Hostname: page-component-77f85d65b8-v2srd Total loading time: 0 Render date: 2026-04-18T01:49:48.800Z Has data issue: false hasContentIssue false
  • English
  • Français

A New Anomaly: The Cross-Sectional Profitability of Technical Analysis

Published online by Cambridge University Press:  06 December 2013

Yufeng Han ,
Ke Yang  and
Guofu Zhou
Yufeng Han
Affiliation:
yufeng.han@ucdenver.edu, Business School, University of Colorado Denver, PO Box 173364, Denver, CO 80217
Ke Yang
Affiliation:
kyang@rgare.com, Reinsurance Group of America, 1370 Timberlake Manor Pkwy, Chesterfield, MO 63017
Guofu Zhou
Affiliation:
zhou@wustl.edu, Olin School of Business, Washington University, 1 Brookings Dr, St. Louis, MO 63130, China Academy of Finance Research (CAFR), and China Economics and Management Academy (CEMA).
Get access Rights & Permissions [Opens in a new window]

Abstract

In this paper, we document that an application of a moving average timing strategy of technical analysis to portfolios sorted by volatility generates investment timing portfolios that substantially outperform the buy-and-hold strategy. For high-volatility portfolios, the abnormal returns, relative to the capital asset pricing model (CAPM) and the Fama-French 3-factor models, are of great economic significance, and are greater than those from the well-known momentum strategy. Moreover, they cannot be explained by market timing ability, investor sentiment, default, and liquidity risks. Similar results also hold if the portfolios are sorted based on other proxies of information uncertainty.

