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Equity Style Investing
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Equity Style Investing, Durham theses, Durham University.
RONG, WU (2013) Available at Durham
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Academic Support Oce, Durham University, University Oce, Old Elvet, Durham DH1 3HP e-mail: email@example.com Tel: +44 0191 334 6107 http://etheses.dur.ac.uk Equity Style Investing Wu Rong Supervisors Dr Jie Michael Guo Professor Krishna Paudyal Dr Emilios Galariotis A thesis submitted in fulfilment of the requirements for the Degree of Doctor of Philosophy Department of Economics and Finance Durham University Business School Durham University Nov 2012 Abstract Despite the well documented benefits of equity style investing in today’s financial markets, the academic view of the underlying cause for such benefits remains an ongoing debate. A number of theories have been proposed to explain why some asset classes earn better returns than others do under the same economic regimes. Rational finance links the outperformance of some stock groups to the equity characteristics that proxy for the common risk factors, behavioural finance, however, argues that mispricing resulting from irrational investor’s sentiment to fundamentals plays a key role. Meanwhile, a variety of business cycle variables have also suggested to contain information useful in explaining the expected stock returns. The observed style returns change all the time with predictable timevarying components, reflecting the structural and cyclical shocks to the macroeconomy.
Motivated by the current ongoing controversy of anomaly versus risk compensation over interpreting equity style premiums, this thesis investigates how firm characteristics and business cycle conditions function separately to affect the style return dynamics based on the size and value-growth categorisations. It adds to the extant literature by explicitly examining the relative importance of the common risk factors versus firm-specific information as driving sources in the divergent equity style returns in the U.K. market. By identifying the dominant driving force that determines the relative style performance, it provides a further dimension to the current debate regarding the sources of style premiums and offers the choice of corresponding style investing strategies.
The divergent style returns and its time-varying nature offer astute investors the opportunity to implement active style management to enhance portfolio returns. Motivated by the benefits of capitalising on such style return cyclicality and in particular the availability and popularity of Exchange Traded Funds based on market segments in leading financial markets as investment vehicle that offers low cost and high liquidity, this thesis examines a dynamic long-short tactical trading strategy by applying a binomial approach to focus on the rotation between pairs of equity styles. By answering key questions of whether equity style cycles exist in the U.K. market and whether the return dynamics of such style momentum strategy is distinct from the price and industry momentum effects, it contributes to the literature by providing valuable empirical evidence to compare with other studies in different economic and institutional environments.
In response to the increasing popularity of using macro information to aid optimal style selection for the quant circles in the investment community, building on the methodology of Brandt and Santa-Clara (2006), this thesis approximates a solution of a mean-variance multistyle investor’s optimal style investing problem incorporating the business cycle predictability. This approach is parsimonious as the optimal style weights are parameterised directly on a set of pervasive business cycle predictors. By exploring how the distributions of the expected style returns and the location or the shape of the optimal style allocations are affected by given shocks to the business cycles, this thesis contributes to the extant literature by demonstrating the transmission mechanism of how business cycle volatility affects equity style return volatility and in turn a mean-variance investor’s optimal style allocation.
Declaration I hereby declare that the content contained in this thesis has not been previously submitted, either in whole or in part, for a degree at this or other universities.
Copyright The copyright of this thesis rests with the author. No quotation from it should be published, electronic or internet, without the author's prior consent. Any content in this thesis or information derived from it should be properly acknowledged.
Acknowledgements This thesis would not have been possible without the help of several individuals who have made various contributions in the preparation and completion of my PhD programme.
First and foremost, my utmost gratitude towards Dr Jie Michael Guo, senior lecture in Finance at Durham University Business School, whose invaluable support and help I will never forget. Michael is someone you will instantly like and never forget once you meet him.
His thoughtful guidance plays a crucial role as I hurdle the obstacles in the completion of this research project.
I offer my boundless gratitude to Prof Krishna Paudyal, University of Strathclyde. Krishna has offered tremendous support throughout the entire programme supervision with his patience as well as invaluable insights and suggestions. I am also deeply indebted to his steadfast confidence in me even I made slow progress. I feel an honour to be supervised by him and one simply could not wish for a better supervisor! This thesis would not have been completed without his continuous support over the entire research period.
I am extremely grateful to Dr Emilios Galariotis, professor in Finance at Audencia Nantes School of Management (France), for all the fantastic discussions and valuable inputs especially in the structure and the practice of effective research management throughout the entire project. Emilios also has shared numerous constructive insights which are relevant in this study. The completion of this thesis would be a ‘mission impossible’ without his continuous yet very kind push over the past years.
I would like to express my heartfelt gratitude to the thesis examiners, Dr Michael Nicholson and Dr Evangelos Vagenas-Nanos, for their constructive suggestions and comments. Their advice significantly improves the thesis.
I remain indebted for Prof David Barr for his support when he was at Durham Business School as a professor in Finance. David taught theory of finance when I was studying at Imperial College London, where I learned GAUSS programming and benefited tremendously from it when conducting empirical tests in this PhD research.
My very special thanks go to Durham University Business School for giving me the opportunity to complete this research programme. The business school generously offered the concession to the suspension and extension of the programme when I confronted health problems over the past years.
I would like to take this opportunity to thank Yoong for the support when pursuing this PhD programme.
