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Is Momentum Really Momentum

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Abstract

Momentum is primarily driven by firms' performance twelve to seven months prior to portfolio formation, not by a tendency of rising and falling stocks to keep rising and falling. Strategies based on recent past performance do generate positive returns, but are less profitable than strategies based on intermediate horizon past performance, especially among the largest, most liquid stocks. The performance of two types of strategies are correlated, however, even when explicitly constructed to be neutral with respect to the past performance characteristic on which the other strategy is formed, especially over the second half of the CRSP sample. As a result, over the last forty years strategies based on recent past performance do not contribute significantly to the investment opportunity set of an investor already trading momentum based on inter-mediate horizon past performance and the three Fama-French factors. These facts are not particular to the momentum observed in the cross-section of US equities. Similar results hold for momentum strategies trading international equity indices, commodi-ties and currencies.

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... Sig. α 1% ***) α 5% **) 1-1 1 (1-2) 0.0129785 2.499**) -0.306324 -9.624***) 2 (2)(3) 0.0184419 9.902***) -0.235268 -3.294**) 3 (3)(4) 0.0233061 8.718***) -0.064124 -3.893**) 4 (4)(5) 0.0108758 6.670***) -0.162227 -7.195***) 5 (5)(6) 0.0226181 6.341***) -0.109363 -6.605***) 6 (6-7) 0.0123619 6.215***) -0.187420 -4.879***) 7 (7)(8) 0.0110160 6.618***) -0.202753 -3.537**) 8 (8)(9) 0.0179625 5.024***) -0.161133 -6.209***) 9 (9)(10) 0.0171315 7.663***) -0.081457 -3.301**) 10 (10)(11) 0.0035459 1.428 -0.274040 -6.530***) 11 (11)(12) 0.0307904 8.496***) -0.007199 -.495 12 -0.0178538 -1.071 -0.280376 -13.657***) 13 (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21) 0 Based on the results presented in table 3, it can be seen that there is a significant difference, which indicates that there has been a change (reversal) of the return the losers to be the winners and the winners to be the losers. ...
... Sig. α 1% ***) α 5% **) 1-1 1 (1-2) 0.0083561 2.277**) -0.345392 -11.734***) 2 (2-3) 0.0109656 8.443***) -0.224392 -3.100**) 3 (3)(4) 0.0221030 7.720***) -0.084196 -4.756***) 4 (4)(5) 0.0112856 6.436***) -0.154829 -6.398***) 5 (5)(6) 0.0233482 6.715***) -0.116205 -7.186***) 6 (6-7) 0.0139178 6.0520*** -0.192803 -4.891***) 7 (7)(8) 0.0104296 5.208***) -0.239464 -4.280**) 8 (8)(9) 0.0176015 4.672***) -0.158760 -5.918***) 9 (9-10) 0.0176379 8.098***) -0.086616 -3.535**) 10 (10-11) 0.0034951 1.395 -0.244859 -5.065***) 11 (11)(12) 0.0281624 11.099***) -0.016614 -1.102 12 -0.0149953 -.951 -0.295979 -14.947***) 13 (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21) 0.0186907 8.978***) -0.072408 -4.513***) 14 (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31) 0 Table 4 has shown that by implemented the contrarian investment strategy, it has obtained a difference favorable from the loser, and an unfavorable difference from the winner. ...
... Sig. α 1% ***) α 5% **) 1-1 1 (1-2) 0.0083561 2.277**) -0.345392 -11.734***) 2 (2-3) 0.0109656 8.443***) -0.224392 -3.100**) 3 (3)(4) 0.0221030 7.720***) -0.084196 -4.756***) 4 (4)(5) 0.0112856 6.436***) -0.154829 -6.398***) 5 (5)(6) 0.0233482 6.715***) -0.116205 -7.186***) 6 (6-7) 0.0139178 6.0520*** -0.192803 -4.891***) 7 (7)(8) 0.0104296 5.208***) -0.239464 -4.280**) 8 (8)(9) 0.0176015 4.672***) -0.158760 -5.918***) 9 (9-10) 0.0176379 8.098***) -0.086616 -3.535**) 10 (10-11) 0.0034951 1.395 -0.244859 -5.065***) 11 (11)(12) 0.0281624 11.099***) -0.016614 -1.102 12 -0.0149953 -.951 -0.295979 -14.947***) 13 (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21) 0.0186907 8.978***) -0.072408 -4.513***) 14 (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31) 0 Table 4 has shown that by implemented the contrarian investment strategy, it has obtained a difference favorable from the loser, and an unfavorable difference from the winner. ...
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... The presence of momentum profits in developed markets is also documented in recent studies (Fama & French, 2012;Novy-Marx, 2012). Jegadeesh and Titman (1993) documented that higher returns firms with three months to 1-year time horizons remained higher returns firms over low returns firms for the same time horizon. ...
... The fair game model states that an asset's estimated returns depend on the level of risk of this asset; the sub martingale model states that an asset's estimated future value is always equal or greater to the current price of this asset; last, the random walk model affirms that the evolution of the price of an asset follows a "random walk pattern": in other terms, it always reflects the information available at this time. However, the efficient market hypothesis theory has been challenged by many authors (De Bondt & Thaler, 1985;Fama & French, 2012;Gharaibeh, 2021;Jegadeesh & Titman, 1993;Novy-Marx, 2012). Among the arguments against the efficient market hypothesis (EMH), one empirical anomaly is often stated: the asset price reversal or continuation; it is also called contrarian or momentum profit. ...
