New strategies:
#301 – Overnight-Intraday Daily Reversal in Commodities
Period of rebalancing: intraday
Markets traded: commodities
Instruments used for trading: futures, CFDs
Complexity: Complex strategy
Bactest period: 2007-2014
Indicative performance: 45.75%
Estimated volatility: 31.02%
Source paper:
Corte, Kosowski, Wang: Market Closure and Short-Term Reversal
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2730304
Abstract:
A strategy that holds daily long and short positions, respectively, in assets with low and high past overnight returns – overnight-intraday reversal strategy – generates for the US stock market an average excess return that is five times larger when compared to a conventional short-term reversal strategy. Our results remain robust to using international stocks as well as equity index, interest rate, commodity, and currency futures. We find that overnight-intraday reversals are consistent with the simulated patterns generated by the continuous-time model with periodic market closures of Hong and Wang (2000). Finally, we demonstrate that only intraday returns matter for the reversal-based liquidity measure of Pastor and Stambaugh (2003).
#302 – Overnight-Intraday Weekly Reversal in Currency Futures
Period of rebalancing: intraday
Markets traded: currencies
Instruments used for trading: futures, CFDs, swaps
Complexity: Complex strategy
Bactest period: 1982-2014
Indicative performance: 9.18%
Estimated volatility: 10.23%
Source paper:
Corte, Kosowski, Wang: Market Closure and Short-Term Reversal
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2730304
Abstract:
A strategy that holds daily long and short positions, respectively, in assets with low and high past overnight returns – overnight-intraday reversal strategy – generates for the US stock market an average excess return that is five times larger when compared to a conventional short-term reversal strategy. Our results remain robust to using international stocks as well as equity index, interest rate, commodity, and currency futures. We find that overnight-intraday reversals are consistent with the simulated patterns generated by the continuous-time model with periodic market closures of Hong and Wang (2000). Finally, we demonstrate that only intraday returns matter for the reversal-based liquidity measure of Pastor and Stambaugh (2003).
#303 – Overnight-Intraday Weekly Reversal in Interest Rate Futures
Period of rebalancing: intraday
Markets traded: bonds
Instruments used for trading: futures, CFDs, swaps
Complexity: Complex strategy
Bactest period: 1982-2014
Indicative performance: 6.83%
Estimated volatility: 7.69%
Source paper:
Corte, Kosowski, Wang: Market Closure and Short-Term Reversal
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2730304
Abstract:
A strategy that holds daily long and short positions, respectively, in assets with low and high past overnight returns – overnight-intraday reversal strategy – generates for the US stock market an average excess return that is five times larger when compared to a conventional short-term reversal strategy. Our results remain robust to using international stocks as well as equity index, interest rate, commodity, and currency futures. We find that overnight-intraday reversals are consistent with the simulated patterns generated by the continuous-time model with periodic market closures of Hong and Wang (2000). Finally, we demonstrate that only intraday returns matter for the reversal-based liquidity measure of Pastor and Stambaugh (2003).
New research papers related to existing strategies:
#49 – S&P 500 Index Addition Effect
Schnitzler: S&P 500 Inclusions and Stock Supply
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2746479
Abstract:
I provide new evidence to the S&P 500 inclusion effect that highlights the importance of stock supply. If the inclusion effect is driven by excess demand of S&P 500-linked capital, it should depend on the effective stock supply as well. Based on two distinct supply proxies, I find a significant relation with the cross-sectional size of the effect. Standard & Poor’s policy to change to free-floated index weights in 2005 enables a natural experiment giving further support to a supply interpretation. Furthermore, evidence from the most recent decade indicates that the controversially discussed persistence in the inclusion effect has disappeared.
#58 – VIX Predicts Stock Index Returns
Smales: Risk-On/Risk-Off: Financial Market Response to Investor Fear
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2717330
Abstract:
This article examines the relationship between changes in the level of investor fear (measured by VIX) and financial market returns. We document a statistically significant relationship, across asset classes, consistent with a flight to quality as investor fear increases. As VIX increase there is a decline in stock markets, bond yields, and high-yielding currencies (AUD and NZD), while the USD appreciates. Returns become more sensitive to changes in the level of investor fear during the financial crisis of 2008-09, when investor fear spikes sharply. Analysis of market returns subsequent to periods of extreme levels of investor fear suggests some predictive ability for future returns, and it is suggested that this may be used to develop a profitable trading strategy. Taken together, the results confirm that financial market returns are closely related to prevailing levels of investor fear.
