DOCSLIB.ORG

Outperforming Cap-Weighted Indices with Limited Risk of Underperformance

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Outperforming Cap-Weighted Indices with Limited Risk of Underperformance JPM_Cover.qxp:Cover 4/17/12 9:02 AM Page 1 THE JOURNAL OF PORTFOLIO MANAGEMENT VOLUME 38 NUMBER 3 www.iijpm.com SPRING 2012 Diversifying the Diversifiers and Tracking the Tracking Error: Outperforming Cap-Weighted Indices with Limited Risk of Underperformance OËL MENC ELIX OLTZ SHISH ODH SPRING 2012 VOLUME 38, NUMBER 3 N A , F G , A L , AND LIONEL MARTELLINI NOËL AMENC odern portfolio theory states Following such early criticism of cap- is a professor of finance that investors should allocate weighted equity portfolios, more recent papers at EDHEC Business their wealth between a tan- have documented that cap-weighted portfo- School and a director of EDHEC-Risk Institute gency portfolio, or maximum lios suffer from numerous shortcomings, and in London, UK. MSharpe ratio (MSR) portfolio, and a riskless various alternative weighting schemes have [email protected] asset. In practice, when trying to follow this been proposed to improve on cap weighting; advice, one obviously has to come up with see Amenc et al. [2011], Arnott, Hsu, and FELIX GOLTZ proxies because neither the true tangency Moore [2005], Choueifaty and Coignard is head of applied research portfolio nor a perfectly risk-free asset can be [2008], and Maillard, Roncalli, and Teiletche at the EDHEC-Risk Insti- tute at EDHEC Business exactly implemented in practice. Traditionally, [2008], to name but a few. School in Nice, France. equity investing has, however, heavily drawn Although it is now commonly accepted [email protected] on the idea of the Tobin separation theorem, that movingThe awayVoi cesfrom of cap Influence weighting | tends iijournals.com and cap-weighted equity indices have long to enhance diversification and increase risk- ASHISH LODH been perceived by many practitioners as rea- adjusted performance over long horizons, it is a quantitative analyst with the EDHEC-Risk sonable proxies for the tangency portfolio. But has to be recognized that each alternative Institute89138_cover.indd at EDHEC 1 a consensus is slowly emerging that market- weighting scheme will expose an investor to 5/11/12 1:18 PM Business School in cap-weighted indices tend to be poorly diver- two related types of risk, namely, model selec- Nice, France. sified portfolios that are not good proxies for tion risk and relative performance risk. [email protected] the tangency portfolio. This result is hardly a Considering model selection risk, it is new finding, because early attempts to provide clear that choosing a weighting scheme corre- LIONEL MARTELLINI is a professor of finance at evidence that cap-weighted portfolios are not sponds to choosing a model of optimal port- EDHEC Business School well-diversified portfolios and thus lead to an folio construction. This is the case, in fact, and scientific director of inefficient risk–return trade-off can be traced even if a weighting scheme does not explic- EDHEC-Risk Institute as far back as Haugen and Baker [1991] or itly refer to portfolio optimization. In fact, in Nice, France. Grinold [1992]. Intuitively, the fact that cap- any weighting scheme can be understood as [email protected] weighted indices are inefficient and poorly reflecting a set of assumptions under which the diversified is perhaps not surprising because resulting portfolio would lead to an optimal they concentrate heavily in the largest mar- portfolio in the sense of modern portfolio ket-cap stocks as a result of their one-dimen- theory; see Martellini [forthcoming] or Melas sional construction mechanism that only takes and Kang [2010]. From a pragmatic perspec- into account a stock’s market cap and thus tive, it seems reasonable to assume that dif- does not allow for any mechanism that can ferent market conditions may favor different enforce proper diversification. assumptions, and thus alternative weighting 72 DIVERSIFYING THE DIVERSIFIERS AND TRACKING THE TRACKING ERROR SPRING 2012 JPM-AMENC.indd 72 4/14/12 11:23:48 AM Diversifying the Diversifiers and Tracking the Tracking Error: Outperforming Cap-Weighted Indices with Limited Risk of Underperformance NOËL AMENC, FELIX GOLTZ, ASHISH LODH, AND LIONEL MARTELLINI NOËL AMENC odern portfolio theory states Following such early criticism of cap- is a professor of finance that investors should allocate weighted equity portfolios, more recent papers at EDHEC Business their wealth between a tan- have documented that cap-weighted portfo- School and a director of EDHEC-Risk Institute gency portfolio, or maximum lios suffer from numerous shortcomings, and in London, UK. MSharpe ratio (MSR) portfolio, and a riskless various alternative weighting schemes have [email protected] asset. In practice, when trying to follow this been proposed to improve on cap weighting; advice, one obviously has to come up with see Amenc et al. [2011], Arnott, Hsu, and FELIX GOLTZ proxies because