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... This study examines the term structure of momentum profits reported by Novy-Marx (2012) in the Korean stock market. Jegadeesh and Titman (1993, JT hereafter) find that past returns can predict future returns: the strategy of buying past winners and selling past losers generates significantly positive profits. ...
... Kim (2012), Jang (2017) and Kim and Lee (2018) also find that momentum profits have become more significant in the Korean stock market [2]. Jang (2017) investigates the term structure of momentum profitability in the Korean stock market according to Novy-Marx (2012). She finds that momentum profits are primarily driven by returns over the intermediate (past t-12 to t-7 months) rather than the recent (past t-6 to t-2 months) horizon. ...
... The estimated coefficients of the control variables are consistent with our expectations: the price reverses at monthly horizons (Jegadeesh, 1990;Lehmann, 1990;Yun and Cho, 2006), high idiosyncratic volatility is associated with lower subsequent returns (Ang et al., 2006;Kang et al., 2014a) and firms with more aggressive investment earn higher average returns (Aharoni et al., 2013). On the contrary, we find that the illiquidity effect (Amihud, 2002) and profitability effect (Novy-Marx, 2012;Fama and French, 2015) are insignificant in the Korean market unlike in the US market. ...
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... For instance, refs. [39,40] use sequential sorts, whereas [41,42] shed light on inverse sequential sorts. Apart from them, refs. ...
... Likewise, from Tables 3 and 4, we see that the risk-adjusted momentum profits of the companies with low timely loss recognition from these two asset pricing models of [39] are significantly negative since the absolute t-statistics lie between 2.475 and 2.936. The negative risk-adjusted momentum profits have absolute values ranging from 3.7% to 4.2% and are also the largest. ...
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... -Enhanced momentum: The traditional momentum effect (Jegadeesh & Titman, 1993) can be enhanced by considering the interaction of the formation period returns with certain firm-level characteristics. Some of these characteristics are the nearness to the 52-Week (George & Hwang, 2004), formation period return consistency (Grinblatt & Moskowitz, 2004), volatility (Bandarchuk & Hilscher, 2013;Jiang, Lee, & Zhang, 2005;Zhang, 2006), intermediate past performance (Novy-Marx, 2012), extreme past returns (Bandarchuk & Hilscher, 2013), information discreteness (Da, Gurun, & Warachka, 2014), continuing overreaction (Byun, Lim, & Yun, 2016), and R-squared (Hou, Xiong, & Peng, 2006). -Long-term return sorted portfolios: In contrast to Jegadeesh and Titman (1993), Bondt and Thaler (1985) and McLean (2010) document a long-term reversal phenomenon based on a stock's three-to-five years cumulative return. ...
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... While many studies investigate a potential hot hand effect in sports, this notion has also been applied to other settings, especially finance; strategies that attempt to identify, follow and profit from market trends are popular among professional investors. In the finance literature, there is abundant evidence that this "momentum" explains some of the cross-section of returns in financial markets (Asness et al., 2013;Barroso and Santa-Clara, 2015;Carhart, 1997;Ehsani and Linnainmaa, 2022;Fama and French, 2012;Jegadeesh and Titman, 2011;Novy-Marx, 2012), as well as defining profitable investment strategies in time series frameworks (Chan et al., 1996;Moskowitz et al., 2012;Zakamulin and Giner, 2022). However, as typically occurs in finance due to the complexity of markets and the multitude of factors that drive asset prices, there are also some findings in the literature that do not support the existence of momentum (Huang et al., 2020;Kim et al., 2016). ...
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... erefore, armed with stochastic simulations, we further dissect the effect of anxiety from the anxious agent in relation to price inertia and reversal. Our analysis also provides experimental explanations for the emergence of inertia and reversal in the real market (e.g., [56][57][58]). Actually, price inertia and reversal are vital indicators for identifying the market volatility (e.g., [59,60]). ...
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... Asness, Moskowitz, and Pedersen [40] find that a momentum return premier exists across diverse markets. Novy-Marx [41] claims that momentum phenomena can be observed from different U.S. and international financial markets, including stock, bond, currency, and commodity markets. ...
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Thesis
Equity markets are amongst the most researched areas in asset pricing literature. Data availability and the liquid and transparent nature of equity markets have aided research in this domain. The research on corporate bond markets is considerably less due to both the illiquid and over-the-counter (OTC) nature of these markets which have resulted in less easy availability of reliable data sources. Corporate bond and equities possess commonalities in their behaviour largely because of being at different points in the capital structure of firms. Indeed, adverse news for a company should adversely affect the pricing of both the firm’s equity and debt. As a result, practitioners often consider corporate bonds as a combination of government-bonds and beta-adjusted equities used as a proxy for credit exposure. In the thesis however, we seek to demonstrate that credit risk, although highly correlated in the short term, can be different from equity risk. The seminal work on the pricing of corporate debt was by Robert Merton (Merton 1974). The Merton model represented corporate debt as the combination of a risk-free asset and a short position in a put option on the assets of the firm. Equity was represented as a long call option on the assets of the firm. Since then models such as Black and Cox (1976) and Leland (1994) have extended the Merton model but the key features of corporate bond pricing and its co-movement with equity prices are still well represented by the Merton model. The Merton model, while capturing a point of commonality – the common effect of changes in asset prices to equity and debt price – and a key difference – the left-tailed nature of corporate debt returns – does not address other key areas of differences between the two asset classes. One area of difference, studied extensively in the empirical literature, but not in structural models is the significant difference in liquidity and trading dynamics between the two markets. Another key area of difference between the two markets comes from the differing type of investors. Regulations, which are much more onerous for corporate debt than equities, can lead to non-market-driven behaviour such as a significant aversion to downgrades. The goal of my PhD thesis is to study the commonality and differences between these two asset classes and Its implication on the cross-section of corporate bond returns. Specifically, we look at three aspects of differences between corporate and equities. The first chapter focuses on the issuance of corporate bonds and contrasts with equity issuance. It starts with the issuance process and analyses the new issue premiums in corporate bonds contrasting it with results seen in equity initial public offerings (IPOs). This chapter also analyses the determinants of corporate bond issuance concessions. The second chapter looks at the short-term commonalities and differences between the performance patterns of corporate bonds and equities. This chapter merges two distinct branches of literature on structural credit models and commonalities in corporate bond-equity behaviour with that of cross-asset momentum. The last two chapters focus on the topical area of exchange traded funds and their dislocations, as measured by the significant deviations between prices and net-asset-values (NAV), seen in this market during the extreme volatility at the peak of the Covid-19 crisis in March 2020. Specifically in chapter 4, we study the dislocation in fixed-income and specifically corporate bond ETFs and contrast it with the relatively better-behaved equity ETFs. We show that this relative dislocation is not just from liquidity differences and that the ETF price may have been an over-reaction. In chapter 5, we build a model for ETF arbitrage specifically taking into account incentives of the arbitrageurs, a critical difference between fixed income and equity ETFs. We show that inventory management by dual market makers and arbitrageurs may have exacerbated the dislocation.
