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ABSTRACT: This paper investigates the dynamic, short-run response of Euro exchange rate returns to the information surprise of global macroeconomic announcements. In addition, it advocates a new approach to modelling intraday exchange rate volatility to allow accurate characterisation of reactions. US macroeconomic news generates far more dramatic responses in EUR-USD returns and returns volatility than news on the macroeconomic performance of other countries. However, some Eurozone and German indicators are also important and UK announcements are important for the EUR-GBP rate. The reaction of exchange rate returns to news is very quick and occurs within the first 5Â min of the release with very little reaction in the 15Â min before and after. These findings show that exchange rates are strongly linked to fundamentals in the 5-min intervals immediately following the data release. Reactions to news are found to vary in magnitude over the sample, with the largest responses to news occurring in response to turning points in the cumulative flow of news.
Journal of International Financial Markets Institutions and Money 01/2010; 20(3):238-258.
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ABSTRACT: Previous research concerned with the investigation of intraday data has typically sought to model that data using techniques to control for intraday periodicity, has applied models of short-horizon and long-horizon dependencies, or has utilised intraday data in the construction of realised variance. Using Euro exchange rate data, we apply these different modelling strategies in forecasting daily volatility and calculating Value-at-Risk measures, benchmarked against a standard GARCH model for daily and raw intraday returns. Our results suggest that the use of intraday data provides improved daily volatility and VaR forecasts relative to daily data and daily realised volatility. Further, use of the raw intraday data, or intraday data subjected to a simple standardisation procedure, provides better forecasts and VaR measures than more complicated models for intraday periodicity. These results also hold in a multi-asset portfolio setting.
Journal of Multinational Financial Management 01/2008;
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ABSTRACT: This paper extends research concerned with the evaluation of alternative volatility forecasting methods under value at risk (VaR) modeling in the context of the Basle Committee adequacy criteria by broadening the class of generalized autoregressive conditional heteroscedasticity models, to include both asymmetric models and long memory models, in addition to the statistical methods commonly used in financial institutions. In the analysis of daily index data for eight emerging stock markets in the Asia - Pacific region, in addition to US and UK benchmark comparators, we find both asymmetric and long memory features to be important considerations in providing improved VaR estimates that minimize occasions when the minimum capital requirement identified by the VaR methodology would have fallen short of actual trading losses. More generally, our results illustrate the importance of adopting the stringent probability level stipulated in the regulatory framework, and of using fully out-of-sample forecast evaluation methods for the identification of forecasting models that mitigate the likelihood of inappropriately small VaRs and consequent regulatory intervention. Copyright (c) International Review of Finance Ltd. 2007.
International Review of Finance. 01/2007; 7(1-2):1-19.
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ABSTRACT: Purpose – In this paper weekly volatility forecasts are considered with applications to risk management; in particular hedge ratios and VaR calculations, with the aim of identifying the most appropriate model for risk management practice. Design/methodology/approach – The study considers a variety of models, including those typically employed within the risk management industry, such as averaging and smoothing techniques, as well as those favored in academic circles, such as the GARCH genre of models, and a more recent realized volatility approach which incorporates both the simplicity in construction favored by the finance industry and the flexibility and theoretical underpinnings recommended by academics. Findings – The results support the view that this realized volatility measure provides not only superior volatility forecasts per se, but also allows for improved hedge ratio and VaR calculations. Practical implications – The research findings carry practical implications for the conduct of risk management, namely that volatility forecasts are best obtained using the realized volatility approach. Originality/value – It is therefore proposed that a future direction for risk management practice may be to utilize such measures, while more generally it is hoped that such approaches may improve the cross-fertilization of ideas and practice between the academic and practitioner communities.
The Journal of Risk Finance 01/2007; 8(May):214-229.
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ABSTRACT: Recent research has suggested that intra-day volatility may possess a component structure, though views differ as to whether this is the consequence of heterogeneous information arrival or the actions of heterogeneous market agents. Estimation results for a HARCH conditional variance model which defines volatility components over differing time horizons provides confirmatory evidence of heterogeneous market components and support for the interpretation of such components as resulting from the presence of different trader types, in which context the impact of high-frequency speculation and noise-trading are particularly apparent.
