Comparing the Predictive Power of Price-to-Earnings Ratio and Customer Satisfaction Index on Firm Performance

Abstract

This paper demonstrates that, based on the Root Mean Square Error (RMSE) criteria, the Price-to-Earnings (P/E) ratio serves as a better predictor of both financial and market performance of firms compared to the Customer Satisfaction index (CS). This conclusion was drawn by analyzing a set of five financial and seven market indicators, which we used as proxies for evaluating financial and market performance. The sample for this study comprised eighty-six companies, and the indicators considered included: Book Value, Dividend Yield, Gross Profit Margin, Price-to-Cash Flows, Price-to-Earnings, Price-to-Sales, Annual Return, Return on Assets (ROA), Return on Equity (ROE), Return on Investment (ROI), Volatility, and Tobin’s Q. The comparison between P/E ratio and Customer Satisfaction index was conducted with the goal of identifying which metric more accurately reflects a company's financial health and market standing. The superior performance of the P/E ratio, as measured by the RMSE, suggests that traditional financial metrics may offer more reliable insight into firm performance than non-financial measures like customer satisfaction. However, further research may be needed to explore the contexts in which customer satisfaction metrics could play a more significant role in predicting long-term performance. However, the Customer Satisfaction index (CS) clearly outperforms our five benchmarks (Tobin’s Q, Price-to-Cash Flows, Price-to-Earnings, Volatility, or the indicator itself) when it comes to forecasting Tobin’s Q, Volatility, Return on Equity (ROE), and Return on Investment (ROI). Notably, in periods of heightened market volatility, such as during the financial crisis of 2008, CS proved to be a more stable and reliable predictor of Volatility and ROE than using those indicators directly (i.e., using Volatility to predict Volatility, or ROE to predict ROE). This suggests that, while financial ratios like the P/E ratio may generally be strong predictors of financial performance, non-financial metrics such as customer satisfaction offer valuable insights, particularly in turbulent market conditions. CS appears to capture underlying factors that traditional financial indicators may overlook, making it a more consistent measure during times of uncertainty, when financial and market performance metrics tend to be more erratic. This highlights the importance of incorporating both financial and non-financial indicators to achieve a more comprehensive view of firm performance, especially in volatile markets.