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Abstract Purpose Over the past three decades, numerous conceptual and empirical studies have discussed momentum investment strategies’ presence, pervasiveness and persistence. However, science mapping in the field is inadequate. Hence, this study aims to comprehend and explore current dynamics, understand knowledge progression, elicit trends through thematic map analysis, synthesize knowledge structures and provide future research directions in this domain. Design/methodology/approach The study applies bibliometric analysis on 562 Scopus indexed articles from 1986 to 2021. Biblioshiny version 3.1.4, a Web-based application included in Bibiliometrix package developed in R-language (Aria and Cuccurullo, 2017), was used to examine: the most prominent articles, journals, authors, institutions and countries and to understand the thematic evolution and to elicit trends through the synthesis of knowledge structures including conceptual, intellectual and social structures of the field. Findings Motor themes, basic transverse, niche and emerging and declining themes were identified using (Callon, 1991) strategic thematic map. Besides, four major clusters based on a cocitation network of documents were identified: empirical evidence and drivers of momentum returns, theories explaining momentum returns and implications for asset pricing and market efficiency, avoiding momentum crashes and momentum in alternative asset classes, alternative explanations for momentum returns. The study infers that momentum research is becoming multidisciplinary given the dominance of behavioral theories and economic aspects in explaining the persistence of momentum profits and offers future research directions. Research limitations/implications The study deploys bibliometric analysis, appropriate for deriving insights from the vast extant literature. However, a meta-analysis might offer deeper insights into specific dimensions of the research topic. Besides, the study’s findings are based on Scopus indexed articles analyzed using bibilioshiny; the database and software limitations might have affected the findings. Practical implications The study is a ready reckoner for scholars who intend to recognize the evolution of momentum investment strategies, current dynamics and future research direction. The study offers practitioners insights into efficiently designing and deploying momentum investment strategies and ways to avoid momentum crashes. Social implications The study offers insights into the irrational behavior and systematic errors committed by market participants that helps regulators and policymakers to direct investors’ educational efforts to minimize systematic behavioral errors and related adverse financial consequences. Originality/value This comprehensive study on momentum investment strategies evaluates research trends and current dynamics draws a thematic map, knowledge progression in the field and offers future research directions.
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The effectiveness of mutual fund performance evaluation measures is a widely debated topic in the literature, due to the apparent inconsistency of predominantly negative performances, in contrast to the simultaneous and continuous demand for actively managed mutual funds. The limitations pointed out to the traditional performance evaluation measures of Treynor (1965), Sharpe (1966) and Jensen (1968), as well as the prevalence of negative alphas in the estimates of the Fama and French (1993, 2015, 2018) and Carhart (1997) models, have motivated new investigations and adaptations to the models. In this study we test the methodology proposed by Angelidis, Giamouridis and Tessaromatis (2013), in which mutual fund performance evaluation is adjusted to the return of a pre-defined benchmark, using a sample of equity mutual funds domiciled in the Portuguese market, between January 2000 and June 2019. The results show that this new methodology partially adjusts the prevalence of negative alphas in the Fama and French (1993, 2018) and Carhart (1997) model estimates, reducing their negative values and bringing them closer to neutrality, with differences being statistically significant at the 1% level. This evidence is consistent with the studies of Angelidis et al. (2013), for the US market, and Mateus, I., Mateus, C. and Todorovic (2016), for the UK market.
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This study comprehensively evaluates and ranks a large number of competing explanations for the momentum anomaly. As a benchmark for evaluation, firm fundamentals are found to be the most promising among well-known explanations of momentum, followed by prospect theory and mental accounting, and anchoring effect. Collectively, all explanations capture 31% of momentum, whereas 69% of momentum remains unexplained. This study thoroughly examines what fractions of the momentum anomaly emerge from the interaction effects between past returns and various firm characteristics. It is further found that strategies based on firm characteristics and residual momentum can significantly alleviate the severity of momentum crashes. Finally, robustness analysis is provided for choosing different formation and holding periods, excluding January observations, and analyze at the level of portfolio rather than individual stock. This paper was accepted by David Simchi-Levi, finance.
