Handbook of Marketing and Finance
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Handbook of Marketing and Finance

Edited by Shankar Ganesan

Many organizations have found that the value to business operations and financial performance created by the marketing function has become very important. The need to demonstrate this importance has also become clear. Top managers are constantly challenging marketers to document marketing’s contribution to the bottom-line and link marketing investments and assets to metrics that matter to them. This Handbook relates marketing actions to various types of risk and return metrics that are typically used in the domain of finance. It provides current knowledge of this marketing-finance interface in a single, authoritative volume and brings together new cutting-edge research by established marketing scholars on a range of topics in the area.
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Chapter 2: Time-Series Models of Pricing the Impact of Marketing on Firm Value

Xueming Luo, Koen H. Pauwels and Dominique M. Hanssens


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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