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Bond Trading Strategy Using Parsimonious Interest Rate Model BOND TRADING STRATEGY USING PARSIMONIOUS INTEREST RATE MODEL CHARIYA PIMOLPAIBOON MASTER OF SCIENCE PROGRAM IN FINANCE (INTERNATIONAL PROGRAM) FACULTY OF COMMERCE AND ACCOUNTANCY THAMMASAT UNIVERSITY, BANGKOK, THAILAND MAY 2008 BOND TRADING STRATEGY USING PARSIMONIOUS INTEREST RATE MODEL CHARIYA PIMOLPAIBOON MASTER OF SCIENCE PROGRAM IN FINANCE (INTERNATIONAL PROGRAM) FACULTY OF COMMERCE AND ACCOUNTANCY THAMMASAT UNIVERSITY, BANGKOK, THAILAND MAY 2008 2 Bond Trading Strategy using Parsimonious Interest rate model Chariya Pimolpaiboon An Independent Study Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science (Finance) Master of Science Program in Finance (International Program) Faculty of Commerce and Accountancy Thammasat University, Bangkok, Thailand May 2008 3 Thammasat University Faculty of Commerce and Accountancy An Independent Study By Chariya Pimolpaiboon “Bond Trading Strategy using Parsimonious Interest rate Model” has been approved as a partial fulfillment of the requirements for the Degree of Master of Science (Finance) On May, 2008 Advisor: …………………………………… (Prof. Dr. Suluck Pattarathammas) 4 ACKNOWLEDGEMENTS I am forever indebted to Asst. Prof. Dr. Suluck Pattarathammas, my independent study advisor, for his invaluable guidance. This study would not have been possible without his thought provoking advice. It is also a pleasure to express my appreciation to my comprehensive examination committee members, Dr. Thanomsak Suwannoi and Aj. Anutchanat Jaroenjitrkam for their detailed comments and suggestions, which benefit me so much. Moreover, I would like also to express my sincere appreciation: - Dr. Supakorn Soontornkit, my boss and my lecturer in Fixed-Income security class at the MIF, for a consultation on interest rate modeling and fixed income markets. - Dr. Charnwut Roonsangmanoon for giving constructive and valuable suggestions. - Pongpit Pinsai for invaluable information, which help accomplished this research. - Kittimet Tatiyakavee for his helping idea on VBA programming. - Rachata Thanboonpairat for being such valued friend and for grammatical editing. My special thanks are expressed to my classmates and staffs at the Master of Science in Finance program, Thammasat University and many names not mentioned here for their encouragement that make my mission possible. Finally, I owe a deep gratitude to my mum and my dad for their moral support and encouragement. 5 Bond Trading Strategy using Parsimonious Interest rate Model ABSTRACT In an efficient financial market a correctly specified term structure estimation model would exactly explain the observed bond prices for all maturities, given that the bonds have same issuer, liquidity and tax treatment. Thus, the estimated term structure of interest rates can be applied to price a fair value of fixed income instruments and to find an opportunity to make profit from relative value between the fair value and the market price value, called pricing errors. Evidence from various models such as Sercu and Wu (1997), Bliss (1997), Ioannides (2003) and Jankowitsch and Pichler (2004) suggests justification for applying such models. So an important question is whether the model that is good at interest rate forecast has a potential to perform as well in bond trading. The major aim of this paper is not only to examine trading strategies, but to identify the best model in terms of its ability to generate excess returns over a benchmark by using pricing error of a competent Thai interest rate forecasting model based on realistic setup. This model incorporates transaction costs, compare to the Thai government bond market benchmark. This study finds that trading strategies based on the Dynamic Nelson-Siegel model proposed Diebold & Li (2003) can yield abnormal return compared to the benchmark portfolio. 6 INTRODUCTION Term structure of interest rates specifies a relationship between yields of zero-coupon bonds and their time to maturities. The applications of the term structure of interest rates may serve as an indicator of monetary policy or as an input in every pricing model for financial instruments. The interest rates are hence essential for many financial areas such as portfolio management, financial engineering, monetary policy, and corporate finance in investment and financing decisions. Unfortunately the full term structures of interest rates are not directly observable in financial markets. Therefore, this information need to be estimated from the data based on existing financial instruments or traded bond prices. And the estimation is done with two different methods: the bootstrapping and the functional form of interest rate modeling. Anderson et al (1996) describe the term structure of interest rate modeling