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Recent literature shows that momentum strategies exhibit significant downside risks over certain periods, called “momentum crashes”. We find that high uncertainty of momentum strategy returns is sourced from the cross-sectional volatility of individual stocks. Stocks with high realised volatility over the formation period tend to lose momentum effect. We propose a new approach, generalised risk-adjusted momentum (GRJMOM), to mitigate the negative impact of high momentum-specific risks. GRJMOM is proven to be more profitable and less risky than existing momentum ranking approaches across multiple asset classes, including the UK stock, commodity, global equity index, and fixed income markets.
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We propose a method to extract the risk-neutral distribution of firm-specific stock returns using both options and credit default swaps (CDS). Options and CDS provide information about the central part and the left tail of the distribution, respectively. Taken together, but not in isolation, options and CDS span the intermediate part of the distribution, which is driven by exposure to the risk of large, but not extreme, returns. Through a series of asset-pricing tests, we show that this intermediate-return risk carries a premium, particularly at times of heightened market stress. This paper was accepted by David Simchi-Levi, finance.
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This paper studies the relation between 36 firm-level characteristics and stock returns in 48 countries using instrumented principal components analysis. A non-U.S. country-neutral conditional factor model performs well in describing risk and returns and generates small and statistically insignificant anomaly intercepts when allowing for three or more latent factors. The non-U.S. model performs better in emerging than in developed markets, while showing substantial differences across countries. On average, only 10 characteristics significantly contribute to the models’ performance. Market beta, momentum, and firm size characteristics instrument for systemic exposure in U.S. and non-U.S. models, while investment and book-to-market do not. (JEL G11, G12, G14, G15) Received January 28, 2021; editorial decision July 30, 2021
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We investigate the profitability of momentum strategies in the market for single-family homes by using 10 city-level Case-Shiller home price indices (HPIs). Compared with the momentum strategies based on the Fama-French 10-industry portfolios of stocks, the profits from the single-family HPIs are more statistically significant, less sensitive to the construction methods of the momentum strategies and more correlated across different strategies. The momentum profits from the HPIs tend to be counter-cyclical, unlike the pro-cyclical behaviors of the momentum profits from stock portfolios. The differences in the momentum profits with HPIs and stocks indicate that a momentum strategy with the former can help diversify the risk in the asset portfolio of investors.
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Purpose Momentum strategies exhibit quarterly seasonality, earning significantly higher average strategy returns in the third month of the quarter than the first month. The authors evaluate the magnitude of quarterly seasonality in various momentum strategies to examine the relation between quarterly seasonality and risk-adjusted monthly returns. Design/methodology/approach The authors construct long-short portfolios for various types of momentum strategies and calculate the average returns of these portfolios in the three months of the quarter. They also calculate the average changes in institutional ownership across the different portfolios. Findings The authors demonstrate that quarterly seasonality is directly associated with quarterly changes in net purchases by institutional investors. Additionally, they show that near-term price momentum exhibits more seasonality than other momentum strategies, consistent with institutional investor incentives. Research limitations/implications Researchers studying momentum should understand that quarterly seasonality increases the standard deviation of monthly returns for different types of momentum strategies. Practical implications Individual investors and investment managers should consider whether it is early or late in the calendar quarter when implementing momentum strategies. Originality/value Quarterly seasonality explains several seemingly independent findings in the momentum literature. In cases where researchers show one momentum strategy outperforms another on a risk-adjusted basis, the authors find that the superior strategy exhibits less quarterly seasonality. This pattern holds across types of momentum strategies, strategy formation periods and asset classes.
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We show that mutual fund ratings generate correlated demand that creates systematic price fluctuations. Mutual fund investors chase fund performance via Morningstar ratings. Until June 2002, funds pursuing the same investment style had highly correlated ratings. Therefore, rating-chasing investors directed capital into winning styles, generating style-level price pressures, which reverted over time. In June 2002, Morningstar reformed its methodology of equalizing ratings across styles. Style-level correlated demand via mutual funds immediately became muted, significantly altering the time-series and cross-sectional variation in style returns.
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We develop an alternative view to the modern finance theory that essentially suggests equilibria in efficient markets by taking a risk-based view of asset returns in stock markets. Based on a mathematical analysis of stock market data using multi-scale approaches, we will alternatively describe markets and factors as trend-based fractal processes and analyze well-known factor premiums, which leads to a return-based view of markets and a model of investors reacting to market environments. We conclude that markets could be viewed alternatively as fractal, non-stationary and, at most, asymptotically efficient.
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This study investigates the relationship between the real economy and stock prices in the context of momentum strategies. While past research has examined momentum in terms of data embedded in market activity, we show that momentum is affected by data from real activity. Using United States sectoral output indices, we show that once the industry effect is considered, the momentum in stocks may lose significance in many cases. In several strategies, the influence of real sectors generates significant anomalous returns and remains robust even when the influence of stock indices is taken into account. The presence of momentum may imply that the world market factor should be augmented with a momentum factor. However, beyond mechanically accounting for a momentum factor without the proper economic mechanism that establishes its relevance, multifactor models are criticized for purely matching the data rather than basing it on solid economic arguments. This paper responds to this criticism by attempting to understand the source of the cross-country model from a real-output perspective.
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This paper is the second of a two-part series that provides essential context for any serious study of alternative risk premium (ARP) strategies. Practitioners uniformly emphasize the academic lineage of ARP strategies, regularly citing seminal papers. However, a single, comprehensive review of the copious research underpinning the category does not exist. This paper provides a comprehensive review of ARP’s academic roots, explaining that it sits at the confluence of decades of research on empirical anomalies, hedge fund replication, multi-factor models, and data snooping.
