#14 – Momentum Effect in Stocks

Authors: van Oord

Title: Optimization of Equity Momentum: (How) Does it Work?

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2653680
 

Abstract:

Standard mean-variance optimized momentum outperforms the traditional equally weighted momentum strategy if the expected return vector used reflects momentum's top and bottom only characteristic. This top and bottom only characteristic is the phenomenon that only the stocks in the top decile of momentum's ranking outperform and that only stocks in the bottom decile underperform, while all stocks in the intermediate deciles of the ranking have similar performance. If the optimization does not take this phenomenon into account the portfolio is also long the deciles 2 to 5 and short the deciles 6 to 9, while all these positions thus do not add anything to the return of the strategy. A new simplified bootstrapping methodology shows that the Sharpe-ratio of 52.8 percent of the optimized portfolio is significantly higher (p-value of 0.006) than the Sharpe-ratio of 29.3 percent for traditional equally weighted momentum. The optimized portfolio also exhibit less time-varying equity risk factor return exposures than traditional momentum and as such have more stable returns over the business cycle and have smaller drawdowns.

Notable quotations from the academic research paper:

"The traditional momentum strategy ranks stocks on their recent 3 to 12 months average returns, skips one month to overcome short-term return reversals and then buys the stocks in the top decile of the ranking and short-sells the stocks in the bottom decile of this ranking. Jegadeesh and Titman (1993) show that this traditional momentum strategy has a signicant positive average return. Using standard mean-variance optimization with these recent average stock returns as input for the expected returns results in a signicantly higher Sharpe-ratio than the traditional momentum strategy if the expected returns reflect momentum's top and bottom only characteristic.

We show that the momentum is a top and bottom only strategy. Given momentum's signicant outperformance of the top decile over the bottom decile of its ranking on the stocks' recent performance one would expect that stocks in the second decile would also outperform stocks in the ninth decile. This is, however, not the case: all stocks in the second to ninth decile have similar performance. When using the recent stocks' performances as expected returns
in the optimization thus results in long positions in the second to fth decile and short positions in the sixth to ninth deciles. These long-short positions do not add to the performance as they have similar returns. In fact, these positions decrease momentum's performance as they reduce the weights in the top and bottom decile that do outperfom each other and do add to the performance."

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#3 – Sector Momentum – Rotational System

Authors: Huhn

Title: Industry Momentum: The Role of Time-Varying Factor Exposures and Market Conditions

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2650378

Abstract:

This paper focuses on momentum strategies based on recent and intermediate past returns of U.S. industry portfolios. Our empirical analysis shows that strategies based on intermediate past returns yield higher mean returns. Moreover, strategies involving both return specifications exhibit time-varying factor exposures, especially the Fama and French (2015) five-factor model. After risk-adjusting for these dynamic exposures, the profitability of industry momentum strategies diminishes and becomes insignificant for strategies based on recent past returns. However, most strategies built on intermediate past returns remain profitable and highly significant. Further analyses reveal that industry momentum strategies are disrupted by periods of strong negative risk-adjusted returns. These so-called momentum crashes seem to be driven by specific market conditions. We find that industry momentum strategies are related to market states and to the business cycle. However, there is no clear evidence that industry momentum can be linked to market volatility or sentiment.

Notable quotations from the academic research paper:

"Our empirical results indicate that momentum strategies based on industry portfolios are profitable within the U.S. Moreover, in line with Novy-Marx (2012), strategies based on intermediate past returns from months twelve to seven exhibit higher returns than strategies based on recent past returns from months six to two prior to portfolio formation. However, when using alternative formation periods for intermediate past returns, our results do not support the hypothesis of momentum being an “echo” in returns.

Our paper seeks to determine whether industry momentum strategies based on recent and intermediate past returns exhibit time-varying factor exposures in the U.S. We therefore apply different factor models and examine which model best explains industry momentum returns. Our results indicate that for both return specifications, industry momentum strategies exhibit time-varying factor exposures, especially using the FF (2015) five-factor model. Hedging these time-varying factor exposures diminishes the outperformance of industry momentum strategies.

To the best of our knowledge, no study so far has analyzed the relation between market conditions and industry momentum strategies based on both recent and intermediate past returns. Giving additional scrutiny to this research area, we examine whether industry momentum strategies are also disrupted by periods of strong negative returns. Our empirical analyses reveal that industry momentum strategies based on both return specifications experience periods with large negative risk-adjusted returns. Moreover, these so-called momentum crashes seem to be driven by specific market conditions. We find that industry momentum strategies are related to market states and are thus only profitable following “UP”-markets. We do not find positive and significant risk-adjusted returns following “DOWN”-markets, regardless of market transitions. These results support behavioral explanations as the source of the profitability of industry momentum strategies. Dividing both recessions and expansions into two halves, our results indicate that most strategies exhibit positive and significant risk-adjusted returns only during the second half of an expansion. Finally, our findings do not support the notion that industry momentum strategies are related to market volatility or investor sentiment."

