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Exploiting uncertainty with market timing in corporate bond markets

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Abstract

The purpose of this article is to show the usefulness of technical analysis in credit markets. We document that an application of a simple moving average timing strategy to US high-yield and US investment-grade corporate bond portfolios sorted by option-adjusted spread generates investment timing portfolios that substantially outperform the corresponding benchmark. For portfolios with high uncertainty, as measured by the option-adjusted spread, the abnormal returns generate economically and statistically significant returns relative to the capital asset pricing model, the four-factor model and additionally the bond factor model from Asness et al. (J Finance 68:929–985, 2013). Our results remain robust to different moving average formation periods, transaction costs, long–short portfolio construction techniques and alternative definitions of information uncertainty.

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Notes

  1. The US bond market is considered as the largest security market in the world, and according to Federal Reserve data, the total market value of US corporate bonds had a growth rate of 8.5% per year from 1990 to 2014.

  2. Since government bond yields are on historically low levels, the demand for credit securities plays a much larger role than in the past. Usually, institutional investors such as pension funds, mutual funds and insurance companies invest in these securities.

  3. For instance, Brock et al. (1992), Lo et al. (2000) and Han et al. (2013) use simple moving average schemes to forecast the equity market.

  4. See, for example, Hong et al. (2012), reporting that stocks lead HY bonds and to a lesser degree IG bonds as well or Bao and Hou (2014), who show that the comovement between equities and bonds is stronger for firms with higher credit risk for a variety of measures of this firm characteristic.

  5. Chordia et al. (2016) state that sophisticated institutions, who in fact dominate corporate bond markets, price risk in the neoclassical sense.

  6. See Hong et al. (2012) or Bao and Hou (2014).

  7. The data on bond value and bond momentum factors are obtained from AQR’s Web site: https://www.aqr.com/library/data-sets/value-and-momentum-everywhere-factors-monthly.

References

  • Asness, C., T. Moskowitz, and L. Pedersen. 2013. Value and momentum everywhere. Journal of Finance 68: 929–985.

    Article  Google Scholar 

  • Baker, M., and J. Wurgler. 2012. Comovement and predictability relationships between bonds and the cross-section of stocks. Review of Asset Pricing Studies 2: 57–87.

    Article  Google Scholar 

  • Baltas, N., and R. Kosowski. 2013. Momentum strategies in futures markets and trend-following funds. Working Paper, Imperial College Business School.

  • Baltas, N., and R. Kosowski. 2017. Demystifying time-series momentum strategies: Volatility estimators, trading rules and pairwise correlations. Working Paper, Imperial College Business School.

  • Bao, J., and K. Hou. 2014. Comovement of corporate bonds and equities. Working Paper, Ohio State University.

  • Barberis, N., and R. Thaler. 2003. A survey of behavioral finance. Handbook of the Economics of Finance 1: 1051–1121.

    Google Scholar 

  • Bektic, D., J.-S. Wenzler, M. Wegener, D. Schiereck, and T. Spielmann. 2016. Extending Fama–French factors to corporate bond markets. Working Paper, Darmstadt University of Technology and Deka Investment GmbH.

  • Brock, W., J. Lakonishok, and B. LeBaron. 1992. Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance 47: 1731–1764.

    Article  Google Scholar 

  • Campbell, J.Y., and G.B. Taksler. 2003. Equity volatility and corporate bond yields. Journal of Finance 58: 2321–2349.

    Article  Google Scholar 

  • Carhart, M. 1997. On persistence in mutual fund performance. Journal of Finance 52: 57–82.

    Article  Google Scholar 

  • Chen, L., D.A. Lesmond, and J. Wei. 2007. Corporate yield spread and bond liquidity. Journal of Finance 62: 119–149.

    Article  Google Scholar 

  • Choi, J., and Y. Kim. 2016. Anomalies and market (dis)integration. Working Paper, University of Illinois at Urbana–Champaign.

  • Chordia, T., A. Goyal, Y. Nozawa, A. Subrahmanyam, and Q. Tong. 2016. Are capital market anomalies common to equity and corporate bond markets? Working Paper, Emory University.

  • Covel, M. 2005. Trend following: How great traders make millions in up or down markets. New York: Prentice-Hall.

    Google Scholar 

  • Crawford, S., P. Perotti, R. Price, and C. Skousen. 2015. Accounting-based anomalies in the bond market. Working Paper, University of Houston, University of Bath and Utah State University.

  • Daniel, K., and D. Hirshleifer. 2015. Overconfident investors, predictable returns, and excessive trading. Journal of Economic Perspectives 29: 61–88.

    Article  Google Scholar 

  • Daniel, K., D. Hirshleifer, and A. Subrahmanyam. 1998. Investor psychology and security market under- and overreactions. Journal of Finance 53: 1839–1885.

    Article  Google Scholar 

  • Daniel, K., D. Hirshleifer, and A. Subrahmanyam. 2001. Overconfidence, arbitrage, and equilibrium asset pricing. Journal of Finance 56: 921–965.

    Article  Google Scholar 

  • Exchange, C. B. O. 2009. The CBOE volatility index VIX. Chicago: CBOE.

    Google Scholar 

  • Fama, E. 1995. Random walks in stock market prices. Financial Analyst Journal 51: 75–80.

    Article  Google Scholar 

  • Frazzini, A., and L. Pedersen. 2014. Betting against beta. Journal of Financial Economics 111: 1–25.

    Article  Google Scholar 

  • Furham, A. 1986. The robustness of the recency effect: Studies using legal evidence. Journal of General Psychology 113: 351–357.

    Article  Google Scholar 

  • Gebhardt, W., S. Hvidkjaer, and B. Swaminathan. 2005. Stock and bond market interaction: Does momentum spill over? Journal of Financial Economics 75: 651–690.