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This paper studies the effect of option trading on corporate investment and financing policies. Based on prior literature, I hypothesize that option market induces informed trading and thus reduces information asymmetry and the cost of capital. As a result, firms with high option trading have more investment and financing. Specifically, based on the United States public data, this paper finds that option trading volume increases corporate investment and financing, but reduces cash holdings and corporate payouts. These results are robust to the inclusion of industry or firm fixed effect, a control for endogenous options trading, and the use of alternative measures of option trading and corporate policies. The effect of option trading is stronger for firms with higher information asymmetry problems. Finally, this paper finds the results are inconsistent with the “quiet Life” hypothesis and the catering hypothesis.
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I develop a method to extract only the priced factors from stock returns. The first step estimates expected returns based on firm characteristics. The second step uses the estimated expected returns to form portfolios. The last step uses principal component analysis to extract factors from the portfolio returns. The procedure isolates and emphasizes the comovement across assets that is related to expected returns as opposed to firm characteristics. It produces three factors–level, slope, and curve–which perform as well or better than other leading models. The methodology performs well in out-of-sample tests. The new factors have macroeconomic risk interpretations.
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We examine five important asset pricing anomalies, namely, size, value, momentum, profitability, and investment rate to evaluate their efficacy in major West European economies, that is, France, Germany, Italy, and Spain. We employ four prominent asset pricing models, namely Capital Asset Pricing Model (CAPM), Fama–French three-factor (FF3) model, Carhart model and Fama–French five-factor (FF5) model to evaluate whether portfolio managers can create trading strategies to generate risk-adjusted extra normal returns for their investors. We also examine the prominent anomalies which pass the test of asset pricing in our sample countries and evaluate the best performing asset pricing model in explaining returns in each of these countries. We find that in spite of being matured markets, these countries provide portfolio managers with opportunities to exploit these strategies to generate extra normal returns for their investors. Momentum anomaly for Germany and profitability anomaly for Italy can be exploited by fund managers for generating risk-adjusted returns. For France, except for net investment rate anomaly, all the other anomalies remained unexplained by asset pricing models. We also find CAPM to be the better model in explaining returns of Italy and Spain. While FF3 factor and FF5 factor models explain returns in Germany, our sample asset pricing models failed to work for France. Our study has implications for portfolio managers, academia, and policymakers.
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This study examines whether price momentum profit is related to earnings information in the Korean stock market. Through time‐series and cross‐sectional asset pricing tests, we find that price momentum profits are captured by return on equity; an earnings surprise or revenue surprise partially explains price momentum. The risk‐based factor models cannot explain the existence of earnings‐based momentum, because an earnings‐based zero‐investment portfolio is significantly negatively related to future macroeconomic variables such as gross domestic product and real consumption growth. On the other hand, the underreaction hypothesis is also not sufficient to explain why earnings‐based momentum seems to capture price momentum.
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Firm‐level studies of sustainable investment performance are typically limited by an errors‐in‐variables bias (i.e., a distortion of estimated regression coefficients caused by measurement error in explanatory variables). Using recent advances in statistical methodology, we present the first cross‐sectional analysis of sustainable stock selection which adequately corrects for this bias and additionally answers the question of whether betas with respect to sustainable risk factors or sustainable characteristics (i.e., environmental, social, and governance ratings) are more relevant in portfolio selection. Within the universe of S&P 500 stocks, which is highly relevant from the investor attention and liquidity perspectives, we find that, after accounting for errors‐in‐variables bias, both types of variables become insignificant. Consequently, they do not add value to investment portfolios and are not vital in models explaining stock returns. Among classic predictors with a long history of use in the investment fund industry, only the market‐to‐book ratio provides independent investment and pricing information.
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This paper evaluates various explanations for the profitability of momentum strategies documented in Jegadeesh and Titman (1993). The evidence indicates that momentum profits have continued in the 1990s, suggesting that the original results were not a product of data snooping bias. The paper also examines the predictions of recent behavioral models that propose that momentum profits are due to delayed overreactions that are eventually reversed. Our evidence provides support for the behavioral models, but this support should be tempered with caution.
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This article studies momentum in stock returns, focusing on the role of industry, size, and book-to-market (B/M) factors. Size and B/M portfolios exhibit momentum as strong as that in individual stocks and industries. The size and B/M portfolios are well diversified, so momentum cannot be attributed to firm- or industry-specific returns. Further, industry, size, and B/M portfolios are negatively autocorrelated and cross-serially correlated over intermediate horizons. The evidence suggests that stocks covary “too strongly” with each other. I argue that excess covariance, not underreaction, explains momentum in the portfolios.
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This paper presents new empirical evidence of predictability of individual stock returns. The negative first-order serial correlation in monthly stock returns is highly significant. Furthermore, significant positive serial correlation is found at longer lags, and the twelve-month serial correlation is particularly strong. Using the observed systematic behavior of stock return, one-step-ahead return forecasts are made and ten portfolios are formed from the forecasts. The difference between the abnormal returns on the extreme decile portfolios over the period 1934-87 is 2.49 percent per month. Copyright 1990 by American Finance Association.
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A test for the ex ante efficiency of a given portfolio of assets is analyzed. The relevant statistic has a tractable small sample distribution. Its power function is derived and used to study the sensitivity of the test to the portfolio choice and to the number of assets used to determine the ex post mean-variance efficient frontier. Several intuitive interpretations of the test are provided, including a simple mean-standard deviation geometric explanation. A univariate test, equivalent to our multivariate-based method, is derived, and it suggests some useful diagnostic tools which may explain why the null hypothesis is rejected. Empirical examples suggest that the multivariate approach can lead to more appropriate conclusions than those based on traditional inference which relies on a set of dependent univariate statistics. Copyright 1989 by The Econometric Society.
