New strategies:
#410 – The Impact of Turnovers on Short-Term Momentum and Reversal
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1963-2016
Indicative performance: 8.86%
Estimated volatility: 9.83%
Source paper:
Medhat, Mamdouh and Schmeling, Maik: Short-Term Momentum
https://ssrn.com/abstract=3150525
Abstract:
We document a striking pattern in the cross-section of U.S. and international stock returns: Double-sorting on the previous month's return and share turnover results in strong and significant short-term reversal for low-turnover stocks whereas high-turnover stocks exhibit short-term momentum. Short-term momentum is as profitable and persistent as conventional momentum, but is not spanned by standard factors, and is significant among the largest, most liquid stocks. Consistent with our model, in which heterogeneous investors disagree about the informativeness of their signals, we find that reversal among low-turnover stocks is driven by noise-trading whereas momentum among high-turnover stocks reflects the gradual diffusion of private information. As a result, purging noise-trades from the previous month's return and turnover results in even stronger short-term momentum.
#411 – Halloween Effect during Low and High CAPE Months
Period of rebalancing: 6 Months
Markets traded: equities
Instruments used for trading: futures, funds, ETFs, CFDs
Complexity: Simple strategy
Bactest period: 1926-2016
Indicative performance: 12.24%
Estimated volatility: 17.78%
Source paper:
Kim, Keunsoo and Byun, Jinho: Stock Return Predictability and Seasonality
https://ssrn.com/abstract=3180992
Abstract:
An examination of the Shiller cyclically adjusted pricing-earnings (CAPE) ratio reveals its forecasting power for 12-month CRSP equally weighted (EW) excess returns and value weighted (VW) excess returns. The 12-month EW excess returns following low CAPE ratios are, on average, 20.7% higher than those following high CAPE ratios for the period of 1927-2016. This dichotomy in the Shiller CAPE ratio has a more reliable predictability than the January barometer. Previous studies report that the Halloween indicator was weak or negative in the US stock market prior to the 1950s. We find that the Halloween effect is strongly present following high CAPE ratios, even for the period of 1926-1971. Our results recommend a practical investment strategy. More specifically, if the CAPE ratio in September is lower than the 36-month median of the CAPE ratio, invest in stock markets from November to October of the following year; otherwise, invest for six months from November to April and sell in May and go away.
New research papers related to existing strategies:
#264 – Dividend Risk Premium Strategy
Ulrich, Florig, Wuchte: A Model-Free Term Structure of U.S. Dividend Premiums
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3217096
Abstract:
We construct a model-free infinite maturity term structure of dividend risk premiums. Applying the method to 2004 – 2017 U.S. data reveals that the U.S. term structure of dividend risk premiums has been hump-shaped on average: zero for instantaneous dividends, increasing for dividends that arrive within the upcoming 13 months and downward sloping thereafter. The model-free dividend risk premiums carry predictive information for future dividend growth and returns on equity and dividends. Buying the next year of S&P 500 dividends whenever the one-year dividend risk premium is positive has earned twice the Sharpe ratio of the index after transaction costs.
#306 – Trading VIX ETFs v2
Dapena, Serur, Siri: Measuring and Trading Volatility on the US Stock Market: A Regime Switching Approach
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3257073
Abstract:
The volatility premium is a well-documented phenomenon, which can be approximated by the difference between the previous month level of the VIX Index and the rolling 30-day close-to-close volatility. Along with the literature, we show evidence that VIX is generally above the 30-day rolling volatility giving rise to the volatility premium, so selling volatility can become a profitable trading strategy as long as proper risk management is under place. As a contribution, we introduced the implementation of a Hidden Markov Model (HMM), identifying two states of the nature and showing that the volatility premium undergoes temporal breaks in its behavior. Based on this, we formulate a trading strategy by selling volatility and switching to medium-term U.S. Treasury Bills when appropriated. We test the performance of the strategy using the conventional Carhart four-factor model showing a positive and statistically significant alpha.
#389 – Cryptomarket Discounts
#409 – Trading Volume in Cryptocurrency Markets and Reversals
Borri, Shakhnov: The Cross-Section of Cryptocurrency Returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3241485
Abstract:
This paper studies cryptocurrency investment strategies from the perspective of U.S. investors. We take Bitcoin as a representative cryptocurrency and consider exchanges around the globe where investors can trade different fiat and cryptocurrency pairs (i.e., U.S. dollar for Bitcoin). We treat each currency pair as a different asset. We start off large, persistent, and mean-reverting deviations in bitcoin prices, converted in U.S. dollars, and uncover two investment strategies based on information on past price deviations that generate large cross-sections of excess returns. A principal component analysis shows that most of the variation in the cross-sections of returns is explained by two common components. We find that these components are correlated with crypto factors but poorly correlated with a large set of standard non-crypto factors.
And three additional related research papers have been included into existing free strategy reviews during last 2 weeks:
#14 – Momentum Effect in Stocks
#25 – Size Premium
#26 – Value (Book-to-Market) Anomaly
#77 – Beta Factor in Stocks
Auer, Rottmann: Have Capital Market Anomalies Worldwide Attenuated in the Recent Era of High Liquidity and Trading Activity?
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3275377
Abstract:
We revisit and extend the study by Chordia et al. (2014) which documents that, in recent years, increased liquidity has significantly decreased exploitable returns of capital market anomalies in the US. Using a novel international dataset of arbitrage portfolio returns for four well-known anomalies (size, value, momentum and beta) in 21 developed stock markets and more advanced statistical methodology (quantile regressions, Markov regime-switching models, panel estimation procedures), we arrive at two important findings. First, the US evidence in the above study is not fully robust. Second, while markets worldwide are characterised by positive trends in liquidity, there is no persuasive time-series and cross-sectional evidence for a negative link between anomalies in market returns and liquidity. Thus, this proxy of arbitrage activity does not appear to be a key factor in explaining the dynamics of anomalous returns.
#41 – Turn of the Month in Equity Indexes
McGroarty, Platanakis, Sakkas, Urquhart: A Seasonality Factor in Asset Allocation
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3266285
Abstract:
Motivated by the seasonality found in equity returns, we create a Turn-of-the-Month (ToM) allocation strategy in the U.S. equity market and investigate its value in asset allocation. By using a wide variety of portfolio construction techniques in an attempt to address the impact of estimation risk in the input parameters, we show significant out-of-sample benefits from investing in the ToM factor along with a traditional stock-bond portfolio. The out-of-sample benefits remain significant after taking into account transaction costs and by using different rolling estimation windows indicating that a market timing strategy based on the ToM offers substantial benefits to investors when determining the allocation of assets.
A new financial research paper gives an ideas of how to allocate capital across several well known factor strategies:
Blin, Ielpo, Lee, Teiletche: Factor Timing Revisited: Alternative Risk Premia Allocation Based on Nowcasting and Valuation Signals
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3247010
Abstract:
Alternative risk premia are encountering growing interest from investors. The vast majority of the academic literature has been focusing on describing the alternative risk premia (typically, momentum, carry and value strategies) individually. In this article, we investigate the question of allocation across a diversified range of cross-asset alternative risk premia over the period 1990-2018. For this, we design an active (macro risk-based) allocation framework that notably aims to exploit alternative risk premia’s varying behavior in different macro regimes and their valuations over time. We perform backtests of the allocation strategy in an out-of-sample setting, shedding light on the significance of both sources of information.
