Time variation in the correlation structure of exchange rates: high‐frequency analyses (original) (raw)
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Correlation patterns in foreign exchange markets
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The value of an asset in a financial market is given in terms of another asset known as numeraire. The dynamics of the value is non-stationary and hence, to quantify the relationships between different assets, one requires convenient measures such as the means and covariances of the respective log returns. Here, we develop transformation equations for these means and covariances when one changes the numeraire. The results are verified by a thorough empirical analysis capturing the dynamics of numerous assets in a foreign exchange market. We show that the partial correlations between pairs of assets are invariant under the change of the numeraire. This observable quantifies the relationship between two assets, while the influence of the rest is removed. As such the partial correlations uncover intriguing observations which may not be easily noticed in the ordinary correlation analysis.
Journal of Economics and Behavioral Studies
The time-variation in asset correlations have broad implications in asset pricing, portfolio management and hedging. Numerous studies in the literature have found that the change in correlations is mainly related to the magnitude of market movements, hence volatility. However, recent research finds that the size of markets fluctuations is not necessarily the primary driver for the time-variation in correlations, but that the effect of market movements is amplified in times of high financial distress, characterised by low liquidity. This paper seeks to investigate the effect of liquidity on time-varying correlations among different asset classes, namely stocks, corporate bonds and commodities. Our findings show that liquidity indeed has a significant effect on the time-variation in asset correlations, particularly in the case of how bond returns comove with other asset classes. We observe that higher liquidity risk is associated with lower correlation of bond returns with stocks as w...
The Distribution of Exchange Rate Volatility
New York University Leonard N Stern School Finance Department Working Paper Seires, 1999
Using high-frequency data on Deutschemark and Yen returns against the dollar, we construct model-free estimates of daily exchange rate volatility and correlation, covering an entire decade. In addition to being model-free, our estimates are also approximately free of measurement error under general conditions, which we delineate. Hence, for all practical purposes, we can treat the exchange rate volatilities and correlations as observed rather than latent. We do so, and we characterize their joint distribution, both unconditionally and conditionally. Noteworthy results include a simple normality-inducing volatility transformation, high contemporaneous correlation across volatilities, high correlation between correlation and volatilities, pronounced and highly persistent temporal variation in both volatilities and correlation, clear evidence of long-memory dynamics in both volatilities and correlation, and remarkably precise scaling laws under temporal aggregation.
Trading Volume, Illiquidity and Commonalities in FX Markets
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In a regime of oating FX rates and open economies, it is important to understand the way through which FX rates, volatility, and trading volume interrelate. To uncover this, we provide a simple theoretical framework to jointly explore these factors in a multi-currency environment. rough the use of a unique intraday data representative for the global FX market, the empirical analysis validates our theoretical predictions: (i) more disagreement increases FX trading volume, volatility, and illiquidity, (ii) stronger commonalities pertain to more e cient (arbitrage-free) currencies, and (iii) the Amihud (2002) measure, for which we provide a theoretical underpinning, is e ective in measuring FX illiquidity. Not only do these ndings support an integrated analysis of FX rate evolution and risk, but our work also o ers a straightforward method to measure FX illiquidity and commonality. For investors, these insights should increase the e ciency of trading and risk analysis. For policy makers, our work highlights the developments of FX global volume, volatility, and illiquidity across time and currencies, which can be important for the implementation of monetary policy and nancial stability.
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The Journal of Finance, 1993
The behavior of quote arrivals and bid-ask spreads is examined for continuously recorded deutsche mark-dollar exchange rate data over time, across locations, and by market participants. A pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns. Models for the conditional mean and variance of returns and bid-ask spreads indicate volatility clustering at high frequencies. The proposition that trading intensity has an independent effect on returns volatility is rejected, but holds for spread volatility. Conditional returns volatility is increasing in the size of the spread.
The Distribution of Realized Exchange Rate Volatility
Journal of the American Statistical Association, 2001
Using high-frequency data on Deutschemark and Yen returns against the dollar, we construct model-free estimates of daily exchange rate volatility and correlation, covering an entire decade. In addition to being model-free, our estimates are also approximately free of measurement error under general conditions, which we delineate. Hence, for all practical purposes, we can treat the exchange rate volatilities and correlations as observed rather than latent. We do so, and we characterize their joint distribution, both unconditionally and conditionally. Noteworthy results include a simple normality-inducing volatility transformation, high contemporaneous correlation across volatilities, high correlation between correlation and volatilities, pronounced and highly persistent temporal variation in both volatilities and correlation, clear evidence of long-memory dynamics in both volatilities and correlation, and remarkably precise scaling laws under temporal aggregation.
Muhasebe Bilim Dünyası Dergisi, 2017
Low liquidity (illiquidity) of a market is considered to have important asset pricing implications such that the higher the transaction costs the lower will be the asset prices and higher the rates of return. This is due to an illiquid asset offering higher rate of return to compensate the investors for having liquidity cost. According to John Maynard Keynes, an asset is defined to be liquid when "it is more certainly realizable at short notice without loss". The major aim of this paper is to analyze the relationship between exchange rate volatility and volatility of stock market illiquidity for Borsa Istanbul. In this way the effects of external shocks and the exchange rate volatility as the risk indicator for an open economy will be investigated. Volatility of stock market illiquidity and exchange rate volatility are estimated by applying different approaches available in the relevant literature. Afterwards the relationship between these two variables is analyzed by using Moon and Yu approach. Based on empirical findings some policy recommendations are made for market players.
Time-varying liquidity in foreign exchange
Journal of Monetary Economics, 2002
This paper addresses whether currency trades have greater price impact during periods of rapid public information flow. Central bankers often suggest that expectations are at times "ripe" for coordinated adjustment, and that periods of rapid information flow are such a time. We develop an optimizing model to account for the joint behavior of order flow and returns around announcements. Using transaction data made available by electronic trading, we estimate the price impact of trades in the DM/$ market precisely. We then test whether trades during periods with macroeconomic announcements have higher price impact. They do. We also test for dependence of liquidity on trading volume and return volatility (two other prominent state variables in the literature on liquidity variation). We do not find any evidence that liquidity depends on these variables. The findings provide policy-makers with guidance for the timing and magnitude intervention.