Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data

Czech Journal of Economics and Finance (Finance a uver) 01/2009; 59(4):334-359.
Source: RePEc

ABSTRACT This paper investigates the behavior of the EUR/CZK, EUR/HUF and EUR/PLN spot exchange rates in the period 2002–2008, using 5-minute intraday data. The authors find that daily returns on the corresponding exchange rates scaled by model-free estimates of daily realized volatility are approximately normally distributed and independent over time. On the other hand, daily realized variances exhibit substantial positive skewness and very persistent, long-memory type of dynamics. The authors estimate a simple three-equation model for daily returns, realized variance and the time-varying volatility of realized variance. The model captures all salient features of the data very well and can be successfully employed for constructing point, as well as density forecasts for future volatility. The authors also discuss some issues associated with measuring volatility from the noisy high-frequency data and employ a simple correction that accounts for the distortions present in our dataset.

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    • "By extending the model in this manner, we are able to capture the volatility-of-volatility effect; i.e., an empirical observation that the volatility of volatility tends to increase (decrease) whenever volatility itself increases (decreases). While the idea is not new (Corsi, Mittnik, Pigorsch, & Pigorsch, 2008), our motivation for generalizing the model with an MGARCH structure is driven by recent findings that a univariate HAR-GARCH model fits very well the realized variances of the Central European exchange rates (Bubak & Zikes, 2009 . ) To model the dynamics of the conditional variance of the innovation process we employ the DCC model of (Engle R. F., 2002). "
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    ABSTRACT: This paper studies the dynamics of volatility transmission between Central European (CE) currencies and the EUR/USD foreign exchange using model-free estimates of daily exchange rate volatility based on intraday data. We formulate a flexible yet parsimonious parametric model in which the daily realized volatility of a given exchange rate depends both on its own lags as well as on the lagged realized volatilities of the other exchange rates. We find evidence of statistically significant intra-regional volatility spillovers among the CE foreign exchange markets. With the exception of the Czech and, prior to the recent turbulent economic events, Polish currencies, we find no significant spillovers running from the EUR/USD to the CE foreign exchange markets. To measure the overall magnitude and evolution of volatility transmission over time, we construct a dynamic version of the Diebold-Yilmaz volatility spillover index and show that volatility spillovers tend to increase in periods characterized by market uncertainty.
    Journal of Banking & Finance 05/2010; 35(11):2829-2841. DOI:10.1016/j.jbankfin.2011.03.012 · 1.29 Impact Factor
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    ABSTRACT: Financial risk modeling, measuring, and managing are an inherent part of management in financial institutions. It is also an important step within the setting of optimal level of capital eligible to cover risk exposures. A significant portion of capital is usually assigned to cover the risk of unexpected changes in FX rates. FX rates (the returns) commonly exhibit significant skewness and relatively huge kurtosis. In this paper, we apply subordinated Lévy models coupled together by ordinary elliptical copula functions in order to estimate the FX rate risk of normalized portfolio. Selected models are applied in order to estimate the risk ex-post, as well as ex-ante. The models are also compared to the more standard assumption of the joint normal distribution. Although the results for both types of modeling are quite different and Lévy measure is ignored, suggested models deliver us improved risk estimation.
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