{"id":722,"date":"2017-01-17T13:52:27","date_gmt":"2017-01-17T13:52:27","guid":{"rendered":"http:\/\/quantpedia.com\/?p=722"},"modified":"2019-08-22T05:48:19","modified_gmt":"2019-08-22T05:48:19","slug":"quantpedia-update-16th-january-2017","status":"publish","type":"post","link":"https:\/\/vvv.quantpedia.com\/es\/quantpedia-update-16th-january-2017\/","title":{"rendered":"Quantpedia Update – 16th January 2017"},"content":{"rendered":"

\n\tNew strategies:<\/u><\/strong><\/p>\n

\t#331 – Timing Betting-Against-Beta (BAB) Anomaly<\/strong><\/p>\n

\n\tPeriod of rebalancing:<\/strong> monthly
\n\tMarkets traded: <\/strong>equities
\n\tInstruments used for trading:<\/strong> stocks
\n\tComplexity:<\/strong> Complex strategy
\n\tBactest period:<\/strong> 1964-2015
\n\tIndicative performance:<\/strong> 21.48%
\n\tEstimated volatility:<\/strong> 16.84%
\n\tSource paper:<\/strong><\/p>\n

\n\tBarroso, Maio: Managing the risk of the "betting-against-beta" anomaly: does it pay to bet against beta?<\/strong>
\n\thttps:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2876450<\/a>
\n\tAbstracto:
\n\tWe study the risk dynamics of the betting-against-beta anomaly. The strategy shows strong and predictable time variation in risk and no risk-return trade-o\u00ef\u00ac\u20ac. A risk-managed strategy exploiting this achieves an annualized Sharpe ratio of 1.28 with a very high information ratio of 0.94 with respect to the original strategy. Similar strategies for the market, size, value, pro\u00ef\u00ac\u0081tability, and investment factors achieve a much smaller information ratio of 0.15 on average. The large economic bene\u00ef\u00ac\u0081ts of risk-scaling aresimilar to those of momentum andset these two anomalies apart fromother equity factors. Decomposing risk into a market and a speci\u00ef\u00ac\u0081c component we \u00ef\u00ac\u0081nd the speci\u00ef\u00ac\u0081c component drives our results.<\/p>\n

\t#332 – Contrast Effect During the Earnings Announcements<\/strong><\/p>\n

\n\tPeriod of rebalancing:<\/strong> daily
\n\tMarkets traded: <\/strong>equities
\n\tInstruments used for trading:<\/strong> stocks
\n\tComplexity:<\/strong> Complex strategy
\n\tBactest period:<\/strong> 1984-2013
\n\tIndicative performance:<\/strong> 15.00%
\n\tEstimated volatility:<\/strong> not stated
\n\tSource paper:<\/strong><\/p>\n

\n\tHartzmark, Shue: A Tough Act to Follow: Contrast Effects in Financial Markets<\/strong>
\n\tAbstracto:
\n\thttps:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2613702<\/a>
\n\tA contrast e\u00ef\u00ac\u20acect occurs when the value of a previously-observed signal inversely biases perception of the next signal. We present the \u00ef\u00ac\u0081rst evidence that contrast e\u00ef\u00ac\u20acects can distort prices in sophisticated and liquid markets. Investors mistakenly perceive earnings news today as more impressive if yesterday’s earnings surprise was bad and less impressive if yesterday’s surprise was good. A unique advantage of our \u00ef\u00ac\u0081nancial setting is that we can identify contrast e\u00ef\u00ac\u20acects as an error in perceptions rather than expectations. Finally, we show that our results cannot be explained by a key alternative explanation involving information transmission from previous earnings announcements.<\/p>\n

\n\tNew research papers related to existing strategies:<\/strong><\/u><\/p>\n

\n\t#118 – Time Series Momentum Effect
\n\t#137 – Trendfollowing in Futures Markets<\/strong><\/p>\n

\n\tHoffman, Kaminski: The TAMING of the SKEW<\/strong>
\n\thttp:\/\/www.valuewalk.com\/wp-content\/uploads\/2016\/06\/The_Taming_of_the_Skew___Campbell__Company.pdf<\/a>
\n\tAbstracto:
\n\tInvestors are often concerned about the negative skewness,  or  left-tail  asymmetry, of equity returns. In response, they seek risk-mitigating strategies to provide offsetting  returns when equity markets fall. Due to their association  with positive skewness,  trend-following  strategies are popular candidates for risk-mitigation or crisis-offset. This paper explores how a trend-following portfolio can achieve positive skewness, and finds that time variation in risk is the primary factor. In fact, any portfolio with a positive Sharpe ratio can achieve positive skewness simply by varying the level of risk taken through time.<\/p>\n

