Abstract
Various trend-following trading rules have been shown to be valuable for predicting market directions and thus the formulation of investment strategies. However, recent equity market research has provided striking evidence that the predictive power of such rules appears to diminish over time due to increased investor attention and lowered arbitrage barriers. Given that trend-following rules are also very successful and have been widely used in futures markets, we analyze whether a similar effect can be observed for commodity futures contracts. Using a trend regression approach based on time-varying success ratios, we detect significantly higher predictive accuracy for cross-sectional than for time-series strategies. In addition, with the exception of a few commodities, we find no significant trending behavior in trading rule reliability. These results, which are robust in a variety of settings, indicate strong momentum stability in futures markets and justify the application of this class of trading rules in commodity futures investing.
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Notes
Moskowitz et al. (2012) alternatively predict time-series continuation and reversal via regressions of (a) scaled returns on past scaled returns and (b) scaled returns on past return signs.
Time-series momentum is a timing strategy, whereas cross-sectional momentum is a selection strategy.
For an excellent review of additional techniques to strengthen traditional momentum signals, see Miffre (2016). Also note that Fuertes et al. (2015) introduce a very intuitive method of forming bivariate and trivariate portfolios (via combined ranking scores) which might set an important standard for future research.
In contrast, Dow Jones UBS commodity indices have a slightly different rollover, from the sixth to the tenth business day (see Bianchi et al. 2015a).
Miffre and Rallis (2007) show that profitability declines with rising holding period length. They even document negative (zero) average returns over horizons of 18–24 months (beyond 24 months).
Similar to Szakmary et al. (2010), we do not form one momentum portfolio based on all commodities but base our analysis on individual securities. Our cross-sectional ranking simply serves the purpose of generating winner/loser signals which may be compared with the actual winner/loser position in the holding period.
The value of w is different from typical stock market settings because this way the strategies generate neutral signals in about one-third of the time and are thus comparable to the cross-sectional strategy outlined above.
Note that Narayan et al. (2015) calculate moving averages based on returns instead of prices.
In a related area of research, Narayan et al. (2013) find that commodity futures are better predictors for spot markets when daily data are used instead of monthly data.
Strobel and Auer (2018) emphasize that alternatively conducting trend regressions based on strategy returns leads to very similar trend conclusions because success ratios and strategy returns are naturally linked.
The observable distinct results for Brent and WTI crude oil are not surprising because their time-series characteristics are quite different (see Tian and Lai 2019).
We would not expect levels very close to one because past returns are unlikely to be able to forecast unforeseeable outside events related to climate phenomena (affecting, for example, wheat prices) or crisis-related investor behavior (influencing, for example, a safe haven asset like gold).
For a detailed empirical analysis of the reasons why momentum strategies behave differently in stock and futures markets, see Chevallier et al. (2013).
Detailed results are available from the authors upon request.
Adding more futures to the winner or loser sides enhances risk diversification at the cost of lowering the dispersion of returns between the best and worst performing futures and thus the profitability of the strategy.
Adaptive averages have also received attention. They seek to identify and adopt changing market conditions via an efficiency ratio derived from the notion of fractal efficiency and a method close to rescaled range analysis (see Ellis and Parbery 2005). However, the corresponding new trading rules leave the classic VMA framework.
References
Auer, B.: Does the choice of performance measure influence the evaluation of commodity investments? Int. Rev. Financ. Anal. 38, 142–150 (2015)
Auer, B., Rottmann, H.: Have capital market anomalies worldwide attenuated in the recent era of high liquidity and trading activity? J. Econ. Bus. 103, 61–79 (2019)
