JOHN AMMER, U.S. Federal Reserve Board of Governors
Email: john.ammer@frb.gov
CLARA VEGA, Board of Governors of the Federal Reserve System
Email: Clara.Vega@frb.gov
JON WONGSWAN, Barclays Global Investors
Email: Jon.Wongswan@barclaysglobal.com

This paper analyzes the impact of U.S. monetary policy announcement surprises on U.S. and foreign firm-level equity prices. We find that U.S. monetary policy has important influences on foreign equity prices on average, but with considerable variation across firms. We have found that this differing response reflects a range of factors, including the extent of a foreign firm's exposure to U.S. demand, its dependence on external financing, the behavior of interest rates in its home country, and its sensitivity to portfolio adjustment by U.S. investors. The cross-firm variation in the response is correlated with the firm's CAPM beta; but it cannot fully explain this variation. More generally, we see these results as shedding some additional light on the nature and extent of the monetary and financial linkages between the United States and the rest of the world. In particular, since we are able to explain differences across foreign firms' responses through established theories of monetary transmission, our results are consistent with the surprisingly large average foreign response to U.S. rates reflecting fundamentals, rather than an across-the-board behavioral over-reaction.

THIJS D. MARKWAT, Econometric Institute (EI) - Erasmus Research Institute of Management (ERIM)
Email: markwat@few.eur.nl
ERIK KOLE, Erasmus University Rotterdam (EUR) - Econometric Institute - Erasmus School of Economics, Erasmus Research Institute of Management (ERIM) - Joint Research Institute of Rotterdam School of Management (RSM) and Erasmus School of Economics(ESE), EUR
Email: kole@few.eur.nl
DICK J. C. VAN DIJK, Econometric Institute - Erasmus University Rotterdam
Email: DJVANDIJK@FEW.EUR.NL

This paper shows that stock market contagion operates through a domino effect, where small crashes evolve into more severe crashes. Using a novel unifying framework we model the occurrence of local, regional and global crashes in terms of past occurrences of these different crashes and financial variables. We find convincing evidence that global crashes do not occur abruptly but are preceded by local and regional crashes. Additionally, interest rates, bond returns and volatility affect the probabilities of different crash types, indicating interdependence. We show that in forecasting global crashes our model outperforms a binomial model for global crashes only.

BRANDES INSTITUTE, Brandes Investment Partners
Email: brandesinstitute@brandes.com

In previous research, Global Small-Cap Stocks: Reexamined and Redefined, the Brandes Institute found divergent construction methodologies among global small-cap index providers and introduced a custom series of country and regional small-cap universes to explore detailed historical fundamental data. In the second phase of this research, Global Small-Cap Stocks: A Life Cycle Perspective, we use life cycle analysis to sort companies into different phases of development and challenge the notion that international small caps are similar to domestic small caps. In this research, we make a number of interesting discoveries on why international small caps are structurally different from domestic small caps, or even international large-cap stocks.

MITYA BOYARCHENKO, University of Chicago - Department of Mathematics
Email: mitya@math.uchicago.edu
SERGEI LEVENDORSKI, University of Texas at Austin - Department of Economics
Email: leven@eco.utexas.edu

The fast Fourier transform (FFT) technique is now a standard tool for the numerical calculation of prices of derivative securities. Unfortunately, in many important situations, such as the pricing of contingent claims of European type near expiry, and the pricing of barrier options close to the barrier, the standard implementation of this technique leads to serious systematic errors. We propose a new, fast and efficient, variant of the FFT technique, which is free of these problems, and is as easy to implement as the most common version of FFT. As an example, we show how our method leads to a pricing algorithm for down-and-out barrier put options that is the most efficient one to date, both in terms of the speed and in terms of the accuracy of the computations.

JERZY REMBEZA, affiliation not provided to SSRN
GRZEGORZ PRZEKOTA, Warsaw Agricultural University (SGGW)
Email: grzegorzprzekota@wp.pl
ANNA SZCZEPANSKA-PRZEKOTA, affiliation not provided to SSRN

This paper investigates the causal relationship between stock and volume on the Warsaw Stock Exchange. The Granger causality test and VAR model have been used. The causality test reveals that there is unidirectional causality running from prices to volume. However, impulse response functions and variance decomposition show a weak relation between price and volume. The results are consistent with the efficient market hypothesis.

MONICA BANYI, McIntire School of Commerce
Email: monica.banyi@virginia.edu
EDWARD ALEXANDER DYL, University of Arizona
Email: edyl@eller.arizona.edu
KATHLEEN M. KAHLE, University of Arizona - Department of Finance
Email: kkahle@eller.arizona.edu

We examine the accuracy of various estimates of firms' repurchases of common stock used in earlier studies, and find high error rates in the most commonly used estimators. We also find that the procedure used to estimate open market share repurchases can significantly impact results. The Compustat-based measure, which is the most accurate, deviates from the actual number of shares repurchased by more than 30% in about 16% of the cases. We conclude that many studies should be revisited now that the SEC mandates disclosure of precise information about share repurchases in Forms 10-Q and 10-K.

ANNASTIINA SILVENNOINEN, University of Technology, Sydney
Email: annastiina.silvennoinen@uts.edu.au
TIMO TERASVIRTA, affiliation not provided to SSRN
Email: tterasvirta@creates.au.dk

In this paper we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new Double Smooth Transition Conditional Correlation GARCH model extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinen and Terasvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. The model is applied to a selection of world stock indices, and it is found that time is an important factor affecting correlations between them.

CHANGLI HE, affiliation not provided to SSRN
Email: chh@du.se
ANNASTIINA SILVENNOINEN, University of Technology, Sydney
Email: annastiina.silvennoinen@uts.edu.au
TIMO TERASVIRTA, affiliation not provided to SSRN
Email: tterasvirta@creates.au.dk

In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. herefore it is of importance to know what properties a model should possess if it is to accommodate unconditional skewness. We consider modelling the unconditional mean and variance using models that respond nonlinearly or asymmetrically to shocks. We investigate the implications of these models on the third-moment structure of the marginal distribution as well as conditions under which the unconditional distribution exhibits skewness and nonzero third-order autocovariance structure. In this respect, an asymmetric or nonlinear specification of the conditional mean is found to be of greater importance than the properties of the conditional variance. Several examples are discussed and, whenever possible, explicit analytical expressions provided for all third-order moments and cross-moments. Finally, we introduce a new tool, the shock impact curve, for investigating the impact of shocks on the conditional mean squared error of return series.