall mean that many supply chains now span the globe, and thus are more susceptible to global events than they were in the past (Cherkasky, 2012). Businesses must look at the specifics of their business systems, appreciate where the risks lie, and put in the appropriate alleviation strategies. The risks that top managers must manage include political risk, strategic risk, portfolio risk, financial risk, shipping risk, among other risks. Therefore, “Risk management is not just something for the risk area, again it has to be embedded and has to be across the organisation” (Willis 2004). In any case informed CEOs are aware that high return comes with high risk.

Top management including CEOs play a crucial role in ensuring firms’ strategies are successfully implemented (Penafort and Ponnu, 1996). For example, foreign exchange risk management require attention of top-level management (Ankrom, 1974). Accordingly, the financial risk management must be clear to CEOs so that CFOs feel 11 comfortable undertaking financial risk management for their firms. However, the cost of risk management approaches’ must not exceed the benefits. The focus of this study is financial risk management, which is the practice of creating economic value in a firm by using financial instruments to manage exposure to risk. Risk management can be qualitative and quantitative. However, the debate on whether managers should spend resources managing risk is unresolved.

2.2.2 Risk Irrelevance Proposition An aspect of modern finance theory is based on two pillars of efficient markets and diversification. Market efficiency means investors do not leave money on the table and that there is no free lunch because information is freely available and is discounted into prices with speed and accuracy and therefore one cannot benefit by trading on it.

Risk irrelevance proposition implies that firm managers should not hedge risks that investors can hedge for themselves at the same cost. Therefore, in a perfect market the firm cannot create value by hedging a risk when the price of bearing that risk within the firm is the same as the price of bearing it outside of the firm (Tapiero, 2004). This therefore renders risk managers functionless in their role of risk management and therefore financial risk management in the form of hedging activity cannot increase a firm’s value. Crouhy, Galai and Mark (2001) risk irrelevance proposition is on foundation of the famous analysis by Modigliani and Miller (1958), which shows that the value of a firm under the perfect capital market assumption is not changed merely by means of financial transactions.

The assumptions are made in a perfect market according to (Stulz,2003).There are no taxes, no transaction costs, no costs to writing and enforcing contracts, no restrictions on investment in securities, no differences in information across investors, and the investors takes prices as given because they are too small to affect prices. What this implies is whatever the firm can achieve even the individual investor can achieve on the same terms and conditions. This line of reasoning also lies behind the works of Sharpe (1964) and his capital asset pricing model (CAPM). In his work, Sharpe establishes that in a world with perfect capital markets, firms should not worry about 12 their specific (or idiosyncratic risk), and should base their investment decisions on their systematic (or beta) risk. All specific risks according to this theory are diversified away in the investor’s portfolios, and the diversification is costless.

Those opposed to risk management also cite the fact that “hedging by non bank corporations is a zero sum game and cannot increase earning or cash flows. Reducing volatility through hedging simply moves earnings and cash flows from one year to another” (Ralfe,1996 ).This simply means the prices of derivatives fully reflect their characteristics therefore their usage cannot add the value of the firm as they also have transaction costs.

Another additional reason against risk hedging as advanced by Crouhy, Galai & Mark 2001 is that it distracts management from their core business. Risk management requires certain skill and knowledge; it also requires infrastructure, data acquisition and data processing. In small and medium scale enterprises, management may lack the skills and time to accomplish these activities.

2.2.3 Risk Relevance Proposition In practice, financial markets are not likely to be perfect markets. This implies that firm managers are likely to have many opportunities to create value for shareholders using financial risk management (Lam, 2003). Therefore, managers should determine which risks are cheaper for the firm to manage than for the shareholders. A general rule of thumb, however, is that diversifiable risks are the best candidates for financial risk management (Tapiero, 2004).

Financial theory suggests that risk management can smooth variability in firm value (Bartram, Brown and Fehle, 2009). The notion that risks are redistributed to those better equipped to handle them is a norm in capital markets. Risk is reduced by hedging. Hedging involves buying and selling derivatives and these can decrease the variance of the expected value of the firm. Hedging removes the tails of the distribution as demonstrated by Stulz (1996).

13 Stulz (1996) identifies three major costs associated with higher variability in business earnings and cash flow. The costs include higher expected bankruptcy costs, higher expected payments to stakeholders and higher expected tax payments. If risk management can smooth variability on terms with stakeholders, it will increase firm value. As for tax payments, risk management works in the simple way as to manage taxable income so to ensure that the largest possible proportion of corporate income falls within the optimal period in the business cycle. The traditional approach to explain why corporations manage financial risks is claim that firms hedge in order to reduce the chance of default and to reduce the cost of financial distress (Smith and Stulz 1985). The arguments arise out of “market imperfections”, in that there are costs associated with financial distress. This suggests that smaller firms should have a greater incentive to hedge (Nance et al. 1993); but instead smaller firms tend to avoid hedging due to lack of capacity.

From agency theory managers seem to act in their own self interest. Since they may not be otherwise able to diversify the personal wealth that they have accumulated in their company, they have an incentive to reduce volatility (Stulz 1984 and Santomero 1995). The approach is consistent with the “agency theory” and implicitly assumes that managers find it costly to diversify their risk in the market. DeMarzo and Duffie (1992) also support the self interest argument, claiming that the observed result of a firm provides signals concerning the skills of its management.

Companies in favor of hedging try to do so to reduce the cost of capital and enhance their ability to finance growth according to the following studies; Froot, Schafstein and Stain 1993,1994; Stulz 1990;and Santomero 1995). Otherwise, in effect., a firm’s volatile cash flows might lead it to reject projects with positive net present values. The debt capacity of the firm may also be affected by high cash flow volatility.

Hedging also rests on the effect of a progressive tax rate (Santomero 1995, Smith and Stulz 1985 and Stulz, 1996).Volatile earnings induce higher taxation than stable earnings. This may be true but in countries where such incentives are not given the point does not hold as pointed out by Ralfe in his study of 1996. Berkman and

14 Bradburry (1996) support this claim that the New Zealand corporations are not subject to progressive tax.

2.3 Market risk types and Management Approaches Market risk reflects the degree to which changes in interest rates, foreign exchange rates, commodity prices, or equity prices can adversely affect an institution’s earnings or economic capital. For some firms market risk is typically synonymous with any of the risks depending on what risks they are exposed to. The various models of handling risks have risk identification; i.e. that potential risks are determined; risk assessment, that is where the risks identified are evaluated and ranked and risk response which is the identification of the way risks are dealt with (Orsipova, 2008).

Companies have three fundamental ways of going about their risk management activities; modifying the firm’s operations, adjusting its capital structure, and employing targeted financial instruments (including derivatives).Their hedging strategy, therefore, is determined by their compensation plan and reputational concerns. There is ambiguous empirical evidence on the dominant hedging motive. It depends on the environment in which firms operate (e.g. tax schedule) and on firm characteristics (e.g. capital intensity).

Corporate managers appear to believe that derivatives are capable of adding value since as they continue to make extensive use of them. When the International Swaps Dealers Association (ISDA) examined the annual reports and regulatory filings of the world’s500 largest companies in 2003, they found that 92% of the firms reported making some use of derivatives.

2.3.1 Equity price risk Companies do hold listed equity securities as a part of their portfolio plus additional non-listed equity securities acquired for long-term strategic purposes. By holding these assets, the firms are exposed to equity price risk defined as the risk of declining equity prices leading to a decline in the fair value of the assets recognised in the balance sheet.

15 2.3.2 Interest rate risk Interest rate risk refers to the effects that unexpected interest changes have on a company’s income cash flows and market value. Interest rate risks are more familiar to financial firms which have mainly financial assets and, thus are expected to exhibit different sensitivity with regard to changes in interest rates, when compared to nonfinancial firms. At the same time, financial firms have the ability to manage their interest rate risk more accurately because they use sophisticated techniques for the identification and quantification of interest rate exposures. However, changes in interest rates are also important for nonfinancial firms because interest rate risk impacts on the value of nonfinancial firms through changes in cash flows generated by operations which arise due to interest rate direct effect on the cost of capital inherent to investment decisions. Interest rate risk does also influence firms’ value due to changes in the value of their financial assets and liabilities.

Studies undertaken for financial institutions between risk management and firm value by Cyree & Huang (2004) on interest rate and FX derivatives use by publicly traded banks or holding companies (1993-96) found banks using derivatives have higher value (Tobin’s Q) than non-users. In the study of Kwan (1991), bank stock returns were found to be related to unanticipated interest rate changes, and the magnitude of the effect can be explained by the maturity composition of assets and liabilities. However, generally after the financial crises firm reduced on the usage of derivatives. In the scope of industrial corporations study by Allayannis & Weston (2001) on the Impact of FX derivatives use on 720 large nonfinancial (1990-95) there exists positive relation between use of FX derivatives and firm value (Tobin’s Q). Bartram, Brown, & Fehle (2004) study on “Impact of interest rate and FX derivatives use for 7,292 companies in U.S. and 47 other countries (2000-2001)” also conclude that the use of derivatives associated with higher firm value (more significant for interest rates than FX).

2.3.3 Commodity price risk Commodity price risk refers to the effects of unexpected changes in commodity prices have on income, cash flows and market value of a company. Commodity prices change because of changes in underlying supply and demand- what are called changes 16 in real prices and changes in the nominal price level inflation. The economic commodity price exposure describes the effect of unexpected price movements of commodities on firm value. This effect is primarily determined by firms’ economic business activity. On the other hand, indirect effects result from the economic interdependence of companies in the economic value chain.

A recent study by Accenture, the international management consulting firm, revealed that 35% of corporate executives surveyed believe that commodity price fluctuations have the potential to cause the greatest increase in risk to their firms (a significantly higher percentage than those who listed other factors such as decreased credit availability and liquidity risk). As a result of this focus, many corporate treasurers have become more concerned with ensuring that firm-wide financial risk is managed efficiently and effectively, incorporating commodity risk management into their current treasury risk management strategy. In general, a relevance of a commodity as an input (output) factor should lead to a negative (positive) exposure.

Despite the fact that changes of all production factors on the range of products have a potential direct economic effect on the firms’ cost and/or revenue, only some inputs and outputs namely commodities, are traded on the spot/or futures exchanges of international financial markets. Apart from the use of exchange traded derivatives, OTC contracts such as swaps, forwards or more complex financial products can also be used to hedge commodity price risk. As well, the price of various commodities that are not exchange traded can be hedged via cross hedging. This is achievable when their price is highly correlated with some other commodities for which derivatives are available.

Bartram (2005) makes use of a sample of 490 German nonfinancial firms, but limits his analysis to the sensitivity of firm value toward commodity price risk. Using time series regression, he tests if commodity price risk that has not been hedged may negatively (positively) affect stock prices in industries for which a certain commodity represents an important input (output) factor in the production process. The author reports that the percentage of firms with significant exposure to commodity price risk is in the range of 4,5% - 15,9%. Thus, commodity price risk is not found to be of 17 greater importance than other financial risks. This result is consistent with few corporate cash flows affected by commodity price changes. In the case of the study carried out by Lookman (2004) Exploration and production (E&P) firms that hedge commodity price risk; unbalanced panel set of 125 firms (364 firm-year observations) (1992-94 and 1999-2000). For undiversified E&P firms where commodity price risk is a primary risk, hedging is associated with lower firm value. For diversified firms with an E&P segment, hedging is associated with higher firm value. In aggregate, no association with hedging and firm value is detected. A research study by Callahan (2002) on the Impact of gold hedging on 20 North American gold mining firms (1996-2000) a negative correlation between extent of gold hedging and performance of firm stock price depicted.

Empirical examination of impact of commodity price risk management by users of commodities by Carter, Rogers, & Simkins (2004) on Impact of fuel hedging on 26 U.S. airlines (1994-2000) show a positive relation between the use of fuel price risk derivatives and firm value(Tobin’s Q).

2.3.4 Foreign exchange risk Currency risk also called as foreign exchange risk refers to changes in the firm’s income, cash flows and market value caused by unexpected exchange rate changes. (Madura, 1989). With the collapse of Bretton Woods Fixed exchange rate international monetary system in the late 1960’s, and its replacement in 1973 by the current managed floating exchange rate system, foreign exchange volatility has increased substantially.