neither the true tangency Moore [2005], Choueifaty and Coignard is head of applied research portfolio nor a perfectly risk-free asset can be [2008], and Maillard, Roncalli, and Teiletche at the EDHEC-Risk Insti- tute at EDHEC Business exactly implemented in practice. Traditionally, [2008], to name but a few. School in Nice, France. equity investing has, however, heavily drawn Although it is now commonly accepted [email protected] on the idea of the Tobin separation theorem, that moving away from cap weighting tends and cap-weighted equity indices have long to enhance diversification and increase risk- ASHISH LODH been perceived by many practitioners as rea- adjusted performance over long horizons, it is a quantitative analyst with the EDHEC-Risk sonable proxies for the tangency portfolio. But has to be recognized that each alternative Institute at EDHEC a consensus is slowly emerging that market- weighting scheme will expose an investor to Business School in cap-weighted indices tend to be poorly diver- two related types of risk, namely, model selec- Nice, France. sified portfolios that are not good proxies for tion risk and relative performance risk. [email protected] the tangency portfolio. This result is hardly a Considering model selection risk, it is new finding, because early attempts to provide clear that choosing a weighting scheme corre- LIONEL MARTELLINI is a professor of finance at evidence that cap-weighted portfolios are not sponds to choosing a model of optimal port- EDHEC Business School well-diversified portfolios and thus lead to an folio construction. This is the case, in fact, and scientific director of inefficient risk–return trade-off can be traced even if a weighting scheme does not explic- EDHEC-Risk Institute as far back as Haugen and Baker [1991] or itly refer to portfolio optimization. In fact, in Nice, France. Grinold [1992]. Intuitively, the fact that cap- any weighting scheme can be understood as [email protected] weighted indices are inefficient and poorly reflecting a set of assumptions under which the diversified is perhaps not surprising because resulting portfolio would lead to an optimal they concentrate heavily in the largest mar- portfolio in the sense of modern portfolio ket-cap stocks as a result of their one-dimen- theory; see Martellini [forthcoming] or Melas sional construction mechanism that only takes and Kang [2010]. From a pragmatic perspec- into account a stock’s market cap and thus tive, it seems reasonable to assume that dif- does not allow for any mechanism that can ferent market conditions may favor different enforce proper diversification. assumptions, and thus alternative weighting DIVERSIFYING THE DIVERSIFIERS AND TRACKING THE TRACKING ERROR SPRING 2012 JPM-AMENC.indd 72 4/14/12 11:23:48 AM schemes may display different performance depending to overperforming the same index by 11.17%, while on market conditions. In fact, when analyzing the per- the minimum-volatility strategy followed the opposite formance of alternative weighting schemes, it is indeed trend. This kind of behavior points to the fact that each the case that performance differences can be pronounced, model behaves well only in a certain kind of market as evidenced by the results shown in Exhibit 1, which condition. Another noteworthy result is that the differ- uses data for four popular non-cap-weighted indices in ence between returns of the best- and worst-performing the U.S. universe over a relatively short time horizon for strategies is substantial and can be as large as 15%. This which data for all of these indices are available. means that no model can pretend to be uniquely supe- It appears that even in a relatively short span of rior. Rather, different models are apparently favored by nine years no single strategy consistently outperforms all different market conditions, and there is always a risk other strategies, even though all four strategies show out- that the chosen model may not yield attractive perfor- performance with respect to cap-weighted indices more mance in a given period. often than they show underperformance. Considering For investors who are agnostic about either their half-year returns, depending on the market conditions, capacity to identify the model with superior assumptions each of the four strategies has ex post been the best-per- or their capacity to take the risk of choosing a particular forming strategy for some subperiod. Also, the worst- model in the wrong market conditions, it may be rea- per forming strategy in one subperiod can be the best sonable to assess whether anything can be gained from performer in the subsequent subperiod, and vice versa. combining models and thus diversifying model selection For example, across two half-year periods from July 2008 risk; see, for example, Kan and Zhou [2007] for a related to June 2009, the equal-weighted strategy went from discussion about combining portfolio strategies. We underperforming the cap-weighted index by –4.53% explore this question in some detail in the next section.