Applied Financial Economics Letters 02/2006; 2(2):99-103.
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ABSTRACT: Recent research has suggested that intra-day volatility may possess a component structure, resulting either from the arrival of heterogeneous information or the actions of heterogeneous market agents. This paper reports direct evidence for the existence of such components in S&P500 index and DM|$ exchange rate data. Estimation of a FIGARCH model supports the contention that volatility dynamics result from multiple sources. Using a HARCH conditional variance model which defines volatility components over differing time horizons, confirmatory evidence of heterogeneous components is reported, in which context the impact of high-frequency speculation and noise-trading are particularly apparent. Copyright © 2006 John Wiley & Sons, Ltd.
International Journal of Finance & Economics. 02/2006; 11(2):115-121.
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ABSTRACT: The fully-revised data typically utilized in empirical research do not reflect the true information available to financial market participants at the time of their decision-making. This paper uses a new real-time macroeconomic dataset to appraise the relative importance of different vintages of data on economic variables as determinants of UK stock returns using the framework of Arbitrage Pricing Theory. We find that two factors influence expected stock returns, namely unanticipated inflation and economic uncertainty, but only when measured in real-time. Moreover, their pricing influence is only present during phases of the business cycle when their associated risks are at their most prevalent. Copyright Blackwell Publishers Ltd, 2006.
Journal of Business Finance & Accounting 01/2006; 33(1-2):263-283. · 0.69 Impact Factor
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ABSTRACT: Volatility plays a key role in asset and portfolio management and derivatives pricing. As such, accurate measures and good forecasts of volatility are crucial for the implementation and evaluation of asset and derivative pricing models in addition to trading and hedging strategies. However, whilst GARCH models are able to capture the observed clustering effect in asset price volatility in-sample, they appear to provide relatively poor out-of-sample forecasts. Recent research has suggested that this relative failure of GARCH models arises not from a failure of the model but a failure to specify correctly the 'true volatility' measure against which forecasting performance is measured. It is argued that the standard approach of using ex post daily squared returns as the measure of 'true volatility' includes a large noisy component. An alternative measure for 'true volatility' has therefore been suggested, based upon the cumulative squared returns from intra-day data. This paper implements that technique and reports that, in a dataset of 17 daily exchange rate series, the GARCH model outperforms smoothing and moving average techniques which have been previously identified as providing superior volatility forecasts. Copyright © 2004 John Wiley & Sons, Ltd.
Journal of Forecasting. 01/2004; 23(6):449-460.
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ABSTRACT: Recent research investigating the properties of high-frequency financial data has suggested that the stochastic nonlinearity widely present in such data may be characterized by heterogeneous components in conditional volatility, and nonlinear dependence of threshold autoregressive form due to market frictions. This article tests for the presence of such effects in intraday long gilt futures returns on the UK LIFFE market. Tests against the null of linearity indicate the significance of smooth transition autoregressive nonlinearities in such returns at the 5-min frequency, which entails a first-order autoregressive process with switching intercept. This nonlinear structure is robust to the presence of asymmetric and component structures in conditional variance, and consistent with the existence of heterogeneous traders facing different levels of transaction costs, noise trader risk, or capital constraints. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:1037–1057, 2002
Journal of Futures Markets 10/2002; 22(11):1037 - 1057. · 0.46 Impact Factor
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ABSTRACT: This paper reconsiders the time-series properties of inter-war pound-franc and pound-dollar exchange rate returns in the context of a smooth transition variant of the threshold autoregressive model. It is found that autoregressive structure in returns is largely confined to values in proximity with thresholds which are possibly associated with market intervention points or market sentiment. Under joint estimation in conjunction with GARCH models of time-varying conditional volatility, these models satisfactorily capture all non-linearity in the data, and in the case of pound-dollar returns provide out-of-sample forecasts superior to alternative linear and non-linear models previously considered in the literature. Copyright 2002 by Taylor and Francis Group
Applied Economics Letters. 01/2002; 9(6):359-64.
