Edited by Shankar Ganesan
Chapter 2: Time-Series Models of Pricing the Impact of Marketing on Firm Value
Xueming Luo, Koen H. Pauwels and Dominique M. Hanssens INTRODUCTION Stock prices fluctuate as a result of continuous trading among investors who have different expectations about the firm’s future earnings. Thus they represent consensus forecasts of the financial value of the firm. As new value-relevant information about the firm or its environment arrives, these forecasts are updated, either immediately or more gradually over time, and either fully or partially. The extent to which such new information is reflected in stock price adjustments reflects the degree of efficiency in the market. Time-series methods are well suited to analyze stock price data and quantify their sensitivity to such new information. In particular, methods that focus on equal interval measurements, such as daily, weekly or minuteby-minute data, are adept at sorting out the magnitude of reaction as well as its distribution over time, that is, the time lags. Time-series methods can be employed without having to resort to strong a priori assumptions about investor behavior such as full market efficiency. Thus they can be used to test such assumptions and, where needed, modify them to more accurate representations of investor behavior. Furthermore, time-series methods allow for inferences around the mean and the variance of stock prices, and as such they connect well to the risk/return paradigm in finance. Finally, time-series techniques can be employed with single equations as well as systems of equations. Such systems allow for the possible feedforward and feedback loops between investor behavior and managerial behavior. In conclusion, time-series methods...
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