As discussed in Bartov and Bodnar (1994) and in several other papers, an appreciation in the domestic currency makes exporting goods more expensive in foreign currency territory, and this may lead to a fall in foreign demand. Consequently, the exporting firm’s value would hurt by an appreciation of the domestic currency. On the other hand, importing firms would benefit from the appreciation of the domestic currency because their imports would become cheaper. Whereas substantial focus on US financial markets, there are studies on other markets, such as Japan (Bodnar & Gentry, 1993; He & Ng, 1998; Williamson, 2001), Canada (Bali et al., 2007; Bodnar 18 & Gentry, 1993), Australia (Khoo,1994; Nguyen & Faff, 2003), Sweden (Hagelin & Pramborg, 2004; Nydahl, 1999). In overall, researchers have had to a certain degree are successful in documenting a significant contemporaneous relation between firm’s stock returns and changes in foreign exchange rates. To manage unexpected currency fluctuations in the long run, managers adopt financial and operational approaches (Chowdhry and Howe 1999, Hommel 2003, Carter et all. 2003).

Nain (2004) who undertook research on U.S. firms on 548 derivatives users and 2,711 non-derivative users with ex ante FX exposure between 1997-99 deduced that foreign exchange risk management increases firm value as measured by Tobin’s Q if many (few or zero ) hedge. Research on risk management of FX exposure of 424 firms beginning 1996 to 2000 found that financial risk management is associated with higher firm value Kim, Mathur, & Nam (2004).

Allayannis, Lei, & Miller (2005) undertook studies on the Impact of use of FX derivatives on firm value (Tobin’s Q) for 379 firms (1990-99). They noted a significant positive premium for users of derivatives with FX exposures. There was positive but insignificant for firms with no exposure.

19 2.4 Conceptual Model A conceptual definition is an element of the scientific research process in which a specific concept is defined as measurable occurrence or in measurable terms; it basically gives one the meaning of the concept (Mugenda, 2008).

Figure 2.1: Conceptual Model

The conceptual framework presents the effect of instruments usage for managing market risk as viewed by the chief executive of the various organizations. In this scenario there will be the latent variable and the items on whose response the latent variable is inferred. The latent variable is a hypothetical trait or construct which is postulated to exist but cannot be measured by a single observable behavior. The value of the firm will be inferred by using multiple questions in testing the effectiveness of the various hedging instruments used by the companies as reported by the CEOs.

20 2.5 Summary The chapter has presented theoretical and empirical literature on financial hedging; discussing various market risk components and whether there is evidence from empirical literature that researchers have mixed opinion on the use of hedging instruments use and the value added to firms. As firms are exposed to market risk and given this causes variability in their returns it is of sense to seek to find out what can be inferred between management of market risk and firm value to bridge the gap. Furthermore these studies were done in the developed world which cannot be generalized to developing countries.

21 CHAPTER THREE RESEARCH METHODOLOGY

3.1 Introduction This chapter clearly defines the research methods used to conduct the study; specifically how data and information to address the research objectives and questions was collected, presented and analyzed.

3.2 Research design Heppner et al (1992:15) describe a research design as a plan or structure for an investigation or a list of specifications and procedure for conducting and controlling a research project. The research employed a descriptive survey method design which Saunders et al (2003) defines as one which looks with intense accuracy at the phenomena of the moment and describes precisely what the researcher sees.

3.3 Population The research targeted all the Chief Executive Officers of the 60 listed Companies because they are answerable to shareholders and are better placed to evaluate the benefits of risk management approaches. Out of the 60 questionnaires administered, 50 were received, which represented a good population valid for analysis.

3.4 Data collection Method The respondents were the CEOs who initiate financial risk management in their respective companies and were assisted by risk officers who handle the day today risk management practices in the organization.

The research employed the use of a close-ended questionnaire in the collection of primary data. Research assistants were engaged to collect data from the various CEOs. Secondary data was also used to basically review documented and relevant information concerning the effect of market risk management at the NSE. Respondents were asked to rank their answers on a 5-point Likert scale with 5 being the highest of the rating. When responding to a Likert questionnaire item, respondents specify their level of agreement to a statement (Likert, 1932). 22 To enhance validity of the instruments a pilot study was done in order to assess the clarity of the items in the questionnaire and those found to be inadequate modified with an aim of improving the instrument.

3.5 Data Analysis In the analysis of this data descriptive statistics was adopted which included frequencies, mean, median, quartiles, standard deviation and standard error of estimate. Quantitative data was presented in tables to allow for comparisons. Data analysis was done using Microsoft Excel to generate quantitative reports through tabulations, inter quartile range and measures of central tendencies. Descriptive summaries from findings presented data in a consolidated and meaningful manner to allow for easy interpretation. Data that will help in understanding the findings have been annexed.

23 CHAPTER FOUR DATA ANALYSIS AND INTERPRETATION OF RESULTS

4.1 Introduction This chapter presents analysis and findings of the study based on data collected from the field. The analysis was focused on addressing the objective of the study. The results present the effect of market risk management on company value among the firms listed at the Nairobi Stock Exchange. The data was gathered exclusively from questionnaire as the research instrument.

In analysis of the data, some characteristics considered were industry, size, and performance. The NSE firms were categorized into nine sectors for analysis of how the different sectors used the various market risk instruments and what they make out of effectiveness of the instrument usage (See appendix III). The following categorization was adopted for coding firms at the NSE into industries.

Table 4.1: Firm categorization at the NSE Sector at the NSE Number adopted for analysis Manufacturing and Allied 1 Agricultural 2 Banking 3 Insurance 4 Commercial and Services 5 Investment 6 Telecommunication and Allied 7 Automobile and Accessories 8 Energy and Petroleum 9 Firms at the NSE were further categorized by size where 1 = small, 2 = medium and 3 = large (See appendix IV) and their views as to usage and effectiveness of the various market risk management instruments were sought. The classification was on capitalization that allowed the researcher to evaluate the risk perception of firms in relation to size.

24 Finally the firms were categorized in terms of performance in a class of 1, 2, 3 and 4 (See appendix VI). The classification was based on the performance of the share price with class 1 being the highest performing and class 4 being the least performing. This was to gauge whether usage and effectiveness of the instruments would infer that there is a high performance to draw conclusions they would add value to the firms.

4.2 Commodity Risk Instruments Usage

Table 4.2: Level of usage of the following commodity risk instruments in your firm Tr St Variables N Mean Median Mean 2Dev SE Mean Forwards 50 3.08 3 3.091 1.007 0.142 Futures 50 3.2 3 3.182 0.881 0.125 Swaps 50 3.06 3 3.091 1.114 0.158 Commodity Bonds 50 2.98 3 3.045 1 0.141 Source: Survey Data, 2012

The respondents who are the CEOs of firms listed at the Nairobi Stock Exchange were to indicate level of usage of commodity risk instruments for their respective firms. Majority of the respondents indicated that futures to hedge price risk are used to a great extent as shown by a mean score of 3.2, There were extremes of scores ranging from 1 and 5 depicting the fact that some of the CEOs may not be conversant with the instruments.

Analysis of how the various instruments are used in the industry (Refer to appendix III) show the spread of use as follows: The automobiles and accessories rank forward contract as the highest in use with a mean of 3.5. The use of futures is preferred by the energy and petroleum sector with a mean of 5 which is the extreme of very strongly agree. Swaps are used to a great extent in energy and petroleum sector with a mean of 4.0. Commodity bonds and loans is also more in use in the energy and petroleum sector with a mean of 4 and standard deviation of 0 and in the automobiles and 25 accessories with a mean of 4. The Energy and petroleum seem to have a high usage of the commodity instruments and this is because inputs in this sector are traded globally and are volatile commodities.

Theory on usage of commodity risk instruments report that while corporations use a variety of different commodity derivatives forward contracts are utilized slightly more than futures, options and swaps. But over ally commodity futures are regarded as the most important derivative for commodity price risk management (Bodnar & Gebhardt 1999). The responses of CEOs at the NSE in their view considered futures as having a high usage which was not consistent with theory.

The size factor of firms was considered in evaluating the response on usage (See appendix IV and VI). Of the four instruments class 3 (large firms) ranked high in usage with a mean of 3.545 and 3.273 which is consistent with empirical evidence suggesting that hedging seems to be driven by economies of scale reflecting high fixed costs of establishing risk management programs that makes derivative usage uneconomical for small firms despite potentially larger benefits.

The firms that are poor in performance in terms of share returns at the NSE (class 4) were topping in agreement to a moderate extent that with means of 3.357, 3.5, 3.429 and 3.071 in usage.

26 4.3 Effectiveness in hedging price risks Table 4.3: Level of agreement in their effectiveness in hedging price risks

Tr St Variable N Mean Median Mean Dev SE Mean

Forwards 50 3.5 4 3.545 0.995 0.141 Futures 50 3.08 3 3.091 1.291 0.183

Swaps 49 3.265 3 3.289 1.076 0.154

Commodity bonds 50 3.12 3 3.136 1.35 0.191 Source: Survey Data, 2012

The study further sought to establish the level of agreement with statements related to the effectiveness of the commodity instruments in hedging price risks. From the study, majority of the respondents were in agreement that forward contracts have a great effect on hedging price and in effect increasing firm value as shown by a mean score of 3.5.

Sector 3 (Banking) strongly agreed that forward contracts were effective in their usage to hedge commodity price risk with a mean of 3.778 and this could have been this way because participants in this sector want to establish and maintain a long term trade relationship. Energy and petroleum agree swaps are effective to them to a mean of 4. For the futures effectiveness was scored highly in industry 7 (telecommunications and technology) who strongly agreed with a mean score of 4.5 and this is because market participants liquidity allows them to meet the daily variation margin requirements. Commodity bonds is more effective in industry 5 with a mean of 3.875 (Refer to appendix III).

Analysis of the of the commodity instruments effectiveness according to size show that small firms with low capitalization strongly agree that all the instruments are effective.

27 CEOs of firms in class 1, 2 and 3 believe the commodity instruments are effective with means of 3.833 for class 1, 3.6 and 3.5 for class 2 and 3.5 for class 3 the instruments to be effective. From the results there is no clear direction as to which class of firms believe in effectiveness of the instruments.

These results are consistent with the findings of other with the study by Jin and Jurion (2004) who examined the relation between stock return and return sensitivity to commodity prices and hedging. They find oil and gas betas are negatively related to the extent of hedging. A test made if market rewards firms that hedge with higher market values measured using different definitions of Tobin Q. The result shows hedging has no discernible effect on firm value. From the findings there is no class

4.4 Foreign exchange risk instruments usage Table 4.4: Level of usage of the following Foreign Exchange Risk Instruments in the Firm Tr St Variable N Mean Median Mean Dev SE Mean Spot transaction 50 2.58 3 2.523 1.012 0.143

Netting out 50 2.34 2 2.273 1.042 0.147 FX Forward contracts 49 2.898 3 2.889 1.141 0.163

Foreign exchange Option 50 2.96 3 2.955 1.142 0.162 Source: Survey Data, 2012

The CEOs view was sought on another component of market risk on the level of usage of foreign exchange instruments. In the findings, foreign exchange option was used most with highest mean score of 2.96, second in ranking was forward contracts with a score of 2.898 followed by spot transactions and lastly netting out with a score of 2.34. In the various industries, the respondents scored spot transactions as used to a 28 moderate extent with a mean of 2.875 in the commercial & services sector, Netting out of foreign currency receipts with foreign currency expenditures is used to a moderate extent in the insurance sector with a score of 3 and FX forward contracts in the energy and petroleum with the highest mean of 5. Foreign exchange options usage scored 4 for usage to a great extent in Automobiles and accessories sector. (Refer to appendix III). Bartram et al (2003) explains the high usage in these sectors is as result of these firms having higher proportions of foreign assets, sales, and income. The extent of hedging is influenced by the amount of foreign sales, the amount of foreign assets, and the number of foreign subsidiaries the firm operates.

The size factor of firms was considered in evaluating the response on usage on this aspect. Of the four instruments the class 1 (small firms) somehow agreed in usage with a mean of 2.923, 3.154 and 3.231 and this can be explained by small capitalization firms experiencing high growth potential, but with higher risk.

Firms that performed well rated under class 1 reported to usage of foreign exchange instruments to a moderate extent with a mean of 2.917 and 3.083. Allayannis and Weston (2001) directly tested the relation between firm value and use of foreign exchange derivatives. Using a sample of 720 large firms between 1990 and 1995, they find that the value of firms that hedge on average is higher by 5 percent.

