Sales Forecasting with Financial Indicators and Experts' Input

• 成果类型: Article
• 署名作者: Osadchiy, Nikolay; Gaur, Vishal; Seshadri, Sridhar
• 署名单位: Emory University; Cornell University; University of Texas System; University of Texas Austin
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12022
• 发表日期: 2013
• 页码: 1056-1076
• 关键词: Retail operations; sales forecasting; Operational hedging; martingale modulated forecast evolution; OPERATIONS; finance interface

摘要

We present a method for forecasting sales using financial market information and test this method on annual data for US public retailers. Our method is motivated by the permanent income hypothesis in economics, which states that the amount of consumer spending and the mix of spending between discretionary and necessity items depend on the returns achieved on equity portfolios held by consumers. Taking as input forecasts from other sources, such as equity analysts or time-series models, we construct a market-based forecast by augmenting the input forecast with one additional variable, lagged return on an aggregate financial market index. For this, we develop and estimate a martingale model of joint evolution of sales forecasts and the market index. We show that the market-based forecast achieves an average 15% reduction in mean absolute percentage error compared with forecasts given by equity analysts at the same time instant on out-of-sample data. We extensively analyze the performance improvement using alternative model specifications and statistics. We also show that equity analysts do not incorporate lagged financial market returns in their forecasts. Our model yields correlation coefficients between retail sales and market returns for all firms in the data set. Besides forecasting, these results can be applied in risk management and hedging.