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This article develops and applies new measures of portfolio performance which use benchmarks based on the characteristics of stocks held by the portfolios that are evaluated. Specifically, the benchmarks are constructed from the returns of 125 passive portfolios that are matched with stocks held in the evaluated portfolio on the basis of the market capitalization, book‐to‐market, and prior‐year return characteristics of those stocks. Based on these benchmarks, “Characteristic Timing” and “Characteristic Selectivity” measures are developed that detect, respectively, whether portfolio managers successfully time their portfolio weightings on these characteristics and whether managers can select stocks that outperform the average stock having the same characteristics. We apply these measures to a new database of mutual fund holdings covering over 2500 equity funds from 1975 to 1994. Our results show that mutual funds, particularly aggressive‐growth funds, exhibit some selectivity ability, but that funds exhibit no characteristic timing ability.
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ABSTRACT Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market {3, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in {3 that is unrelated to size, the relation between market {3 and average return is flat, even when {3 is the only explanatory variable. THE ASSET-PRICING MODEL OF Sharpe (1964), Lintner (1965), and Black (1972)
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Book-to-market ratio (BE/ME), market equity (ME), and one- year past return (momentum) (MOM) help explain the cross- section of expected individual stock returns within the U.S. and within other countries. Examining equity markets as a whole, in contrast to individual stocks, we uncover strong parallels between the explanatory power of these variables for individual stocks and for countries. First, country versions of BE/ME, ME, and MOM help explain the cross-section of expected country returns. Second, the January seasonal in ME's explanatory power for stocks also appears for countries. Third, portfolios formed by sorting stocks and countries on these variables produce similar patterns in profitability before and after the portfolio formation date.
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This article analyzes the degree to which return consistency in the past predicts future returns. I show that consistency is a strong predictive measure for future stock returns. In a portfolio context, positively consistent stocks exhibit positive future risk-adjusted returns, and negatively consistent stocks exhibit negative future risk-adjusted returns. The results are economically and statistically significant over multiple subperiods. Also, odd return behavior persists for nearly two years after portfolio formation. Stocks that have been consistently positive (negative) for longer time horizons have higher (lower) risk-adjusted returns during the followingmonththan those thathavebeenconsistent for shorter time periods. Finally, high consistency enhances momentum when the two factors are allowed to interact. Thus, there appears to be strong path dependence in the momentum effect, and consistency in stock returns appears to be an important component of return predictability.
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Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or of how investors form beliefs, which is consistent with the empirical findings. The model is based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values.
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Better proxies for the information about future returns contained in firm characteristics such as size, book-to-market equity, cash flow-to-price, percent change in employees, and various past return measures are obtained by breaking these explanatory variables into two industry-related components. The components represent (1) the difference between firms' own characteristics and the average characteristics of their industries (within-industry variables), and (2) the average characteristics of firms' industries (across-industry variables). Each variable is reliably priced within-industry and measuring the variables within-industry produces more precise estimates than measuring the variables in their more common form. Contrary to Moskowitz and Grinblatt [1999], we find that within-industry momentum (i.e., the firm's past return less the industry average return) has predictive power for the firm's stock return beyond that captured by across-industry momentum. We also document a significant short-term (one-month) industry momentum effect which remains strongly significant when we restrict the sample to only the most liquid firms.
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This study examines momentum and reversals in currencies and international equity market indices. We find momentum in country equity market indices during the first year after the portfolio formation date and reversals during the subsequent two years. We also find momentum in currencies up to three years after the portfolio formation date but no reversals. Positive currency momentum predicts low stock index returns in the future weakening momentum and strengthening reversals in U.S. dollar-denominated stock index returns. Additional tests show that countries with positive (negative) equity momentum experience declining (increasing) nominal federal fund rates in the first year after portfolio formation date and increasing (decreasing) interest rates in the subsequent two years. We discuss the implications of our findings for rational and behavioral theories.
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The value premium in U.S. stock returns is robust. The positive relation between average return and book-to-market equity is as strong for 1929 to 1963 as for the subsequent period studied in previous papers. A three-factor risk model explains the value premium better than the hypothesis that the book-to-market characteristic is compensated irrespective of risk loadings.
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Investors may be able to benefit from equity style management. We find that three company characteristics—market value of equity, book-to-market ratio, and dividend yield-capture style-related trends in equity returns. We study all firms in the Standard and Poor's-500 index since 1976. Strategies that buy stocks with characteristics that are currently in favor (past winners) and that sell stocks with characteristics that are out-of-favor (past losers) perform well for periods up to 1 year and possibly longer. Style momentum in equity returns is an empirical phenomenon that is distinct from price and industry momentum.
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The tendency of some investors to hold on to their losing stocks, driven by prospect theory and mental accounting, creates a spread between a stock's fundamental value and its equilibrium price, as well as price underreaction to information. Spread convergence, arising from the random evolution of fundamental values and the updating of reference prices, generates predictable equilibrium prices interpretable as possessing momentum. Empirically, a variable proxying for aggregate unrealized capital gains appears to be the key variable that generates the profitability of a momentum strategy. Controlling for this variable, past returns have no predictability for the cross-section of returns.
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This paper identifies five common risk factors in the returns on stocks and bonds. There are three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity. There are two bond-market factors, related to maturity and default risks. Stock returns have shared variation due to the stock-market factors, and they are linked to bond returns through shared variation in the bond-market factors. Except for low-grade corporates, the bond-market factors capture the common variation in bond returns. Most important, the five factors seem to explain average returns on stocks and bonds.
