Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature: many studies focus solely on measuring accuracy. Methods...

This paper proposes two dimension-reduction and forecasting quantile methods (i.e., the quantile group lasso and the quantile group SCAD models) to predict carbon futures returns and investigate the predictability of a comprehensive group of factors including market fundamental variables and...

We propose two types of equal predictive ability (EPA) tests with panels to compare the predictions made by two forecasters. The first type, namely S-statistics, focuses on the overall EPA hypothesis which states that the EPA holds on average over all panel units and over time. The second,...

This paper presents a computational approach for predicting the S&P CNX Nifty 50 Index. A neural network based model has been used in predicting the direction of the movement of the closing value for the next day of trading. The model presented in the paper also confirms that it can be used to...

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment...

This paper investigates how effectively value factors can forecast future returns for stocks in the S&P 500. Ranked portfolios and linear models are constructed from a set of quarterly value factor from 1998 to 2013. Portfolios are drawn from the quarterly S&P 500 stock universe to avoid...

Simulated test marketing (STM) is a quantitative technique used to forecast new product sales, one of the most validated tools in all marketing research. Forecasting awareness is an important stage in that process, one critical to STM performance. Awareness models incorporated into popular STMs...

The purpose of this research is to determine whether bankruptcy forecasting models are subject to industry and time specific effects. A sample of 15,848 firms was obtained from the Compustat and CRSP databases, spanning the time period 1950 to 2013, of which 396 were bankrupt. Using five models...

Two new predictive screening tools that are based on analyzing records of over one-million people who experienced homelessness have been placed in the public domain by the Economic Roundtable. The two groups targeted by these tools are low-wage workers who have just lost their jobs and youth...