New strategies:
#426 – 1 Month Momentum in Bonds
Period of rebalancing: Monthly
Markets traded: bonds
Instruments used for trading: futures, swaps
Complexity: Simple strategy
Bactest period: 1961-2018
Indicative performance: 6.04%
Estimated volatility: 9.69%
Source paper:
Zaremba, Adam and Karathanasopoulos, Andreas and Long, Huaigang: Short-Term Momentum (Almost) Everywhere
https://ssrn.com/abstract=3340085
Abstract:
Is there a short-term reversal effect outside the universe of individual stocks? To answer this, we investigate a comprehensive dataset of more than two centuries of returns on five major asset classes: equity indices, government bonds, treasury bills, commodities, and currencies. Contrary to stock-level evidence, we find a striking short-term momentum pattern: the most recent month’s return positively predicts future performance. The effect is not explained by established return predictors — including the standard momentum — and is robust to many considerations. The short-term momentum is strongest among assets of high idiosyncratic volatility and in periods of elevated return dispersion. Also, the strategy payoffs display partial commonality across different asset classes.
#427 – 1 Month Momentum in International Equities
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: futures, CFDs, ETFs
Complexity: Simple strategy
Bactest period: 1961-2018
Indicative performance: 16.21%
Estimated volatility: 20.38%
Source paper:
Zaremba, Adam and Karathanasopoulos, Andreas and Long, Huaigang: Short-Term Momentum (Almost) Everywhere
https://ssrn.com/abstract=3340085
Abstract:
Is there a short-term reversal effect outside the universe of individual stocks? To answer this, we investigate a comprehensive dataset of more than two centuries of returns on five major asset classes: equity indices, government bonds, treasury bills, commodities, and currencies. Contrary to stock-level evidence, we find a striking short-term momentum pattern: the most recent month’s return positively predicts future performance. The effect is not explained by established return predictors — including the standard momentum — and is robust to many considerations. The short-term momentum is strongest among assets of high idiosyncratic volatility and in periods of elevated return dispersion. Also, the strategy payoffs display partial commonality across different asset classes.
#428 – 1 Month Momentum in Commodities
Period of rebalancing: Monthly
Markets traded: commodities
Instruments used for trading: futures, CFDs
Complexity: Simple strategy
Bactest period: 1961-2018
Indicative performance: 21.12%
Estimated volatility: 20.86%
Source paper:
Zaremba, Adam and Karathanasopoulos, Andreas and Long, Huaigang: Short-Term Momentum (Almost) Everywhere
https://ssrn.com/abstract=3340085
Abstract:
Is there a short-term reversal effect outside the universe of individual stocks? To answer this, we investigate a comprehensive dataset of more than two centuries of returns on five major asset classes: equity indices, government bonds, treasury bills, commodities, and currencies. Contrary to stock-level evidence, we find a striking short-term momentum pattern: the most recent month’s return positively predicts future performance. The effect is not explained by established return predictors — including the standard momentum — and is robust to many considerations. The short-term momentum is strongest among assets of high idiosyncratic volatility and in periods of elevated return dispersion. Also, the strategy payoffs display partial commonality across different asset classes.
New research papers related to existing strategies:
#118 – Time Series Momentum Effect
Cheng, Struck: Time-Series Momentum: A Monte-Carlo Approach
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3345849
Abstract:
This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create 10,000 paths of different TSM strategies based on the S&P 500 and a cross-asset class futures portfolio. The simulations reveal a probability distribution which shows that strategies that outperform Buy-and-Hold in-sample using historical backtests may out-of- sample i) exhibit sizable tail risks, ii) under-perform or outperform. Our results are robust to using different time-series models, time periods, asset classes, and risk measures.
#18 – Liquidity Effect in Stocks
Pastor, Stambaugh: Liquidity Risk After 20 Years
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3371948
Abstract:
The Critical Finance Review commissioned Li, Novy-Marx, and Velikov (2017) and Pontiff and Singla (2019) to replicate the results in Pastor and Stambaugh (2003). Both studies successfully replicate our market-wide liquidity measure and find similar estimates of the liquidity risk premium. In the sample period after our study, the liquidity risk premium estimates are even larger, and the liquidity measure displays sharp drops during the 2008 financial crisis. We respond to both replication studies and offer some related thoughts, such as when to use our traded versus non-traded liquidity factors and how to improve the precision of liquidity beta estimates.
And one additional related research paper has been included into existing free strategy reviews during last 2 weeks:
Momentum In International Government Bonds Can Be Explained By Currency Momentum. A new academic paper related to:
#8 – Currency Momentum Factor
Zaremba, Kambouris: The Sources of Momentum in International Government Bond Returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3332942
Abstract:
This study aims to offer a new explanation for the momentum effect in international government bonds. Using cross-sectional and time-series tests, we examine a sample of bonds from 22 countries for the years 1980 through 2018. We document significant momentum profits that are not attributable to bond-specific risk factors, such as volatility or credit risk. The global bond momentum is driven by the returns on underlying foreign exchange rates. Controlling for currency movements fully explains the abnormal returns on momentum strategies in international government bonds. The results are robust to many considerations including alternative sorting periods, portfolio construction methods, as well as subperiod and subsample analysis.
