{"id":850,"date":"2018-10-05T21:02:18","date_gmt":"2018-10-05T21:02:18","guid":{"rendered":"http:\/\/quantpedia.com\/?p=850"},"modified":"2019-08-22T05:48:57","modified_gmt":"2019-08-22T05:48:57","slug":"three-new-academic-research-papers-related-to-momentum-in-stocks","status":"publish","type":"post","link":"https:\/\/vvv.quantpedia.com\/es\/three-new-academic-research-papers-related-to-momentum-in-stocks\/","title":{"rendered":"Three New Academic Research Papers Related to Momentum in Stocks"},"content":{"rendered":"

\n\tRelated to:<\/strong><\/span><\/p>\n

\t#14 – Momentum Effect in Stocks<\/a><\/strong><\/p>\n

\n\tAuthor:<\/strong> Muller, Muller<\/p>\n

\n\tT\u00edtulo:<\/strong> The Remarkable Relevance of Characteristics for Momentum Profits<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3240609<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tThis paper provides a comprehensive analysis of a large set of momentum<\/span> enhancing strategies for global equity markets. Our findings reveal the relevance of characteristics in enhancing and explaining momentum<\/span> after accounting for possible interrelations with idiosyncratic volatility and extreme past returns. Out of a set of eighteen stock characteristics, we find particularly age, book-to-market, maximum daily return, R², information diffusion, and 52-week high price to matter for momentum<\/span> profits. Overall, and consistent with behavioral explanation attempts, momentum<\/span> appears to work best for hard-to-value firms with high information uncertainty. There are however substantial cross-country differences with regard to which characteristics truly enhance momentum<\/span>. Our results imply that the link between idiosyncratic volatility, extreme past returns, and momentum<\/span> profits itself is unable to comprehensively explain enhanced momentum<\/span> returns and corroborate the heterogeneity of stock markets around the globe.<\/p>\n

\n\tAuthor:<\/strong> Abhyankar, Filippou, Garcia-Ares, Haykir<\/p>\n

\n\tT\u00edtulo:<\/strong> Overcoming Arbitrage Limits: Option Trading and Momentum Returns<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3206873<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tReturns to cross-sectional momentum<\/span> in the U.S. equity market, over 1996-2016, are fifty percent lower and statistically insignificant relative to the previous two decades. The decline is linked to larger arbitrage capital flows, lower stock trading costs, and greater investor awareness after publication. During this period stocks with traded options rose to more than seventy percent of all listed stocks. We find strong evidence that the reduction in momentum<\/span> profits is also related to stock option trading that offers alternate avenues for short sales and information flows that contribute to more efficient stock pricing.<\/p>\n

\n\tAuthor:<\/strong> Avramov, Hore<\/p>\n

\n\tT\u00edtulo:<\/strong> Cross-Sectional Factor Dynamics and Momentum Returns<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3033349<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tThis paper proposes and implements an inter-temporal model wherein aggregate consumption and asset-specific dividend growths jointly move with two mean-reverting state variables. Consumption beta varies through time and cross sectionally due to variation in half-lives and stationary volatilities of the dividend signals. Winner (Loser) stocks exhibit high (low) half-lives and stationary volatilities, and thus exhibit high (low) consumption beta commanding high (low) risk-premium. The model also rationalizes the "momentum<\/span> crashes" phenomenon discussed in Daniel and Moskowitz (2014). High half-lives of dividend signals in Winners keep their consumption betas low long after recovering from a prolonged economic downturn, while low half-lives in Losers make their consumption betas grow rather quickly. Thus, coming out of a recession, the long Winner\/short Loser strategy reduces in consumption beta and, hence, risk-premia.<\/p>","protected":false},"excerpt":{"rendered":"

\n\tRelated to:<\/strong><\/span><\/p>\n

\t#14 – Momentum Effect in Stocks<\/a><\/strong><\/p>\n

\n\tAuthor:<\/strong> Muller, Muller<\/p>\n

\n\tT\u00edtulo:<\/strong> The Remarkable Relevance of Characteristics for Momentum Profits<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3240609<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tThis paper provides a comprehensive analysis of a large set of momentum<\/span> enhancing strategies for global equity markets. Our findings reveal the relevance of characteristics in enhancing and explaining momentum<\/span> after accounting for possible interrelations with idiosyncratic volatility and extreme past returns. Out of a set of eighteen stock characteristics, we find particularly age, book-to-market, maximum daily return, R², information diffusion, and 52-week high price to matter for momentum<\/span> profits. Overall, and consistent with behavioral explanation attempts, momentum<\/span> appears to work best for hard-to-value firms with high information uncertainty. There are however substantial cross-country differences with regard to which characteristics truly enhance momentum<\/span>. Our results imply that the link between idiosyncratic volatility, extreme past returns, and momentum<\/span> profits itself is unable to comprehensively explain enhanced momentum<\/span> returns and corroborate the heterogeneity of stock markets around the globe.<\/p>\n

\n\tAuthor:<\/strong> Abhyankar, Filippou, Garcia-Ares, Haykir<\/p>\n

\n\tT\u00edtulo:<\/strong> Overcoming Arbitrage Limits: Option Trading and Momentum Returns<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3206873<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tReturns to cross-sectional momentum<\/span> in the U.S. equity market, over 1996-2016, are fifty percent lower and statistically insignificant relative to the previous two decades. The decline is linked to larger arbitrage capital flows, lower stock trading costs, and greater investor awareness after publication. During this period stocks with traded options rose to more than seventy percent of all listed stocks. We find strong evidence that the reduction in momentum<\/span> profits is also related to stock option trading that offers alternate avenues for short sales and information flows that contribute to more efficient stock pricing.<\/p>\n

\n\tAuthor:<\/strong> Avramov, Hore<\/p>\n

\n\tT\u00edtulo:<\/strong> Cross-Sectional Factor Dynamics and Momentum Returns<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3033349<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tThis paper proposes and implements an inter-temporal model wherein aggregate consumption and asset-specific dividend growths jointly move with two mean-reverting state variables. Consumption beta varies through time and cross sectionally due to variation in half-lives and stationary volatilities of the dividend signals. Winner (Loser) stocks exhibit high (low) half-lives and stationary volatilities, and thus exhibit high (low) consumption beta commanding high (low) risk-premium. The model also rationalizes the "momentum<\/span> crashes" phenomenon discussed in Daniel and Moskowitz (2014). High half-lives of dividend signals in Winners keep their consumption betas low long after recovering from a prolonged economic downturn, while low half-lives in Losers make their consumption betas grow rather quickly. Thus, coming out of a recession, the long Winner\/short Loser strategy reduces in consumption beta and, hence, risk-premia.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-850","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/850","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/comments?post=850"}],"version-history":[{"count":0,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/850\/revisions"}],"wp:attachment":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/media?parent=850"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/categories?post=850"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/tags?post=850"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}