testing for nonlinear dependence in daily foreign exchange rates the purpose of this article is to investigate whether daily changes in five major foreign exchange rates contain any nonlinearities although the data contain no linear correlation evidence indicates the presence of substantial nonlinearity in a multiplicative rather than additive form further examination reveals that a generalized autoregressive conditional heteroskedasticity model can explain a large part of the nonlinearities for all five exchange rates copyright 1989 by the university of chicago

answering the skeptics yes standard volatility models do provide accurate forecasts a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using arch and stochastic volatility models while most of these studies have documented highly significant in sample parameter estimates and pronounced intertemporal volatility persistence traditional ex post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts contrary to this contention we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications new methods for improved ex post interdaily volatility measurements based on high frequency intradaily data are also discussed

evaluating interval forecasts a complete theory for evaluating interval forecasts has not been worked out to date most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage consequently i set out to build a consistent framework for conditional interval forecast evaluation which is crucial when higher order moment dynamics are present the new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management

further long memory properties of inflationary shocks several previous studies have found fractionally integrated or long memory behavior in the conditional mean of inflation this paper notes that extremely similar phenomena are also apparent in the squared and absolute values of residuals from fractionally filtered inflation series hence the inflation process appears to have a dual long memory feature in both its first and its second conditional moments we suggest a parametric model of long memory in both the conditional mean and the conditional variance some monte carlo evidence is presented that supports estimation of the model by approximate maximum likelihood methods we then report estimated models for the inflation series for several different industrialized countries including the united states for nearly all of the countries in our study there is strong evidence of statistically significant long memory parameters in both the conditional mean and the variance we note some of the implications for modeling inflation

conditional heteroscedasticity in time series of stock returns evidence and forecasts this article presents new evidence about the time series behavior of stock prices daily return series exhibit significant levels of second order dependence and they cannot be modeled as linear white noise processes a reasonable return generating process is empirically shown to be a first order autoregressive process with conditionally heteroskedastic innovations in particular generalized autoregressive conditional heteroskedastic garch 1 1 processes fit to data very satisfactorily various out of sample forecasts of monthly return variances are generated and compared statistically forecasts based on the garch model are found to be superior copyright 1989 by the university of chicago

fractional integration in agricultural futures price volatilities this article tests whether the volatility of agricultural futures prices exhibits fractional integration volatility series were constructed for fourteen agricultural futures price series with over 5 300 observations per series the volatility series exhibit strong long term dependence which is an indicator of fractional integration a fractional integration model figarch 1 d 1 performs significantly better than a traditional volatility model garch 1 1 in modeling agricultural futures price volatility

a word of caution on calculating market based minimum capital risk requirements this paper demonstrates that the use of garch type models for the calculation of minimum capital risk requirements mcrrs may lead to the production of inaccurate and therefore inefficient capital requirements we show that this inaccuracy stems from the fact that garch models typically overstate the degree of persistence in return volatility a simple modification to the model is found to improve the accuracy of mcrr estimates in both back and out of sample tests given that internal risk management models are currently in widespread usage in some parts of the world most notably the usa and will soon be permitted for ec banks and investment firms we believe that our paper should serve as a valuable caution to risk management practitioners who are using or intend to use this popular class of models

volatility forecasting without data snooping abstract data snooping arises when the properties of a data series influence the researcher s choice of model specification when data has been snooped tests undertaken using the same series are likely to be misleading this study seeks to predict equity market volatility using daily data on u k stock market returns over the period 1955 1989 we find that even apparently innocuous forms of data snooping significantly enhance reported forecast quality and that relatively sophisticated forecasting methods operated without data snooping often perform worse than naive benchmarks for predicting stock market volatility we therefore recommend two alternative models both of which are extremely simple

the relation between implied and realized volatility abstract previous research finds the volatility implied by s p 100 index option prices to be a biased and inefficient forecast of future volatility and to contain little or no incremental information beyond that in past realized volatility in contrast we find that implied volatility outperforms past volatility in forecasting future volatility and even subsumes the information content of past volatility in some of our specifications our results differ from previous studies because we use longer time series and nonoverlapping data a regime shift around the october 1987 crash explains why implied volatility is more biased in previous work

model risk and capital reserves abstract we propose a procedure to take model risk into account in the computation of capital reserves this addresses the need to make the allocation of capital reserves to positions in given markets dependent on the extent to which reliable models are available the proposed procedure can be used in combination with any of the standard risk measures such as value at risk and expected shortfall we assume that models are obtained by usual econometric methods which allows us to distinguish between estimation risk and misspecification risk we discuss an additional source of risk which we refer to as identification risk by way of illustration we carry out calculations for equity and fx data sets in both markets estimation risk and misspecification risk together explain about half of the multiplication factors employed by the bank for international settlements bis