Information

Type
Research Articles
Information
Journal of Financial and Quantitative Analysis , Volume 48 , Issue 5 , October 2013 , pp. 1433 - 1461
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Ang, A., and Bekaert, G.. “Stock Return Predictability: Is It There?” Review of Financial Studies, 20 (2007), 651–707.CrossRefGoogle Scholar
Ang, A.; Hodrick, R. J.; Xing, Y.; and Zhang, X.. “The Cross-Section of Volatility and Expected Returns.” Journal of Finance, 61 (2006), 259–299.CrossRefGoogle Scholar
Asparouhova, E.; Bessembinder, H.; and Kalcheva, I.. “Noisy Prices and Inference Regarding Returns.” Journal of Finance, 68 (2013), 665–714.CrossRefGoogle Scholar
Avramov, D.; Chordia, T.; Jostova, G.; and Philipov, A.. “Dispersion in Analysts’ Earnings Forecasts and Credit Rating.” Journal of Financial Economics, 91 (2009), 83–101.CrossRefGoogle Scholar
Baker, M. P., and Wurgler, J.. “Investor Sentiment and the Cross-Section of Stock Returns.” Journal of Finance, 61 (2006), 1645–1680.CrossRefGoogle Scholar
Baker, M. P., and Wurgler, J.. “Investor Sentiment in the Stock Market.” Journal of Economic Perspectives, 21 (2007), 129–151.CrossRefGoogle Scholar
Balduzzi, P., and Lynch, A. W.. “Transaction Costs and Predictability: Some Utility Cost Calculations.” Journal of Financial Economics, 52 (1999), 47–78.CrossRefGoogle Scholar
Barberis, N.; Shleifer, A.; and Vishny, R.. “A Model of Investor Sentiment.” Journal of Financial Economics, 49 (1998), 307–343.CrossRefGoogle Scholar
Berkman, H.; Dimitrov, V.; Jain, P. C.; Koch, P. D.; and Tice, S.. “Sell on the News: Differences of Opinion, Short-Sales Constraints, and Returns around Earnings Announcements.” Journal of Financial Economics, 92 (2009), 376–399.CrossRefGoogle Scholar
Bharath, S. T., and Shumway, T.. “Forecasting Default with the Merton Distance to Default Model.” Review of Financial Studies, 21 (2008), 1339–1369.CrossRefGoogle Scholar
Blume, L.; Easley, D.; and O’Hara, M.. “Market Statistics and Technical Analysis: The Role of Volume.” Journal of Finance, 49 (1994), 153–181.CrossRefGoogle Scholar
Brock, W.; Lakonishok, J.; and LeBaron, B.. “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47 (1992), 1731–1764.CrossRefGoogle Scholar
Brown, D. P., and Jennings, R. H.. “On Technical Analysis.” Review of Financial Studies, 2 (1989), 527–551.CrossRefGoogle Scholar
Campbell, J. Y., and Thompson, S. B.. “Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?” Review of Financial Studies, 21 (2008), 1509–1531.CrossRefGoogle Scholar
Cespa, G., and Vives, X.. “Dynamic Trading and Asset Prices: Keynes vs. Hayek.” Review of Economic Studies, 79 (2012), 539–580.CrossRefGoogle Scholar
Chabot, B. R.; Ghysels, E.; and Jagannathan, R.. “Momentum Cycles and Limits to Arbitrage: Evidence from Victorian England and Post-Depression U.S. Stock Markets.” Working Paper, University of North Carolina-Chapel Hill and Northwestern University (2010).CrossRefGoogle Scholar
Chincarini, L. B., and Kim, D.. Quantitative Equity Portfolio Management: An Active Approach to Portfolio Construction and Management. New York, NY: McGraw-Hill (2006).Google Scholar
Chordia, T., and Shivakumar, L.. “Momentum, Business Cycle, and Time-Varying Expected Returns.” Journal of Finance, 57 (2002), 985–1019.CrossRefGoogle Scholar
Cochrane, J. H. “The Dog That Did Not Bark: A Defense of Return Predictability.” Review of Financial Studies, 21 (2008), 1533–1575.CrossRefGoogle Scholar
Collin-Dufresne, P.; Goldstein, R. S.; and Martin, J. S.. “The Determinants of Credit Spread Changes.” Journal of Finance, 56 (2001), 2177–2207.CrossRefGoogle Scholar
Cooper, M. J.; Gutierrez, R. C. Jr.; and Hameed, A. S.. “Market States and Momentum.” Journal of Finance, 59 (2004), 1345–1365.CrossRefGoogle Scholar
Covel, M. W. Trend Following: How Great Traders Make Millions in Up or Down Markets. New York, NY: Prentice-Hall (2005).Google Scholar
Cowles, A. “Can Stock Market Forecasters Forecast?” Econometrica, 1 (1933), 309–324.CrossRefGoogle Scholar
Daniel, K.; Hirshleifer, D.; and Subrahmanyam, A.. “Investor Psychology and Security Market Under- and Overreactions.” Journal of Finance, 53 (1998), 1839–1885.CrossRefGoogle Scholar
Diether, K. B.; Malloy, C. J.; and Scherbina, A.. “Differences of Opinion and the Cross Section of Stock Returns.” Journal of Finance, 57 (2002), 2113–2141.CrossRefGoogle Scholar
Ericsson, J.; Jacobs, K.; and Oviedo, R.. “The Determinants of Credit Default Swap Premia.” Journal of Financial and Quantitative Analysis, 44 (2009), 109–132.CrossRefGoogle Scholar
Faber, M. T. “A Quantitative Approach to Tactical Asset Allocation.” Journal of Wealth Management, 9 (2007), 69–79.CrossRefGoogle Scholar
Fama, E. F., and French, K. R.. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Financial Economics, 33 (1993), 3–56.CrossRefGoogle Scholar
Fama, E. F., and Schwert, W.. “Asset Returns and Inflation.” Journal of Financial Economics, 5 (1977), 115–146.CrossRefGoogle Scholar
Ferson, W. E., and Harvey, C. R.. “The Variation of Economic Risk Premiums.” Journal of Political Economy, 99 (1991), 385–415.CrossRefGoogle Scholar
Ferson, W. E., and Schadt, R. W.. “Measuring Fund Strategy and Performance in Changing Economic Conditions.” Journal of Finance, 51 (1996), 425–461.CrossRefGoogle Scholar
Fung, W., and Hsieh, D. A.. “The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers.” Review of Financial Studies, 14 (2001), 313–341.CrossRefGoogle Scholar
Gehrig, T., and Menkhoff, L.. “Extended Evidence on the Use of Technical Analysis in Foreign Exchange.” International Journal of Finance and Economics, 11 (2006), 327–338.CrossRefGoogle Scholar
Goh, J.; Jiang, F.; Tu, J.; and Zhou, G.. “Forecasting Government Bond Risk Premia Using Technical Indicators.” Working Paper, Singapore Management University and Washington University in St. Louis (2013).Google Scholar