4.5 Effectiveness in hedging foreign exchange risks

Table 4.5: The level of agreement in the effectiveness of these instruments in hedging foreign exchange risks Tr St Variable N Mean Median Mean Dev SE Mean Spot transaction 50 3.74 4 3.818 1.065 0.151 Netting out 50 3.56 4 3.614 1.033 0.146 FX Forward contracts 50 3.32 4 3.364 1.151 0.163 Foreign exchange options 46 3.783 4 3.81 0.758 0.112 The study sought to know the effectiveness of the usage of foreign exchange instruments in contribution to the value of the firm and the respondents scored high 29 for foreign exchange options among the instruments they believed protected their firms from losses with a mean of 3.783, median of 4 and a standard deviation of 0.758. The respondents agree that spot transactions are effective with a score 3.74, followed by netting out of foreign currency receipts with foreign expenditure which scores agree recording 3.56 in the insurance industry. FX forward contract is the last in ranking in effectiveness with a score of 3.32. In the industry categorization, Agricultural sector seemed to have a stronger view of spot transaction instrument as being effective with a mean of 4.143, netting out of foreign currency instrument being appreciated as effective by the insurance industry at a mean of 3.833.Respondents in commercial and services sector agree at a mean of 3.625 on effectiveness for forward contracts in eliminating all or most of the transaction exposure. In the case foreign exchange options effectiveness to protect a company from losses, Commercial and services view the instrument as effective at a score at 3.857.

In all the four instruments the respondents were to give the level of agreement in effectiveness. The firms under class 3(large firms) agree they are effective with a mean of 3.727, 3.818 and 4.111 and this meant the large firms could have risk management in practice in their organizations to gauge effectiveness.

Classification of firms according to performance class 3 takes the lead in gauging effectiveness of foreign exchange instruments with means of 4, 3.7 and 3.7 and class 2 follows with 3.833, 3.615 and 3.833.

30 4.6 Interest rate risk instruments usage in your firm

Table 4.6: Level Of Usage of the following Interest rate risk instruments in your firm Tr St Variable N Mean Median Mean Dev SE Mean Immunization strategy 50 2.6 3 2.591 0.969 0.137 Net income smoothing 50 3.14 3 3.159 0.969 0.137 Volume strategy 50 2.98 3 2.977 1.134 0.16 Interest rate forwards 50 2.9 3 2.909 1.111 0.157 Interest rate futures 48 3.063 3 3.068 1.137 0.164

Securitization 50 3.06 3 3.068 1.132 0.16

For the respondents interviewed, they view volume strategy as moderately used with a mean score of 3. The respondents had a moderate extent of mean score for usage of immunization strategy in agricultural sector at 3.286. The usage of net income smoothing had a mean of 4 depicting usage to a great extent in the agricultural and telecommunication sector, volume strategy was used to a great extent in the commercial and services and telecommunications with a mean of 3.5 mean each. Interest rate forwards are used to a great extent in commercial and services sector with a mean 3.625. The CEOs admitted to usage of interest rate futures to a great extent in telecommunications industry at 4.0. Securitization is put to use to a great extent in the energy and petroleum sector at a mean score 4 (Refer to appendix III).

Interest rate derivatives are used more often by transportation and utility companies, as well as firms with high credit ratings. The banking industry, investments and insurance fall under firms with high credit ratings seemed to have a high usage of the

31 instruments in the survey. Firms with high proportion of short term and floating rate debt are frequent users of interest rate derivatives as well. The instruments are primarily employed to convert floating rate payments into fixed payments and also from fixed to floating to lock in the spread on new debt issues. (Bodnar & Gebhart 1999).

The size factor of firms was considered in evaluating the response on usage on this aspect. Of the six instruments class 1 (small firms) somehow agreed in usage with a mean of 2.846, 3.385, 3.385, 3.333 and 3.462.

In assessing usage of interest rate instruments class 3 reported moderate use of the instruments with the highest score on four instruments having means of 3.1, 3.2, 3.2 and 3.2.,class 4 with one of 3.286 and class 2 with 2.929 ( Refer to appendix V).

This is in variance with Visvanathan (1998) findings that the use of interest rate derivatives could be related to strategies meant to increase value.

4,7 Effectiveness in hedging interest rate risks Table 4.7: Level of agreement in their effectiveness in hedging interest rate risks Tr St Variable N Mean Median Mean Dev SE Mean Immunization strategy 50 3.7 4 3.773 1.055 0.149 Net income smoothing 50 3.38 4 3.432 1.338 0.189 Volume strategy 50 3.32 4 3.364 1.186 0.168 Interest rate forwards 50 3.66 4 3.75 1.154 0.163 Interest rate futures 50 3.36 4 3.409 1.274 0.18 Securitization 50 2.8 3 2.773 1.161 0.164

32 The study sought to find out the effectiveness of the interest rates instruments and the respondents agreed that immunization strategy was the most effective recording a mean score of 3.7. Analysis of the industry performance on effectiveness, industry 3 agree that immunization strategy as an instrument was effective with a mean of 4, the banking industry agree that net income smoothing was the most effective with a mean of 3.889. Volume strategy is effective as was viewed by the insurance industry with a mean of 4.167. Interest rate forwards was believed to be effective in the manufacturing industry with a mean of 4.273. The investments industry strongly agree and rated interest rate futures at 4.5 almost to the extreme as being effective in hedging risks and securitization is considered effective in telecommunication and technology with a mean of 5.

Of the six instruments the respondents were to give the level of agreement in effectiveness. The firms under class 3 (large firms) agree they are effective with a mean of 3.727,3.636, 3.818, 3.727 and 3.364 (See appendix IV) and this meant the large firms could have risk management in practice in their organizations to gauge effectiveness.

Firms categorized according to classes of performance showed the following under the aspect of effectiveness in use of interest rate instruments. Class 2 topped the list with somehow agree of means of 4.2, 3.714, 3.429 and 4, Class 3 followed with two scores of 4.2 and 3.04 and class 1 with 3.75.

4.8 Conclusions The survey demonstrates that usage of commodity and interest rate instruments do not add value to the share price of firms but it is only the use of exchange rate instruments where value is derived. This demonstrates that not all hedging activities in firms do add value.

In managing the risks firms must understand the risks they are exposed to by developing a risk profile thus requiring an examination of both the immediate risks from competition and product market changes as well as the more indirect effects of macro - economic forces. This will enable firms take on the various options of either 33 letting the risk pass through, protecting themselves by using the hedging instruments or intentionally increasing exposure to some of the risks because the feeling of having significant advantages over the competition.

In the findings there is usage to some extent of various instruments which is not translated to effectiveness and eventually loss of value on the share.

As with everything else in corporate finance, firms have to make the trade off. The objective, after all, is not complete protection against risk, but as much protection as makes sense, given the marginal benefits and costs of acquiring it.

34 CHAPTER FIVE SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.1 Introduction The chapter presented the discussion of key data findings, conclusion drawn from the findings highlighted and recommendation made there-to. The conclusions and recommendations drawn were addressing the objective of the study. The objective of the study was to determine the effect of market risk management on the value of the firm among companies listed at the NSE.

5.2 Summary Of the 50 CEOs who responded to the survey all reported usage of the various risk instruments to the extent of their views and apportioned various strengths of agreement of levels of usage and effectiveness.

A point of note was the extremes of choices on the Likert scale of one and five which could be interpreted as lack of knowledge of the instruments by the respondent. In commodity instrument usage, futures are used most as ranked by the firms that used them. The commodity instruments were notably used more in the energy and petroleum, automobiles and accessories. This is because firms in these sectors are multinational in nature and are thus exposed to the risks given mother companies are abroad. Their inputs are also sourced from across borders thus prone to fluctuations in prices.

Large firms (size3) rank high in usage as they are able to absorb the fixed costs that come with risk management.

The firms that categorized under class 4 (those with negative returns on share return) responded that they employed high usage on commodity risk instruments. The findings proved that as much as they used the instruments no value was gained.

Commodity instrument find forward contracts to be the most used among the instruments and the industries that dominate in their usage are the banking, energy 35 and petroleum and the telecommunications sector. Low capitalized firms ranked the instruments as more effective which is not in tandem with value addition.

In hedging foreign exchange risk, research findings show that the sectors comprising of multinational companies namely insurance, energy and petroleum, automobiles and the agricultural sector. They use and believe the instruments are effective. This is reflected in the share price as firms classified under class 1 report the high usage and effectiveness.

Interest rate derivatives are used more often by transportation and utility companies, as well as firms with high credit ratings. The banking industry, investments and insurance fall under firpis with high credit ratings seemed to have a high usage of the instruments in the survey. Firms with high proportion of short term and floating rate debt are frequent users of interest rate derivatives as well. The instruments are primarily employed to convert floating rate payments into fixed payments and also from fixed to floating to lock in the spread on new debt issues. (Bodnar & Gebhart 1999).

Class 3 reported moderate use taking the lead in the means scored for usage. This is not mirrored in the share price and therefore put a disparity as to the usage and value addition. This disapproves the fact that use of interest rate instruments add value to firms.

5.2 Conclusions The results of this survey provide a broad understanding of market risk perception of CEOs of the listed companies at the NSE and whether the huge investments they are charged with in initiating the practices of risk management add value or this practice is in futility. Majority of these firms face material risk in foreign exchange, commodity and interest rate and it would of great importance to ascertain for sure which hedging activities add value. Findings in this study show that most of the firms reported usage of basic instruments with forward contracts and options being rated as those in high usage and effective. This can be attributed to lack of developed financial

36 instruments market in Kenya and unavailability of credit lines that constrain access to the instruments.

One of the pillars in modem finance (theory of efficient markets) comes into play to support the findings of the study. Market efficiency means markets do no leave their money on the table. Information that is freely accessible is incorporated in prices with sufficient speed and accuracy that one cannot profit by trading on it.

The lesson of market efficiency for the CEOs is that an attempt to earn higher returns in most financial markets means bearing large unfamiliar risks and thereby making losses thus reducing firm value. According to Stulz 1995, highly liquid markets such as those of interest rate and FX futures are not favorable to industrial firms as they are unlikely to have a comparative advantage in bearing these risks.

5.3 Recommendations Because market risk is inherent and presents both threats and opportunities CEOs need to respond to each side accordingly. The threat side should be protected through hedging and the upside should be taken up to take advantage of the opportunity. From the findings there is no consistency in practice and performance as the usage does not reflect in performance.

Beyond methodologies, data, and technology capabilities, effectiveness in market risk management may require enhancing or, in some cases, creating a pervasive risk- awareness culture throughout the organization and creating an environment with incentives that sustain this culture over time.

Executive management should provide leadership, with oversight and input from the board of directors, towards enhancing and making more transparent the institution’s risk strategy, risk appetite, and risk management framework.

The CEOs could also infuse risk management responsibilities throughout the organization and these integrated into performance goals and compensation decisions to achieve value. 37 This should be an ongoing process to be refreshed with changing business conditions so as to remain relevant to guiding business decisions. • •

5.4 Suggestion for further studies Future studies should focus on alternative methods of ascertaining the effect of market risk management to help in understanding whether a different approach may lead to a different conclusion on the value added. This study was carried out employing a survey method while future studies could incorporate quantitative data on hedging activities contained in the annual reports. This would be advantageous as annual reports provide data that is a more reliable source of information than surveys. Data collected from audited financial statements also do not have response bias inherent in survey designs.

5.5 Limitations of the study The instrument used to carry out the research was a questionnaire which sought opinions of the CEOs. Personal opinions and perceptions may differ with the official company stand (policy).

In view of the ever increasing competition, even though the firms may have had risk policy in place, some respondents may intentionally have withheld information fearing that the researcher could give out their strategies competitors.

The target population of the study (60 firms) was huge in relation to the time available for the study. The study was involving CEOs of firms listed at the NSE with offices in diverse areas in Kenya and to cover these areas research assistants were engaged which could have posed the challenge of validity.

Since the CEOs tend to have busy schedules, the CEOs or the Executives in charge of risk management, may not be necessarily those who responded to the questionnaire thus reducing reliability.

