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In this paper, we implement a methodology to identify and measure premia in the pricing of forward foreign exchange that involves application of signal-extraction techniques from the engineering literature. Diagnostic tests indicate that these methods are quite successful in capturing the essence of the time-series properties of premium terms. The estimated premium models indicate that premia show a certain degree of persistence over time and that more than half the variance in the forecast error that results from the use of current forward rates as predictors of future spot rates is accounted for by variation in premium terms. The methodology can be applied straightforwardly to the measurement of unobservables in other financial markets. THERE EXISTS A GROWING body of empirical research on premia inthe pricing of forward foreign exchange. Conditional on the hypothesis that the foreign exchange market is efficient or rational, the existence of time-varying premia has been documented in the literature by Fama [6], Hansen and Hodrick [10, 11], Hodrick and Srivastava [15, 16], Hsieh [171, and Korajczyk [20]. Frankel [9] fails to identify such premia, and Domowitz and Hakkio [51 obtain different results for different currencies. Recent methodologies to measure time-varying premia are usually centered around regression equations. Fama [6] applied regression analysis to estimate empirically the degree of variation of the premium over time and to investigate the degree of covariation of the premium with the expected future spot exchange rate. His findings indicate that most of the variation in forward rates is due to variation in premia and that the premium and expected future spot rate components of forward rates are negatively correlated. Hodrick and Srivastava [161 confirmed Fama's results on the basis of Generalized Method of Moments (GMM) estimation and other techniques. Hansen and Hodrick [11] relied on the first-order conditions of optimality for a rational representative investor (and some auxiliary assumptions) to construct a single-beta latent variable model to * London Business School. This paper builds on Chapter 6 of the author's doctoral dissertation at the Graduate School of Business, University of Chicago. He is very grateful to the members of his dissertation committee-Michael Mussa (Chairman),

SUMMARYWe apply extreme value analysis to US sectoral stock indices in order to assess whether tail risk measures like value-at-risk and extremal linkages were significantly altered by 9/11. We test whether semi-parametric quantile estimates of 'downside risk' and 'upward potential' have increased after 9/11. The same methodology allows one to estimate probabilities of joint booms and busts for pairs of sectoral indices or for a sectoral index and a market portfolio. The latter probabilities measure the sectoral response to macro shocks during periods of financial stress (so-called 'tail-ˇs'). Taking 9/11 as the sample midpoint we find that tail-ˇs often increase in a statistically and economically significant way. This might be due to perceived risk of new terrorist attacks. Copyright  2008 John Wiley & Sons, Ltd. Received 13 May 2005; Revised 1 September 20061. INTRODUCTION Does US common stock exhibit a higher propensity toward sharp price declines since the dreadful 9/11 events? Do sharp drops in stock prices tend to co-move more frequently since 9/11? Most financial practitioners would probably give a positive answer to both questions. Answering these two questions is crucial from a regulatory (potential 9/11 impact on US systemic stability) and risk management point of view (potential 9/11 impact on the scope for risk diversification during times of market stress). The more stocks or sectoral indices jointly drop in value, the more in danger are even large investment banks and institutional investors that hold widely diversified trading portfolios. The number of stocks or sectors affected by a crisis situation may also determine the severity of any real effects that might follow.The question arises why one would expect a lasting impact of 9/11 in the financial markets. Empirical evidence suggests that US common equity rapidly recovered in the aftermath of 9/11 (see, for example, Chen and Siems, 2004). However, 9/11, the Madrid and London bombings, as well as the Al-Qaeda threats toward the US-led 'War on Terror' coalition created the perception of a globalization of 'terrorism risk' (see de Mey, 2003;Brown et al., 2004). This may well have increased systematic risk in the equity markets. A number of event studies investigated the 9/11 impact on a few sectors like airlines (Drakos, 2004) and the (re)insurance business (Kunreuther and Michel-Kerjan, 2004). This paper extends the scant 9/11 finance literature with a volatility and dependence analysis of extreme events for different indices of US common stock on a sectoral level. More specifically, we try to assess whether 9/11 has a statistically and economically significant impact on our volatility and co-movement measures. We opt for a sectoral focus because some sectors are by nature more vulnerable to terrorist attacks than others (e.g., banking, insurance, transportation or public utilities). The study of asset return linkages during crisis periods is not new, although most previous studies focused on cross-country linkages between asset returns. The bu...

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