New strategies:
#431 – Intraday Momentum in the Indian Equity Markets
Period of rebalancing: Intraday
Markets traded: equities
Instruments used for trading: futures
Complexity: Complex strategy
Bactest period: 2010-2019
Indicative performance: 12.36%
Estimated volatility: 12.81%
Source paper:
Srivastava, Sonam and Chakravorty, Gaurav and Singhal, Mansi: Momentum in the Indian Equity Markets: Positive Convexity and Positive Alpha
https://ssrn.com/abstract=3345280
Abstract:
We present effective momentum strategies over the liquid equity futures market in India. We evaluate and determine the persistence of the returns at various look-backs ranging from quarterly and weekly to more granular look-backs. We look at a universe of the liquid equity instruments traded across the Indian markets to evaluate this anomaly. We evaluate momentum across the two datasets based on frequency – daily data and intraday bar data. On the daily scale we compare momentum with other style factors. In the intraday scale we evaluate time series momentum or absolute momentum and cross-sectional momentum or relative momentum. We demonstrate that at the optimal horizon, momentum strategies on securities in India can be a source of uncorrelated alpha. We use active riskbudgeting at a given target risk for portfolio construction. We will show in a separate publication how it outperforms mean-variance optimization.
#432 – Investment-Momentum Strategy
Period of rebalancing: 6-Months
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1965-2015
Indicative performance: 8.99%
Estimated volatility: 11.66%
Source paper:
Xu, Fangming and Zhao, Huainan and Zheng, Liyi, Investment-Momentum: A Two-Dimensional Behavioral Strategy
https://ssrn.com/abstract=3346289
Abstract:
We propose an investment-momentum strategy of buying past winners with low investment and selling past losers with high investment, which exploits simultaneously two dimensions of market inefficiencies. The new strategy generates twice the monthly returns earned by either the price momentum or investment strategy (1.44% vs. 0.75% or 0.61%) for 1965-2015. Despite of the diminishing anomalies in recent decades, the investment-momentum stays persistent. The mispricing-based strategy performs better in periods of high investor sentiment or for stocks with high limits-to-arbitrage, which is consistent with our expectation. Overall, we show that, in addition to “fundamentals” enhanced momentum strategies, one can simultaneously condition on multi-dimension of inefficiencies to attain superior performance.
New research papers related to existing strategies:
#4 – Overnight Anomaly
Branch, Ma: Overnight Return, the Invisible Hand Behind The Intraday Return? A Retrospective
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3259614
Abstract:
In an effort to extend our study on the relationship between overnight and intraday returns, we expand the study horizon to include more recent, relatively “calm” market years. We find that the autocorrelation between overnight and intraday returns persisted among smaller stocks, but not for the S&P500. Such a relationship is monotonic in nature – the stronger the overnight return, the further the opposite direction of the intraday return tends to be. We also find evidence that the market has indeed become less volatile in recent years, and the market factor plays a more significant role in stock returns.
#33 – Post-Earnings Announcement Effect
Kim, Kim: A Multi-factor Explanation of Post-Earnings-Announcement Drift
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3267792
Abstract:
To explain post-earnings announcement drift, we construct a risk factor related to unexpected earnings surprise, and propose a four-factor model by adding this risk factor to Fama and French’s (1993), (1995) three-factor model. This earnings surprise risk factor provides a remarkable improvement in explaining post-earnings announcement drift when included in addition to the three factors of Fama and French. After adjusting raw returns for the four risk factors, the cumulative abnormal returns over the 60 trading days subsequent to quarterly earnings announcements are economically and statistically insignificant. Furthermore, except for the first two days after the earnings announcement, the cumulative abnormal returns and the arbitrage returns from our four-factor model are relatively stable over the testing period and never significant on any day of the testing period. On the other hand, the arbitrage returns from the other models increase over the 60-day testing period. We argue that most of the post-earnings announcement drift observed in prior studies may be a result of using misspecified models and failing to appropriately adjust raw returns for risk.
And three additional related research papers have been included into existing free strategy reviews during last 2 weeks:
Related to all factor strategies …
Baltas: The Impact of Crowding in Alternative Risk Premia Investing
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3360350
Abstract:
Crowding is a major concern for investors in the alternative risk premia space. By focusing on the distinct mechanics of various systematic strategies, we contribute to the discussion with a framework that provides insights on the implications of crowding on subsequent strategy performance. Understanding such implications is key for strategy design, portfolio construction, and performance assessment. Our analysis shows that divergence premia, like momentum, are more likely to underperform following crowded periods. Conversely, convergence premia, like value, show signs of outperformance as they transition into phases of larger investor flows.
A very important research paper related to all equity factor strategies …
Li, Chow, Pickard, Garg: Transaction Costs of Factor Investing Strategies
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3359947
Abstract:
Although hidden, implicit market impact costs of factor investing strategies may substantially erode the strategies' expected excess returns. The authors explain these market impacts costs and model them using rebalancing data of a suite of large and longstanding factor investing indices. They introduce a framework to assess the costs of rebalancing activities, and attribute these costs to characteristics such as rate of turnover and the concentration of turnover, which intuitively describe the strategies' demands on liquidity. The authors evaluate a number of popular factor-investing strategy implementations and identify how index construction methods, when thoughtfully designed, can reduce market impact costs.
And guys at AlphaArchitect have been really generous and they have provided a space for us to write a short article in which we 1) briefly discuss the lottery effect, 2) we discuss the research on this topic in the context of commodities, and 3) we conduct an independent replication effort of the commodity lottery effect identified in academic research:
Vojtko, Padysak: Skewness Effect in Commodities
Link: https://alphaarchitect.com/2019/05/30/skewness-effect-in-commodities/