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44 APPENDICES

APPENDIX I: COMPANIES LISTED AT THE NSE

AGRICULTURAL \

Eaagads Ltd

Kapchorua Tea Co. Ltd

Kakuzi

Limuru Tea Co. Ltd

Rea Vipingo Plantations Ltd

Sasini Ltd

Williamson Tea Kenya Ltd

COMMERCIAL AND SERVICES

Express Ltd

Kenya Airways Ltd

Nation Media Group

Standard Group Ltd

TPS Eastern Africa (Serena) Ltd

Scangroup Ltd

Uchumi Supermarket Ltd

Hutchings Biemer Ltd

Longhorn Kenya Ltd

45 TELECOMMUNICATION AND TECHNOLOGY

AccessKenya Group Ltd

Safaricom Ltd

AUTOMOBILES AND ACCESSORIES

Car and General (K) Ltd

CMC Holdings Ltd

Sameer Africa Ltd

Marshalls (E.A.) Ltd

BANKING

Barclays Bank Ltd

CFC Stanbic Holdings Ltd

Diamond Trust Bank Kenya Ltd

Housing Finance Co Ltd

Kenya Commercial Bank

National Bank of Kenya Ltd

NIC Bank Ltd

Standard Chartered Bank Ltd

Equity Bank Ltd

The Co-operative Bank of Kenya Ltd

- m INSURANCE

Jubilee Holdings Ltd

Pan Africa Insurance Holdings Ltd

Kenya Re-Insurance Corporation Ltd

CFC Insurance Holdings

British-American Investments Company (Kenya) Ltd \

CIC Insurance Group Ltd

INVESTMENT

City Trust Ltd

Olympia Capital Holdings ltd

Centum Investment Co ltd

Trans-Century

MANUFACTURING AND ALLIED

A. Baumann

B.O.C Kenya Ltd

British American Tobacco Kenya Ltd

Carbacid Investments Ltd

East African Breweries Ltd

Mumias Sugar Co. Ltd

Unga Group Ltd

TT Eveready East Africa Ltd

Kenya Orchards Ltd

CONSRUCTION AND ALLIED

Athi River Mining

Bamburi

Crown Berger

East African Cables

East African Power Company

ENERGY AND PETROLEUM

KenGen

Kenol Kobil

KPLC

Total Kenya

48 APPENDIX II: QUESTIONNAIRE

PART I: GENERAL INFORMATION 1. Firm: ______2. Physical Address______3. Industry ______4. Other (Please specify) ______5. How is your firm categorized Small [ ] Medium [ ] Large [ ]

PART II II a. Indicate the level of usage of the following commodity risk instruments in your firm. 6. Forward contracts as hedging instruments to help in eliminating price changes. Very little extent Little extent Moderate extent [ ] Great extent [ ] Very great extent [ ] 7. Futures to hedge price risk. Very little extent Little extent Moderate extent [ ] Great extent [ ] Very great extent 8. Swaps. Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent Very great extent [ ]

9. Commodity bonds and loans for price hedging. Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent Very great extent [ ]

49 II b. Indicate the level of agreement in their effectiveness in hedging price risks. 10. Forward contracts as hedging instruments to help in eliminating price changes. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 11. Futures to hedge price risk. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 12. Swaps Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 13. Commodity bonds and loans for price hedging. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ 1

PART III III a. Indicate the level of usage of the following foreign exchange risk instruments in your firm. 14. Spot transactions as hedging instruments in reducing foreign exchange exposure.

Very little extent [ 1 Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ] 15. Netting out of foreign currency receipts with foreign currency expenditures. Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ]

50 16. Foreign exchange forward contracts to hedge foreign exchange risk. Very little extent [ ] Little extent [ ] Moderate extent [ 1 Great extent [ ] Very great extent [ ]

17. Foreign exchange option hedges Very little extent [ ] Little extent Moderate extent [ ] Great extent [ ] Very great extent [ ]

III b. Indicate the level of agreement in their effectiveness in hedging foreign exchange risks. 18. Spot transactions can reduce the difference between receipts and payments thus improving cash flows.

Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 19. Netting out foreign currency receipts with foreign expenditures to improve foreign exchange balance. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] Forward contracts eliminate all or most of the transaction exposure a firm faces.

Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 20. Foreign exchange option hedges protect a company from losses. Strongly agree [ ] Agree [ ] Strongly disagree [ ]

51 PART IV IV a. Indicate the level of usage of the following interest rate risk instruments in your firm. 22. Immunization as strategy.

Very little extent [ ] Little extent [ : Moderate extent [ ] Great extent [ Very great extent [ ] 23. Usage of net income smoothing.

Very little extent [ ] Little extent [ ] Moderate extent f I Great extent [ ] Very great extent [ ] 24. Use of volume strategy

Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ] 25. Use of interest rate pricing strategy

Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ] 26. Use of ideal portfolio as a hedging instrument.

Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ] 27. Use interest rate forwards

Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ] 28. Use interest rate futures

Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ]

52 29. Use of securitization. Very little extent [ ] Little extent [ ] Moderate extent [ ] Great extent [ ] Very great extent [ ] IV b. Indicate the level of agreement in their effectiveness in hedging interest rate risks.

30. The use of immunization as a hedging instrument aid firms in receiving predetermined returns from bonds regardless of fluctuations of interest rates. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 31. Net income smoothing is effective in ensuring that the net interest received on assets is greater than the interest payment on liabilities. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 32. Volume strategy facilitates firms in maximizing potential returns.

Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 33. Interest rate pricing strategy is effective in positioning the balance sheet. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 34. Ideal portfolio usage is effective. Strongly agree [ ] Agree [ ] Somehow agree Disagree [ ] Strongly disagree [ ] 35. Interest rate forwards are effective. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 53 36. Interest rate futures are effective. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ] Strongly disagree [ ] 37. Securitization does eliminate funding exposure in terms of duration and pricing. Strongly agree [ ] Agree [ ] Somehow agree [ ] Disagree [ ]

Strongly disagree [ ]

54 APPENDIX III

Variable N M ean M edian T rM ean StDev SE M ean M inim um M axim um 0 1 0 3

FCH 6 50 3.08 3 3.091 1.007 0.142 1 5 2.75 4

FH PR7 50 3.2 3 3.182 0.881 0.125 1 5 3 4

SW APS 8 50 3.06 3 3.091 1.114 0.158 1 5 3 4

C B L 9 50 2.98 3 3.045 1 0.141 1 4 2 4

Variable N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um 0 1 0 3

FCH 10 50 0 3.5 4 3.545 0.995 0.141 1 5 3 4

FHPR11 50 0 3.08 3 3.091 1.291 0.183 1 5 2 4

SW APS 12 49 1 3.265 3 3.289 1.076 0.154 1 5 2 4

CB L 13 50 0 3.12 3 3.136 1.35 0.191 1 5 2 4

V ariable N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um 0 1 0 3

STH14 50 0 2.58 3 2.523 1.012 0.143 1 5 2 3

N O F15 50 0 2.34 2 2.273 1.042 0.147 1 5 2 3

FEFC 16 49 1 2.898 3 2.889 1.141 0.163 1 5 2 4

FEO H 17 50 0 2.96 3 2.955 1.142 0.162 1 5 2 4

V ariable N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um Ql 0 3

STRD18 50 0 3.74 4 3.818 1.065 0.151 1 5 3 5

N FC 19 50 0 3.56 4 3.614 1.033 0.146 1 5 3 4

55 FC E 20 50 0 3.32 4 3.364 1.151 0.163 1 5 3 4

F E 021 46 4 3.783 4 3.81 0.758 0.112 1 5 3 4

V ariable N N* M ean M edian T rM ean StDev SE M ean M inim um M aximum 0 1 0 3

IS22 50 0 2.6 3 2.591 0.969 0.137 1 5 2 3

UN IS23 50 0 3.14 3 3.159 0.969 0.137 1 5 3 4

U V S24 50 0 2.98 3 2.977 1.134 0.16 1 5 2 4

U1RF27 50 0 2.9 3 2.909 1.111 0.157 1 5 2 4

U IR F28 48 2 3.063 3 3.068 1.137 0.164 1 5 2 4

U SEZ29 50 0 3.06 3 3.068 1.132 0.16 1 5 2 4

SE V ariable N M ean M edian T rM ean StDev M ean M inim um M axim um 0 1 Q3

IM H 30 50 3.7 4 3.773 1.055 0.149 1 5 3 4.25

NIS31 50 3.38 4 3.432 1.338 0.189 1 5 2.75 4.25

V SF32 50 3.32 4 3.364 1.186 0.168 1 5 2.75 4

IRPS33 50 3.58 4 3.659 1.214 0.172 1 5 3 4.25

1PU34 50 3.68 4 3.705 0.819 0.116 2 5 3 4

IRFE35 50 3.66 4 3.75 1.154 0.163 1 5 3 4.25

IRF36 50 3.36 4 3.409 1.274 0.18 1 5 3 4

SEC 37 50 2.8 3 2.773 1.161 0.164 1 5 2 4

ANALYSIS

56 BY INDUSTRY

V ariable Industry N M ean M edian T rM ean StDev SE M ean M inim um M axim um 01 Q3

FCH6 1 II 3.091 3 3.111 0.831 0.251 2 4 2 4

2 7 2.857 3 2.857 1.215 0.459 1 5 2 3

3 9 3 3 3 1.118 0.373 1 4 2 4

4 6 3 3 3 1.095 0.447 1 4 2.5 4

5 8 3.5 3.5 3.5 0.926 0.327 2 5 3 4

6 4 2.75 3 2.75 0.5 0.25 2 3 2.25 3

7 2 3 3 3 2.83 2 1 5 * *

8 2 3.5 3.5 3.5 0.707 0.5 3 4 * *

9 I 3 3 3 * * 3 3 * *

FH PR7 1 11 3.091 3 3.111 0.701 0.211 2 4 3 4

2 7 3.143 3 3.143 1.215 0.459 1 5 3 4

3 9 3.333 3 3.333 0.707 0.236 2 4 3 4

4 6 3.167 3 3.167 0.753 0.307 2 4 2.75 4

5 8 3 3 3 0.756 0.267 2 4 2.25 3.75

6 4 3.25 3.5 3.25 0.957 0.479 2 4 2.25 4

7 2 3 3 3 1.41 1 2 4 * *

8 2 3.5 3.5 3.5 2.12 1.5 2 5 * *

9 1 5 5 5 * * 5 5 * *

SW A PS 8 1 11 2.636 3 2.667 1.206 0.364 1 4 1 4

2 7 3.143 3 3.143 0.9 0.34 2 4 2 4

3 9 3.778 4 3.778 0.667 0.222 3 5 3 4

4 6 2.833 3 2.833 0.983 0.401 1 4 2.5 3.25

5 8 3.25 3 3.25 1.165 0.412 1 5 3 4

57 6 4 3 3.5 3 1.414 0.707 1 4 1.5 4

7 2 2.5 2.5 2.5 2.12 1.5 1 4 * *

8 2 2 2 2 1.41 1 1 3 * *

9 1 4 4 4 * * 4 4 * *

C B L 9 1 11 3.364 3 3.444 0.674 0.203 2 4 3 4

2 7 2.143 2 2.143 1.345 0.508 1 4 1 4

3 9 3.111 3 3.111 0.782 0.261 2 4 2.5 4

4 6 3 3.5 3 1.265 0.516 1 4 1.75 4

5 8 3.125 3 3.125 0.835 0.295 2 4 2.25 4

6 4 2.5 2.5 2.5 0.577 0.289 2 3 2 3

7 2 2 2 2 1.41 1 1 3 * *

8 2 4 4 4 0 0 4 4 * *

9 1 4 4 4 * * 4 4 * *

V ariable Industry N N* M ean M edian T rM ean StDev SE M ean M inim um M aximum 0 1

FCH 10 1 11 0 3.727 4 3.778 0.905 0.273 2 5 3

2 7 0 3.571 3 3.571 0.976 0.369 3 5 3

3 9 0 3.778 4 3.778 0.833 0.278 2 5 3.5

4 6 0 3.667 3.5 3.667 0.816 0.333 3 5 3

5 8 0 3.5 4 3.5 1.069 0.378 2 5 2.25

6 4 0 3.5 3.5 3.5 0.577 0.289 3 4 3

7 2 0 2 2 2 1.41 1 1 3 *

8 2 0 3 3 3 1.41 1 2 4 *

9 1 0 1 1 1 * * 1 1 *

58 FHPR11 1 11 0 3.455 4 3.556 1.508 0.455 1 5 2

2 7 0 2.286 2 2.286 1.113 0.421 1 4 1

3 9 0 3.444 4 3.444 1.13 0.377 1 5 3

4 6 0 3 3 3 1.095 0.447 1 4 2.5

5 8 0 2.875 3 2.875 1.458 0.515 1 5 1.25

6 4 0 3 3.5 3 1.414 0.707 1 4 1.5

7 2 0 4.5 4.5 4.5 0.707 0.5 4 5 *

8 2 0 2 2 2 0 0 2 2 *

9 1 0 3 3 3 * * 3 3 *

SW APS 12 1 11 0 3.636 4 3.667 1.12 0.338 2 5 2

2 7 0 3.286 3 3.286 0.951 0.36 2 5 3

3 9 0 2.889 3 2.889 1.054 0.351 1 4 2

4 6 0 3.333 3.5 3.333 1.211 0.494 2 5 2

5 8 0 3.25 3.5 3.25 1.035 0.366 1 4 3

6 3 1 2.667 2 2.667 1.155 0.667 2 4 2

7 2 0 3.5 3.5 3.5 2.12 1.5 2 5 *

8 2 0 3 3 3 1.41 1 2 4 *

9 1 0 4 4 4 * * 4 4 *

CBL13 1 11 0 2.727 2 2.667 1.555 0.469 1 5 1

2 7 0 2.857 3 2.857 1.464 0.553 1 5 1

3 9 0 2.889 3 2.889 1.364 0.455 1 5 1.5

4 6 0 3 3 3 1.265 0.516 1 5 2.5

5 8 0 3.875 4 3.875 0.835 0.295 3 5 3

6 4 0 3.25 3 3.25 0.5 0.25 3 4 3

7 2 0 3 3 3 2.83 2 1 5 *

59 8 2 0 5 5 5 0 0 5 5 *

9 1 0 2 2 2 * * 2 2 *

Variable Industry N N* M ean M edian TrM ean StDev SE M ean M inimum M axim um 0 1

