This paper defines systematic value investing as an empirical optimization problem. Predictive modeling is introduced as a systematic value investing methodology with dynamic and optimization features. A predictive modeling process is demonstrated using financial metrics from Gray & Carlisle and...

We create a market-wide measure of dispersion in options investors' expectations by aggregating across all stocks the dispersion in trading volume across moneynesses (DISP). DISP exhibits strong negative predictive power for future market returns and its information content is not subsumed by...

In this paper, we forecast industry returns out-of-sample using the cross-section of book-to-market ratios and investigate whether investors can exploit this predictability in portfolio allocation. Cash-flow and return forecasting regressions show that cross-industry book-to-market ratios...

Stock selection models often use analysts' expectations, momentum, and fundamental data. We found support for composite modeling using these sources of data for global stocks during 1997-2011. We found additional evidence to support the use of SunGard APT and Axioma multi-factor models for...

What predicts returns on assets with "hard-to-value" fundamentals, such as Bitcoin and stocks in new industries? We propose an equilibrium model that shows how rational learning enables return predictability through technical analysis. We document that ratios of prices to their moving averages...

We introduce a new measure of stock misevaluation, 𝑄, which is consistent with the Gordon growth model for firm valuation. In our empirical application, we use 𝑄 to relate analyst forecasts to stock returns and measure the profitability of investment strategies that rely on information in...

We compare the stock return forecasting performance of alternative payout yields. The net payout yield produces more accurate forecasts relative to alternatives, including the traditional dividend yield. This remains true even after excluding several years during the Great Depression when...

Portfolio optimization focuses on risk and return prediction, yet implementation costs critically matter. Predicting trading costs is challenging because costs depend on trade size and trader identity, thus impeding a generic solution. We focus on a component of trading costs that applies...

The purpose of this paper is to make a quantitative and qualitative critical analyse regarding the three important aspects of stock market evolution. First, the forecasting problems are presented and analyse in order to establish the main problems and the potential solutions. Second, the...

Risk forecasting is crucial for informed investment decision-making. Moreover, the salience of investment risk increases during economically uncertain times. In this paper, we study how sell-side analysts form expectations of firm risk, under different macroeconomic conditions (low versus high...