New strategies:
#445 – Hazard Fear in Commodity Markets
Period of rebalancing: Weekly
Markets traded: commodities
Instruments used for trading: futures, CFDs
Complexity: Very complex strategy
Backtest period: 2004 – 2018
Indicative performance: 8.23%
Estimated volatility: 9.26%
Source paper:
Fernandez-Perez, Adrian and Fuertes, Ana-Maria and González-Fernández, Marcos and Miffre, Joelle: Hazard Fear in Commodity Markets
https://ssrn.com/abstract=3411117
Abstract:
We introduce a commodity futures return predictor related to fear about impending weather, disease, geopolitical and economic hazards that can shift the commodity supply or demand. Exploiting the commodity hazard-fear characteristic as a trading signal in a long-short portfolio framework, we find a sizeable and significant commodity premium. The hazard-fear premium reflects compensation for known factors such as basis, momentum and illiquidity risks, but is not subsumed by them. Exposure to hazard-fear is strongly priced in the cross-section of individual commodity futures returns and commodity portfolios beyond known risk factors. We identify a strong role for general investor sentiment in the commodity hazard-fear premium.
#446 – Fundamental Strength and the 52-Week High Anomaly
Period of rebalancing: 6-Months
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 1985-2015
Indicative performance: 12.68%
Estimated volatility: 21.06%
Source paper:
Zhu, Zhaobo and Sun, Licheng and Chen, Min: Fundamental Strength and the 52-Week High Anomaly
https://ssrn.com/abstract=3421545
Abstract:
We test for competing explanations of the 52-week high anomaly. We report that a fundamental-strength enhanced 52-week high trading strategy significantly improves the unconditional strategy by nearly doubling its average return. Although the q-factor model offers a promising risk-based explanation, we find that the model’s explanatory power is sensitive to several outliers during momentum crash months. Our findings are consistent with the anchoring bias hypothesis that claims the 52-week high triggers investor underreaction to fundamental news. We document that this anomalous effect is most evident when investor sentiment is high, but absent among more sophisticated institutions and short sellers.
New research papers related to existing strategies:
#31 – Market Seasonality Effect in World Equity Indexes
Plastun, Sibande, Gupta, Wohar: Halloween Effect in Developed Stock Markets: A US Perspective
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3362154
Abstract:
In this paper, we conduct a comprehensive investigation of the Halloween effect evolution in the US stock market over its entire history. We employ various statistical techniques (average analysis, Student’s t-test, ANOVA, and the Mann-Whitney test) and the trading simulation approach to analyse the evolution of the Halloween effect. The results suggest that in the US stock market the Halloween effect became more persistent since the middle of the 20th century. Despite the decline in its prevalence since that time, nowadays it is still present in the US stock market and provides opportunities to build a trading strategy which can beat the market. These results are well in line with other developed stock markets. Therefore, in the main, our results are inconsistent with the Efficient Market Hypothesis.
#44 – Paired Switching
Zakamulin: Trend Following with Momentum Versus Moving Average: A Tale of Differences
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3293521
Abstract:
Despite the ever-growing interest in trend following and a series of publications in academic journals, there is still a great shortage of theoretical results on the properties of trend following rules. Our paper fills this gap by comparing and contrasting the two most popular trend following rules, the Momentum (MOM) and Moving Average (MA) rules, from a theoretical perspective. Our approach is based on the return-based formulation of trading rules and modelling the price trends by an autoregressive return process. We provide theoretical results on the similarity between various trend following rules and the forecast accuracy of trading rules. Our results show that the similarity between the MOM and MA rules is rather high and increases with increasing trend strength. However, as compared to the MOM rule, the MA rules have a more robust forecast accuracy of the future direction of price trends. As a result, under uncertain market dynamics the MA rules tend to gain an advantage over the MOM rule. Overall, the results reported in this paper help traders to understand more deeply the properties of trend following rules as well as the differences and similarities between them.
And two short free blog posts about interesting related research papers have been published during last 2 weeks:
Do retail day traders have a chance in current financial markets? They often lack proper trading research and infrastructure; they are facing high fees and stiff competition from professionals. But it’s always useful to view actual hard numbers and performance statistics and not just rely on feelings. Luckily, some academic research papers are exploring the question of the performance of retail traders. Chague, De-Losso, and Giovannetti have written the newest one, and as expected, their findings are not very favorable for retail day traders.
Chague, De-Losso, Giovannetti: Day Trading for a Living?
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3423101
Abstract:
We show that it is virtually impossible for an individual to day trade for a living, contrary to what course providers claim. We observe all individuals who began to day trade between 2013 and 2015 in the Brazilian equity futures market, the third in terms of volume in the world, and persisted for at least 300 days: 97% of them lost money, only 0.4% earned more than a bank teller (US$54 per day), and the top individual earned only US$310 per day with great risk (a standard deviation of US$2,560). Additionally, we find no evidence of learning by day trading.
Commodities are an essential exporting asset for a lot of countries around the world. Therefore, it is not surprising that the stock market returns of some emerging market countries are dependent on the returns of those commodities. What is more striking is that commodities do not forecast equity returns for only those few small exporting countries. Academic research paper written by Alves & Szymanowska shows that commodity futures returns predict stock market returns in 65 out of 70 countries and macroeconomic fundamentals in 62 countries. That is looking like an idea worth dig into …
Alves, Szymanowska: The Information Content of Commodity Futures Markets
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3352822
Abstract:
We find that commodity futures returns contain information relevant to stock market returns and macroeconomic fundamentals for a large number of countries. Commodity futures returns predict stock market returns in 65 out of 70 countries and macroeconomic fundamentals in 62 countries. This predictability is not concentrated in the energy and industrial metals sectors, as it is economically and statistically significant across all sectors. Surprisingly, we find that the role of countries’ dependence on commodity trade is limited in its ability to account for this predictability. This holds true even when considering new measures that take into account indirect exposures through financial and trade linkages between countries. We find much stronger evidence of predictability being related to the ability of commodities to forecast inflation rates. Overall, our evidence is consistent with commodity markets having a truly global information discovery role in relation to financial markets and the real economy.
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