#264 – Dividend Risk Premium Strategy
Cejnek, Randl: Dividend Risk Premia
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2725073
Abstract:
This paper studies time variation in expected excess returns of traded claims on dividends, bonds, and stock indices for US and international markets. We construct dividend risk factors corresponding to the well-known bond risk factors of Cochrane and Piazzesi (2005) and run predictive regressions of one-year annual excess returns on both risk factors. We find both return forecasting factors to be important for the prediction of returns on stock indices and traded dividends, but only the bond risk factor is highly relevant for bond returns. Further analyzing the components of risk, we find global factors to explain the largest part of the variation in index excess returns, while local factors still improve the fit for bond and dividend markets. The return-forecasting factors also predict excess returns for regions and assets that we did not use to construct the risk factors (equity indices in developed and emerging markets, emerging market bonds, corporate bond indices and a volatility selling strategy), suggesting substantial comovement in international risk premia.
Three additional related research papers have been included into existing free strategy reviews during last 2 week:
#20 – Volatility Risk Premium Effect
Israelov, Nielsen: Covered Calls Uncovered
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2444999
Abstract:
Equity index covered calls have historically provided attractive risk-adjusted returns largely because they collect equity and volatility risk premia from their long equity and short volatility exposures. However, they also embed exposure to an uncompensated risk, a naïve equity market reversal strategy. This paper presents a novel performance attribution methodology, which deconstructs the strategy into these three identified exposures, in order to measure each’s contribution to the covered call’s return. The covered call’s equity exposure is responsible for most of the strategy’s risk and return. The strategy’s short volatility exposure has had a realized Sharpe ratio close to 1.0, but its contribution to risk has been less than 10 percent. The equity reversal exposure is responsible for about one-quarter of the covered call’s risk, but provides little reward. Finally, we propose a risk-managed covered call strategy that hedges the equity reversal exposure in an attempt to eliminate this uncompensated risk. Our proposed strategy improved the covered call’s Sharpe ratio, and reduced its volatility and downside equity beta.
An academic paper related to multiple strategies:
Docherty: How Smart is Smart Beta Investing? Evidence from Australia
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2706246
Abstract:
"Smart beta" investing is an alternative to the traditional active and passive approaches to funds management, whereby investors adopt a systematic method that provides exposure to factors that are argued to be related with expected returns at low cost. Therefore, the question of how smart is smart beta investing can be empirically examined by testing the performance of those factors that underlie smart beta portfolios. We use a long time-series of data and show that the value, momentum, low volatility and quality factors all generate positive abnormal returns in the Australian equity market. Rather than ranking these factors based on relative performance, we argue that the optimal approach to smart beta investing is to diversify across these factors, given the low correlations between factor returns. Our results provide important implications for the Australian funds management industry. First, while this study does not examine the specific strategies applied by smart beta fund managers, the evidence presented provides a justification for the application of smart beta as a low cost alternative to active investment. Second, given evidence that multiple factors explain equity returns, multi-factor models should be used to measure active portfolio manager performance in order to distinguish pure alpha from abnormal returns generated due to smart beta exposure.
#21 – Momentum Effect in Commodities
#22 – Term Structure Effect in Commodities
#118 – Time Series Momentum Effect
Blocher, Cooper, Molyboga: Benchmarking Commodity Investments
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2744766
Abstract:
While much is known about the financialization of commodities, less is known about how to profitably invest in commodities. Existing studies of Commodity Trading Advisors (CTAs) do not adequately address this question because only 19% of CTAs invest solely in commodities, despite their name. We compare a novel four-factor asset pricing model to existing benchmarks used to evaluate CTAs. Only our four-factor model prices both commodity spot and term risk premia. Overall, our four-factor model prices commodity risk premia better than the Fama-French three-factor model prices equity risk premia, and thus is an appropriate benchmark to evaluate commodity investment vehicles.
