New strategy:
#357 – Using Intensity of Book to Market to Identify Growth Premium
Period of rebalancing: quarterly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1971 – 2015
Indicative performance: 4.49%
Estimated volatility: 9.58%
Source paper:
Jia, Yuecheng and Yang, Haoxi : Growth Stocks Are More Risky: New Evidence on Cross–Sectional Stock Returns
https://ssrn.com/abstract=2988137
Abstract:
The conventional wisdom argues that the growth stocks are more risky to earn higher premium. However the empirical evidence points out that the value stocks, which are classified based on the Book-to-Market ratio, tend to have higher premium. To solve for this tension, this paper proposes a novel but simple transformation of the Book-to-Market ratio, the intensity of Book-to-Market ratio to captures the dynamics of growth options. Our results show the intensity of Book-to-Market ratio has a strong negative relation with future cross–sectional stock returns even after controlling for main return predictors including Book-to-Market ratio. Therefore, consistent with conventional wisdom, our results confirm that growth stocks tend to earn higher expected premium and more risky than value stocks.
#358 – Reversal, Momentum and Intraday Returns
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1993 – 2014
Indicative performance: 5.12%
Estimated volatility: 9.21%
Source paper:
Xu, Haoyu: Reversal, Momentum and Intraday Returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2991183
Abstract:
This paper studies the trades immediately after the market open and immediately before the market close. The trades in the morning positively predict future returns and cause price continuation. The trades in the afternoon negatively predict future returns and cause price reversals. The momentum trading strategies based on morning returns and the reversal trading strategies based on afternoon returns generate significant abnormal returns, which cannot be explained by standard risk factors including momentum and reversal factors. The results provide strong evidence that trades in the morning are mostly information driven and trades in the afternoon are mostly liquidity driven.
New research paper related to existing strategy:
#356 – The Dollar Ahead of FOMC Target Rate Changes
Borisenko, Pozdeev: Monetary Policy and Currency Returns: The Foresight Saga
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2983043
Abstract:
We document a drift in exchange rates before monetary policy changes across major economies. Currencies tend to depreciate by 0.7 percent over ten days before policy rate cuts and appreciate by 0.5 percent before policy rate increases. We show that available fixed income instruments allow to accurately forecast monetary policy decisions and thus that the drift is foreseeable and exploitable by investors. A simple trading strategy buying currencies against USD ten days ahead of predicted local interest rate hikes and selling currencies before predicted cuts earns on average a statistically significant return of 42 basis points per ten-day period. We further demonstrate that this return is robust to the choice of holding horizon and monetary policy forecast rule. Our results thus pose a major challenge for the risk-based explanations of the exchange rate dynamics.
Two additional related research papers have been included into existing free strategy reviews during last 2 weeks:
An important paper about correlation structure of anomalies:
Geertsema, Lu: The Correlation Structure of Anomaly Strategies
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3002797
Abstract:
We investigate the correlation structure of anomaly strategy returns. From an initial 434 anomalies, we select 116 anomalies that are significant in the mean and not highly correlated with other anomalies. Cluster analysis reveals 24 clusters and 29 singleton anomalies that can be grouped into 3 essentially uncorrelated blocks. Correlations between anomaly strategies exhibit some stability over time at both a pairwise and aggregate level. The exception is a correlation spike in 2001, possibly related to the aftermath of the dot-com crisis. In volatile markets correlations increase in magnitude while maintaining their sign. Short and long legs of the same anomaly are highly correlated but becomes largely uncorrelated once we use market excess returns, suggesting that the long and short legs of anomalies follow different dynamics once market-wide influences are compensated for. Correlations based on the residuals of benchmark models are substantially lower, with mean absolute correlation declining by up to half. The existence of 116 anomaly strategies that are not highly correlated echoes other findings in the literature that the return generating process for realised returns appears to be of a high dimension.
How should investor weight commodity strategies in his portfolio? Is it better to use simple approach or some sophisticated weighting scheme?
Fernandez-Perez, Fuertes, Miffre: Harvesting Commodity Styles: An Integrated Framework
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3005347
Abstract:
This paper develops a portfolio allocation framework to study the benefits of style integration and to compare the effectiveness of alternative integration methods in commodity markets. The framework is flexible enough to be applicable to any asset class for either long-short, long- or short-only styles. We study the naïve equal-weighted integration and sophisticated integrations where the style exposures are sample-based by utility maximization, style rotation, volatility-timing, cross-sectional pricing or principal components analysis. Considering the “universe” of eleven long-short commodity styles, we document that the naïve integration enhances each of the individual styles in terms of their reward-to-risk tradeoff and crash risk profile. Sophisticated integrations do not challenge the naïve integration and the rationale is that, while also achieving multiple-style exposures, the equal-weighting approach circumvents estimation risk and perfect-foresight bias. The findings hold after trading costs, various reformulations of the sophisticated integrations, economic sub-period analyses and data snooping tests inter alia.
