New strategies:
#348 – The Tax Day Trade
Period of rebalancing: daily
Markets traded: equities
Instruments used for trading: futures, CFDs, ETFs
Complexity: Simple strategy
Bactest period: 1980 – 2015
Indicative performance: 2.50%
Estimated volatility: not stated
Source paper:
Moffitt: The Tax Day Trade: An Efficient Market Anomaly
https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2910752
Abstract:
A one day trade that gains an average of 1/2% per day, the Tax Day Trade, is analyzed. The trade was developed using the Strategic Analysis of Markets Method (SAMM) described in the two volume series "The Strategic Analysis of Financial Markets" (forthcoming from World Scientific). Detective work reveals the dynamics behind its success and behavioral analysis shows that its impact won't diminish without significant countervailing arbitrage. This is a clear-cut efficient markets "anomaly" whose origins are known, and which has not been arbitraged away.
#349 – Trading Options During Expiration Weekends
Period of rebalancing: daily
Markets traded: equities
Instruments used for trading: options
Complexity: Complex strategy
Bactest period: 1996-2014
Indicative performance: 21.26%
Estimated volatility: not stated
Source paper:
Jones, Shemesh: Option Mispricing Around Nontrading Periods
http://www-bcf.usc.edu/~christoj/pdf/jones_shemesh.pdf
Abstract:
We find that option returns are significantly lower over nontrading periods, the vast majority of which are weekends. Our evidence suggests that nontrading returns cannot be explained by risk, but are rather the result of widespread and highly persistent option mispricing driven by the incorrect treatment of non-smoothness in stock return variance. The size of the effect implies that the broad spectrum of finance research involving option prices should account for nontrading effects and non-smoothness in variance more generally. Our study further suggests how alternative industry practices could improve the effciency of option markets in a meaningful way.
New research paper related to existing strategy:
#24 – Merger Arbitrage
McCarron: Anomalous Deal Return Capture: A Cross-Sectional Study of Three Hypothetical Global Merger Risk Arbitrage Portfolios 2000-2016
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2950742
Abstract:
This paper examines the annual risks and returns of three disparate, hypothetical merger arbitrage portfolio strategies as an attempt to capture alpha from an in-sample study of 793 global M&A transactions covering the January 2000 thru December 2016 time period. Previously written and undoubtedly the most prominent literature into M&A and merger arbitrage [Schleifer & Vishny ‘97], [Mitchell & Pulvino ‘01] and [Baker & Savasoglu ‘02] focus on the limits of pure arbitrage the creation of such from noise/shock trading and the risk & return characteristics of a merger arbitrage trading strategy respectively. This paper by no means covers the universe of the arbitrage literature and touches only a fraction of arbitrage research – yet, this is the only paper I know of examining global merger arbitrage transactions and the construct of a long-only merger arbitrage strategy encompassing both US as well as non-US merger arbitrage deals and bench-marking the portfolios' risk and returns series against a non-U.S. benchmark. This study demonstrates that alpha can be added by purchasing target companies as part of a long-only global merger arbitrage strategy. Furthermore, above benchmark returns can be earned by also buying the targets of terminated deals. This study is less conclusive on the incremental value of purchasing the acquiring company's shares following a successful or terminated deal where stock is part of the deal consideration.
Two additional related research papers have been included into existing free strategy reviews during last 2 week:
A very interesting example of FX trading strategy created by Richard Olsen (Founder of OANDA):
Golub, Glattfelder, Olsen: The Alpha Engine: Designing an Automated Trading Algorithm
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2951348
Abstract:
We introduce a new approach to algorithmic investment management that yields profitable automated trading strategies. This trading model design is the result of a path of investigation that was chosen nearly three decades ago. Back then, a paradigm change was proposed for the way time is defined in financial markets, based on intrinsic events. This definition lead to the uncovering of a large set of scaling laws. An additional guiding principle was found by embedding the trading model construction in an agent-base framework, inspired by the study of complex systems. This new approach to designing automated trading algorithms is a parsimonious method for building a new type of investment strategy that not only generates profits, but also provides liquidity to financial markets and does not have a priori restrictions on the amount of assets that are managed.
A recent paper takes a look on a long-term behaviour of momentum portfolios. Related to all equity momentum strategies, mainly to:
#14 – Momentum Effect in Stocks
Ali, Daniel, Hirshleifer: One Brief Shining Moment(um): Past Momentum Performance and Momentum Reversals
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2956493
Abstract:
Motivated by behavioral theories, we test whether recent past performance of the momentum strategy (Past Momentum Performance–PMP) negatively predicts the performance of stale momentum portfolios. Following periods of top-quintile PMP, momentum portfolios exhibit strong reversals 2-5 years after formation, whereas, following periods of bottom-quintile PMP, stale momentum portfolios earn positive returns. The difference in cumulative five-year Fama-French alphas for momentum portfolios formed in high- and low-PMP months is 40%. A value-weighted trading strategy based on this effect generates an alpha of 0.40% per month (t = 3.74). These patterns are confirmed in international data. These findings present a puzzle for existing theories of momentum.
