{"id":99530,"date":"2021-08-18T10:55:00","date_gmt":"2021-08-18T14:55:00","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=99530"},"modified":"2024-05-15T10:29:39","modified_gmt":"2024-05-15T14:29:39","slug":"an-important-analysis-of-stock-momentum-and-reversal-factors","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/an-important-analysis-of-stock-momentum-and-reversal-factors\/","title":{"rendered":"An Important Analysis of Stock Momentum and Reversal Factors"},"content":{"rendered":"\n

Excerpt<\/em><\/strong><\/p>\n\n\n\n

So much was written about\u00a0stock momentum<\/a>\u00a0since the Jegadeesh and Titman (1993) that it might have started to be confusing. Still, there seems to be a consensus among academics and practitioners that there is a stock\u00a0momentum<\/a>\u00a0based on past twelve returns and short-term\u00a0reversal<\/a>\u00a0based on the past month. However, there is also an\u00a0industry momentum<\/a>,\u00a0sector momentum<\/a>, peers momentum, and the newest addition is the\u00a0factor momentum<\/a>.\u00a0These numerous anomalies raise a question \u2013 can the initial momentum be explained by industry, sector or factor momentum? Moreover, similar question could be raised about the short-term reversal.\u00a0<\/p>\n\n\n\n

The novel research by Li and Turkington (2021) uses a robust regression model where variables are standardized and include returns of individual securities as the dependent variable. The explanatory variables include returns over the industry, industry over industry group, industry group over the sector, sector over the market, various risk factors and even returns of statistical peers (measured by Mahalanobis distance). As a result, the authors provide an in-depth analysis of both momentum and reversal anomalies, and the approach yields compelling results. These analyses are even divided into a more prolonged sample and the most recent period of 2010-2020. <\/p>\n\n\n\n

The individual momentum anomaly that broader market groups do not fully explain exists in the whole sample but is statistically weak. On the other hand, the reversal anomaly is highly significant. Secondly, the traditional 12-months momentum can be better explained by the factor momentum than the industry or sector momentum. Still, the industries, industry groups, sectors, and even factors have distinct drivers, and the anomalies seem different. <\/p>\n\n\n\n

The most recent sample offers captivating results too. Firstly, it seems that the 12-month momentum in industries does not exist anymore, but the opposite holds for a 1-month reversal. The reversal in industries or sectors is even more apparent. <\/p>\n\n\n\n

To sum it up, there are several takeaways for every quant investor, and we highly recommend diving deeper into the paper. <\/p>\n\n\n\n

Authors:<\/strong> Yimou Li and David Turkington<\/p>\n\n\n\n

Title:<\/strong> Mapping Momentum<\/p>\n\n\n\n

Link<\/strong>: https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3883504<\/a><\/p>\n\n\n\n

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

Findings on momentum and reversal effects in the stock market are often disparate. Differences in methodology, calibration, data universe, and the granularity of tests have made it challenging to reconcile and unify the various documented relationships. Our goal is to attribute stock return predictability to a variety of distinct momentum (and reversal) components within a single coherent framework. We focus on S&P 500 stocks and implement consistent data transformations, nested sets of excess returns, and panel regressions to facilitate this attribution. We find that sector and factor momentum coexist, but they operate on different horizons, and sector momentum is more prone to crash during volatile markets. Collectively, sector and factor momentum explains away most of the security-specific 12-month momentum effect, with factors explaining more. Traditional 12-month momentum is much more prevalent for past \u201closer\u201d stocks whereas crashes and reversals are found mostly among past \u201cwinners.\u201d Lastly, we show that in the decade after the 2008-2009 financial crisis compared to the decade prior, sector and industry momentum disappeared at the 12-month horizon but intensified in terms of 1-month reversals.<\/p>\n\n\n\n

Visit Quantpedia to read the full article: https:\/\/quantpedia.com\/an-important-analysis-of-stock-momentum-and-reversal-factors\/<\/a>.<\/em><\/p>\n\n\n\n

Past performance is not indicative of future results.<\/em><\/p>\n\n\n\n

Any stock, options or futures symbols displayed are for illustrative purposes only and are not intended to portray recommendations.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

The novel research by Li and Turkington (2021) uses a robust regression model where variables are standardized and include returns of individual securities as the dependent variable. 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