Dynamic stop-loss rules as universal performance enhancers
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DOIhttp://dx.doi.org/10.21511/imfi.15(2).2018.01
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Article InfoVolume 15 2018, Issue #2, pp. 1-16
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This paper provides ample empirical evidence, using US equity and bond indices, why daily stop-loss rules can be considered as viable performance enhancers. While a longer-term stop-loss rule can help investors to avoid market crashes by being out of the market, investors may obviously lose on the up-market days too. Furthermore, a shorter-term stop-loss rule may not miss the good market days by allowing investors to stay for a longer time in the market at the obvious expense of increased risk and higher drawdowns. This paper illustrates how daily stop-loss rules can significantly outperform the buy and hold equity and bond benchmarks, their equally weighted portfolio and the trend following strategy, simple moving average, which is driven from those asset classes – for both long and short positions. The results are robust to a variety of variations on the initial theme and it’s shown that performance enhancements can come from a variety of other sources related to a static stop-loss rule.
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JEL Classification (Paper profile tab)C50, G10, G11, G15
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References41
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Tables7
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Figures5
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- Figures 1-4. Cumulative return and maximum drawdown January 1, 2004 – October 13, 2015
- Figures 5-8. Cumulative return and maximum drawdown January 1, 2004 – October 13, 2015
- Figures 9-10. Cumulative return and maximum drawdown January 1, 2004 – October 13, 2015
- Figures 11-12. SPY-SMA cumulative return and maximum drawdown January 1, 2004 – October 13, 2015
- Figures 13-14. TLT-SMA cumulative return and maximum drawdown January 1, 2004 – October 13, 2015
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- Table 1. SPY summary statistics with daily stop loss January 1, 2004 – October 13, 2015
- Table 2. TLT summary statistics with daily stop loss January 1, 2004 – October 13, 2015
- Table 3. Summary statistics of SPY-TLT equal weight portfolio with daily stop loss January 1, 2004 – October 13, 2015
- Table 4. Summary statistics of SPY-SMA with daily stop loss January 1, 2004 – October 13, 2015
- Table 5. Yearly return of SPY-SMA with daily stop loss January 1, 2004 – October 13, 2015
- Table 6. Summary statistics of TLT-SMA with daily stop loss January 1, 2004 – October 13, 2015
- Table 7. Yearly return of TLT-SMA with daily stop loss January 1, 2004 – October 13, 2015
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- Adam, Y. C., Lei, Huihua Li. (2009). The value of stop-loss strategies. Financial Services Review, 18, 23-51.
- Arrow, K. (1970) (1974). Essays in the Theory of Risk Bearing. The Journal of Business, 47(1), 96-98.
- Balduzzi, P., & Lynch, A. W. (1999). Transaction Costs and Predictability: Some Utility Cost Calculations. Journal of Financial Economics, 52(1), 47-78.
- Benartzi, S., & Thaler, R. (1995). Myopic Loss Aversion and the Equity Premium Puzzle. Quarterly Journal of Economics, 110(1), 73-92.
- Bird, R., Dennis, D., & Tippett, M. (1988). A stop loss approach to portfolio insurance. Journal of Portfolio Management, 14(1), 35-40.
- Blitz, David, Huij, Joop, Martens, Martin (2011). Residual Momentum. Journal of Empirical Finance, 18(3), 506-521.
- Brennan, M., Schwartz, E., & Lagnado, R. (1997). Strategic Asset Allocation. Journal of Economic Dynamics and Control, 21(8-9), 1377-1403.
- Campbell, J., Chan, Y., & Viceira, L. (2003). A Multivariate Model of Strategic Asset Allocation. Journal of Financial Economics, 67(1), 41-80.
- Christian Gollier (1997). On the Inefficiency of Bang-Bang and Stop-Loss Portfolio Strategies. Journal of Risk and Uncertainty, 14(2), 143-154.
- Clare, Seaton, & Thomas (2012). BREAKING INTO THE BLACKBOX: Trend Following, Stop Losses, and the Frequency of Trading: the case of the S&P500 (Working paper). University of York, UK.
- Clarke, R., Krase, S., & Statman, M. (1994). Tracking Errors, Regret, and Tactical Asset Allocation. Journal of Portfolio Management, 20(3), 16-24.
- Clifford, S., Asness, Tobias, Moskowitz, J., & Lasse Heje Pedersen (2013). Value and Momentum Everywhere. The Journal of Finance, 68(3), 929-985.
