Academic journal article Atlantic Economic Journal

Foreign Exchange Risk, Equity Risk Factors and Economic Growth

Academic journal article Atlantic Economic Journal

Foreign Exchange Risk, Equity Risk Factors and Economic Growth

Article excerpt

Introduction

Since the second half of the last century, more and more academics across the world have been developing models that try to forecast economic growth with the use of variables from capital asset markets such as market prices, stock returns, bond yields, credit spreads and exchange rates (Fama 1981, 1990; Schwert 1990; Cheung and Cheung and Ng 1998; Lee 1992; Aylward and Glen 2000; Binswanger 2000a, 2000b, 2004; Wongbangpo and Sharma 2002; Mauro 2003; Chaudhuri and Smiles 2004; Henry et al. 2004; Mao and Wu 2007). The rationale of such a relationship is based on the forward-looking characteristic of capital markets. If asset prices discount all future expected cash flows and the market price of a stock equals the present value of all future income, then it should contain incremental information about future macroeconomic growth.

Another strand of the literature deals with the identification of the variables which proxy for common risk factors, the theoretical foundation of the relationship between potential risk factors and stock returns, and the modeling of the systematic risk using econometric methods. Although the Capital Asset Pricing Model (CAPM) (Sharpe 1964; Lintner 1965; Treynor 1965) has been the dominant model in the area for several years, empirical studies have documented patterns in average stock returns that cannot be explained by the CAPM, casting doubt on its validity and leading to the development of alternative asset pricing models such as the Fama and French (1992, 1993, 1995, 1996, 1998) three factor model (3FM) and its extension the Carhart (1997) four factor model (4FM).

In the present paper, we shift focus from the stock market variables per se and examine the information content of the equity risk factors, that have been proven capable of explaining the cross variation of stock returns in predicting future macroeconomic growth, effectively combining the above two areas of research. So far, in the literature, there are only two attempts that examine this relationship, the seminal work of Liew and Vassalou (2000) and the paper of Hanhard and Ansotegui (2008). Both papers focus only on the four traditional risk factors, ignoring all other sources of cross-sectional return variability that might contain information for future macroeconomic growth.

However, there are a number of studies in the financial economics literature providing evidence that foreign exchange risk is an important risk factor (Doukas et al. 1999, 2003; Vassalou 2000; Muller and Verschoor 2006; Kolari et al. 2008; Du 2009; Apergis et al. 2011) that captures a significant portion of the variability of stock returns and should not be ignored when predicting future stock returns. Thus, in the present paper we examine for the first time the information content of a new foreign exchange risk factor, along with the traditional risk factors, in predicting future macroeconomic growth. By incorporating the foreign exchange risk factor, we provide important insights into the relationship between risk factors and the business cycle.

The setting of the study is Germany, the leading economy in the Eurozone. Germany is the largest economy in the Eurozone in terms of gross domestic product (GDP) and the largest importer and exporter during all years of the research. The German stock exchange (Deutsche Borse) is the largest in terms of number of firms listed and total market capitalization for the whole time period of the research, according to the World Federation of Exchanges database (www.world-exchanges.org).

In addition to the inclusion of a new risk factor in the analysis, the importance and novelties of our work signify this study does not rely only on the stepwise regression analysis followed by Liew and Vassalou (2000) and Hanhard and Ansotegui (2008), but also performs a number of additional exhaustive statistical and econometric tests, thus, shedding more light on the relationship between equity risk factors and the business cycle and corroborating the empirical findings from the regression analysis. …

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