Bajgrowicz, P., Scaillet, O.: Technical trading revisited: false discoveries, persistence tests and transaction costs. J. Financ. Econ. 106(3), 473–491 (2012)
Bianchi, R., Drew, M., Fan, J.: Combining momentum with reversal in commodity futures. J. Bank. Finance 59, 423–444 (2015a)
Bianchi, R., Drew, M., Fan, J.: Microscopic momentum in commodity futures. Griffith University Discussion Papers Finance No. 2015-10 (2015b)
Bianchi, R., Drew, M., Fan, J.: Commodities momentum: a behavioral perspective. J. Bank. Finance 72, 133–150 (2016)
Brock, W., Lakonishok, J., LeBaron, B.: Simple technical trading rules and the stochastic properties of stock returns. J. Finance 47(5), 1731–1764 (1992)
Chevallier, J., Gatumel, M., Ielpo, F.: Understanding momentum in commodity markets. Appl. Econ. Lett. 20(15), 1383–1402 (2013)
Chordia, T., Subrahmanyam, A., Tong, Q.: Have capital market anomalies attenuated in the recent era of high liquidtiy and trading activity? J. Account. Econ. 58(1), 41–58 (2014)
Clare, A., Seaton, J., Smith, P., Thomas, S.: Trend following, risk parity and momentum in commodity futures. Int. Rev. Financ. Anal. 31, 1–12 (2014)
de Groot, W., Karstanje, D., Zhou, W.: Exploiting commodity momentum along the futures curves. J. Bank. Finance 48, 79–93 (2014)
Ellis, C., Parbery, S.: Is smarter better? A comparison of adaptive, and simple moving average trading strategies. Res. Int. Bus. Finance 19(3), 399–411 (2005)
Erb, C., Harvey, C.: The strategic and tactical value of commodity futures. Financ. Anal. J. 62(2), 69–97 (2006)
Fama, E., French, K.: Dissecting anomalies. J. Finance 63(4), 1653–1678 (2008)
Fama, E., French, K.: Size, value, and momentum in international stock returns. J. Financ. Econ. 105(3), 457–472 (2012)
Fifield, S., Power, D., Knipe, D.: The performance of moving average rules in emerging stock markets. Appl. Financ. Econ. 18(19), 1515–1532 (2008)
Fleming, J., Ostdiek, B., Whaley, R.: Trading costs and the relative rates of price discovery in stock, futures, and option markets. J. Futures Mark. 16(4), 353–387 (1996)
Foltice, B., Langer, T.: Profitable momentum trading strategies for individual investors. Financ. Mark. Portf. Manag. 29, 85–113 (2015)
Fong, W., Wong, W., Lean, H.: International momentum strategies: a stochastic dominance approach. J. Financ. Mark. 8(1), 89–109 (2005)
Fuertes, A., Miffre, J., Fernandez-Perez, A.: Commodity strategies based on momentum, term structure and idiosyncratic volatility. J. Futures Mark. 35(3), 274–295 (2015)
Fuertes, A., Miffre, J., Rallis, G.: Tactical allocation in commodity futures markets: combining momentum and term structure signals. J. Bank. Finance 34(10), 2530–2548 (2010)
Georgopoulou, A., Wang, J.: The trend is your friend: time-series momentum strategies across equity and commodity markets. Rev. Finance 21(4), 1557–1592 (2017)
Gorton, G., Rouwenhorst, K.: Facts and fantasies about commodity futures. Financ. Anal. J. 62(2), 47–68 (2006)
Hendershott, T., Jones, C., Menkveld, A.: Does algorithmic trading improve liquidity? J. Finance 66(1), 1–33 (2011)
Hong, H., Yogo, M.: What does futures market interest tell us about the macroeconomy and asset prices? J. Financ. Econ. 105(3), 473–490 (2012)
Irwin, S., Yoshimaru, S.: Managed futures, positive feedback trading, and futures price volatility. J. Futures Mark. 19(7), 759–776 (1999)
Jacobs, H.: What explains the dynamics of 100 anomalies? J. Bank. Finance 57, 65–85 (2015)
Jacobs, H., Müller, S.: Anomalies across the globe: once public, no longer existent? J. Financ. Econ. 135(1), 213–230 (2020)
Jegadeesh, N., Titman, S.: Returns to buying winners and selling losers: implications for stock market efficiency. J. Finance 48(1), 65–91 (1993)
Jegadeesh, N., Titman, S.: Profitability of momentum strategies: an evaluation of alternative explanations. J. Finance 56(2), 699–720 (2001)
Katusiime, L., Shamsuddin, A., Agbola, F.: Foreign exchange market efficiency and profitability of tradingrules: evidence from a developing country. Int. Rev. Econ. Finance 35, 315–332 (2015)
Kavajecz, K., Odders-White, E.: Technical analysis and liquidity provision. Rev. Financ. Stud. 17(4), 1043–1071 (2004)
Kho, B.: Time-varying risk premia, volatility, and technical trading rule profits: evidence from foreign currency futures markets. J. Financ. Econ. 41(2), 249–290 (1996)
Korajczyk, R., Sadka, R.: Are momentum profits robust to trading costs? J. Finance 59(3), 1039–1082 (2004)
Lesmond, D., Schill, M., Zhou, C.: The illusory nature of momentum profits. J. Financ. Econ. 71(2), 349–380 (2004)
Locke, P., Venkatesch, P.: Futures market transaction costs. J. Futures Mark. 17(2), 229–245 (1997)