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This paper identifies observable firm-specific attributes that drive momentum. We find that a firm's revenues, costs, and growth options combine to determine the dynamics of its return autocorrelation. We use these insights to implement momentum strategies (buying winners and selling losers) with both numerically simulated returns and CRSP/Compustat data. In both sets of data, momentum strategies that use firms with high revenue growth volatility, low costs, or valuable growth options outperform traditional momentum strategies by approximately 5% per year.
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Our paper re-examines the profitability of relative strength or momentum trading strategies (buying past strong performers and selling past weak performers). We find that standard relative strength strategies require frequent trading in disproportionately high cost securities such that trading costs prevent profitable strategy execution. In the cross-section, we find that those stocks that generate large momentum returns are precisely those stocks with high trading costs. We conclude that the magnitude of the abnormal returns associated with these trading strategies creates an illusion of profit opportunity when, in fact, none exists.
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This paper presents a new pattern in the cross-section of expected stock returns. Stocks tend to have relatively high (or low) returns every year in the same calendar month. We recognize the annual cross-sectional autocorrelation pattern documented in Jegadeesh [1990. Evidence of predictable behavior of security returns. Journal of Finance 45, 881–898] at lags of 12, 24, and 36 months as part of a general pattern that lasts up to 20 annual lags, superimposed on the general momentum/reversal patterns. This pattern explains an economically and statistically significant magnitude of the cross-sectional variation in average stock returns. Volume and volatility exhibit similar seasonal patterns but they do not explain the seasonality in returns. The pattern is independent of size, industry, earnings announcements, dividends, and fiscal year. The results are consistent with the existence of a persistent seasonal effect in stock returns.
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The consistency of positive past returns and tax-loss selling significantly affects the relation between past returns and the cross-section of expected returns. Analysis of these additional effects across stock characteristics, seasons, and tax regimes provides clues about the sources of temporal relations in stock returns, pointing to potential explanations for this relation. A parsimonious trading rule generates surprisingly large economic returns despite controls for confounding sources of return premia, microstructure effects, and data snooping biases.
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This study examines momentum and reversals in international stock market indices. We find that country stock indices exhibit momentum during the first year after the portfolio formation date and reversals during the subsequent 2 years. Positive currency momentum predicts low stock index returns in the future, thereby weakening momentum and strengthening reversals in U.S. dollar-denominated stock index returns. Cross-sectional regression tests involving individual stock indices confirm the portfolio findings. Our results are consistent with a key prediction of recent behavioral theories, that initial momentum should be accompanied by subsequent reversals.
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The value premium in U.S. stocks returns is robust. The positive relation between average return and book-to-market equity (BE/ME) is as strong for 1929-63 as for the subsequent period studied in previous papers. Like others, we also find a size premium in stock returns. Small stocks have higher average returns than big stocks. The size premium is, however, weaker and less reliable than the value premium. The relations between average return and firm characteristics (size and BE/ME) are better explained by a three-factor risk model than by the behavioral hypothesis that investor overreaction causes characteristics to be compensated irrespective of risk loadings.
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I argue that the slow diffusion of industry information is a leading cause of the lead-lag effect in stock returns. I find that the lead-lag effect between big firms and small firms is predominantly an intra-industry phenomenon. Moreover, this effect is driven by sluggish adjustment to negative information, and is robust to alternative determinants of the lead-lag effect. Small, less competitive and neglected industries experience a more pronounced lead-lag effect. The lead-lag effect is related to the post-announcement drift of small firms following the earnings releases of big firms within the industry. , Oxford University Press.
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We identify a “slope” factor in exchange rates. High interest rate currencies load more on this slope factor than low interest rate currencies. This factor accounts for most of the cross-sectional variation in average excess returns between high and low interest rate currencies. A standard, no-arbitrage model of interest rates with two factors—a country-specific factor and a global factor—can replicate these findings, provided there is sufficient heterogeneity in exposure to global or common innovations. We show that our slope factor identifies these common shocks, and we provide empirical evidence that it is related to changes in global equity market volatility. By investing in high interest rate currencies and borrowing in low interest rate currencies, U.S. investors load up on global risk.
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Commodity futures risk premiums vary across commodities and over time depending on the level of physical inventories. The convenience yield is a decreasing, nonlinear function of inventories. Price measures, such as the futures basis, prior futures returns, prior spot returns, and spot price volatilities reflect the state of inventories and are informative about commodity futures risk premiums. We verify these theoretical predictions using a comprehensive data set on 31 commodity futures and physical inventories between 1971 and 2010. We find no evidence that the positions of participants in futures markets predict risk premiums on commodity futures.
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It is well established that recent prior winner and loser stocks exhibit return continuation; a momentum strategy of buying recent winners and shorting recent losers appears profitable in the post 1945 era. In contrast, the risk exposure of such a strategy has not been well understood; the strategy's unconditional average risk exposure can be deceptive. The stock selection method of a momentum strategy guarantees that large and time varying factor exposured will be borne in accordance with the performance of the common risk factors during the periods in which stocks were ranked to determine their winner/losed status.
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We examine whether the predictability of future returns from past returns is due to the market's underreaction to information, in particular to past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. Market risk, size, and book-to-market effects do not explain the drifts. There is little evidence of subsequent reversals in the returns of stocks with high price and earnings momentum. Security analysts' earnings forecasts also respond sluggishly to past news, especially in the case of stocks with the worst past performance. The results suggest a market that responds only gradually to new information. Copyright 1996 by American Finance Association.
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This paper documents that strategies that buy stocks that have performed well in the past and sell stocks that hav e performed poorly in the past generate significant positive returns o ver three- to twelve-month holding periods. The authors find that the profitability of these strategies are not due to their systematic risk or to delay ed stock price reactions to common factors. However, part of the abnorm al returns generated in the first year after portfolio formation dissipates in the following two years. A similar pattern of returns around the earnings announcements of past winners and losers is also documented. Copyright 1993 by American Finance Association.