STH14 1 11 0 2.273 2 2.333 0.647 0.195 1 3 2

2 7 0 2.429 2 2.429 1.397 0.528 1 5 1

3 9 0 2.444 2 2.444 0.882 0.294 1 4 2

4 6 0 2.833 3 2.833 0.983 0.401 1 4 2.5

5 8 0 2.875 3 2.875 1.126 0.398 1 5 2.25

6 4 0 2.75 2.5 2.75 0.957 0.479 2 4 2

7 2 0 3 3 3 0 0 3 3 *

8 2 0 1.5 1.5 1.5 0.707 0.5 1 2 *

9 1 0 5 5 5 * * 5 5 *

NO F15 1 11 0 2.273 2 2.222 0.786 0.237 1 4 2

2 7 0 2.429 2 2.429 1.272 0.481 1 5 2

3 9 0 2.333 2 2.333 1.323 0.441 1 5 1.5

4 6 0 3 3 3 1.095 0.447 2 4 2

5 8 0 2.125 2 2.125 0.991 0.35 1 4 1.25

6 4 0 2 2 2 0.816 0.408 1 3 1.25

7 2 0 1.5 1.5 1.5 0.707 0.5 1 2 *

8 2 0 3 3 3 1.41 1 2 4 *

9 1 0 2 2 2 * * 2 2 *

FEFC 16 1 11 0 3.273 3 3.222 1.104 0.333 2 5 2

2 6 1 2.833 3 2.833 1.169 0.477 1 4 1.75

60 3 9 0 2.444 2 2.444 0.882 0.294 1 4 2

4 6 0 3 3 3 0.632 0.258 2 4 2.75

5 8 0 2.75 2.5 2.75 1.282 0.453 1 5 2

6 4 0 3 3 3 1.826 0.913 1 5 1.25

7 2 0 3.5 3.5 3.5 0.707 0.5 3 4 *

8 2 0 1.5 1.5 1.5 0.707 0.5 1 2 *

9 1 0 5 5 5 * * 5 5 *

F E 0 H 1 7 1 11 0 2.545 3 2.556 1.036 0.312 1 4 2

2 7 0 3.571 4 3.571 1.397 0.528 1 5 3

3 9 0 2.778 3 2.778 0.972 0.324 1 4 2

4 6 0 3.333 3 3.333 1.033 0.422 2 5 2.75

5 8 0 2.625 2.5 2.625 1.061 0.375 1 4 2

6 4 0 3.5 3.5 3.5 1.291 0.645 2 5 2.25

7 2 0 2 2 2 1.41 1 1 3 *

8 2 0 4 4 4 1.41 1 3 5 *

9 1 0 3 3 3 * * 3 3 *

V ariable Industry N N* M ean M edian T rM ean StDev SE M ean M inimum M axim um 01

STRD 18 1 11 0 3.545 4 3.667 1.036 0.312 1 5 3

2 7 0 4.143 5 4.143 1.464 0.553 1 5 4

3 9 0 4.111 4 4.111 0.782 0.261 3 5 3.5

4 6 0 3.333 3.5 3.333 0.816 0.333 2 4 2.75

5 8 0 3.75 3.5 3.75 1.165 0.412 2 5 3

6 4 0 3.5 4 3.5 1 0.5 2 4 2.5

7 2 0 3.5 3.5 3.5 2.12 1.5 2 5 *

61 * 8 2 0 4 4 4 1.41 1 3 5 * 9 1 0 3 3 3 * * 3 3

N FC 19 1 11 0 3.818 4 4 1.25 0.377 1 5 3

2 7 0 3 3 3 1.155 0.436 2 5 2

3 9 0 3.889 4 3.889 0.601 0.2 3 5 3.5

4 6 0 3.833 4 3.833 0.753 0.307 3 5 3

5 8 0 3.375 3.5 3.375 1.188 0.42 1 5 3

6 4 0 3 3 3 1.155 0.577 2 4 2 * 7 2 0 4 4 4 0 0 4 4 * 8 2 0 4 4 4 0 0 4 4 * 9 1 0 2 2 2 * * 2 2

FC E 20 1 11 0 3 4 3.111 1.265 0.381 1 4 2

2 7 0 3.143 3 3.143 0.69 0.261 2 4 3

3 9 0 3.444 4 3.444 1.424 0.475 1 5 2.5

4 6 0 3.5 3.5 3.5 1.049 0.428 2 5 2.75

5 8 0 3.625 4 3.625 1.188 0.42 2 5 2.25

6 4 0 3.5 3 3.5 1 0.5 3 5 3

7 2 0 3 3 3 2.83 2 1 5 *

8 2 0 3.5 3.5 3.5 0.707 0.5 3 4 * * 9 1 0 3 3 3 * * 3 3

F E 021 1 11 0 3.727 4 3.778 0.467 0.141 3 4 3

2 6 1 3.333 3.5 3.333 1.366 0.558 1 5 2.5

3 7 2 3.857 4 3.857 0.69 0.261 3 5 3

4 6 0 3.667 4 3.667 0.516 0.211 3 4 3

5 7 1 3.857 4 3.857 0.69 0.261 3 5 3

62 6 4 0 4 4 4 0.816 0.408 3 5 3.25

7 2 0 5 5 5 0 0 5 5 *

8 2 0 4 4 4 0 0 4 4 *

9 1 0 3 3 3 * * 3 3 *

Variable Industry N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um 01

IS22 1 11 0 2.364 3 2.333 1.027 0.31 1 4 1

2 7 0 3.286 3 3.286 0.488 0.184 3 4 3

3 9 0 2.556 2 2.556 1.014 0.338 1 4 2

4 6 0 2.333 3 2.333 1.033 0.422 1 3 1

5 8 0 2.875 3 2.875 1.246 0.441 1 5 2

6 4 0 2.5 2.5 2.5 0.577 0.289 2 3 2

7 2 0 2 2 2 1.41 1 1 3 *

8 2 0 2 2 2 0 0 2 2 *

9 1 0 3 3 3 * * 3 3 *

UN IS23 1 11 0 2.636 3 2.556 1.362 0.411 1 5 1

2 7 0 4 4 4 0.577 0.218 3 5 4

3 9 0 2.667 3 2.667 0.707 0.236 2 4 2

4 6 0 3 3 3 0.632 0.258 2 4 2.75

5 8 0 3.375 3.5 3.375 0.744 0.263 2 4 3

6 4 0 3.5 3 3.5 1 0.5 3 5 3

7 2 0 4 4 4 0 0 4 4 *

8 2 0 3 3 3 0 0 3 3 *

9 1 0 3 3 3 * * 3 3 *

U V S24 I 11 0 3.091 3 3.111 1.221 0.368 1 5 2

63 2 7 0 3 3 3 1.291 0.488 1 5 2

3 9 0 2.778 3 2.778 0.972 0.324 1 4 2

4 6 0 2.833 3 2.833 1.329 0.543 1 5 1.75

5 8 0 3.5 3.5 3.5 0.926 0.327 2 5 3

6 4 0 2.5 2.5 2.5 0.577 0.289 2 3 2

7 2 0 3.5 3.5 3.5 2.12 1.5 2 5 *

8 2 0 2.5 2.5 2.5 2.12 1.5 1 4 *

9 1 0 2 2 2 * * 2 2 *

U IRF27 1 11 0 2.364 3 2.444 0.809 0.244 1 3 2

2 7 0 2.429 3 2.429 0.976 0.369 1 3 1

3 9 0 2.667 3 2.667 __ 1 0.333 1 4 2

4 6 0 3.667 4 3.667 1.366 0.558 1 5 3.25

5 8 0 3.625 4 3.625 1.188 0.42 1 5 3.25

6 4 0 3 3 3 0.816 0.408 2 4 2.25

7 2 0 2.5 2.5 2.5 2.12 1.5 1 4 *

8 2 0 3.5 3.5 3.5 0.707 0.5 3 4 *

9 1 0 3 3 3 * * 3 3 *

UIRF28 1 11 0 2.818 3 2.889 0.982 0.296 1 4 2

2 6 1 2.833 3.5 2.833 1.472 0.601 1 4 1

3 9 0 3.667 4 3.667 1 0.333 2 5 3

4 5 1 2.6 2 2.6 0.894 0.4 2 4 2

5 8 0 3.125 3 3.125 1.356 0.479 1 5 2.25

6 4 0 3.25 3.5 3.25 0.957 0.479 2 4 2.25

7 2 0 4 4 4 1.41 1 3 5 *

8 2 0 2 2 2 1.41 1 1 3 *

64 9 1 0 3 3 3 * * 3 3 *

USEZ29 1 11 0 3.091 4 3.222 1.136 0.343 1 4 2

2 7 0 3.714 4 3.714 1.113 0.421 2 5 3

3 9 0 3.111 3 3.111 0.928 0.309 2 5 2.5

4 6 0 2.167 2 2.167 1.169 0.477 1 4 1

5 8 0 3.125 3 3.125 1.553 0.549 1 5 1.5

6 4 0 3 3 3 0.816 0.408 2 4 2.25

7 2 0 3 3 3 0 0 3 3 *

8 2 0 2.5 2.5 2.5 0.707 0.5 2 3 *

9 1 0 4 4 4 * * 4 4 *

Variable Industry N M ean M edian T rM ean StDev SE M ean M inim um M aximum 0 1 0 3

