Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2019 Essays on active investing Rüegg, Roger Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-168092 Dissertation Published Version Originally published at: Rüegg, Roger. Essays on active investing. 2019, University of Zurich, Faculty of Economics. Essays on Active Investing Dissertation submitted to the Faculty of Business, Economics and Informatics of the University of Zurich to obtain the degree of Doktor der Wirtschaftswissenschaften, Dr. oec. (corresponds to Doctor of Philosophy, PhD) presented by Roger Rüegg from Weisslingen, ZH approved in February 2019 at the request of Prof. Dr. Markus Leippold Prof. Dr. Michael Wolf The Faculty of Business, Economics and Informatics of the University of Zurich hereby authorizes the printing of this dissertation, without indicating an opinion of the views expressed in the work. Zurich, 13.02.2019 Chairman of the Doctoral Board: Prof. Dr. Steven Ongena Acknowledgements Firstly, I want to express my gratitude to Prof. Dr. Markus Leippold, my thesis supervisor, for his excellent guidance, his motivation, and the immense knowledge that I could benefit from. I highly appreciated our insightful discussions and his infectious energy for our research. I am also very grateful to Prof. Dr. Michael Wolf, my PhD co-examiner, for the time he dedicated to me and the inputs he shared when difficulties arose. His teaching, starting from the very first statistic lecture at university, and research shaped my ideas. I deeply appreciate all the support I received from my heads at Swisscanto Invest by Zürcher Kantonalbank, Iwan Deplazes, and Dr. René Nicolodi. Without their patience I could have not achieved the research quality. Furthermore, I had the chance to be in a wonderful team at Zürcher Kanontalbank. My biggest thank goes to Dr. Fabian Ackermann who always helped me to combine my research and work. I would like to thank Florian Arnold, Michael Bretscher, Dr. Andreas Kappler, and Andri Silberschmidt, my colleagues, for always being ready to help and for all the good times I had together with them. Special thanks go to my friends, Martin Gillholm, Meriton Ibraimi, and Istvan Redl, for the discussions and support during the last part of my thesis. Moreover, my studies wouldn’t have been as joyful as it had been without my flat mate, Pascal Buri. Finally, I wish to express my deepest gratitude to my parents, Monika and Martin, and my sib- lings, Nicole and Kevin, for supporting me in every step toward my PhD. My deepest gratitude goes to my fiancée, Marielle, who encouraged me throughout all the ups and downs. Winterthur, October 2018 Roger Rueegg Contents I Introduction 7 1 Introduction and Summary of Research Results 9 Roger Rueegg II Research Papers 13 1 The Mixed vs the Integrated Approach to Style Investing: Much Ado About Nothing? 15 Markus Leippold and Roger Rueegg 2 Is Active Investing a Zero-Sum Game? 59 Markus Leippold and Roger Rueegg 3 The Long-Only Integrated Approach to Factor Timing 119 Roger Rueegg IIIAppendix 167 1 Curriculum Vitae 169 Roger Rueegg I Introduction Introduction and Summary of Research Results This dissertation gives answers to three timely questions in the field of active investing. The discus- sion about the merits of active investing significantly affects the structure of the asset management industry. In addition, the emergence of the so-called style or factor investors that base their invest- ment strategy on the pioneering work of Fama and French (1992) puts further pressure on traditional active management. Thus, we take the opportunity to shed light on important issues that arise in this highly competitive discipline. The three research papers don’t take the recent results in literature for granted. With extensive data samples and a battery of robust statistical tests we highlight different shades of active and factor investing. Because we agree with Bailey et al. (2014) on the fact that the increasing computational power and incentive of institutions to deliver extraordinary results make it crucial to apply the most advanced statistical testing frameworks. The first research paper, The Mixed vs the Integrated Approach to Style Investing: Much Ado About Nothing?, shows that there is no difference in performance between the integrated and the standard mixed approach to style investing. The standard approach regards factors such as bundles of securities and mixes different factor portfolios for the multi-factor investment. On the other hand, the integrated approach regards stocks such as bundles of factors, and invests only in the stocks that share the best factor characteristics on aggregate. Recent literature argues that the integrated approach offers lower risks and higher returns. However, their argumentation contradicts the standard paradigm that higher returns can only be achieved by taking higher risks. We thus build a robust statistical test framework and compare 104 different factor combinations and portfolio