Load more

Recommended publications
  • Asset and Risk Allocation Policy
    ____________________________________________________________________________ UNIVERSITY OF CALIFORNIA GENERAL ENDOWMENT POOL ASSET AND RISK ALLOCATION POLICY Approved March 15, 2018 ______________________________________________________________________________ UNIVERSITY OF CALIFORNIA GENERAL ENDOWMENT POOL ASSET AND RISK ALLOCATION POLICY POLICY SUMMARY/BACKGROUND The purpose of this Asset and Risk Allocation Policy (“Policy”) is to define the asset types, strategic asset allocation, risk management, benchmarks, and rebalancing for the University of California General Endowment Pool (“GEP”). The Investments Subcommittee has consent responsibilities over this policy. POLICY TEXT ASSET CLASS TYPES Below is a list of asset class types in which the GEP may invest so long as they do not conflict with the constraints and restrictions described in the GEP Investment Policy Statement. The criteria used to determine which asset classes may be included are: Positive contribution to the investment objective of GEP Widely recognized and accepted among institutional investors Low cross correlations with some or all of the other accepted asset classes Based on the criteria above, the types of assets for building the portfolio allocation are: 1. Public Equity Includes publicly traded common and preferred stock of issuers domiciled in US, Non-US, and Emerging (and Frontier) Markets. The objective of the public equity portfolio is to generate investment returns with adequate liquidity through a globally diversified portfolio of common and preferred stocks. 2. Liquidity (Income) Liquidity includes a variety of income related asset types. The portfolio will invest in interest bearing and income based instruments such as corporate and government bonds, high yield debt, emerging markets debt, inflation linked securities, cash and cash equivalents. The portfolio can hold a mix of traditional (benchmark relative) strategies and unconstrained (benchmark agnostic) strategies.
    [Show full text]
  • Tracking Error
    India Index Services & Products Ltd. Tracking Error TRACKING ERROR An Index Fund is a mutual fund scheme that invests in the securities in the target Index in the same proportion or weightage of the securities as it bears to the target index. The investment objective of an index fund is to achieve returns which are commensurate to that of the target Index. An investment manager attempts to replicate the investment results of the target index by holding all the securities in the Index. Though Index Funds are designed to provide returns that closely track the benchmarked Index, Index Funds carry all the risks associated with the type of asset the fund holds. Indexing merely ensures that the returns of the Index Fund will not stray far from the returns on the Index that the fund mimics. Still there are instances, which are mentioned below, that leads to mismatch of the returns of the index with that of the fund. This mismatch or the difference in the returns of the Index with that of the fund is known as Tracking Error. Tracking Error Tracking error is defined as the annualised standard deviation of the difference in returns between the Index fund and its target Index. In simple terms, it is the difference between returns from the Index fund to that of the Index. An Index fund manager needs to calculate his tracking error on a daily basis especially if it is open-ended fund. Lower the tracking error, closer are the returns of the fund to that of the target Index.