IM H 30 1 11 3.909 4 4.111 1.221 0.368 1 5 3 5

2 7 4 4 4 1 0.378 3 5 3 5

3 9 3.333 4 3.333 0.866 0.289 2 4 2.5 4

4 6 3.833 4 3.833 0.753 0.307 3 5 3 4.25

5 8 3.25 3.5 3.25 1.282 0.453 1 5 2.25 4

6 4 4 4 4 0.816 0.408 3 5 3.25 4.75

7 2 5 5 5 0 0 5 5 * *

8 2 3 3 3 1.41 1 2 4 * *

9 1 3 3 3 * * 3 3 * *

NIS31 I 11 3.273 4 3.333 1.191 0.359 1 5 2 4

2 7 2.857 3 2.857 1.676 0.634 1 5 1 5

3 9 3.889 4 3.889 1.269 0.423 1 5 3.5 5

4 6 3.5 3.5 3.5 1.517 0.619 1 5 2.5 5

65 5 8 3.375 3.5 3.375 1.408 0.498 1 5 2.25 4.75

6 4 2.5 2.5 2.5 1.291 0.645 1 4 1.25 3.75

7 2 3.5 3.5 3.5 0.707 0.5 3 4 * *

8 2 5 5 5 0 0 5 5 * * * 9 1 3 3 3 * 3 3 * *

VSF32 1 11 3.182 3 3.222 1.401 0.423 1 5 2 4

2 7 2.714 3 2.714 1.113 0.421 1 4 2 4

3 9 3 3 3 1.225 0.408 1 5 2 4

4 6 4.167 4 4.167 0.408 0.167 4 5 4 4.25

5 8 3.625 4 3.625 0.916 0.324 2 5 3 4

6 4 2.5 2.5 2.5 1.291 0.645 1 4 1.25 3.75

7 2 4.5 4.5 4.5 0.707 0.5 4 5 * *

8 2 4.5 4.5 4.5 0.707 0.5 4 5 * *

9 1 3 3 3 * * 3 3 * *

IRPS33 1 11 3.545 4 3.667 1.128 0.34 1 5 3 4

2 7 3.429 4 3.429 1.718 0.649 1 5 1 5

3 9 3.333 3 3.333 1 0.333 2 5 2.5 4

4 6 4 4.5 4 1.265 0.516 2 5 2.75 5

5 8 3.625 4 3.625 1.302 0.46 1 5 3 4.75

6 4 3.75 3.5 3.75 0.957 0.479 3 5 3 4.75

7 2 5 5 5 0 0 5 5 * *

8 2 3 3 3 1.41 1 2 4 * *

9 1 2 2 2 * * 2 2 * *

IPU 34 1 11 3.455 4 3.556 0.82 0.247 2 4 3 4

2 7 3.429 3 3.429 0.976 0.369 2 5 3 4

66 3 9 3.556 4 3.556 0.527 0.176 3 4 3 4

4 6 3.833 3.5 3.833 0.983 0.401 3 5 3 5

5 8 4.125 4 4.125 0.641 0.227 3 5 4 4.75

6 4 4 4 4 0.816 0.408 3 5 3.25 4.75

* * 7 2 3.5 3.5 3.5 0.707 0.5 3 4

* * 8 2 4.5 4.5 4.5 0.707 0.5 4 5

* * * * 9 1 2 2 2 2 2

IRFE35 1 11 4.273 4 4.333 0.647 0.195 3 5 4 5

2 7 3.429 3 3.429 1.397 0.528 1 5 3 5

3 9 3.667 4 3.667 1.225 0.408 2 5 2.5 5

4 6 4 4 4 0.632 0.258 3 5 3.75 4.25

5 8 3.5 3.5 3.5 0.926 0.327 2 5 3 4

6 4 3.75 4 3.75 0.5 0.25 3 4 3.25 4 * * 7 2 3 3 3 2.83 2 1 5

* * 8 2 2.5 2.5 2.5 2.12 1.5 1 4 * * 9 1 1 1 1 * * 1 1

IRF36 1 11 3.636 4 3.778 1.502 0.453 1 5 3 5

2 7 3.143 4 3.143 1.773 0.67 1 5 1 5

3 9 2.889 3 2.889 1.269 0.423 1 4 1.5 4

4 6 3.333 3.5 3.333 0.816 0.333 2 4 2.75 4

5 8 3 3 3 0.926 0.327 1 4 3 3.75

6 4 4.25 4.5 4.25 0.957 0.479 3 5 3.25 5 * * 7 2 3 3 3 1.41 1 2 4

* * 8 2 4.5 4.5 4.5 0.707 0.5 4 5

* * * 9 1 4 4 4 * 4 4

67 SEC37 1 11 2.182 2 2.111 1.079 0.325 1 4 1 3

2 7 2.571 2 2.571 1.134 0.429 1 4 2 4

3 9 3 3 3 1 0.333 2 5 2 3.5

4 6 2.5 3 2.5 1.225 0.5 1 4 1 3.25

5 8 3.375 3.5 3.375 1.302 0.46 2 5 2 4.75

6 4 3 3 3 1.155 0.577 2 4 2 4 * * 7 2 4 4 4 1.41 1 3 5 * * 8 2 3 3 3 1.41 1 2 4 * * 9 1 3 3 3 * * 3 3

68 APPENDIX IV

A N A LY SIS B Y CLASS

V ariable Perfo N M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1 Q3

FCH 6 1 12 2.75 3 2.8 0.866 0.25 1 4 2 3

2 14 2.929 3 3 0.829 0.221 1 4 2.75 3.25

3 10 3.3 3.5 3.375 1.337 0.423 1 5 2 4.25

4 14 3.357 3.5 3.417 1.008 0.269 1 5 3 4

FH PR7 1 12 3.333 3 3.3 0.778 0.225 2 5 3 4

2 14 2.929 3 3 0.917 0.245 1 4 2 4

3 10 3 3 3 0.816 0.258 2 4 2 4

4 14 3.5 3.5 3.5 0.941 0.251 2 5 3 4

SW A PS 8 1 12 2.667 3 2.7 1.155 0.333 1 4 1.25 3.75

2 14 2.857 3 2.917 1.027 0.275 1 4 2 4

3 10 3.3 3 3.375 1.059 0.335 1 5 3 4

4 14 3.429 4 3.5 1.158 0.309 1 5 3 4

C B L 9 1 12 3.083 3 3.2 0.996 0.288 1 4 2.25 4

2 14 2.714 3 2.75 1.204 0.322 1 4 1.75 4

3 10 3.1 3 3.125 0.738 0.233 2 4 2.75 4

4 14 3.071 3 3.167 0.997 0.267 1 4 2 4

69 V ariable Perfo N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um 01

FCH 10 1 12 0 3.833 4 3.9 0.937 0.271 2 5 3

2 14 0 3.429 3 3.417 0.756 0.202 2 5 3

3 10 0 3.6 4 3.75 1.35 0.427 1 5 2.75

4 14 0 3.214 3.5 3.333 0.975 0.261 1 4 2.75

FHPR11 1 12 0 2.667 3 2.7 1.073 0.31 1 4 2

2 14 0 3.071 3.5 3.083 1.592 0.425 1 5 1

3 10 0 3.6 4 3.75 1.265 0.4 1 5 2.75

4 14 0 3.071 3 3.083 1.141 0.305 1 5 2.75

SW A PS 12 1 12 0 2.917 2.5 2.9 1.311 0.379 1 5 2

2 14 0 3.571 4 3.583 0.852 0.228 2 5 3

3 10 0 3.6 4 3.75 1.075 0.34 1 5 3

4 13 1 3 3 2.909 1 0.277 2 5 2

CBL13 1 12 0 2.667 3 2.6 1.435 0.414 1 5 1

2 14 0 3.5 3.5 3.583 1.345 0.359 1 5 3

3 10 0 3.1 3 3.125 1.449 0.458 1 5 2

4 14 0 3.143 3 3.167 1.231 0.329 1 5 2.75

V ariable Perfo N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1

STH 14 1 12 0 2.083 2 2.1 0.793 0.229 1 3 1.25

2 14 0 2.5 3 2.417 1.092 0.292 1 5 1.75

3 10 0 2.7 3 2.75 0.949 0.3 1 4 2

4 14 0 3 3 2.917 1.038 0.277 2 5 2

70 N 0 F 1 5 1 12 0 2.917 2.5 2.9 1.24 0.358 1 5 2

2 14 0 2.214 2 2.167 0.975 0.261 1 4 1.75

3 10 0 2.7 2 2.5 1.059 0.335 2 5 2

4 14 0 1.714 2 1.75 0.469 0.125 1 2 1

FEFC 16 1 12 0 2.667 3 2.6 1.303 0.376 1 5 1.25

2 13 1 3 3 3 1.155 0.32 1 5 2

3 10 0 2.8 3 2.875 1.033 0.327 1 4 2

4 14 0 3.071 3 3 1.141 0.305 2 5 2

F E 0 H 1 7 1 12 0 3.083 3 3.1 1.165 0.336 1 5 2.25

2 14 0 3.071 3 3.083 1.141 0.305 1 5 2

3 10 0 3 3 3 1.155 0.365 1 5 2

4 14 0 2.714 3 2.667 1.204 0.322 1 5 1.75

V ariable Perfo N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um Q1

STR D 18 1 12 0 3.833 4 3.8 0.718 0.207 3 5 3

2 14 0 3.357 3.5 3.417 1.336 0.357 1 5 2.75

3 10 0 4 4.5 4.125 1.247 0.394 2 5 2.75

4 14 0 3.857 4 3.917 0.864 0.231 2 5 3

N FC 19 1 12 0 3.667 4 3.8 1.231 0.355 1 5 3

2 14 0 3.5 4 3.583 1.225 0.327 1 5 2.75

3 10 0 3.7 4 3.75 0.823 0.26 2 5 3

4 14 0 3.429 3.5 3.417 0.852 0.228 2 5 3

FC E 20 1 12 0 3.333 4 3.4 0.888 0.256 2 4 2.25

71 2 14 0 3.429 3 3.5 1.158 0.309 1 5 3

3 10 0 3.7 4 3.875 1.16 0.367 1 5 3

4 14 0 2.929 3 2.917 1.328 0.355 1 5 1.75

F E 021 1 12 0 3.667 4 3.7 0.492 0.142 3 4 3

2 13 1 3.615 4 3.727 1.044 0.29 1 5 3

3 8 2 3.75 4 3.75 0.707 0.25 3 5 3

4 13 1 4.077 4 4.091 0.641 0.178 3 5 4

V ariable Perfo N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1

IS22 1 12 0 2.583 3 2.6 0.793 0.229 1 4 2

2 14 0 2.429 3 2.417 1.016 0.272 1 4 1

3 10 0 3.1 3 3 0.994 0.314 2 5 2

4 14 0 2.429 2.5 2.417 1.016 0.272 1 4 1.75

U N IS23 1 12 0 3 3 3 1.044 0.302 1 5 2.25

2 14 0 3.143 3 3.167 1.099 0.294 1 5 2

3 10 0 3.1 3 3.125 0.738 0.233 2 4 2.75

4 14 0 3.286 3 3.333 0.994 0.266 1 5 3

U V S24 1 12 0 2.583 2.5 2.5 1.379 0.398 1 5 1.25

2 14 0 2.929 3 3 0.997 0.267 1 4 2.75

3 10 0 3.7 4 3.75 0.949 0.3 2 5 3

4 14 0 2.857 2.5 2.75 1.027 0.275 2 5 2

U IR F27 1 12 0 3 3 3.1 1.128 0.326 1 4 2.25

72 2 14 0 2.786 3 2.75 1.477 0.395 1 5 1

3 10 0 3.2 3 3.25 0.632 0.2 2 4 3

4 14 0 2.714 3 2.75 0.994 0.266 1 4 2

U IRF28 1 12 0 3 3 3 1.206 0.348 1 5 2

2 13 1 3 3 3 1.291 0.358 1 5 2

3 10 0 3.2 3 3.25 1.135 0.359 1 5 2.75

4 13 1 3.077 3 3.091 1.038 0.288 1 5 2.5

U SEZ 29 1 12 0 2.917 3 3 0.996 0.288 1 4 2

2 14 0 3 3.5 3 1.468 0.392 1 5 1.75

3 10 0 3.2 3 3.125 0.919 0.291 2 5 2.75

4 14 0 3.143 3 3.167 1.099 0.294 1 5 2.75

V ariable Perfo N M ean M edian TrM ean StDev SE M ean M inim um M aximum 0 1 0 3