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#38 – Accrual Anomaly

Authors: Patatoukas

Title: Asymmetrically Timely Loss Recognition and the Accrual Anomaly

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2653979

Abstract:

Conditionally conservative accounting practices mandate the more timely recognition of losses relative to gains through transitory negative accrual items. A direct implication of asymmetrically timely loss recognition is asymmetry in the persistence of accruals depending on whether the firm experiences a gain or a loss in the current year: accruals should be less persistent for loss years relative to profit years. If investors naively fixate on total earnings, however, conditional conservatism would imply that investors will tend to overestimate the persistence of accruals especially in loss years. Consistent with naïve earnings fixation, I find that Sloan’s (1996) accrual anomaly, i.e., the negative association between accruals and future abnormal stock returns, is more pronounced for loss firms relative to profit firms. The evidence is relevant for understanding the origins of the accrual anomaly and highlights that inferences with respect to the pricing of accruals can be affected by pooling loss firms with profit firms.

Notable quotations from the academic research paper:

"Separating firms based on the sign of reported earnings, I find that although the accrual anomaly extends across profit and loss firms, it appears to be stronger for loss firms. The average hedge return from buying/selling low/high accrual loss firms is 16.99 percent, while the hedge return from buying/selling low/high accrual profit firms is 5.82 percent. Evidence of accrual mispricing further increases when I separate loss firms experiencing negative contemporaneous abnormal returns (roughly 72 percent of all loss firms), with the hedge return from buying/selling low/high accrual loss firms rising to 21.77 percent.

Overall, the evidence suggests that the subsample of loss firms is more susceptible to accruals mispricing, which is consistent with the prediction that investors naively fixate on total earnings and, therefore, tend to overestimate the persistence of accruals especially in loss years. The evidence presented here also highlights that inferences regarding variation in the accrual anomaly across profit and loss firms are sensitive to the measurement of the accrual component of earnings."

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#5 – FX Carry Trade

Authors: Breedon, Rime, Vitale

Title: Carry Trades, Order Flow and the Forward Bias Puzzle

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2643531

Abstract:

We investigate the relation between foreign exchange (FX) order flow and the forward bias. We outline a decomposition of the forward bias according to which a negative correlation between interest rate differentials and order flow creates a time-varying risk premium consistent with that bias. Using ten years of data on FX order flow we find that more than half of the forward bias is accounted for by order flow — with the rest being explained by expectational errors. We also find that carry trading increases currency-crash risk in that order flow generates negative skewness in FX returns.

Notable quotations from the academic research paper:

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#25 – Small Capitalization Stocks Premium Anomaly
#26 – Value (Book-to-Market) Anomaly

Authors: Lambert, Fays, Hubner

Title: Size and Value Matter, But Not the Way You Thought

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2647298

Abstract:

Fama and French factors do not reliably estimate the size and book-to-market effects. We demonstrate inconsistent pricing of those factors in the US stock market. We replace Fama and French’s independent rankings with the conditional ones introduced by Lambert and Hübner (2013). Controlling ex-ante for noise in the estimation procedure, we have been able to highlight a much stronger book-to-market and size effects than have conventionally been documented similar to Asness et al. (2015). As a significant related outcome, the alternative risk factors have been found to deliver less specification errors when used to price investment portfolios.

Notable quotations from the academic research paper:

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#14 – Momentum Effect in Stocks
#25 – Small Capitalization Stocks Premium Anomaly

Authors: Schmidt, Von Arx, Schrimpf, Wagner, Ziegler

Title: Size and Momentum Profitability in International Stock Markets

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2642185

Abstract:

We study the link between the profitability of momentum strategies and firm size, drawing on an extensive dataset covering 23 stock markets across the globe. We first present evidence of an “extreme” size premium in a large number of countries. These size premia, however, are most likely not realizable due to low stock market depth. We also show that international momentum profitability declines sharply with market capitalization. Momentum premiums are also considerably diminished by trading costs, when taking into account the actual portfolio turnover incurred when implementing this strategy. In contrast to strategies based on size, we find that momentum premia especially for medium-sized stocks still remain economically and statistically significant in most equity markets worldwide after adjusting for transaction costs.

Notable quotations from the academic research paper:

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