- Ellis, C., & Parbery, S. A. (2005). Is smarter better? A comparison of adaptive and simple moving average trading strategies. Research in International Business and Finance, 19(3), 399-411.
- David L. Schalow (1996). Setting Stops with standard Deviation. The Journal of Portfolio Management, 22(4), 58-61.
- Eugene F. Fama, & Kenneth R. French (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3-56.
- Faber, Mebane T. (2007). A quantitative approach to tactical asset allocation. Journal of Wealth Management, 9, 69-79.
- G. William Schwerz (1989). Why Does Stock Market Volatility Change Over Time? The Journal of Finance, 44(5), 1115- 1153.
- Hans R. Stoll, & Robert E. Whaley (1990). Stock Market Structure and Volatility. The review of financial studies, 3, 37-71.
- Hirotugu Akaike (1973). Maximum Likelihood Identification of Gaussian Autoregressive Moving Average. Biometrika, 60(2), 255-265.
- Jegadeesh, Narasimhan, & Sheridan Titman (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48, 65-91.
- John Y. Campbell, & Ludger Hentschel (1992). No news is a good news: an asymmetric model of changing volatility and stock return. Journal of Financial Econometrics, 31(3), 218-318.
- Kathryn M. Kaminski, & Andrew W. Lo (2014). When Do Stop Loss Rules Stop Loss? Journal of Financial Markets, 18(C), 234-254.
- Larry J. Lockwood, & Scott C. Linn (1990). An Examination of Stock Market Return Volatility During Overnight and Intraday Periods 1964–1989. The Journal of Finance, 45(2), 591-601.
- Louis H. Ederington, & Jae Ha Lee (1993). How Markets Process Information: New Releases and Volatility. The Journal of Finance, 48(4), 1161-1191.
- Mark J. Ready (1997). Profits from Technical Trading Rules (Working paper). University of Wisconsin- Madison.
- Michael Cliff, Michael J. Cooper, & Huseyin Gule (2008). Return Differences between Trading and Non-trading Hours Like Night and Day. Virginia.
- Niels Pedersen, Sébastien Page, CFA, & Fei He, CFA (2014). Asset Allocation: Risk Models for Alternative Investments. Financial Analysts Journal, 70(3), 34-45.
- Odean, Terrance (1998). Are investors reluctant to realize their losses? Journal of Finance, 53, 1775-17.
- Odean, Terrance (1999). Do Investors Trade Too Much. American Economic Review, 89(5), 1279-1298.
- Philip H. Dybvig (1988). Inefficient Dynamic Portfolio Strategies or How to Throw Away a Million Dollars in the Stock Market. The Review of Financial Studies, 1(1), 67-88.
- Richard Sias (2007). Causes and Seasonality of Momentum Profit. Financial Analysts Journal, 73(2), 48-54.
- Sarah Maretta Tooth (2014). On the Efficacy of Stop-Loss Strategies. The Journal of Trading, 4(9), 100-107.
- Schalow, D. L. (1996). Setting stops with standard deviations. Journal of Portfolio Management, 22, (4), 58-61.
- Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. Journal of Finance, 40(3), 777-790.
- Staff Report (2002). Stop-loss orders and price cascades in currency markets. Federal Reserve Bank of New York (No 152).
- Stephen, Morris, & Hyun Song Shin (2004). Liquidity black holes. Review of Finance, 8(1), 1-18.
- Thiago Raymon Cruz Cacique da Costa, Rodolf Toribio Nazario, Gabriel Soares Zica Bergo, Vinicius Amorim Sobreiro, Herbert Kimura (2015). Trading System based on the use of technical analysis: A computational experiment. Journal of Behavioral and Experimental Finance, 6, 42-55.
- Torben G. Andersen, & Tim Bollerslev (1997). Intraday periodicity and volatility persistence in financial markets. Journal of Empirical Finance, 4(2- 3), 115-158.
- Waai Mun Fong, Lawrence H. M Yong (2004). Chasing trends: recursive moving average trading rules and internet stocks. Journal of Empirical Finance, 12(1), 43-76.
- William Brock, Josef Lakonishok, Blake LeBaron (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
- Yufeng Han, Guofu Zhou, & Yingzi Zhu (2014). Taming Momentum Crashes: A Simple StopLoss Strategy (Working paper). University of North Carolina at Charlotte.