IM H 30 1 12 4.083 4 4.2 0.996 0.288 2 5 3.25 5

2 14 3.357 3.5 3.417 1.216 0.325 1 5 3 4

3 10 4.2 4 4.25 0.632 0.2 3 5 4 5

4 14 3.357 3 3.333 1.008 0.269 2 5 2.75 4

NIS31 1 12 3.25 4 3.3 1.603 0.463 1 5 1.25 4.75

2 14 3.714 4 3.833 1.383 0.37 1 5 2.75 5

3 10 3.4 4 3.5 1.35 0.427 1 5 2.5 4

4 14 3.143 3 3.167 1.099 0.294 1 5 2.75 4

V SF32 1 12 3.333 4 3.5 0.985 0.284 1 4 3 4

73 2 14 3.429 4 3.5 1.342 0.359 1 5 2.75 4.25

3 10 3.3 3 3.25 1.16 0.367 2 5 2 4.25

4 14 3.214 3.5 3.25 1.311 0.35 1 5 2 4

IRPS33 1 12 3.333 4 3.4 1.303 0.376 1 5 2.25 4

2 14 3.643 4 3.75 1.55 0.414 1 5 2 5

3 10 3.6 3.5 3.625 0.966 0.306 2 5 3 4.25

4 14 3.714 4 3.75 0.994 0.266 2 5 3 4.25

IPU 34 1 12 3.583 3.5 3.6 0.9 0.26 2 5 3 4

2 14 4.143 4 4.167 0.77 0.206 3 5 3.75 5

3 10 3.5 4 3.625 0.707 0.224 2 4 3 4

4 14 3.429 4 3.5 0.756 0.202 2 4 3 4

IRFE35 1 12 3.417 4 3.5 1.443 0.417 1 5 2.25 4.75

2 14 4 4 4 0.784 0.21 3 5 3 5

3 10 3.7 4 3.75 1.059 0.335 2 5 2.75 4.25

4 14 3.5 4 3.583 1.286 0.344 1 5 3 4.25

IR F36 1 12 3.75 4 3.9 1.288 0.372 1 5 3 5

2 14 2.929 3 2.917 1.269 0.339 1 5 1.75 4

3 10 3.6 4 3.75 1.174 0.371 1 5 3 4.25

4 14 3.286 4 3.333 1.326 0.354 1 5 2 4

SEC37 1 12 2.5 2.5 2.5 1 0.289 1 4 2 3

2 14 2.571 2 2.5 1.284 0.343 1 5 1.75 4

3 10 3.4 3.5 3.5 1.43 0.452 1 5 2 5

4 14 2.857 3 2.833 0.864 0.231 2 4 2 4

74 APPENDIX V

A N A L Y SIS B Y SIZE

V ariable C lass N M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1 Q3

FCH 6 1 13 3.231 3 3.273 1.166 0.323 1 5 2.5 4

2 26 3.038 3 3.083 0.871 0.171 1 4 3 4

3 11 3 3 3 1.183 0.357 1 5 2 4

FH PR7 1 13 3.154 3 3.091 0.899 0.249 2 5 2.5 4

2 26 3.269 3 3.292 0.962 0.189 1 5 3 4

3 11 3.091 3 3.111 0.701 0.211 2 4 3 4

SW APS8 1 13 3 3 3.091 1.08 0.3 1 4 2.5 4

2 26 2.885 3 2.875 1.143 0.224 1 5 2 4

3 11 3.545 4 3.667 1.036 0.312 1 5 3 4

C B L 9 1 13 2.615 3 2.636 1.193 0.331 1 4 1.5 4

2 26 3.038 3 3.083 0.958 0.188 1 4 2 4

3 11 3.273 3 3.333 0.786 0.237 2 4 3 4

V ariable C lass N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um

FCH 10 1 13 0 3.692 3 3.636 0.855 0.237 3 5

2 26 0 3.423 4 3.458 1.027 0.201 1 5

3 11 0 3.455 4 3.556 1.128 0.34 1 5

FHPR11 1 13 0 3.538 4 3.636 1.266 0.351 1 5

2 26 0 2.769 3 2.75 1.366 0.268 1 5

3 11 0 3.273 4 3.444 1.009 0.304 1 4

75 SW A PS 12 1 13 0 3.308 4 3.364 1.109 0.308 1 5

2 25 1 3.24 3 3.217 1.012 0.202 2 5

3 11 0 3.273 3 3.333 1.272 0.384 1 5

CBL13 1 13 0 3.308 3 3.364 1.251 0.347 1 5

2 26 0 3.077 3 3.083 1.412 0.277 1 5

3 11 0 3 3 3 1.414 0.426 1 5

V ariable Class N N* M ean M edian T rM ean StDev SE M ean M inim um M axim um

STH 14 1 13 0 2.923 3 2.818 0.862 0.239 2 5

2 26 0 2.423 2.5 2.375 0.987 0.194 1 5

3 11 0 2.545 2 2.444 1.214 0.366 1 5

N 0 F 1 5 1 13 0 2.154 2 2.091 0.801 0.222 1 4

2 26 0 2.308 2 2.25 1.087 0.213 1 5

3 11 0 2.636 2 2.556 1.206 0.364 1 5

FEFC 16 1 13 0 3.154 3 3.182 1.068 0.296 1 5

2 25 1 2.88 3 2.87 1.201 0.24 1 5

3 11 0 2.636 2 2.556 1.12 0.338 1 5

F E 0 H 1 7 1 13 0 3.231 3 3.273 1.423 0.395 1 5

2 26 0 2.808 3 2.792 1.167 0.229 1 5

3 11 0 3 3 3 0.632 0.191 2 4

V ariable Class N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1

STR D 18 1 13 0 4 4 4.091 1 0.277 2 5 3

2 26 0 3.577 4 3.625 1.137 0.223 1 5 3

3 11 0 3.818 4 3.889 0.982 0.296 2 5 3

76 N FC 19 1 13 0 3.538 4 3.545 1.127 0.312 2 5 2.5

2 26 0 3.5 4 3.542 0.99 0.194 1 5 3

3 11 0 3.727 4 3.889 1.104 0.333 1 5 3

FC E20 1 13 0 2.923 3 2.909 1.188 0.329 1 5 2

2 26 0 3.308 3.5 3.333 1.123 0.22 1 5 2.75

3 11 0 3.818 4 4 1.079 0.325 1 5 4

F E 021 1 12 1 3.583 4 3.7 0.996 0.288 1 5 3

2 25 1 3.76 4 3.739 0.597 0.119 3 5 3

3 9 2 4.111 4 4.111 0.782 0.261 3 5 3.5

V ariable C lass N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1

IS22 1 13 0 2.846 3 2.818 1.281 0.355 1 5 1.5

2 26 0 2.538 3 2.542 0.859 0.169 1 4 2

3 11 0 2.455 2 2.444 0.82 0.247 1 4 2

UN IS23 1 13 0 3.385 3 3.364 0.87 0.241 2 5 3

2 26 0 3.038 3 3.042 0.916 0.18 1 5 3

3 11 0 3.091 3 3.111 1.221 0.368 1 5 2

U V S24 1 13 0 3.385 3 3.364 1.193 0.331 2 5 2

2 26 0 2.769 3 2.75 1.07 0.21 1 5 2

3 11 0 3 3 3 1.183 0.357 1 5 2

U IR F27 1 13 0 2.615 3 2.636 0.87 0.241 1 4 2

2 26 0 3.038 3 3.042 1.183 0.232 1 5 2

3 11 0 2.909 3 3 1.221 0.368 1 4 2

UIRF28 1 12 1 3.333 3.5 3.4 1.303 0.376 1 5 3

2 25 1 2.88 3 2.87 1.092 0.218 1 5 2

3 11 0 3.182 3 3.111 1.079 0.325 2 5 2

77 U SEZ 29 1 13 0 3.462 4 3.545 1.198 0.332 1 5 2.5

2 26 0 2.769 3 2.75 1.142 0.224 1 5 2

3 11 0 3.273 3 3.222 0.905 0.273 2 5 3

V ariable Class N M ean M edian T rM ean StDev SE M ean M inim um M aximum Qi Q3

IM H 30 1 13 4.154 4 4.182 0.801 0.222 3 5 3.5 5

2 26 3.577 4 3.625 1.102 0.216 1 5 3 4.25

3 11 3.455 ___4_, 3.556 1.128 0.34 1 5 3 4

NIS31 1 13 2.846 3 2.818 1.405 0.39 1 5 1.5 4

2 26 3.5 4 3.542 1.304 0.256 1 5 3 5

3 11 3.727 4 3.889 1.272 0.384 1 5 3 5

V SF32 1 13 3.077 3 3.091 1.115 0.309 1 5 2 4

2 26 3.308 4 3.333 1.258 0.247 1 5 2.75 4

3 11 3.636 4 3.667 1.12 0.338 2 5 3 5

IRPS33 1 13 3.769 4 3.909 1.013 0.281 1 5 3.5 4

2 26 3.462 4 3.5 1.363 0.267 1 5 2 5

3 11 3.636 4 3.667 1.12 0.338 2 5 3 5

IPU 34 1 13 3.615 4 3.636 0.768 0.213 2 5 3 4

2 26 3.731 4 3.75 0.874 0.171 2 5 3 4

3 11 3.636 4 3.667 0.809 0.244 2 5 3 4

IRFE35 1 13 3.385 4 3.455 1.387 0.385 1 5 2.5 4.5

2 26 3.731 4 3.792 1.041 0.204 1 5 3 4

3 11 3.818 4 3.889 1.168 0.352 2 5 3 5

IR F36 1 13 3 4 3 1.581 0.439 1 5 1 4

2 26 3.385 3 3.417 1.169 0.229 1 5 3 4

3 11 3.727 4 3.889 1.104 0.333 1 5 3 4

78 SEC37 1 13 2.769 2 2.727 1.166 0.323 1 5 2 4

2 26 2.577 2.5 2.583 1.027 0.201 1 4 2 3.25

3 11 3.364 3 3.444 1.362 0.411 1 5 2 5

V ariable Perfo N M ean M edian T rM ean StDev SE M ean M inim um M aximum 0 1 0 3

FCH 6 1 12 2.75 3 2.8 0.866 0.25 1 4 2 3

2 14 2.929 3 3 0.829 0.221 1 4 2.75 3.25

3 10 3.3 3.5 3.375 1.337 0.423 1 5 2 4.25

4 14 3.357 3.5 3.417 1.008 0.269 1 5 3 4

FH PR7 1 12 3.333 3 3.3 0.778 0.225 2 5 3 4

2 14 2.929 3 3 0.917 0.245 1 4 2 4

3 10 3 3 3 0.816 0.258 2 4 2 4

4 14 3.5 3.5 3.5 0.941 0.251 2 5 3 4

SW APS 8 1 12 2.667 3 2.7 1.155 0.333 1 4 1.25 3.75

2 14 2.857 3 2.917 1.027 0.275 1 4 2 4

3 10 3.3 3 3.375 1.059 0.335 1 5 3 4

4 14 3.429 4 3.5 1.158 0.309 1 5 3 4

C B L 9 1 12 3.083 3 3.2 0.996 0.288 1 4 2.25 4

2 14 2.714 3 2.75 1.204 0.322 1 4 1.75 4

3 10 3.1 3 3.125 0.738 0.233 2 4 2.75 4

4 14 3.071 3 3.167 0.997 0.267 1 4 2 4

79 V ariable Perfo N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um Q1

FCH 10 1 12 0 3.833 4 3.9 0.937 0.271 2 5 3

2 14 0 3.429 3 3.417 0.756 0.202 2 5 3

3 10 0 3.6 4 3.75 1.35 0.427 1 5 2.75

4 14 0 3.214 3.5 3.333 0.975 0.261 1 4 2.75

FHPR11 1 12 0 2.667 3 2.7 1.073 0.31 1 4 2

2 14 0 3.071 3.5 3.083 1.592 0.425 1 5 1

3 10 0 3.6 4 3.75 1.265 0.4 1 5 2.75

4 14 0 3.071 3 3.083 1.141 0.305 1 5 2.75

SW A PS 12 1 12 0 2.917 2.5 2.9 1.311 0.379 1 5 2

2 14 0 3.571 4 3.583 0.852 0.228 2 5 3

3 10 0 3.6 4 3.75 1.075 0.34 1 5 3

4 13 1 3 3 2.909 1 0.277 2 5 2

CBL13 1 12 0 2.667 3 2.6 1.435 0.414 1 5 1

2 14 0 3.5 3.5 3.583 1.345 0.359 1 5 3

3 10 0 3.1 3 3.125 1.449 0.458 1 5 2

4 14 0 3.143 3 3.167 1.231 0.329 1 5 2.75

V ariable Perfo N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1

STH 14 1 12 0 2.083 2 2.1 0.793 0.229 1 3 1.25

2 14 0 2.5 3 2.417 1.092 0.292 1 5 1.75

3 10 0 2.7 3 2.75 0.949 0.3 1 4 2

80 4 14 0 3 3 2.917 1.038 0.277 2 5 2

N 0 F 1 5 1 12 0 2.917 2.5 2.9 1.24 0.358 1 5 2

2 14 0 2.214 2 2.167 0.975 0.261 1 4 1.75

3 10 0 2.7 2 2.5 1.059 0.335 2 5 2

4 14 0 1.714 2 1.75 0.469 0.125 1 2 1

FEFC 16 1 12 0 2.667 3 2.6 1.303 0.376 1 5 1.25

2 13 1 3 3 3 1.155 0.32 1 5 2

3 10 0 2.8 3 2.875 1.033 0.327 1 4 2

4 14 0 3.071 3 3 1.141 0.305 2 5 2

F E 0 H 1 7 1 12 0 3.083 3 3.1 1.165 0.336 1 5 2.25

2 14 0 3.071 3 3.083 1.141 0.305 1 5 2

3 10 0 3 3 3 1.155 0.365 1 5 2

4 14 0 2.714 3 2.667 1.204 0.322 __ 1 J 5 1.75

V ariable Perfo N N* M ean M edian TrM ean StDev SE M ean M inim um M axim um 0 1