Lubnau, T., Todorova, N.: Trading on mean-reversion in energy futures markets. Energy Econ. 51, 312–319 (2015)
Lukac, L., Brorsen, B., Irwin, S.: A test of futures market disequilibrium using twelve different technical trading systems. Appl. Econ. 20(5), 623–639 (1988)
Marshall, B., Cahan, R., Cahan, J.: Can commodity futures be profitably traded with quantitative market timing strategies? J. Bank. Finance 32(9), 1810–1819 (2008)
McLean, R., Pontiff, J.: Does academic research destroy stock return predictability? J. Finance 71(1), 5–32 (2016)
Miffre, J.: Long-short commodity investing: a review of the literature. J. Commod. Mark. 1(1), 3–13 (2016)
Miffre, J., Fernandez-Perez, A.: The case for long-short commodity investing. J. Altern. Invest. 18(1), 92–104 (2015)
Miffre, J., Rallis, G.: Momentum strategies in commodity futures markets. J. Bank. Finance 31(6), 1863–1886 (2007)
Morana, C.: A semiparametric approach to short-term oil price forecasting. Energy Econ. 23(3), 325–338 (2001)
Moskowitz, T., Ooi, Y., Pedersen, L.: Time series momentum. J. Financ. Econ. 104(2), 228–250 (2012)
Narayan, P., Ahmed, H., Narayan, S.: Do momentum-based trading strategies work in the commodity futures markets? J. Futures Mark. 35(9), 868–891 (2015)
Narayan, P., Narayan, S., Sharma, S.: An analysis of commodity markets: what gain for investors? J. Bank. Finance 37(10), 3878–3889 (2013)
Olson, D.: Have trading rule profits in the currency markets declined over time? J. Bank. Finance 28(1), 85–105 (2004)
Park, C., Irwin, S.: The profitability of technical trading rules in US futures markets: a data snooping free test. AgMAS Project Research Report 2005-04 (2005)
Park, C., Irwin, S.: A reality check on technical trading rule profits in the U.S. futures markets. J. Futures Mark. 30(7), 633–659 (2010)
Park, C., Irwin, S.: What do we know about the profitability of technical analysis? J. Econ. Surv. 21(4), 786–826 (2007)
Pindyck, R., Rubinfeld, D.: Econometric Models and Economic Forecasts. McGraw-Hill, Singapore (1998)
Rachev, S., Jas̆ić, T., Stoyanov, S., Fabozzi, F.: Momentum strategies based on reward-risk stock selection criteria. J. Bank. Finance 31(8), 2325–2346 (2007)
Ratner, M., Leal, R.: Tests of technical trading strategies in the emerging equity markets of Latin America and Asia. J. Bank. Finance 23(12), 1887–1905 (1999)
Rosillo, R., de la Fuente, D., Brugos, J.: Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies. Appl. Econ. 45(12), 1541–1550 (2013)
Shen, Q., Szakmary, A., Sharma, S.: An examination of momentum strategies in commodity futures markets. J. Futures Mark. 27(3), 227–256 (2007)
S&P Dow Jones Indices: S&P GSCI Methodology. McGraw Hill Financial, New York (2016)
Strobel, M., Auer, B.: Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies? Int. Rev. Econ. Finance 53, 168–184 (2018)
Swinkels, L.: Momentum investing: a survey. J. Asset Manag. 5, 120–143 (2004)
Szakmary, A., Shen, Q., Sharma, S.: Trend-following trading strategies in commodity futures: a re-examination. J. Bank. Finance 34(2), 409–426 (2010)
Taylor, N.: The rise and fall of technical trading rule success. J. Bank. Finance 40, 286–302 (2014)
Taylor, S.: Stock index and price dynamics in the UK and the US: new evidence from a trading rule and statistical analysis. Eu. J. Finance 6(1), 39–69 (2000)
Tian, H., Lai, W.: The causes of stage expansion of WTI/Brent spread. Pet. Sci. 16, 1493–1505 (2019)
Wang, C., Yu, M.: Trading activity and price reversals in futures markets. J. Bank. Finance 28(6), 1337–1361 (2004)
Wang, S., Yu, L., Lai, K.: A novel hybrid AI system framework for crude oil price forecasting. In: Shi, Y., Xu, W., Chen, Z. (eds.) Data Min. Knowl. Manag., pp. 233–242. Springer, Berlin, Heidelberg (2004)
Yao, Y.: Momentum, contrarian, and the January seasonality. J. Bank. Finance 36(10), 2757–2769 (2012)
Zaremba, A.: Strategies based on momentum and term structure in financialized commodity markets. Bus. Econ. Res. J. 7(1), 31–46 (2016)
Zhang, H., Auer, B., Vortelinos, D.: Performance ranking (dis)similarities in commodity markets. Glob. Finance J. 35, 115–137 (2018)
Acknowledgements
The author thanks Horst Rottmann, Julia Mehlitz, Anja Vinzelberg and an anonymous reviewer for valuable comments and suggestions. He is also indebted to the Fritz Thyssen Stiftung (Grant 20.18.0.016WW) for generous financial support.
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Auer, B.R. Have trend-following signals in commodity futures markets become less reliable in recent years?. Financ Mark Portf Manag 35, 533–553 (2021). https://doi.org/10.1007/s11408-021-00385-5
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DOI: https://doi.org/10.1007/s11408-021-00385-5