New strategies:
#254 – Federal Open Market Committee Meeting Effect in US Dollar
Period of rebalancing: daily
Markets traded: currencies
Instruments used for trading: futures, CFDs, ETFs
Complexity: Simple strategy
Bactest period: 1994 – 2011
Indicative performance: 7.71%
Estimated volatility: 13.78%
Source paper:
Mueller, Porchia, Vedolin: Policy Announcements in FX Markets
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2480131
Abstract:
A strategy that is short the US dollar and long the rest of the world earns large excess returns on days of scheduled meetings of the Federal Open Market Committee (FOMC). Moreover, the difference between announcement and non announcement returns becomes larger during periods of high uncertainty and bad economic conditions. To reconcile our findings, we develop a model of an international long-run risk economy in which asset prices respond to revisions of monetary policy. Monetary policy uncertainty commands a risk premium that is larger in weaker economic conditions. A calibrated version is consistent with the cross-sectional pattern of currency risk premia observed in the data.
#255 – Turn of the Month Effect in Futures Momentum Strategy
Period of rebalancing: daily
Markets traded: currencies, bonds, equities, commodities
Instruments used for trading: futures, CFDs
Complexity: Complex strategy
Bactest period: 2000 – 2014
Indicative performance: 4.80%
Estimated volatility: 1.50%
Source paper:
Van Hemert: The MOM-TOM Effect: Detecting the Market Impact of CTA Trading
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515900
Abstract:
Motivated by the explosive growth in CTA assets under management, in combination with the recent poor performance of many managers in this sector, we explore whether the trend-following trading style employed by many CTAs has become crowded. Explicitly, we test for market impact using the following hypothesis: around the turn of the month (TOM), trend-following (MOM) strategies digest sizeable inflows, causing the managers to trade up their existing positions, thereby pushing prices temporarily in their favor. The main empirical test is whether there is an above average return for MOM strategies on TOM days, which we refer to as the MOM-TOM effect. We found a very strong MOM-TOM effect in the Newedge Trend Index returns, with 90% of cumulative returns since 2000 being realized on the three TOM days. In addition, a replicating strategy we designed to closely track the Newedge Trend Index displayed a strong MOM-TOM effect.
New research papers related to existing strategies:
#54 – Momentum and State of Market (Sentiment) Filters
Chabot, Ghysels, Jagannathan: Momentum Trading, Return Chasing and Predictable Crashes
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2516796
Abstract:
We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine over 140 years of risk and return of one of the most popular mechanical trading strategies — momentum. We find that the momentum strategy has earned abnormally high risk-adjusted returns — a three factor alpha of 1 percent per month between 1927 and 2012 and 0.5 percent per month between 1867 and 1907 — both statistically significantly different from zero. However, the momentum strategy also exposed investors to large losses (crashes) during both periods. Momentum crashes were predictable. Crashes were more likely when momentum had recently performed well (both eras), interest rates were relatively low (1867-1907), or momentum had recently outperformed the stock market (CRSP era) — times when borrowing or attracting return chasing “blind capital” would have been easier. We argue based on a stylized model and simulated outcomes from a richer model that a money manager who competes for funds from return-chasing investors and is compensated via fees that are convex in the amount of money managed and the return on that money has an incentive to remain invested in momentum even when the crash risk is known to be high.
#107 – Short Term Reversal with ETFs
Smith: Losers Win, Winners Lose: Evidence Against Market Efficiency
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2508088
Abstract:
The goal of this research project was to evaluate whether there is statistically significant evidence of the Winner / Loser Phenomenon identified in DeBondt and Thaler (1985) using a unique data set and multiple examination windows. This paper uses sector ETFs as proxies for general market performance, which minimizes the impact of turn-of-the-year and seasonality effects that influenced the acceptance of the anomaly indenified in DeBondt and Thaler’s “Does the Stock Market Overreact” paper (i.e. the finding that previous ‘Losers’ tend to outperform the ‘Winners’ over different time horizons). This study finds statistically significant evidence of short-run negative autocorrelation of returns. More importantly, if investors used a daily rebalance over this time period and invested simultaneously in the previous day’s loser ETF and the previous day’s winner ETF they would have obtained Cumulative Abnormal Returns of 113.50% and -134.13%, respectively. In addition, this study supports the experimental research findings documented in Bloomfield, R., Libby, R., and Nelson, M. (1998) and Bloomfield, R. and Hales, J. (2002) by illustrating that there is evidence of trends in both the market portfolio and the loser portfolio (i.e. sign tests were conducted and the results were significant using an α of .001); moreover, the loser portfolio shows signs of significant outperformance when the preceding day’s performance is negative (i.e. the researcher found that the average returns for the loser portfolios were greater than the market portfolio using an α of .10). In summary, this study provides further evidence of short-run negative autocorrelation in stock market price performance, adds to the literature that suggests that the stock market tends to show signs of short-term ‘overreaction’ to information and this overreaction seems to be relatively short lived, that there does not seem to be evidence that the outperformance is due to systemic risk, and evidence to substantiate, in a market environment, the experimental findings presented in Bloomfield et al. (1998) and Bloomfield et al. (2002).