STR D 18 1 12 0 3.833 4 3.8 0.718 0.207 3 5 3

2 14 0 3.357 3.5 3.417 1.336 0.357 1 5 2.75

3 10 0 4 4.5 4.125 1.247 0.394 2 5 2.75

4 14 0 3.857 4 3.917 0.864 0.231 2 5 3

N FC 19 1 12 0 3.667 4 3.8 1.231 0.355 1 5 3

2 14 0 3.5 4 3.583 1.225 0.327 1 5 2.75

3 10 0 3.7 4 3.75 0.823 0.26 2 5 3

4 14 0 3.429 3.5 3.417 0.852 0.228 2 5 3

FC E 20 1 12 0 3.333 4 3.4 0.888 0.256 2 4 2.25

2 14 0 3.429 3 3.5 1.158 0.309 1 5 3

3 10 0 3.7 4 3.875 1.16 0.367 1 5 3

81 4 14 0 2.929 3 2.917 1.328 0.355 1 5 1.75

F E 021 1 12 0 3.667 4 3.7 0.492 0.142 3 4 3

2 13 1 3.615 4 3.727 1.044 0.29 1 5 3

3 8 2 3.75 4 3.75 0.707 0.25 3 5 3

4 13 1 4.077 4 4.091 0.641 0.178 3 5 4

Variable Perfo N N* M ean M edian TrM ean StDev SE M ean M inim um M aximum 0 1

IS22 1 12 0 2.583 3 2.6 0.793 0.229 1 4 2

2 14 0 2.429 3 2.417 1.016 0.272 1 4 1

3 10 0 3.1 3 3 0.994 0.314 2 5 2

4 14 0 2.429 2.5 2.417 1.016 0.272 1 4 1.75

U N IS23 1 12 0 3 3 3 1.044 0.302 1 5 2.25

2 14 0 3.143 3 3.167 1.099 0.294 1 5 2

3 10 0 3.1 3 3.125 0.738 0.233 2 4 2.75

4 14 0 3.286 3 3.333 0.994 0.266 1 5 3

U V S24 1 12 0 2.583 2.5 2.5 1.379 0.398 1 5 1.25

2 14 0 2.929 3 3 0.997 0.267 1 4 2.75

3 10 0 3.7 4 3.75 0.949 0.3 2 5 3

4 14 0 2.857 2.5 2.75 1.027 0.275 2 5 2

U IRF27 1 12 0 3 3 3.1 1.128 0.326 1 4 2.25

2 14 0 2.786 3 2.75 1.477 0.395 1 5 1

3 10 0 3.2 3 3.25 0.632 0.2 2 4 3

4 14 0 2.714 3 2.75 0.994 0.266 1 4 2

U IR F28 1 12 0 3 3 3 1.206 0.348 1 5 2

2 13 1 3 3 3 1.291 0.358 1 5 2

3 10 0 3.2 3 3.25 1.135 0.359 1 5 2.75

82 4 13 1 3.077 3 3.091 1.038 0.288 1 5 2.5

U SEZ 29 1 12 0 2.917 3 3 0.996 0.288 1 4 2

2 14 0 3 3.5 3 1.468 0.392 1 5 1.75

3 10 0 3.2 3 3.125 0.919 0.291 2 5 2.75

4 14 0 3.143 3 3.167 1.099 0.294 1 5 2.75

V ariable Perfo N M ean M edian T rM ean StDev SE M ean M inim um M axim um 0 1 0 3

IM H 30 1 12 4.083 4 4.2 0.996 0.288 2 5 3.25 5

2 14 3.357 3.5 3.417 1.216 0.325 1 5 3 4

3 10 4.2 4 4.25 0.632 0.2 3 5 4 5

4 14 3.357 3 3.333 1.008 0.269 2 5 2.75 4

N1S31 1 12 3.25 4 3.3 1.603 0.463 1 5 1.25 4.75

2 14 3.714 4 3.833 1.383 0.37 1 5 2.75 5

3 10 3.4 4 3.5 1.35 0.427 1 5 2.5 4

4 14 3.143 3 3.167 1.099 0.294 1 5 2.75 4

V SF32 1 12 3.333 4 3.5 0.985 0.284 1 4 3 4

2 14 3.429 4 3.5 1.342 0.359 1 5 2.75 4.25

3 10 3.3 3 3.25 1.16 0.367 2 5 2 4.25

4 14 3.214 3.5 3.25 1.311 0.35 1 5 2 4

IRPS33 1 12 3.333 4 3.4 1.303 0.376 1 5 2.25 4

2 14 3.643 4 3.75 1.55 0.414 1 5 2 5

3 10 3.6 3.5 3.625 0.966 0.306 2 5 3 4.25

4 14 3.714 4 3.75 0.994 0.266 2 5 3 4.25

IPU 34 1 12 3.583 3.5 3.6 0.9 0.26 2 5 3 4

2 14 4.143 4 4.167 0.77 0.206 3 5 3.75 5

3 10 3.5 4 3.625 0.707 0.224 2 4 3 4

83 4 14 3.429 4 3.5 0.756 0.202 2 4 3 4

IRFE35 1 12 3.417 4 3.5 1.443 0.417 1 5 2.25 4.75

2 14 4 4 4 0.784 0.21 3 5 3 5

3 10 3.7 4 3.75 1.059 0.335 2 5 2.75 4.25

4 14 3.5 4 3.583 1.286 0.344 1 5 3 4.25

IRF36 1 12 3.75 4 3.9 1.288 0.372 1 5 3 5

2 14 2.929 3 2.917 1.269 0.339 1 5 1.75 4

3 10 3.6 4 3.75 1.174 0.371 1 5 3 4.25

4 14 3.286 4 3.333 1.326 0.354 1 5 2 4

SEC37 1 12 2.5 2.5 2.5 1 0.289 1 4 2 3

2 14 2.571 2 2.5 1.284 0.343 1 5 1.75 4

3 10 3.4 3.5 3.5 1.43 0.452 1 5 2 5

4 14 2.857 3 2.833 0.864 0.231 2 4 2 4

84 APPENDIX VI

Capitalization of firms at the NSE

Jul-12 C om pany MRT CAP '000' A.Baumann & Co Ltd Ord 5.00 AIM 42624.7326 AccessKenya Group Ltd Ord. 1.00 998804.6208 Athi River Mining Ord 5.00 19711945 B.O.C Kenya Ltd Ord 5.00 2362578.966 Bamburi Cement Ltd Ord 5.00 59888280.38 Barclays Bank Ltd Ord 0.50 71696275.2 British American Tobacco Kenya Ltd Ord 10.00 38000000 British-American Investments Co(Kenya) Ltd Ord 0.10 9930122.213 Car & General (K) Ltd Ord 5.00 935743.872 Carbacid Investments Ltd Ord 5.00 4145592.33 Centum Investment Co Ltd Ord 0.50 8684015.164 CFC Insurance Holdings Ltd ord. 1.00 4070635.876 CFC Stanbic Holdings Ltd ord.5.00 11973684.23 City Trust Ltd Ord 5.00 AIM 1598199.606 CMC Holdings Ltd Ord 0.50 7866577.44 Crown Berger Ltd Ord 5.00 806718 Diamond Trust Bank Kenya Ltd Ord 4.00 18684052.62 E.A.Cables Ltd Ord 0.50 2645156.25 E.A.Portland Cement Ltd Ord 5.00 5400000 Eaagads Ltd Ord 1.25 AIM 514512 East African Breweries Ltd Ord 2.00 188995071.1 Equity Bank Ltd Ord 0.50 79609705.93 Eveready East Africa Ltd Ord. 1.00 357000 Express Ltd Ord 5.00 AIM 139844.9705 Housing Finance Co Ltd Ord 5.00 3536250 Hutchings Biemer Ltd Ord 5.00 7290 Jubilee Holdings Ltd Ord 5.00 8984250 Kakuzi Ord.5.00 1567999.92 Kapchorua Tea Co. Ltd Ord Ord 5.00 AIM 489000 KenGen Ltd Ord. 2.50 19125744.67 KenolKobil Ltd Ord 0.05 23474591.14 Kenya Airways Ltd Ord 5.00 21474330.65 Kenya Commercial Bank Ltd Ord 1.00 69021239.93 Kenya Orchards Ltd Ord 5.00 AIM 38604.372 Kenya Power & Lighting Co Ltd Ord 2.50 29759872.44 Kenya Re-Insurance Corporation Ltd Ord 2.50 6330000 85 Limuru Tea Co. Ltd Ord 20.00 AIM 540000 Longhorn Kenya Ltd Ord 1.00 1091025 Marshalls (E.A.) Ltd Ord 5.00 179194.1697 Mumias Sugar Co. Ltd Ord 2.00 9486000 Nation Media Group Ord. 2.50 27652868.67 National Bank of Kenya Ltd Ord 5.00 5600000 NIC Bank Ltd Ord 5.00 14315036.62 Olympia Capital Holdings ltd Ord 5.00 144000 Pan Africa Insurance Holdings Ltd Ord 5.00 3552000 Rea Vipingo Plantations Ltd Ord 5.00 963000 Safaricom Ltd Ord 0.05 142000000 Sameer Africa Ltd Ord 5.00 1141203.811 Sasini Ltd Ord 1.00 2839290.975 Scangroup Ltd Ord 1.00 14666640.09 Standard Chartered Bank Ltd Ord 5.00 57415426.6 Standard Group Ltd Ord 5.00 1740387.111 The Co-operative Bank of Kenya Ltd Ord 1.00 46937464.9 Total Kenya Ltd Ord 5.00 2704193.508 TPS Eastern Africa (Serena) Ltd Ord 1.00 6743584.12 Trans-Century Ltd Ord 0.50 AIM 6574806.816 Uchumi Supermarket Ltd Ord 5.00 4260097.155 Unga Group Ltd Ord 5.00 976644.4617 Williamson Tea Kenya Ltd Ord 5.00 AIM 2451769.6

Source: Nairobi Securities Exchange

86 APPENDIX VII Performance of companies at the NSE

PERFORMANCE Company RPShare(%) PerClass British-American Investments Co(Kenya) Ltd Ord 1 0.10 263.21 1 2 Pan Africa Insurance Holdings Ltd Ord 5.00 78.31 1 3 KenolKobil Ltd Ord 0.05 56.37 1 4 Limuru Tea Co. Ltd Ord 20.00 50.50 1 5 British American Tobacco Kenya Ltd Ord 10.00 46.15 1 6 Williamson Tea Kenya Ltd Ord 5.00 33.97 1 7 Uchumi Supermarket Ltd Ord 5.00 33.75 1 8 City Trust Ltd Ord 5.00 32.86 1 9 Unga Group Ltd Ord 5.00 30.30 1 10 Kenya Airways Ltd Ord 5.00 25.73 1 11 CMC Holdings Ltd Ord 5.00 22.73 1 12 Kenya Re-Insurance Corporation Ltd Ord 2.50 22.67 1 13 East African Breweries Ltd Ord 2.00 21.94 1 14 Crown Berger Ltd Ord 5.00 13.33 1 15 Sasini Ltd Ord 5.00 12.16 2 16 Kakuzi Ord.5.00 11.11 2 17 Rea Vipingo Plantations Ltd Ord 5.00 10.69 2 18 Athi River Mining Ord 5.00 9.34 2 19 Nation Media Group Ord. 5.00 6.67 2 20 Longhorn Kenya Ltd Ord 1.00 5.07 2 21 B.O.C Kenya Ltd Ord 5.00 3.42 2 22 Jubilee Holdings Ltd Ord 5.00 1.97 2 23 A.Baumann & Co.Ltd Ord 5.00 0.00 2 24 Carbacid Investments Ltd Ord 5.00 0.00 2 25 Hutchings Biemer Ltd Ord 5.00 0.00 2 26 Kenya Orchards Ltd Ord 5.00 0.00 2 27 Kenya Commercial Bank Ltd Ord 10.00 -0.44 2 28 ScanGroup Ord. 1.00 -1.90 2 29 Marshalls (E.A.) Ltd Ord 5.00 -2.35 2 30 Kapchorua Tea Co. Ltd Ord Ord 5.00 -7.41 2 31 Bamburi Cement Ltd Ord 5.00 -8.33 3 32 Safaricom Ltd Ord.0.05 -8.97 3 33 Car & General (K) Ltd Ord 5.00 -9.68 3 34 Mumias Sugar Co. Ltd Ord 2.00 -13.29 3 35 CFC Stanbic Holdings Ltd ord.5.00 -15.05 3 36 Standard Chartered Bank Ltd Ord 5.00 -15.25 3 87 37 Equity Bank Ltd Ord 0.5 -15.69 3 38 The Co-operative Bank of Kenya Ord. 1.00 -16.00 3 39 NIC Bank Ltd Ord 5.00 -16.67 3 40 Eveready East Africa Ltd Ord. 1.00 -17.07 3 41 Olympia Capital Holdings ltd Ord 5.00 -18.18 3 42 Kenya Power & Lighting Ltd Ord 20.00 -18.30 3 43 Express Ltd Ord 5.00 -18.56 3 44 Sameer Africa Ltd Ord 5.00 -19.61 3 45 E.A.Cables Ltd Ord 5.00 -19.62 3 46 Diamond Trust Bank Kenya Ltd Ord 4.00 -19.75 4 47 Barclays Bank Ltd Ord 10.00 -21.89 4 48 Eaagads Ltd Ord 1.25 -22.42 4 49 E.A.Portland Cement Ltd Ord 5.00 -25.00 4 50 TPS Eastern Africa (Serena) Ltd Ord 1.00 -32.09 4 51 Standard Group Ltd Ord 5.00 -32.86 4 52 AccessKenya Group Ltd Ord. 1.00 -33.33 4 53 Housing Finance Co Ltd Ord 5.00 -35.48 4 54 KenGen Ltd. Ord. 2.50 -35.56 4 55 Trans-Century Ltd Ord 0.50 AIM -36.84 4 56 Total Kenya Ltd Ord 5.00 -36.94 4 57 Centum Investment Co. Ltd Ord 5.00 -38.26 4 58 National Bank of Kenya Ltd Ord 5.00 -41.18 4 59 CFC Insurance Holdings Ltd ord. 1.00 -46.44 4

Source: Nairobi Securities Exchange

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