New strategies:
#342 – Global Cross-Asset Time Series Momentum in Bond and Equity Markets
Period of rebalancing: monthly
Markets traded: equities, bonds
Instruments used for trading: futures, ETFs
Complexity: Moderately complex strategy
Bactest period: 1980 – 2015
Indicative performance: 6.50%
Estimated volatility: 10.00%
Source paper:
Pitkäjärvi, Suominen, Vaittinen: Cross-Asset Signals and Time Series Momentum
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2891434
Abstract:
We document a new cross-asset phenomenon in bond and equity markets that we refer to as cross-asset time series momentum. Using a broad international data set, we show that past bond market returns are positive predictors of future equity market returns, and past equity market returns are negative predictors of future bond market returns. We use these patterns of cross-asset predictability to construct a diversified cross-asset time series momentum portfolio that yields a Sharpe ratio over 40% higher than a standard time series momentum portfolio. We then present evidence that both time series momentum and cross-asset time series momentum are driven by slow-moving capital in bond and equity markets.
#343 – Impact of Macro News on PEAD Strategy
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1997-2014
Indicative performance: 12.28%
Estimated volatility: not stated
Source paper:
Sheng: Macro News, Micro News, and Stock Prices
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2890864
Abstract:
I investigate interactions between macro-announcements and the processing of earnings news. Existing theories suggest that macro-news should crowd out attention to firm-level news, implying less efficient pricing. However, I find the opposite: on macro-news days price reactions to earnings news are 17% stronger and the post-earnings announcement drift is 71% weaker. To explain these results, I show that institutional investor attention is higher on macro-news days. Hence, macro-news appears not to be a distraction from firm-level news, but instead serves to enhance overall attention to financial markets. I suggest extensions of existing theories that could be consistent with these findings.
New research paper related to existing strategy:
#224 – Profitability Factor Combined with Value Factor
Wahal: The Profitability and Investment Premium: Pre-1963 Evidence
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2891491
Abstract:
I investigate the profitability and investment premium in stock returns using hand-collected data from Moody’s Manuals for 1940-1963. Three results emerge. First, the profitability premium in 1940-1963 is similar in magnitude to the post-1963 period. Second, I detect no reliable relation between investment and returns, regardless of whether investment is measured using growth in total assets or book equity. The lack of an investment premium extends back to 1926. Third, unlike in 1963-2013, HML is not redundant in the Fama and French (2015) five-factor model.
Two additional related research papers have been included into existing free strategy reviews during last 2 week:
A recent paper gives a summary of theoretical explanations of asset price properties (based on neurology) and reasons for trendfollowing strategies. Related to all trend-based strategies, mainly to:
#1 – Asset Class Trend Following
#144 – Trendfollowing Effect in Stocks
Bouchaud, Challet: Why have asset price properties changed so little in 200 years
https://arxiv.org/pdf/1605.00634.pdf
Abstract:
We first review empirical evidence that asset prices have had episodes of large fluctuations and been inefficient for at least 200 years. We briefly review recent theoretical results as well as the neurological basis of trend following and finally argue that these asset price properties can be attributed to two fundamental mechanisms that have not changed for many centuries: an innate preference for trend following and the collective tendency to exploit as much as possible detectable price arbitrage, which leads to destabilizing feedback loops.
And a recent paper takes a look on Time-Series (TS) vs. Cross-Sectional (CS) version of momentum strategy. Analysis is made on equities but, in our opinion, has implication also on TS vs. CS momentum strategies on futures:
Cheema, Nartea, Man: Cross-Sectional and Time-Series Momentum Returns and Market States
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2931620
Abstract:
Recent evidence on momentum returns shows that the time-series (TS) strategy outperforms the cross-sectional (CS) strategy. We present new evidence that this happens only when the market continues in the same state, UP or DOWN. In fact, we find that the TS strategy underperforms the CS strategy when the market transitions to a different state. Our results show that the difference in momentum returns between TS and CS strategies is related to both the net long and net short positions of the TS strategy.