Goldman, M. B.; Sosin, H. B., and Gatto, M. A.. “Path Dependent Options: ‘Buy at the Low, Sell at the High.’ ” Journal of Finance, 34 (1979), 1111–1127.Google Scholar
Griffin, J. M.; Ji, X.; and Martin, J.. “Momentum Investing and Business Cycle Risk: Evidence from Pole to Pole.” Journal of Finance, 58 (2003), 2515–2547.CrossRefGoogle Scholar
Han, Y. “Asset Allocation with a High Dimensional Latent Factor Stochastic Volatility Model.” Review of Financial Studies, 19 (2006), 237–271.CrossRefGoogle Scholar
Han, Y., and Lesmond, D. A.. “Liquidity Biases and the Pricing of Cross-Sectional Idiosyncratic Volatility.” Review of Financial Studies, 24 (2011), 1590–1629.CrossRefGoogle Scholar
Han, Y.; Wang, X.; Zhou, G.; and Zou, H.. “Are There Trends in Chinese Stock Market?” Working Paper, University of Colorado Denver and Washington University in St. Louis (2013).Google Scholar
Han, Y., and Zhou, G.. “Trend Factor: A New Determinant of Cross-Section Stock Returns.” Working Paper, University of Colorado Denver and Washington University in St. Louis (2013a).CrossRefGoogle Scholar
Han, Y., and Zhou, G.. “Twin Momentums in the Stock Market.” Working Paper, University ofColorado Denver and Washington University in St. Louis (2013b).Google Scholar
Henriksson, R. D., and Merton, R. C.. “On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills.” Journal of Business, 54 (1981), 513–533.CrossRefGoogle Scholar
Hjalmarsson, E. “Predicting Global Stock Returns.” Journal of Financial and Quantitative Analysis, 45 (2010), 49–80.CrossRefGoogle Scholar
Hong, H., and Stein, J. C.. “A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets.” Journal of Finance, 54 (1999), 2143–2184.CrossRefGoogle Scholar
Huang, D. “Market States and International Momentum Strategies.” Quarterly Review of Economics and Finance, 46 (2006), 437–446.CrossRefGoogle Scholar
Jegadeesh, N., and Titman, S.. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” Journal of Finance, 48 (1993), 65–91.CrossRefGoogle Scholar
LeBaron, B. “Technical Trading Rule Profitability and Foreign Exchange Intervention.” Journal of International Economics, 49 (1999), 125–143.CrossRefGoogle Scholar
Leland, H. E., and Toft, K. B.. “Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads.” Journal of Finance, 51 (1996), 987–1019.CrossRefGoogle Scholar
Lo, A. W., and Hasanhodzic, J.. The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. New York, NY: Bloomberg Press (2009).Google Scholar
Lo, A. W.; Mamaysky, H.; and Wang, J.. “Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation.” Journal of Finance, 55 (2000), 1705–1770.CrossRefGoogle Scholar
Longstaff, F. A., and Schwartz, E. S.. “A Simple Approach to Valuing Risky Fixed and Floating Rate Debt.” Journal of Finance, 50 (1995), 789–819.CrossRefGoogle Scholar
Lynch, A. W., and Balduzzi, P.. “Predictability and Transaction Costs: The Impact on Rebalancing Rules and Behavior.” Journal of Finance, 66 (2000), 2285–2309.CrossRefGoogle Scholar
Merton, R. C. “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates.” Journal of Finance, 29 (1974), 449–470.Google Scholar
Merton, R. C. “On Market Timing and Investment Performance. I. An Equilibrium Theory of Value for Market Forecasts.” Journal of Business, 54 (1981), 363–406.CrossRefGoogle Scholar
Neely, C. J. “The Temporal Pattern of Trading Rule Returns and Central Bank Intervention: Intervention Does Not Generate Technical Trading Rule Profits.” Working Paper, Federal Reserve Bank of St. Louis (2002).CrossRefGoogle Scholar
Neely, C. J.; Rapach, D. E.; Tu, J.; and Zhou, G.. “Forecasting the Equity Risk Premium: The Role of Technical Indicators.” Management Science, forthcoming (2013).Google Scholar
Newey, W. K., and West, K. D.. “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55 (1987), 703–708.CrossRefGoogle Scholar
Pástor, L., and Stambaugh, R. F.. “Liquidity Risk and Expected Stock Returns.” Journal of Political Economy, 111 (2003), 642–685.CrossRefGoogle Scholar
Rapach, D. E.; Strauss, J. K.; and Zhou, G.. “Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy.” Review of Financial Studies, 23 (2010), 821–862.CrossRefGoogle Scholar
Rapach, D. E.; Strauss, J. K.; and Zhou, G.. “International Stock Return Predictability: What Is the Role of the United States?” Journal of Finance, 68 (2013), 1633–1662.CrossRefGoogle Scholar
Schwager, J. D. Market Wizards: Interviews with Top Traders. New York, NY: Collins (1993).Google Scholar
Schwert, G. W. “Anomalies and Market Efficiency.” In Handbook of the Economics of Finance, Vol. 1, Constantinides, G. M., Harris, M., and Stulz, R. M., eds. Amsterdam, Netherlands: Elsevier (2003), 939–974.Google Scholar
Spiegel, M., and Wang, X.. “Cross-Sectional Variation in Stock Returns: Liquidity and Idiosyncratic Risk.” Working Paper, Yale University (2005).Google Scholar
Stambaugh, R. F.; Yu, J.; and Yuan, Y.. “The Short of It: Investor Sentiment and Anomalies.” Journal of Financial Economics, 104 (2012), 288–302.CrossRefGoogle Scholar
Stoll, H. R. “The Pricing of Security Dealer Services: An Empirical Study of Nasdaq Stocks.” Journal of Finance, 33 (1978), 1153–1172.CrossRefGoogle Scholar
Treynor, J. L., and Mazuy, K.. “Can Mutual Funds Outguess the Market?” Harvard Business Review, 44 (1966), 131–136.Google Scholar
Wilcox, C., and Crittenden, E.. “Does Trend Following Work on Stocks?” Working Paper, Blackstar Funds, LLC (2009).Google Scholar
Zhang, X. F. “Information Uncertainty and Stock Returns.” Journal of Finance, 61 (2006), 105–137.CrossRefGoogle Scholar
Zhou, G., and Zhu, Y.. “An Equilibrium Model of Moving-Average Predictability and Time-Series Momentum.” Working Paper, Tsinghua University and Washington University in St. Louis (2013).CrossRefGoogle Scholar
Zhu, Y., and Zhou, G.. “Technical Analysis: An Asset Allocation Perspective on the Use of Moving Averages.” Journal of Financial Economics, 92 (2009), 519–544.CrossRefGoogle Scholar