\n\t#308 – Short-Term Momentum in Currencies<\/strong><\/p>\n

\n\tKarnaukh: Currency Strategies and Sovereign Ratings<\/strong>
\n\thttps:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2868522<\/a>
\n\tAbstracto:
\n\tThis paper investigates a link between the most popular currency strategies (carry trade, momentum, value) and sovereign ratings. I document that the profitability of the momentum strategy is large and significant among higher credit risk currencies, but is nonexistent among lower credit risk currencies. The profitability of currency momentum disappears when currencies rated BBB- or worse (16% of currency months) are excluded from the sample. The country credit risk conditions do not apply to the carry trade and value, which are profitable among lower and higher credit risk currencies. Sovereign rating changes do not have a significant impact on the performance of the most popular currency strategies.<\/p>\n

\n\tTwo additional related research papers have been included into existing free strategy reviews during last 2 week:<\/strong><\/u><\/p>\n

\n\t#7 – Volatility Effect in Stocks – Long-Only Version
\n\t#14 – Momentum Effect in Stocks
\n\t#26 – Value (Book-to-Market) Anomaly
\n\t#229 – Earnings Quality Factor<\/p>\n

\tde Carvalho, Xiao, Soupe, Dugnolle: Diversify and Purify Factor Premiums in Equity Markets<\/strong>
\n\thttps:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2894171<\/a>
\n\tAbstracto:
\n\tIn this paper we consider the question of how to improve the efficacy of strategies designed to capture factor premiums in equity markets and, in particular, from the value, quality, low risk and momentum factors. We consider a number of portfolio construction approaches designed to capture factor premiums with the appropriate levels of risk controls aiming at increasing information ratios. We show that information ratios can be increased by targeting constant volatility over time, hedging market beta and hedging exposures to the size factor, i.e. neutralizing biases in the market capitalization of stocks used in factor strategies. With regards to the neutralization of sector exposures, we find this to be of importance in particular for the value and low risk factors. Finally, we look at the added value of shorting stocks in factor strategies. We find that with few exceptions the contributions to performance from the short leg are inferior to those from the long leg. Thus, long-only strategies can be efficient alternatives to capture these factor premiums. Finally, we find that factor premiums tend to have fatter tails than what could be expected from a Gaussian distribution of returns, but that skewness is not significantly negative in most cases.<\/p>\n

\n\t#125 – 12 Month Cycle in Cross-Section of Stocks Returns<\/strong><\/p>\n

\tHirschleifer, Jiang, Meng: Mood Beta and Seasonalities in Stock Returns<\/strong>
\n\thttps:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2880257<\/a>
\n\tAbstracto:
\n\tExisting research has documented cross-sectional seasonality of stock returns – the periodic outperformance of certain stocks relative to others during the same calendar month, weekday, or pre-holiday periods. A model based on the differential sensitivity of stocks to investor mood explains these effects and implies a new set of seasonal patterns. We find that relative performance across stocks during positive mood periods (e.g., January, Friday, the best-return month realized in the year, the best-return day realized in a week, pre-holiday) tends to persist in future periods with congruent mood (e.g., January, Friday, pre-holiday), and to reverse in periods with non-congruent mood (e.g., October, Monday, post-holiday). Stocks with higher mood betas estimated during seasonal windows of strong moods (e.g., January\/October, Monday\/Friday, or pre-holidays) earn higher expected returns during future positive mood seasons but lower expected returns during future negative mood seasons.<\/p>\n

\t <\/p>","protected":false},"excerpt":{"rendered":"

\n\tTwo new strategies have been added:<\/p>\n

\t #331 – Timing Betting-Against-Beta (BAB) Anomaly
\n\t#332 – Contrast Effect During the Earnings Announcements<\/strong><\/p>\n

\n\tTwo new related research paper have been included into existing strategy reviews. And two additional related research papers have been included into existing free strategy reviews during last 2 weeks.<\/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-722","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/722","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=722"}],"version-history":[{"count":0,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/722\/revisions"}],"wp:attachment":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/media?parent=722"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/categories?post=722"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/tags?post=722"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}