in two approaches. The first approach as suggested by Vasicek (1977), Dothan (1978), Brennan and Schwartz (1979), Cox et al (1985), Ho and Lee (1986), Hull and White (1990), is called “Financial Engineering”. This approach has one major assumption about the evolution of state variables that is short-term interest rates follow some statistical process and relate to long-term interest rates. The second approach, financial econometrics based on statistical techniques recommended by researchers such as McCulloch (1971, 1975), Nelson and Siegel (1987), Svesson (1994), Diebold et al (2003) and Chen (1996), show that the full term structure of interest rates is illustrated by smoothing data obtained from traded financial instruments. In Thailand, there are only a few researches related to the term structure estimation. Promchan (2004) constructs CIR interest rate model to compare with Vasicek model using data of Thai government bonds from January 1999 to January 2004. This study shows that CIR model outperformed Vasicek model. Khanthavit and Jaroenjitrkam (2006) compare CIR model with Vasicek model using Kalman filtering technique, which can solve all flaws in the previous study of Promchan (2004). Thamchamrassri (2006) estimates the term structure of Thai government bond yields by using B-Spline method. This study estimates four fitting Models non-restricted discount fitting, restricted discount fitting, spot fitting and forward fitting and then compares these estimations with the Thai Bond Market Association spot curve, which is 7 estimated by Cubic-Spline technique. Recently Pinsai (2007) studies the Dynamic Nelson- Siegel Approach proposed by Diebold and Li (2003) to estimate the Thai government bond term structure of interest rate. The results of this study suggest that the dynamic Nelson-Siegel with AR (1) outperforms all other models in 1-month forecasting horizon and the dynamic Nelson-Siegel with VAR (1) work well for the 6 and 12-month horizon. In an efficient financial market a correctly specified term structure estimation model would exactly explain the observed bond prices for all maturities, given that the bonds have same issuer, liquidity and tax treatment. Thus, the estimated term structure of interest rate can be applied as a tool to price a fair value of fixed income instruments and to find opportunity to make profit from relative value between the fair value and the market price value of same bond. Bond trading opportunity is described in terms of yield spreads between pairs of 1 residuals from an underlying bond price model signals a quasi-arbitrage opportunity for the trader. Evidence from various studies such as Flavell et al. (1994), Sercu and Wu (1997), Bliss (1997), Ioannides (2003) and Jankowitsch and Pichler (2004) suggests that there is justification for applying such models. For the Belgian, German, and respectively UK government bond markets, these studies find significant abnormal returns compared to government bond market benchmark. So an important question is whether the model that is good at interest rate forecast has a potential to perform as well in bond trading. The major aim of this paper is not only to examine trading strategy results, but to identify the best model in terms of its ability to generate excess returns compare to the benchmark by using pricing error of a competent Thai interest rate forecasting model based on realistic setup, which is fully incorporate transaction costs compare to a Thai government bond market benchmark. In this study the trading signals are received by using trading rules and by calibrating interest rate model to the pricing errors. Besides, this study aims to be intuitive model parameters that help market practitioners detect mispriced government bonds. Every model described in this study has been implemented in EXCEL/VBA, which is widely used for financial analysis and is very easy to setup platform to present these models. 1 A quasi-arbitrage trading opportunity is opportunity to trade at better price. 8 I. LITERATURE REVIEW In an efficient financial market, the estimated interest rates should accurately explain the prices of traded bonds. Practically there are a number of different methods to estimate the term structure of interest rate. A commonly used procedure to estimate the term structure from a set of coupon bonds is the bootstrapping approach. This approach requires having at least one zero coupon bond. Given this bond's rate, a coupon bond with the next highest maturity is used to obtain an implied spot rate; then the next highest maturity coupon bond would be used to find the next spot rates, and so on. According to Fabozzi and Fong (1994) the bootstrapping approach is used as a quick approximation, but it fails to satisfy objective of term structure
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