Finally, I would like to acknowledge the most precious treasury in my life – my children, namely, Wilona, Daralis and Reginal. It is their love that ultimately made it possible for me to put this project to the end.
Dedications To my father in the heaven, Xiangjing Rong
Your love, support, encouragement and positive attitude towards education as well as the optimistic spirit when facing hardship has inspired me throughout my life Content Chapter 1 Introductions
1.1 Equity style
1.2 Equity style investing
1.3 Motivations and objective for the research
1.4 Basic findings in each chapter
1.5 Research structure
Chapter 2 Literature Review
2.2 The dimension of equity styles
2.3 Size, value and growth investing
2.4 Explanations for size and value premiums
2.5 Contrarian and Momentum investing
2.6 The cyclicality of style returns and macro cycle
2.7 Time-varying style returns and business cycle variables..... 47
2.8 Equity multi-style rotation strategy
2.9 Optimal style allocation incorporating return predictability.. 55 Chapter 3 Equity Style Drivers: Business Cycle Risk versus Firm-specific Characteristics
3.2 Econometric framework
3.3 Data and methodology
3.3.1 Data description
3.3.2 Style portfolio construction
3.4 Empirical results
3.4.1 The returns of simple style investing strategies.................. 83 3.4.2 Style returns and the business cycles
3.4.3 Predicted and unpredicted returns across styles................ 91 3.4.4 Style premiums after adjusting for the predicted returns from the business cycle model
3.4.5 Style premiums regressed on macroeconomic variables..... 102 3.4.6 Contemporaneous relations between equity characteristics, common risk factors and the pricing error of the business cycle model
3.5 Summary and conclusions
Chapter 4 Equity Style Momentum Strategies
4.2 General framework of momentum trading
4.3 Data descriptions and methodology
4.4 Characteristics of equity style portfolios
4.5 The profitability of style momentum strategies.................. 150
4.6 Style, price and industry momentum
4.7 The risk exposures of style momentum strategies............. 178
4.8 Summary and conclusions
Chapter 5 Optimal Multi-Style Investing Parameterising on Business Cycle Predictors
5.2 Motivation and research questions
5.3 Testable Hypothesis
5.4 Methodology and econometric framework
5.5 Data, style definition and test results
5.5.2 Style definition and investor type
5.5.3 Test results and discussion
5.6 Summary and conclusions
Chapter 6 Summary, Conclusions, Implementations and Recommendations for Future Research
6.1 Summary of the research
6.4 The practical implementations
6.3 Recommendations for areas of future research.................. 249 Bibliography
List of Tables Table 3-1 Correlation matrix of the macro variables
Table 3-2 Time-series average equity characteristics of quintile portfolios
Table 3-3 Profit of simple style investing (J, K) = (6, 12) and (12, 6)
Table 3-4 Style investing returns classified by business cycles..... 90 Table 3-5 Style investing returns adjusted for macro variables and firm-specific component from model
Table 3-6 Style investing profits regressed on the business cycle variables
Table 3-7 Style investing returns regressed on macroeconomic variables: 5-year subperiod results (J, K) = (6, 12)
Table 3-8 Regressions of unpredicted stock returns on firm characteristics and risk factors
Table 4-1 Characteristics of equity style investing portfolios...... 145 Table 4-2 The performance of simple equity style investing........ 147 Table 4-3 The profitability of style momentum strategies........... 154 Table 4-4 Style momentum portfolios by quarter and year 1982Table 4-5 The composition of style momentum portfolios........... 163 Table 4-6 Average migration rate (%) for stocks in consecutive extreme styles
Table 4-7 Raw returns and style, price and industry adjusted returns
Table 4-8 The returns of price and industry momentum portfolios that vary in style momentum
Table 4-9 Momentum effects and the cross-sectional stock returns
Table 4-10 The risk of style momentum returns
Table 4-11 Style momentum returns in selected time periods.... 182 Table 5-1 Descriptive statistics of the performance of simple style investing strategies
Table 5-2 Parameters used to control the test
Table 5-3 Single-period optimal style Investing (portfolio are based on stocks sorted on firm characteristic APC)
Table 5-4 Traditional versus conditional style investing on state variables
Table 5-5 Average coefficients of business cycle predictors in conditional expected return regressions and conditional style allocations
List of Figures Figure 1-1 Equity style box
Figure 3-1 Number of stocks based on the available firm characteristics in the sample
Figure 3-2 U.K. GDP quarterly growth rate (1980:01-2004:12)..... 85 Figure 3-3 Median predicted and unpredicted returns around formation period
Figure 4-1 Equity style investing box
Figure 4-2 The time-varying returns in annual SV, LG style portfolios
Figure 4-3 Size and value premiums dynamics
Figure 4-4 Average stock migration rate % for winner and loser styles
Figure 5-1 Style portfolio weights of conditional and unconditional policies
Figure 5-2 The time-series of style weights based on traditional and unconditional (regression-based) style investing
1.1 Equity style Human beings have the unique behaviour of classifying objects into different categories (Wilson and Keil (1999)). When facing complex environment we are able to simplify the decision-making process based on such categorisation. For example, a product displayed in a supermarket can be classified as luxury or necessity, a customer can decide whether to purchase it or not given his budget constraint.