New strategies:
#344 – Dynamic Momentum and Contrarian Trading
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1927 – 2015
Indicative performance: 21.74%
Estimated volatility: 26.74%
Source paper:
Dobrynskaya: Dynamic Momentum and Contrarian Trading
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2942641
Abstract:
High momentum returns cannot be explained by risk factors, but they are negatively skewed and subject to occasional severe crashes. I explore the timing of momentum crashes and show that momentum strategies tend to crash in 1-3 months after the local stock market plunge. Next, I propose a simple dynamic trading strategy which coincides with the standard momentum strategy in calm times, but switches to the opposite contrarian strategy in one month after a market crash and keeps the contrarian position for three months, after which it reverts back to the momentum position. The dynamic momentum strategy turns all major momentum crashes into gains and yields average return, which is about 1.5 times as high as the standard momentum return. The dynamic momentum returns are positively skewed and not exposed to risk factors, have high Sharpe ratio and alpha, persist in different time periods and geographical markets around the Globe.
#345 – Betting Against Correlation Effect
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1963-2015
Indicative performance: 12.28%
Estimated volatility: 13.20%
Source paper:
Asness, Frazzini, Gormsen, Pedersen: Betting Against Correlation: Testing Theories of the Low-Risk Effect
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2913508
Abstract:
We test whether the low-risk effect is driven by (a) leverage constraints and thus risk should be measured using beta vs. (b) behavioral effects and thus risk should be measured by idiosyncratic risk. Beta depends on volatility and correlation, where only volatility is related to idiosyncratic risk. Hence, the new factor betting against correlation (BAC) is particularly suited to differentiating between leverage constraints vs. lottery explanations. BAC produces strong performance in the US and internationally, supporting leverage constraint theories. Similarly, we construct the new factor SMAX to isolate lottery demand, which also produces positive returns. Consistent with both leverage and lottery theories contributing to the low-risk effect, we find that BAC is related to margin debt while idiosyncratic risk factors are related to sentiment.
New research paper related to existing strategy:
#115 – Short-Term Residual Reversal
#136 – Residual Momentum
Huij, Lansdorp: Residual Momentum and Reversal Strategies Revisited
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2929306
Abstract:
In this note we revisit the 2011 and 2013 papers of Blitz, Huij, and Martens (BHM2011), and Blitz, Huij, Lansdorp, and Verbeek (BHLV2013) in which momentum and reversal strategies on residual returns are proposed. Our results indicate that the main findings of these studies, that residual momentum and reversal strategies exhibit significantly lower time-varying exposures to the Fama-French factors than conventional momentum and reversal strategies and consequently have significantly higher return-to-risk ratios, are robust across different global stock universes and out-of-sample periods after the publication of the first results.
Two additional related research papers have been included into existing free strategy reviews during last 2 week:
An interesting academic paper about the intristic value of Gold:
Harris, Shen: The Intrinsic Value of Gold: An Exchange Rate-Free Price Index
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2926454
Abstract:
In this paper, we propose a gold price index that enables market participants to separate the change in the ‘intrinsic’ value of gold from changes in global exchange rates. The index is a geometrically weighted average of the price of gold denominated in different currencies, with weights that are proportional to the market power of each country in the global gold market, where market power is defined as the impact that a change in a country’s exchange rate has on the price of gold expressed in other currencies. We use principal components analysis to reduce the set of global exchange rates to four currency ‘blocs’ representing the U.S. dollar, the euro, the commodity currencies and the Asian currencies. We estimate the weight of each currency bloc in the index in an error correction framework using a broad set of variables to control for the unobserved intrinsic value. We show that the resulting index is less volatile than the USD price of gold and, in contrast with the USD price of gold, has a strong negative relationship with global equities and a strong positive relationship with the VIX index, both of which underline the role of gold as a safe haven asset.
Our favorite research paper about the performance of long-only investment strategies in commodities:
Erb, Harvey: Conquering Misperceptions about Commodity Futures Investing
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2645444
Abstract:
Long-only commodity futures returns have been very disappointing over the last decade, leading some to wonder if it was a mistake to invest in commodities. The poor performance is the result of poor “income returns” and not of falling commodity prices. This observation may be surprising for many commodity investors who were not aware, who misperceived, they were making a bet on income returns, a return building block similar to a stock’s dividend yield or a bond’s yield. For investors seeking an inflation hedge, it may be surprising that the historical linkage of commodity returns with inflation seems to be the result of a connection between commodity income returns and inflation, not, as commonly misperceived, commodity price returns and inflation. It may be surprising that the value of commodity investments is smaller than the market capitalization of Facebook, a potentially striking misperception for investors seeking a portfolio diversifier with abundant capacity. There has been no change in the way that price returns and income returns drive the total returns of stocks, bond and commodities. What has changed is that maybe a good number of commodity investors now realize that they were operating outside of their “circle of competence” and did not have a sense of what future price and income returns could be and would be.