    [Show full text]
  • TRACKING ERROR: an Essential Tool in Evaluating Index Funds
    JOURNAL OF INVESTMENT CONSULTING TRACKING ERROR: An Essential Tool in Evaluating Index Funds By Chris Tobe, CFA As the dollars being indexed grow and portfolio management becon1es more sophisticated, consultants should demand tighter tracking to the index in question from their index n1anagers. In fact, the key to assessiI1g index fund managers is determining if their performance has tracked their benchmarks within reasonable tolerances. The alltl10r reviews what is known about this aspect of performance evaluation. He also sl1ares 11is experie11ce in detern1ining what factors caused a difference in performance for a $3 billion S&P 500 index fund. This article is based on a study written by the author and should be no attempt to outperform the index or Dr. Ken Miller for Kentucky State Auditor Edward B. bencl1mark. William F Sharpe holds that a passive Hatchett Jr. The study was reported in the July 27, 1998, strategy requires the manager issue of Pensions and Investments. Earlier versions of this ... to hold every security from the market, with each article were presented at two conferences on indexing. represented in the same manner as in the n1arket. Thus, if security X represents 3 percent of the value ver $1 trillion is now being managed of the securities in the market, a passive investor's within index funds. Lipper lists the portfolio will have 3 percent of its value invested in Vanguard 500 Index fund as the second X. Equivalently; a passive manager will hold the same percentage of the total outstanding amount of largest stock fllnd in the world with a each security in the market.
    [Show full text]
  • Hedging Climate Risk Mats Andersson, Patrick Bolton, and Frédéric Samama
    AHEAD OF PRINT Financial Analysts Journal Volume 72 · Number 3 ©2016 CFA Institute PERSPECTIVES Hedging Climate Risk Mats Andersson, Patrick Bolton, and Frédéric Samama We present a simple dynamic investment strategy that allows long-term passive investors to hedge climate risk without sacrificing financial returns. We illustrate how the tracking error can be virtually eliminated even for a low-carbon index with 50% less carbon footprint than its benchmark. By investing in such a decarbonized index, investors in effect are holding a “free option on carbon.” As long as climate change mitigation actions are pending, the low-carbon index obtains the same return as the benchmark index; but once carbon dioxide emissions are priced, or expected to be priced, the low-carbon index should start to outperform the benchmark. hether or not one agrees with the scientific the climate change debate is not yet fully settled and consensus on climate change, both climate that climate change mitigation may not require urgent Wrisk and climate change mitigation policy attention. The third consideration is that although the risk are worth hedging. The evidence on rising global scientific evidence on the link between carbon dioxide average temperatures has been the subject of recent (CO2) emissions and the greenhouse effect is over- debates, especially in light of the apparent slowdown whelming, there is considerable uncertainty regarding in global warming over 1998–2014.1 The perceived the rate of increase in average temperatures over the slowdown has confirmed the beliefs of climate change next 20 or 30 years and the effects on climate change. doubters and fueled a debate on climate science There is also considerable uncertainty regarding the widely covered by the media.
    [Show full text]
  • Tracking Error and the Information Ratio
    It Is More Than]ust Performance: TRACKING ERROR AND THE INFORMATION RATIO By Jay L. Shein, Ph.D., ClMA, CFP ONE OF OUR MOST POPULAR CONTRIBUTORS REVIEWS SOME QUANTITATIVE TECHNIQUES THAT CAN ASSIST THE CONSULTANT IN MANAGER SELECTIONS AND IN ASSET ALLOCATION DESIGN. Introduction properly these statistical measures can be dentifying and selecting the most appropri­ useful tools. ate mutual fund or money manager to use Tracking error was defined by Tobe (1999) as in an investor's portfolio are major aspects the percentage difference in total return between of the investment consultants responsibili­ an index fund and the benchmark index the fund ties. This is true for both active and passive was designed to replicate. This definition of track­ money manager searches and selection. ing error is best used for evaluation of a passive When searching for and selecting money man­ manager such as an index fund. Tracking error agers, consultants and investment advisors typical­ used in the context of active manager evaluation is ly look at both qualitative and quantitative infor­ better defined as active manager risk. For purpos­ mation before making their recommendations. The es of this commentary, tracking error is defined as investment consultant knows that items such as the standard deviation between two return series philosophy, process, people, and strategic business written as: 1 plans are important, if not sometimes more impor­ tant than historical performance. Even though the qualitative side is important, the investment con­ TE= i-I sultant will ultimately use some quantitative mea­ N-l sure such as a ratio, statistic, risk-adjusted measure of performance, and/or absolute performance to Where: validate the qualitative component of money man­ IE = Tracking Error ager search and selection.