constructions during the long history from 1963 to 2016. When we naively test the hypothesis, we arrive at the same conclusion as Bender and Wang (2016), Clarke et al. (2016), or Fitzgibbons et al. (2016). However, we find that the integrated approach by construction has a higher active risk. When we build a fair comparison of the two approaches with similar active risks, the advantage of the integrated approach vanishes, and we can not find statistical evidence for either approach. Still, the integrated approach can offer implementation advantages, as we can see in the third research paper. We also demonstrate 9 that the integrated approach leads to a higher sensitivity to the low-volatility anomaly. Our second research paper, Is Active Investing a Zero-Sum Game?, explores an extensive dataset of more than 60,000 equity and fixed income mutual funds among different investment categories. For our analysis, we build a novel statistical framework that takes the observed cross-sectional and serial dependence of the mutual funds’ returns into account. At the same time, it adjusts for the multiple hypothesis problems that arise with different fund providers and investment categories. Our results show that we cannot reject the hypothesis of a zero-sum game between active and index investing for a vast majority of investment categories. Thus, we find evidence for the theory of Berk and Green (2004), who demonstrated that rational markets lead to a zero-sum game after fees. When we analyze the performance drivers of the difference between active and index investing, we expected active management to protect investors from sudden volatility shocks. Counter-intuitively, we find that active management tends to outperform in calm market environments and to be negatively affected during crisis periods. We also find that active equity relative to index funds show a positive exposure to small-cap and growth stocks while active fixed income relative to index funds show a higher sensitivity to credit risk. Contrary to that, index managers exhibit a higher sensitivity to the traditional market and duration risk premium. When we investigate the role of performance persistence, fees, and size, we find that active low-fee winner portfolios and active small winner portfolios tend to outperform index investors. However, their alpha does not survive our robust test statistics. On the other hand, our results show significant negative alphas as well after the multiple hypothesis adjustment for active equity retail investors that invested in high-fee losers. In the third research paper, The Long-Only Integrated Approach to Factor Timing, I try to time the factors in a realistic long-only setting. It shows that a Markov switching model with one month lag and two states can generate an alpha of 0.36% per month. The alpha is adjusted for the underlying factor exposures and thus reflects the timing contribution of the strategy. Hence, this adds evidence to the recent findings of factor momentum by Arnott et al. (2018). In contrast to their long-short mixed approach, I show that factor momentum also works in the highly transparent long-only integrated approach. Moreover, the timing ability exists not only in the US but also in the developed and emerging markets, among different factor sets, and for holding periods of up to 12 months. Most of the combinations tested survive the robust alpha test that we developed in the second research paper. 10 One caveat of short-term timing strategies is the high turnover. Trading costs may erase the gains in markets with high transaction costs. When I reduce rebalancing frequencies in markets with high transaction costs to limit the turnover, the alphas stay positive and mostly survive the robust test statistics. However, the significance vanishes when I adjust for multiple hypothesis. Still, I achieve an alpha of 0.29% per month after transactions costs which looks economically significant. Hence, there is evidence that the Markov switching strategy may offer a promising source of alpha, which implies that the market prices of risk adjust only slowly over time. 11 References Arnott, Robert D., Mark Clements, Vitali Kalesnik, and Juhani T. Linnainmaa, 2018, Factor mo- mentum, Available at SSRN 3116974. Bailey, David H., Jonathan M. Borwein, Marcos L. de Prado, and Qiji J. Zhu, 2014, Pseudomathemat- ics and financial charlatanism: The effects of backtest over fitting on out-of-sample performance, Notices of the American Mathematical Society 61, 458–471. Bender, Jennifer, and Taie Wang, 2016, Can the whole be more than the sum of the parts? Bottom-up versus top-down multifactor portfolio construction, Journal of Portfolio Management 42, 39–50. Berk, Jonathan B., and Richard C. Green, 2004, Mutual fund flows and performance in rational markets, Journal of Political Economy 112, 1269–1295. Clarke, Roger G., Harindra De Silva, and Steven Thorley, 2016, Fundamentals of efficient factor investing, Financial Analysts Journal 72, 9–26.