1 edition of Exchange rate returns standardized by realized volatility are (nearly) Gaussian found in the catalog.
Exchange rate returns standardized by realized volatility are (nearly) Gaussian
|Statement||Torben G. Andersen ... [et al.].|
|Series||NBER working paper series -- no. 7488, Working paper series (National Bureau of Economic Research) -- working paper no. 7488.|
|Contributions||Andersen, Torben G., Bollerslev, Tim, 1958-, Diebold, Francis X., 1959-, Labys, Paul., National Bureau of Economic Research.|
|The Physical Object|
|Pagination||18,  p. :|
|Number of Pages||18|
A IMF study (Exchange Rate Volatility and Trade Flows - Some New Evidence, by Peter Clark, Natalia Tamirisa, and Shang-Jin Wei, May ) notes that on average, during the s, 80s and 90s the volatility of fixed exchange rates was approximately the same as that of floating rates. There are two reasons this can occur. Judging from the volatility signature plots, the critical sampling frequencies for estimating the realized volatility of the returns to the year Treasury securities and, even more so, of the returns to the dollar/euro pair are much higher, and the associated critical sampling interval lengths are therefore shorter, than those reported in the.
Volatility Risk Premia and Exchange Rate Predictabilityy Pasquale DELLA CORTE Tarun RAMADORAI Lucio SARNO March premia for exchange rate returns. The volatility risk premium is the di⁄erence between realized volatility and a model-free measure of expected volatility that is derived from exchange rate returns over the to TY - JOUR. T1 - The distribution of realized exchange rate volatility. AU - Andersen, Torben G. AU - Bollerslev, Tim. AU - Diebold, Francis X. AU - Labys, PaulCited by:
sources of exchange rate volatility in South Africa1. However, these studies use cross-country data and –nd aggregate results which do not isolate coun-try speci–c e⁄ects. Besides, Hau () states that the theoretical linkage between openness and File Size: KB. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX) detects market volatility and measures investor risk, by calculating the implied volatility (IV) in the prices of a basket of put Author: Hans Wagner.
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Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian * by Torben G. Andersen a, Tim Bollerslev b, Francis X. Diebold c and Paul Labys d September This version: Octo _____ * This work was supported by the National Science Foundation.
We are grateful to Olsen and. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," New York University, Leonard N. Stern School Finance Department Working Paper SeiresNew York University, Leonard N.
Stern School of G. Andersen & Tim Bollerslev &. Downloadable. It is well known that high-frequency asset returns are fat-tailed relative to the Gaussian distribution tails are typically reduced but not eliminated when returns are standardized by volatilities estimated from popular models such as GARCH.
We consider two major dollar exchange rates, and we show that returns standardized instead by the realized volatilities of. Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian* Torben G.
Andersen Northwestern University, U.S.A. Tim Bollerslev Duke University and N BER, U.S.A. Francis X. Diebold University of Pennsylvania and N BER, U.S.A. Paul Labys University of Pennsylvania, U.S.A. We consider two major dollar exchange rates, and we show that returns standardized instead by the realized volatilities of Andersen, Bollerslev, Diebold.
Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian Torben G. Andersen, Tim Bollerslev, Francis X. Diebold, Paul Labys.
NBER Working Paper No. Issued in January NBER Program(s):Asset Pricing Program. Exchange rate returns standardized by realized volatility are (nearly) Gaussian. Cambridge, MA: National Bureau of Economic Research, © (OCoLC) Material Type: Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors: Torben G Andersen; National Bureau of Economic Research.
It is well known that high-frequency asset returns are fat-tailed relative to the Gaussian distribution, and that the fat tails are typically reduced but not eliminated when returns are standardized by volatilities estimated from popular ARCH and stochastic volatility models.
We consider two major dollar exchange rates, and we show that returns standardized instead by. Get this from a library. Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian.
[Paul Labys; Torben G Andersen; Tim Bollerslev; Francis X Diebold; National Bureau of Economic Research;] -- It is well known that high-frequency asset returns are fat-tailed relative to the Gaussian distribution tails are typically reduced but not eliminated when returns are.
Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility Article in Journal of Empirical Finance 15(4) September. 2 This approach is exemplified by the highly influential “RiskMetrics” of J.P. Morgan (). 3 Earlier work by Comte and Renault (), within the context of estimation of a long-memory stochastic volatility model, helped to elevate the discussion of realized and integrated volatility to a more rigorous theoretical level.
4 The direct modeling of observable volatility proxies was File Size: KB. This paper examines the relation between dollar-real exchange rate volatility implied in option prices and subsequent realized volatility.
It investigates whether implied volatilities contain information about volatility over the remaining life of the option which is not present in past returns.
Using GMM estimation consistentFile Size: KB. Andersen, Bollerslev, Diebold, and Labys: w Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian: Aghion, Bacchetta, Rancière, and Rogoff: w Exchange Rate Volatility and Productivity Growth: The Role of Financial Development: Obstfeld and Rogoff: w Exchange Rate Dynamics Redux: Schwert: w Why Does Stock Cited by: Francis X.
Diebold (born Novem ) is an American economist known for his work in predictive econometric modeling, financial econometrics, and macroeconometrics. He earned both his B.S.
and Ph.D. degrees at the University of Pennsylvania ("Penn"), where his doctoral committee included Marc Nerlove, Lawrence Klein, and Peter has spent most of his Alma mater: University of Pennsylvania (B.S., Ph.D.). Abstract. Realized volatility is a fully nonparametric approach to ex post measurement of the actual realized return variation over a specific trading period.
It encompasses specific empirical procedures and an associated continuous-record asymptotic theory for arbitrage-free jump diffusions. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian" (with Torben G.
Andersen, Francis X. Diebold, and Paul Labys). 1 A new approach to Exchange Rate Volatility Forecasting Sanja Dudukovic, Ph.D Franklin College Switzerland Email: [email protected] Abstract: The aim of this paper is to elucidate a need for the optimization of the two most used methods of exchange rate volatility forecasting: GARCH method based on daily returns and ARMA realized volatility.
This paper examines the effect of exchange rate volatility on trade, prepared in response to a request from the Director General of the World Trade Organization to the IMF.
The IMF produced a study in for the General Agreement on Tariffs and Trade on this subject. Since then, there have been major developments in the world economy, some perhaps having exacerbated.
Anderson, T.G., Bollerslev, T.: Exchange rate returns standardized by realized volatility are nearly Gaussian. Multinational Finance Journal 4, – () CrossRef Google Scholar : Xinwu Zhang, Yan Wang, Handong Li. Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk.
A quantile forecast is the product of two factors: the model used to forecast volatility, and the method of computing quantiles from the volatility forecasts. In this paper we calculate and evaluate quantile forecasts of the daily exchange rate returns of five currencies.
The Distribution of Exchange Rate Volatility * Torben G. Andersen a, Tim Bollerslev b, Francis X. Diebold c and Paul Labys d November This Version: November 2, Abstract Using high-frequency data on Deutschemark and Yen returns against the dollar, we construct.Alternatively, if the market risk premium is an increasing function of volatility, large negative returns increase the future volatility by more than positive returns due to a volatility feedback effect (Campbell and Hentschel, ).
We now reevaluate the underlying empirical evidence on the basis of our realized volatility by: We have shown that movements in the market's sensitivity to information, jointly with movements in the rate of information arrival, can, to a very large degree, explain the long-run dynamics of realized exchange rate volatility.