New strategies:
#272 – Overnight Stock Trading
Period of rebalancing: daily
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1995 – 2014
Indicative performance: 21.28%
Estimated volatility: 6.60%
Source paper:
Lachance: Night Trading: Lower Risk But Higher Returns?
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2633476
Abstract:
This paper demonstrates that overnight returns are subject to highly persistent biases and examines the profitability of overnight-only investments in that context. Overnight returns tend to exceed their intraday counterparts, and the paper first reconciles these patterns by introducing a model that factors in recurring biases. This model identifies one fifth of stocks as having positive and statistically significant overnight biases. Investing overnight in these stocks in the next year yields twice the market’s return for a third of the market beta. Results have also implications for daytime investors as these stocks average negative returns intraday. Implementation costs and issues are discussed.
#273 – Overreaction to Merger and Acquisition Announcements
Period of rebalancing: daily
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1980 – 2012
Indicative performance: 15.83%
Estimated volatility: not stated
Source paper:
Bessembinder, Zhang: Overreaction to Merger and Acquisition Announcements
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2595329
Abstract:
We examine investor reactions to merger and acquisition announcements, focusing on the Initial Target Price (ITP) ratio, which is the target firm stock price on the first day after the announcement relative to the offer price, and can be interpreted as a measure of investor optimism regarding deal outcomes. We find that high price-to-offer-price ratios are associated with surprisingly low likelihoods of deal success, and significant negative abnormal returns of 3.5% over the two months following the announcement. We investigate potential explanations for the results, and find that they are most consistent with the interpretation that high ITP ratios indicate investor overreaction.
New research papers related to existing strategies:
#7 – Volatility Effect in Stocks – Long-Only Version
Van Vliet: Low Turnover: A Virtue of Low Volatility
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2612790
Abstract:
Excessive trading can be linked to human behavior. One explanation for unnecessary turnover is the well-documented overconfidence bias. Another explanation is a misalignment of interest between asset managers and asset owners: trading sends a positive signal to superiors and clients. To actively get exposure to low-volatility stocks requires a certain amount of trading. Using a meta-study combining 21 previous analyses we find a weak concave relation between turnover and the achieved risk reduction. In general 30% annualized turnover should be enough to reduce portfolio volatility by 25% compared to a market-weighted index, and low-volatility stocks are also relatively cheap to trade. Thus long-term investors can get efficient exposure to the low-volatility effect, at moderate trading levels.
#175 – Pairs Trading on Intraday Basis
Fallahpour, Hakimian, Taheri, Ramezanifar: Pairs Trading Strategy Optimization Using the Reinforcement Learning Method: A Cointegration Approach
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2624328
Abstract:
Recent studies show that the growing popularity of the pairs trading strategy may pose a problem as the opportunities to trade become much smaller. Hence optimizing pairs trading strategy has gained widespread attention among high-frequency traders. In this paper, by employing reinforcement learning, we examine the optimum level of pairs trading specifications over time. The reinforcement learning agent chooses the optimum level of parameters of pairs trading to maximize the objective function. Results are obtained by applying a combination of reinforcement learning method and cointegration approach. We find that boosting pairs trading specifications by using the proposed approach is significantly over perform the previous methods. Empirical results based on the intraday data which are obtained from S&P 500 constituent stocks support our method.
Two additional related research paper have been included into existing free strategy reviews during last 2 week:
#5 – FX Carry Trade
Clare, Seaton, Smith, Thomas: Carry and Trend Following Returns in the Foreign Exchange Market
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2633752
Abstract:
Recent research has confirmed the behaviour of traders that significant excess returns can be achieved from following the predictions of the carry trade which involves buying currencies with relatively high short-term interest rates, or equivalently a high forward premium, and selling those with relatively low interest rates. This paper shows that similar-sized excess returns can be achieved by following a trend-following strategy which buys long positions in currencies that have achieved positive returns and otherwise holds cash. We demonstrate that market risk is an important determinant of carry returns but that the standard unconditional CAPM is inadequate in explaining the cross-section of forward premium ordered portfolio returns. We also show that the downside risk CAPM fails to explain this cross-section, in contrast to recent literature. A conditional CAPM which makes the impact of the market return as a risk factor depend on a measure of market liquidity performs very well in explaining more than 90% of the variation in portfolio returns and more than 90% of the average returns to the carry trade. Trend following is found to provide a significant hedge against these risks. The performance of the trend following factor is more surprising given that it does not have the negative skewness or maximum drawdown characteristic which is shown by the carry trade factor.
#14 – Momentum Effect in Stocks
#26 – Value (Book-to-Market) Anomaly
Moskowitz: Asset Pricing and Sports Betting
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2635517
Abstract:
I use sports betting markets as a laboratory to test behavioral theories of cross-sectional asset pricing anomalies. Two unique features of these markets provide a distinguishing test of behavioral theories: 1) the bets are completely idiosyncratic and therefore not confounded by rational theories; 2) the contracts have a known and short termination date where uncertainty is resolved that allows any mispricing to be detected. Analyzing more than a hundred thousand contracts spanning two decades across four major professional sports (NBA, NFL, MLB, and NHL), I find momentum and value effects that move betting prices from the open to the close of betting, that are then completely reversed by the game outcome. These findings are consistent with delayed overreaction theories of asset pricing. In addition, a novel implication of overreaction uncovered in sports betting markets is shown to also predict momentum and value returns in financial markets. Finally, momentum and value effects in betting markets appear smaller than in financial markets and are not large enough to overcome trading costs, limiting the ability to arbitrage them away.
