New strategies:
#353 – US Sector Rotation with Five-Factor Fama-French Alphas
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: ETFs
Complexity: Complex strategy
Bactest period: 1967 – 2014
Indicative performance: 11.07%
Estimated volatility: 15.83%
Source paper:
Sarwar, Mateus, Todorovic: US Sector Rotation with Five-Factor Fama-French Alphas
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2987819
Abstract:
In this paper we investigate the risk-adjusted performance of US sector portfolios and sector rotation strategy using the alphas from the Fama-French five factor model. We find that five-factor model fits better the returns of US sector portfolios than the three factor model, but that significant alphas are still present in all the sectors at some point in time. In the full sample period, 50% of sectors generate significant five-factor alpha. We test if such alpha signifies a true sector out/underperformance by applying simple long-only and long-short sector rotation strategies. Our long-only sector rotation strategy that buys a sector with a positive five-factor alpha generates four times higher Sharpe ratio than the S&P500 buy-and-hold. If the strategy is adjusted to switch to the risk-free asset in recessions, the Sharpe ratio achieved is ten-fold that of the buy-and-hold. The long-short strategy fares less well.
New research papers related to existing strategies:
#118 – Time Series Momentum Effect
Hurst, Ooi, Pedersen: A Century of Evidence on Trend-Following Investing
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2993026
Abstract:
In this article, the authors study the performance of trend-following investing across global markets since 1880, extending the existing evidence by more than 100 years using a novel data set. They find that in each decade since 1880, time series momentum has delivered positive average returns with low correlations to traditional asset classes. Further, time-series momentum has performed well in 8 out of 10 of the largest crisis periods over the century, defined as the largest drawdowns for a 60/40 stock/bond portfolio. Lastly, time series momentum has performed well across different macro environments, including recessions and booms, war and peacetime, high- and low-interest rate regimes, and high- and low-inflation periods.
#118 – Time Series Momentum Effect
#229 – Earnings Quality Factor
Cook, Hoyle, Sargaison, Taylor, Hemert: The Best Strategies for the Worst Crises
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2986753
Abstract:
Hedging equity portfolios against the risk of large drawdowns is notoriously difficult and expensive. Holding, and continuously rolling, at-the-money put options on the S&P 500 is a very costly, if reliable, strategy to protect against market sell-offs. Holding ‘safe-haven’ US Treasury bonds, while providing a positive and predictable long-term yield, is generally an unreliable crisis-hedge strategy, since the post-2000 negative bond-equity correlation is a historical rarity. Long gold and long credit protection portfolios appear to sit between puts and bonds in terms of both cost and reliability. In contrast to these passive investments, we investigate two dynamic strategies that appear to have generated positive performance in both the long-run but also particularly during historical crises: futures time-series momentum and quality stock factors. Futures momentum has parallels with long option straddle strategies, allowing it to benefit during extended equity sell-offs. The quality stock strategy takes long positions in highest-quality and short positions in lowest-quality company stocks, benefitting from a ‘flight-to-quality’ effect during crises. These two dynamic strategies historically have uncorrelated return profiles, making them complementary crisis risk hedges. We examine both strategies and discuss how different variations may have performed in crises, as well as normal times, over the years 1985 to 2016.
Three additional related research papers have been included into existing free strategy reviews during last 2 week:
Financial variables have become the main driving factors explaining the variation in crude oil returns:
Adams, Kartsakli: Has Crude Oil Become a Financial Asset? Evidence from Ten Years of Financialization
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2999717
Abstract:
The financialization of crude oil markets over the last decade has changed the behavior of oil prices in fundamental ways. In this paper, we uncover the gradual transformation of crude oil from a physical to a financial asset. Although economic demand and supply factors continue to play an important role, recent indicators associated with financialization have emerged since 2008. We show that financial variables have become the main driving factors explaining the variation in crude oil returns and volatility today. Our findings have important implications for portfolio analysis and for the effectiveness of hedging in crude oil markets.
An interesting idea to create a CAPE Ratio with a better predictability:
Davis, Aliaga-Diaz, Ahluwalia, Tolani: Improving U.S. Stock Return Forecasts: A 'Fair-Value' Cape Approach
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2983860
Abstract:
The accuracy of U.S. stock return forecasts based on the cyclically-adjusted P/E (CAPE) ratio has deteriorated since 1985. The issue is not the CAPE ratio, but CAPE regressions that assume it reverts mechanically to its long-run average. Our approach conditions mean reversion in the CAPE ratio on real (not nominal) bond yields, reducing out-of-sample forecast errors by as much as 50%. At present, low real bond yields imply low real earnings yields and an above-average “fair-value” CAPE ratio. Nevertheless, with Shiller’s CAPE ratio now well above its fair value, our model predicts muted U.S. stock returns over the next decade. We believe that our framework should be adopted by the investment profession when forecasting stock returns for strategic asset allocation.
It is very hard to do a successful un-biased out-of-sample prediction of equity premium:
Bartsch, Dichtl, Drobetz, Neuhierl: Data Snooping in Equity Premium Prediction
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2972011
Abstract:
We study the performance of a comprehensive set of equity premium forecasting strategies that have been shown to outperform the historical mean out-of-sample when tested in isolation. Using a multiple testing framework, we find that previous evidence on out-of-sample predictability is primarily due to data snooping. We are not able to identify any forecasting strategy that produces robust and statistically significant economic gains after controlling for data snooping biases and transaction costs. By focusing on the application of equity premium prediction, our findings support Harvey’s (2017) more general concern that many of the published results in financial economics will fail to hold up.
