In previous articles, we discussed the ideas behind portfolio replication with market factors. However, overall robustness of the results suffers significantly if the model portfolio or trading strategy we attempt to synthetize is driven by a market-timing model. We do not know the rules driving the underlying strategy we could apply ourselves beforehand. Furthermore, there is no simple mechanism of market-timing rule detection we could potentially utilize in our regression model. Hypothetically, we could include a variety of market-timing strategies into the factor universe. But since there are countless market-timing methods, covering everything is simply unrealistic. Particularly in context of historic factor universe construction. In an attempt to capture the effects of underlying timing rules, we came up with a simple approach to address this problem to a somewhat satisfactory extent.

Approximately 18 months ago, when we started Quantpedia Pro service, we promised to systematically expand its analytical capabilities by adding new tools and reports to it. We kept this promise and enlarged Quantpedia Pro to over 30 reports with hundreds of tables and charts. Factor regression analysis, risk scenarios, seasonality analysis, alternative weighting schemes, risk parity, CPPI, volatility targeting, correlation analysis, Markowitz portfolio optimization, clustering, market phases analysis, ETF replication etc. offer insight into the matters of portfolio construction or risk management. But our disciplined tempo also means that some users can become lost in the number of tools Quantpedia Pro offers. Therefore, we would like to introduce to you our new Quantpedia Answers section, which contains practical examples of how to use the growing capabilities of Quantpedia Pro reporting.

Post–earnings-announcement drift (abbr. PEAD) is a well-researched phenomenon that describes the tendency for a stock’s cumulative abnormal returns to drift in the direction of an earnings surprise for some time (several weeks or even several months) following an earnings announcement. There have been many explanations for the existence of this phenomenon. One of the most widely accepted explanations for the effect is that investors under-react to the earnings announcements. Although we already addressed such an effect in some of our previous articles and strategies, we now present a handy method of improving the PEAD by using linguistic analysis of earnings call transcripts.

Have you ever wondered if your trading asset trends or mean-reverts? Everyone involved in trading or investments daily solves the task of – What trading strategy should I apply to my assets to generate profits? As always, we at Quantpedia will try to help you a bit with this never-ending task with our new tool/report, which will be unveiled next week for all Quantpedia Pro subscribers. The following article serves as an introduction to the methodology we will use to find new trading edges for you automatically.