    [Show full text]
  • Risk Attribution and Portfolio Performance Measurement$An Overview 1
    Risk Attribution and Portfolio Performance Measurement-An Overview Yongli Zhang Department of Economics University of California, Santa Barbara, CA93016, USA Svetlozar Rachev Department of Econometrics and Statistics University of Karlsruhe, D-76128 Karlsruhe, Germany and Department of Statistics and Applied Probability University of California, Santa Barbara, CA93106, USA September, 2004 Abstract A major problem associated with risk management is that it is very hard to identify the main resource of risk taken, especially in a large and complex portfolio. This is due to the fact that the risk of individual securities in the portfolio, measured by most of the widely used risk measures such as standard deviation and value-at-risk, don’t sum up to the total risk of the portfolio. Although the risk measure of beta in the Capital Asset Pricing Model seems to survive this major de…ciency, it su¤ers too much from other pitfalls to become a satis- factory solution. Risk attribution is a methodology to decompose the total risk of a portfolio into smaller terms. It can be applied to any positive homogeneous risk measures, even free of models. The problem is solved in a way that the smaller decomposed units of the total risk are interpreted as the risk contribution of the corresponding subsets of the portfolio. We present here an overview of the methodology of risk attribution, di¤erent risk measures and their properties. S. Rachev’s research was supported by grants from Division of Mathematical, Life and Physical Sciences, College of Letters and Science, University of California at Santa Barbara and the Deutschen Forschungsgemeinschaft.
    [Show full text]
  • Understanding Active Risk and Tracking Error by Commonfund |
    Quant Corner: Understanding Active Risk and Tracking Error by Commonfund | www.commonfund.org Investors frequently focus on the total return they Yet good performance and bad performance should not be experience in their portfolios. In periods when absolute evaluated in a vacuum, they should be evaluated relative to returns are high, they feel good; in periods when the risks undertaken in their portfolios. Indeed, these risks absolute returns are low, they feel bad. are typically reflected in the investor’s benchmark, or policy portfolio which embodies the tradeoffs between an inves- tor’s appetite for risk and desire for return over long periods of time. For instance, an investor may feel that a 70% MSCI ACWI Global Equity Index/30% Barclays U.S. Aggregate Bond Index (70/30) benchmark appropriately captures this tension. When equity outperforms fixed income, the 70/30 investor would be expected to trail an 80/20 portfolio and beat a 60/40 portfolio. Appropriate benchmarking is the first step in the investment decision-making process. Quant Corner: Understanding Active Risk and Tracking Error Past performance is not indicative of future results. Source: Commonfund Research The second step is measuring performance relative to that The first chart shows rolling 12-month absolute and active benchmark. This requires a shift in frame of reference from returns for this custom portfolio. absolute return and absolute risk to active return and active risk.1 Active return equals the difference in return between It is evident from the chart that both absolute returns and a portfolio and its benchmark. Tracking error, as active risk active returns vary significantly over time and, furthermore, is more commonly called, measures the volatility of active that the volatility of absolute and active returns also changes returns.