    Article  Google Scholar 

  • Georgopoulou, A., and J. Wang. 2017. The trend is your friend: Time-series momentum strategies across equity and commodity markets. Review of Finance 21: 1557–1592.

  • Goh, J., F. Jiang, J. Tu, and G. Zhou. 2013. Forecasting government bond risk premia using technical indicators. Working Paper, Singapore Management University and Washington University in St. Louis.

  • Han, Y., K. Yang, and G. Zhou. 2013. A new anomaly: The cross-sectional profitability of technical analysis. Journal of Financial and Quantitative Analysis 48: 1433–1461.

    Article  Google Scholar 

  • Harvey, C.R., Y. Liu, and H. Zhu. 2016. …and the cross-section of expected returns. Review of Financial Studies 29: 5–68.

    Article  Google Scholar 

  • Henriksson, R., and R. Merton. 1981. On market timing and investment performance. II. Statistical procedures for evaluating forecasting skills. Journal of Business 54: 513–533.

    Article  Google Scholar 

  • Hong, Y., H. Lin, and C. Wu. 2012. Are corporate bond market returns predicable? Journal of Banking & Finance 36: 2216–2232.

    Article  Google Scholar 

  • Houweling, P., and J. van Zundert. 2017. Factor investing in the corporate bond market. Financial Analysts Journal 73: 100–115.

  • Hurst, B., Y. Ooi, and L. Pedersen. 2013. Demystifying managed futures. Journal of Investment Management 11: 42–58.

    Google Scholar 

  • Israel, R., D. Palhares, and S. Richardson. 2016. Common factors in corporate bond and bond fund returns. Working Paper, AQR Capital Management.

  • Jacobs, H. 2016. Market maturity and mispricing. Journal of Financial Economics 122: 270–287.

  • Jiang, G., C. Lee, and Y. Zhang. 2005. Information uncertainty and expected returns. Review of Accounting Studies 10: 185–221.

    Article  Google Scholar 

  • Jostova, G., S. Nikolova, A. Philipov, and C. Stahel. 2013. Momentum in corporate bond returns. Review of Financial Studies 26: 1649–1693.

    Article  Google Scholar 

  • Lo, A., H. Mamaysky, and J. Wang. 2000. Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. Journal of Finance 55: 1705–1765.

    Article  Google Scholar 

  • Lu, C.-W., T.-K. Chen, and H.-H. Liao. 2010. Information uncertainty, information asymmetry and corporate bond yield spreads. Journal of Banking & Finance 34: 2265–2279.

    Article  Google Scholar 

  • Malkiel, B. 1981. A random walk down wall street. New York: Norton.

    Google Scholar 

  • Merton, R. 1974. On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance 29: 449–470.

    Google Scholar 

  • Moskowitz, T., Y. Ooi, and L. Pedersen. 2012. Time series momentum. Journal of Financial Economics 104: 228–250.

    Article  Google Scholar 

  • Neely, C., D. Rapach, J. Tu, and G. Zhou. 2014. Forecasting the equity risk premium: The role of technical indicators. Management Science 60: 1772–1791.

    Article  Google Scholar 

  • Newey, W.K., and K.D. West. 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55: 703–708.

    Article  Google Scholar 

  • Schwager, J. 2012. Hedge fund market wizard: How winning traders win. New Jersey: Wiley.

    Book  Google Scholar 

  • Shleifer, A., and R.W. Vishny. 1997. The limits of arbitrage. Journal of Finance 52: 35–55.

    Article  Google Scholar 

  • Treynor, J., and K. Mazuy. 1966. Can mutual funds outguess the market? Harvard Business Review 44: 131–136.

    Google Scholar 

  • Whaley, R. 2009. Understanding the VIX. Journal of Portfolio Management 35: 98–105.

    Article  Google Scholar 

  • Zhang, X.F. 2006. Information uncertainty and stock returns. Journal of Finance 61: 105–137.

    Article  Google Scholar 

  • Zhu, Y., and G. Zhou. 2009. Technical analysis: An asset allocation perspective on the use of moving averages. Journal of Financial Economics 92: 519–544.

    Article  Google Scholar 

Download references

Acknowledgements

We wish to express our thanks for helpful comments and valuable suggestions to an anonymous referee, Stephen Satchell (editor), Brian Teng Yuan Cheng (discussant), Patrick Jahnke, Dirk Schiereck and Esad Smajlbegović as well as seminar participants at the Behavioural Finance Working Group Conference 2017. This paper was also accepted for presentation at the 2017 Financial Management Association (FMA) Annual Meeting, European Financial Management Association (EFMA) 2017 Annual Meetings, 3rd Symposium on Quantitative Finance and Risk Analysis (QFRA) and the 34th International Conference of the French Finance Association (AFFI), but not presented at either conference due to scheduling conflicts. Views expressed in this paper are those of the authors and do not necessarily reflect those of Deka Investment and Allianz Global Investors or their employees. Parts of this research project have been conducted while the first author was at the University of Chicago Booth School of Business.

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Authors and Affiliations

  1. Department of Law and Economics, Darmstadt University of Technology, Hochschulstrasse 1, 64289, Darmstadt, Germany

    Demir Bektić

  2. Deka Investment GmbH and IQ-KAP, Mainzer Landstrasse 16, 60325, Frankfurt am Main, Germany

    Demir Bektić

  3. Allianz Global Investors GmbH, Bockenheimer Landstrasse 42-44, Frankfurt am Main, Germany

    Tobias Regele

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  1. Demir Bektić
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Correspondence to Demir Bektić.

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Bektić, D., Regele, T. Exploiting uncertainty with market timing in corporate bond markets. J Asset Manag 19, 79–92 (2018). https://doi.org/10.1057/s41260-017-0063-6

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