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ABSTRACT: This study reappraises the evidence for nonlinear dependence in the monthly black market exchange returns of the Polish zloty, 1955-1990. Predictive asymmetry is reported in conditional variance such that depreciatory shocks have a greater impact on subsequent volatility than appreciatory shocks, jointly with conditional mean nonlinearity of smooth transition between regimes which suggests a simple trading strategy capable of generating positive profit over the sample period. However, support is also found for a competing variance-in-mean model consistent with a time-varying risk premium that is able to rationalize the presence of unexploited profit opportunities, particularly over the latter half of the sample. Copyright 2001 by Taylor and Francis Group
Applied Financial Economics. 02/2001; 11(2):209-20.
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Journal of International Money and Finance 02/2001; 20(3):367-378. · 1.02 Impact Factor
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Resources Policy. 02/2001; 27(3):199-207.
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ABSTRACT: Tests against the null of linearity indicate smooth transition autoregressive nonlinearities in the conditional mean of intra-day UK long gilt futures returns at the five and fifteen minute frequencies. The higher frequency model entails a first-order autoregressive process with switching intercept. The lower frequency model is first-order autoregressive for returns near zero, but a near random-walk for large returns, consistent with the rapid extraction of profitable opportunities in excess of friction transaction cost boundaries. These nonlinearities are robust to the presence of asymmetric and component structures in conditional variance, but suggest that the potential for predictable regularities are confined to small price movements over fine time intervals.
08/1999;
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Applied Economics Letters. 02/1999; 6(4):209-14.
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Applied Economics Letters. 02/1998; 5(6):375-81.
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ABSTRACT: Reappraises the stylised facts of the contemporary UK business cycle and the robustness of associated sample moments to detrending under the Hodrick-Prescott (HP) filter and an unobserved components (UC) model based on the structural time series mode of Harvey and advocated in this context by Harvey and Jaeger. For the majority of series considered, findings broadly confirm the earlier HP-based results of Blackburn and Ravn, but important differences with previous results are reported for labour productivity, the real wage and the real interest rate. However, under neither detrending method are the anticipated cross-correlations between output and the pivotal variables in standard real business cycle (RBC) models (labour productivity, real wages, the real interest rate and nominal variables) simultaneously confirmed. Indeed, on balance, these results may be interpreted as more suggestive of an orthodox demand-led or policy-induced cycle.
Journal of Economic Studies. 01/1998; 25(October):370-391.
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ABSTRACT: Extant empirical research has reported nonlinear behavior within arbitrage relationships. In this article, the authors consider potential nonlinear dynamics within FTSE-100 index and index-futures. Such nonlinearity can be rationalized by the existence of transactions costs or through the interaction between informed and noise traders. They consider several empirical models designed to capture these alternative dynamics. Their empirical results provide evidence of a stationary basis term, and thus cointegration between index and index-futures, and the presence of nonlinear dynamics within that relationship. The results further suggest that noise traders typically engage in momentum trading and are more prone to this behavior type when the underlying market is rising. Fundamental, or arbitrage, traders are characterized by heterogeneity, such that there is slow movement between regimes of behavior. In particular, fundamental traders act more quickly in response to small deviations from equilibrium, but are reluctant to act quickly in response to larger mispricings that are exposed to greater noise trader price risk. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:343–368, 2006
Journal of Futures Markets 26(4):343 - 368. · 0.46 Impact Factor
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ABSTRACT: This paper analyses the nature and extent of interdependence, and return and volatility spillovers, in three euro exchange rates, namely the US dollar, Japanese yen and British pound sterling. Using the realised variance method in order to avoid pitfalls inherent in the GARCH methodology, we consider such effects at several time horizons over the trading day. Substantial evidence is reported of contemporaneous relationships between returns on these rates, and their volatility, with some further market-specific spillovers between returns and volatility. Variance decompositions from an estimated VAR suggest that the dollar rate dominates the other two rates in terms of both return and volatility spillovers. That is, innovations to the sterling and yen rates have, at best, a marginal effect on the dollar whilst, in contrast, news affecting the dollar can account for as much as 30% of the movement in sterling and yen returns and volatility. Further, using the recently introduced spillovers index, which is derived from the variance decomposition and examines the degree of cross-market spillover error variance relative to total variance, our results show that the extent of spillovers within these series increases with temporal aggregation from the 10-min to half-day frequency, but remains constant thereafter.
Journal of Economics and Business.