    [Show full text]
  • Lazard UK Omega Equity Fund B Dist
    Lazard July 2019 UK Omega Equity Fund Fact Sheet B Dist GBP Share Class A sub-fund of Lazard Global Active Funds PLC, a Dublin-based OEIC Performance Data (Annualised Return* in GBP % p.a.) Periods ended 31 July 2019 12 Months ended 31 December 1M 3M YTD 1Y 3Y 5Y 10Y 2018 2017 2016 2015 2014 Lazard UK Omega Equity Fund -0.3 -1.2 11.3 -6.6 4.5 3.8 6.4 -16.0 12.6 15.7 -2.2 -0.4 Quartile 4 4 4 4 4 4 4 4 2 2 4 4 MStar UK Large-Cap Blend Equity 2.0 2.1 15.1 0.5 7.3 6.1 9.4 -9.8 11.6 13.1 2.4 1.0 FTSE All-Share Index 2.0 2.6 15.2 1.3 8.3 6.8 9.6 -9.5 13.1 16.8 1.0 1.2 Source: Morningstar, NAV to NAV basis, Net Income Reinvested, Net of Fees. Past performance is not a reliable indicator of future results. *Performance data for periods less than 1 year is illustrated on a cumulative growth basis. Investors may be liable to taxation on the income from the fund, depending upon their personal circumstances. The effect of taxation would have been to reduce the returns stated. £100 Invested Over Five Years 145 130 115 100 85 Jul 2014 Jul 2015 Jul 2016 Jul 2017 Jul 2018 Jul 2019 Lazard UK Omega Equity Fund (20.78%) FTSE All-Share Index (38.95%) MStar UK Large-Cap Blend Equity (34.84%) Source: Morningstar, Cumulative Growth, NAV to NAV Price, Net of fees, Net Income Reinvested to 31 July 2019 in GBP.
    [Show full text]
  • How to Manage Tracking Error with Greater Certainty
    Hillsdale Investment Management Inc. How to Manage Tracking MayError 2014 with Greater Certainty White Paper Series October 2015 WHITE PAPER SERIES Alfred Sum, MASc, FRM, CFA Portfolio Manager, Partner Harry Marmer, MBA, CFA Executive Vice President, Partner Chris Guthrie, BA, CFA President and CEO OCTOBER 2015 How to Manage Tracking Error with Greater Certainty Alfred Sum, Portfolio Manager, Partner, Hillsdale Investment Management Inc. Harry Marmer, Executive Vice President, Partner, Hillsdale Investment Management Inc. Chris Guthrie, President and CEO, Hillsdale Investment Management Inc. Abstract In the Canadian equity manager universe, there is no evidence that tracking error risk is proactively managed. This is especially troubling and surprising given that tracking error is an important measure of active investment management risk as it provides investors with a tool to estimate the expected variability of their manager’s value added. This paper examines two different techniques a Canadian equity manager can employ to manage tracking error risk. The first approach employs an optimization model where the objective is to control tracking error and to maximize a portfolio’s information ratio, which is an important measure of the portfolio’s risk‐adjusted active return. However, using an optimizer to control tracking error is not the ideal solution as it has limited capability in forecasting and effectively managing tracking error. Instead, we employ an intuitive multi‐strategy allocation process that manages tracking error with greater certainty providing for superior risk‐adjusted returns and consistent attributes. This approach is not only valuable for managers but for investors as well for it provides them with a higher degree of confidence that their investment managers will achieve their investment objectives resulting in superior value added adjusted for risk.
    [Show full text]
  • Is the Tracking Error Time Varying? Evidence from Agricultural Etcs
    Is the tracking error time varying? Evidence from agricultural ETCs Revised: 15 June 2019 Abstract This study conducts an extensive analysis of a recently popularized asset class, namely, exchange-traded commodities (ETCs). We demonstrate that the tracking error of ETCs is dependent on the volatility of the underlying commodity prices but not persistent. Furthermore, we find the tracking ability of agricultural ETCs is affected by the replication method and also by the leverage of the ETCs. Our findings are important for academics and market regulators, as they indicate the structure of an ETC matters for its tracking performance. Keywords: Agricultural Commodity Market, Exchange-Traded Commodities, Markov Switching Regression, Tracking Error JEL Classification: C24, G14, G23, Q14 Is the tracking error time varying? Evidence from agricultural ETCs Devmali Perera* Jedrzej Bialkowski† Martin T. Bohl‡ Revised: 15 June 2019 Abstract This study conducts an extensive analysis of a recently popularized asset class, namely, exchange-traded commodities (ETCs). We demonstrate that the tracking error of ETCs is dependent on the volatility of the underlying commodity prices but not persistent. Furthermore, we find the tracking ability of agricultural ETCs is affected by the replication method and also by the leverage of the ETCs. Our findings are important for academics and market regulators, as they indicate the structure of an ETC matters for its tracking performance. Keywords: Agricultural Commodity Market, Exchange-Traded Commodities, Markov Switching Regression, Tracking Error JEL Classification: C24, G14, G23, Q14 * Department of Economics and Finance, UC Business School, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. Phone: +64 22 165 1494.
