Editor’s note: This was originally published at Social Market Analytics and is reprinted here with permission. Social Market Analytics (SMA) aggregates the intentions of investors as expressed on the StockTwits platform.   SMA creates proprietary S-Factor metrics that quantitatively describe the current conversation relative to historical benchmarks.  This data provides strong predictors of future price movement.  This blog will focus on the deterministic nature of the StockTwits data set when aggregated into SMA S-Factors.    StockTwits is a community for active traders to share ideas enabling you to tap into the pulse of the market:  http://stocktwits.com/ The charts and tables below illustrate the subsequent open to close return of stocks that are being spoken about abnormally positively or abnormally negatively on StockTwits twenty minutes prior to market open.  Sharpe and Sortino ratios for the theoretical portfolios are included as well.  The SMA S-Score looks at the current conversation relative to historical benchmarks and creates effectively

Editor’s note: this was originally published at Alpha Architect and is reprinted with permission. We’ve discussed return seasonalities in the past, especially as they pertain to our approach to momentum. Turns out seasonality effects aren’t confined to momentum — they are literally everywhere and they are incredibly strong. This paper will blow your mind once you let the results settle in a bit. Source paper Slides Turns out stock returns are lumpy across the calendar. Stocks don’t earn “average” returns each month, they earn a lot of return in some months and little to no returns in other months…and this pattern is predictable, persistent, and powerful. Here is an image from the authors the explains the basic idea: Abstract: A strategy that selects stocks based on their historical same-calendar-month returns earns an average return of 13% per year. We document similar return seasonalities in anomalies, commodities, international stock market indices, and at the daily frequency. The seasonalities overwhelm unconditional differences in expected

How would you describe your job? I help clients make better decisions to fuel their retirement goals. What led you to look at the particular markets you specialize in? When I was in my early twenties I was captivated by the work of William O’Neil so naturally I gravitated towards US equities. As I learned more about correlations and intermarket analysis, I became interested in commodities and fixed income as well. Do you look at any fundamental or economic inputs to develop your opinions? I consider myself a pure technician, so I am comfortable forming opinions without the aid of fundamentals. Oftentimes, I will cross-reference my viewpoints with those who specialize in fundamentals to gain perspective.  Using an approach that incorporates currencies, commodities, fixed income, and equities is paramount in today’s macro environment. I consider interest rates and central bank policy to be the starting point for any type of market analysis. What advice would you