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Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or of how investors form beliefs, which is consistent with the empirical findings. The model is based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values.
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This paper tests whether the "disposition effect," that is the tendency of investors to ride losses and realize gains, induces "underreaction" to news, leading to return predictability. I use data on mutual fund holdings to construct a new measure of reference purchasing prices for individual stocks, and I show that post-announcement price drift is most severe whenever capital gains and the news event have the same sign. The magnitude of the drift depends on the capital gains (losses) experienced by the stock holders on the event date. An event-driven strategy based on this effect yields monthly alphas of over 200 basis points. Copyright 2006 by The American Finance Association.
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This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences. Copyright The American Finance Association 1999.
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We test whether momentum strategies remain profitable after considering market frictions induced by trading. Intraday data are used to estimate alternative measures of proportional and non-proportional (price impact) trading costs. The price impact models imply that abnormal returns to portfolio strategies decline with portfolio size. We calculate break-even fund sizes that lead to zero abnormal returns. In addition to equal- and value-weighted momentum strategies, we derive a liquidity-weighted strategy designed to reduce the cost of trades. Equal-weighted strategies perform the best before trading costs and the worst after trading costs. Liquidity-weighted and hybrid liquidity/value-weighted strategies have the largest break-even fund sizes: $5 billion or more (relative to December 1999 market capitalization) may be invested in these momentum strategies before the apparent profit opportunities vanish. Copyright 2004 by The American Finance Association.
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Momentum effects in stock returns need not imply investor irrationality, heterogeneous information, or market frictions. A simple, single-firm model with a standard pricing kernel can produce such effects when expected dividend growth rates vary over time. An enhanced model, under which persistent growth rate shocks occur episodically, can match many of the features documented by the empirical research. The same basic mechanism could potentially account for underreaction anomalies in general. Copyright The American Finance Association 2002.
Article
Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market "beta", size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in "beta" that is unrelated to size, t he relation between market "beta" and average return is flat, even when "beta" is the only explanatory variable. Copyright 1992 by American Finance Association.
Article
We propose a theory of securities market under- and overreactions based on two well-known psychological biases: investor overconfidence about the precision of private information; and biased self-attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. We show that overconfidence implies negative long-lag autocorrelations, excess volatility, and, when managerial actions are correlated with stock mispricing, public-event-based return predictability. Biased self-attribution adds positive short-lag autocorrelations ("momentum"), short-run earnings "drift," but negative correlation between future returns and long-term past stock market and accounting performance. The theory also offers several untested implications and implications for corporate financial policy. Copyright The American Finance Association 1998.
Article
: We model a market populated by two groups of boundedly rational agents: "newswatchers" and "momentum traders". Each newswatcher observes some private information, but fails to extract other newswatchers' information from prices. If information diffuses gradually across the population, prices underreact in the short run. The underreaction means that the momentum traders can profit by trend-chasing. However, if they can only implement simple (i.e., univariate) strategies, their attempts at arbitrage must inevitably lead to overreaction at long horizons. In addition to providing a unified account of under- and overreactions, the model generates several other distinctive implications. * Stanford Business School and MIT Sloan School of Management and NBER. This research is supported by the National Science Foundation and the Finance Research Center at MIT. We are grateful to Denis Gromb, Ren Stulz, an anonymous referee, and seminar participants at MIT, Michigan, Wharton, Duke, UCLA, Berk...
Article
: Various theories have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion modelofHong and Stein (1999) and establish three key results. First, once one moves past the very smallest stocks, the profitability of momentum strategies declines sharply with firm size. Second, holding size fixed, momentum strategies work better among stocks with low analyst coverage. Finally, the effect of analyst coverage is greater for stocks that are past losers than for past winners. These findings are consistent with the hypothesis that firm-specific information, especially negative information, diffuses only gradually across the investing public. * Hong is from the Stanford Business School, Lim is from the AmosTuck School, Dartmouth College, and Stein is from the MIT Sloan School of Management and the National Bureau of Economic Research. This research is supported by the National Science Foundation and the Finance Research Center at MIT. We are grateful to J...
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Previous studies identify predetermined variables that predict stock and bond returns through time. This paper shows that loadings on the same variables provide significant cross-sectional explanatory power for stock portfolio returns. The loadings are significant given the three factors advocated by Fama and French (1993) and the four factors of Elton, Gruber and Blake (1995). The explanatory power of the loadings on lagged variables is robust to various portfolio grouping procedures and other considerations. The results carry implications for risk analysis, performance measurement, cost-of-capital calculations and other applications. EMPIRICAL ASSET PRICING is in a state of turmoil. The Capital Asset Pricing Model (CAPM, Sharpe (1964), Black (1972)) has long served as the backbone of academic finance and numerous important applications. However, studies have identified empirical deficiencies in the CAPM, challenging its preeminence. The most powerful challenges include market capit...
Returns to Buying Winners and Selling Losers
  • Jegadeesh
  • Sheridan Narasimhan
  • Titman
Jegadeesh, Narasimhan, and Sheridan Titman, 1993, “Returns to Buying Winners and Selling Losers,” Journal of Finance, Vol. 48, pp. 65-91.
  • Cliff S Asness
  • J Tobias
  • Lasse Heje Moskowitz
  • Pedersen
Asness, Cliff S., Tobias J. Moskowitz, and Lasse Heje Pedersen, 2008, " Value and Momentum Everywhere, " working paper.