    [Show full text]
  • Retirement Benefits & Investment Risk Management
    ACTEX Learning Learn Today. Lead Tomorrow. ACTEX Study Manual for Retirement Benefits & Investment Risk Management Fall 2017 Edition Anna Wong, ASA, MBA ACTEX Study Manual for Retirement Benefits & Investment Risk Management Fall 2017 Edition Anna Wong, ASA, MBA ACTEX Learning New Hartford, Connecticut ACTEX Learning Learn Today. Lead Tomorrow. Actuarial & Financial Risk Resource Materials Since 1972 Copyright © 2017, ACTEX Learning, a division of SRBooks Inc. ISBN: 978-1-63588-055-7 Printed in the United States of America. No portion of this ACTEX Study Manual may be reproduced or transmitted in any part or by any means without the permission of the publisher. YOUR OPINION IS IMPORTANT TO US ACTEX is eager to provide you with helpful study material to assist you in gaining the necessary knowledge to become a successful actuary. In turn we would like your help in evaluating our manuals so we can help you meet that end. We invite you to provide us with a critique of this manual by sending this form to us at your convenience. We appreciate your time and value your input. Publication: ACTEX RB & Investment Risk Management Study Manual, Fall 2017 Edition I found Actex by: (Check one) A Professor School/Internship Program Employer Friend Facebook/Twitter In preparing for my exam I found this manual: (Check one) Very Good Good Satisfactory Unsatisfactory I found the following helpful: I found the following problems: (Please be specific as to area, i.e., section, specific item, and/or page number.) To improve this manual I would: Name: Address: Phone: E-mail: (Please provide this information in case clarification is needed.) Send to: Stephen Camilli ACTEX Learning P.O.
    [Show full text]
  • It's Time to Talk About Tracking Error
    Lazard Equity Advantage AUG Letter from the Manager 2019 It´s Time to Talk about Tracking Error, but Not for the Reason You May Think Investors are often tempted to loosen their active risk tolerance during periods of low market volatility, either in the belief that a low tracking error will fail to deliver expected returns or in the pursuit of higher active returns. When volatility is extremely low, the dispersion of individual stock returns typically compresses while cross-asset class correlation can increase as investments become influenced more by macroeconomic drivers than idiosyncratic factors. Dialling up a strategy’s active risk, or tracking error, during periods of low market volatility could result in an accumulation of unwanted and unrewarded risks at the portfolio level that leaves an investor vulnerable to sharp capital drawdowns. Our actively managed quantitative equity strategies are built around multi-dimensional risk models that seek to minimise risk factors where we believe investors are not being adequately compensated for the risk taken, and instead focus on more rewarding sources of returns. In order to understand whether the active risk being taken is being adequately compensated, it first helps to understand the drivers of tracking error. Fundamental and quantitative portfolio managers tend to stay within a range of number of stocks held in their portfolio and maximum allowable position sizes and may have certain sector and country biases. However, the other determinants of the tracking error are more prone to variations: • Market capitalisation is one area where risks are often ignored by investors. Idiosyncratic opportunities are What Is Tracking Error? typically found lower down the market capitalisation spectrum and for unconstrained investors, larger Tracking error, also known as active risk, capitalisation stocks will tend to be natural underweight measures, in standard deviation, the fluctuation holdings.
    [Show full text]