garch vs stochastic volatility option pricing and risk management this paper examines the out of sample performance of two common extensions of the black scholes framework namely a garch and a stochastic volatility option pricing model the models are calibrated to intraday ftse 100 option prices we apply two sets of performance criteria namely out of sample valuation errors and value at risk oriented measures when we analyze the fit to observed prices garch clearly dominates both stochastic volatility and the benchmark black scholes model however the predictions of the market risk from hypothetical derivative positions show sizable errors the fit to the realized profits and losses is poor and there are no notable differences between the models overall we therefore observe that the more complex option pricing models can improve on the black scholes methodology only for the purpose of pricing but not for the value at risk forecasts author s abstract

a utility based comparison of some models of exchange rate volatility abstract when estimates of variances are used to make asset allocation decisions underestimates of population variances lead to lower expected utility than equivalent overestimates a utility based criterion is asymmetric unlike standard criteria such as mean squared error to illustrate how to estimate a utility based criterion we use five bilateral weekly dollar exchange rates 1973 1989 and the corresponding pair of eurodeposit rates of homoskedastic garch autoregressive and non parametric models for the conditional variance of each exchange rate garch models tend to produce the highest utility on average a mean squared error criterion also favors garch but not as sharply

improving the parkinson method of estimating security price volatilities the author proposes a new method for estimating the volatility parameters of security prices which is an improvement of the estimation method by m parkinson 1980 the author assumes that the security prices follow the geometric brownian motion however contrary to the setting of parkinson the geometric brownian motion may have nonzero drift terms the author shows that the efficiency of his estimator is about 10 in comparison with the standard sample variance estimator since the efficiency of the estimator by parkinson is about 4 91 his estimation method may considerably improve the estimation methods already known in financial economics copyright 1992 by university of chicago press

united arab emirates fdi outlook fdi is important in building a sustainable and diversified knowledge based uae economy the stock of fdi grew at an average annual growth rate of 45 3 percent over the past decade reaching us 95 billion or nearly 27 percent of gdp in 2012 fdi flows have not recovered from the global financial crises most fdi stock is concentrated in finance construction and real estate recent greenfield fdi is concentrated in construction while more than half of top m a deals took place in finance transportation communications and utilities the list of top oecd home countries for fdi flows to the uae include italy germany chile united kingdom luxembourg france united states and belgium though uae investment policy limits foreign investment and reduces competition the government has undertaken reforms and contracted investment treaties that have encouraged investment efforts are under way to speed up the ratification of a new foreign investment law which removes several of the current legal barriers to fdi and offers foreign investors similar rights to those of uae nationals the uae has high fdi potential with plenty of room for improving fdi performance and benefiting the economy

implications of nonlinear dynamics for financial risk management this paper demonstrates that when log price changes are not iid their conditional density may be more accurate than their unconditional density for describing short term behavior using the bds test of independence and identical distribution daily log price changes in four currency futures contracts are found to be not iid while there appear to be no predictable conditional mean changes conditional variances are predictable and can be described by an autoregressive volatility model that seems to capture all the departures from independence and identical distribution based on this model daily log price changes are decomposed into a predictable part which is described parametrically by the autoregressive volatility model and an unpredictable part which can be modeled by an empirical density either parametrically or nonparametrically this two step seminonparametric method yields a conditional density for daily log price changes which has a number of uses in financial risk management

option values under stochastic volatility theory and empirical estimates abstract this paper numerically solves the call option valuation problem given a fairly general continuous stochastic process for return volatility statistical estimators for volatility process parameters are derived and parameter estimates are calculated for several individual stocks and indices the resulting estimated option values do not differ dramatically from black scholes values in most cases although there is some evidence that for longer maturity index options black scholes overvalues out of the money calls in relation to in the money calls

accurate minimum capital risk requirements a comparison of several approaches in this paper we estimate for several investment horizons minimum capital risk requirements for short and long positions using the unconditional distribution of three daily indexes futures returns and a set of short and long memory stochastic volatility and garch type models we consider the possibility that errors follow a t student distribution in order to capture the kurtosis of the returns series the results suggest that accurate modelling of extreme observations obtained for long and short trading investment positions is possible with an autoregressive stochastic volatility model moreover modelling futures returns with a long memory stochastic volatility model produces in general excessive volatility persistence and consequently leads to large minimum capital risk requirement estimates finally the models predictive ability is assessed with the help of out of sample conditional tests

how relevant is volatility forecasting for financial risk management it depends if volatility fluctuates in a forecastable way volatility forecasts are useful for risk management hence the interest in volatility forecastability in the risk management literature volatility forecastability however varies with horizon and different horizons are relevant in different applications moreover existing assessments of volatility forecastability are plagued by the fact that they are joint assessments of volatility forecastability and an assumed model and the results can vary not only with the horizon but also with the assumed model to address this problem we develop a model free procedure for assessing volatility forecastability across horizons perhaps surprisingly we find that volatility forecastability decays quickly with horizon volatility forecastability although clearly of relevance for risk management at the short horizons relevant for say trading desk management may be much less important at longer horizons

value at risk for long and short trading positions in this paper we model value at risk var for daily stock index returns using a collection of parametric models of the arch family based on the skewed student distribution we show that models that rely on a symmetric density distribution for the error term underperform with respect to skewed density models when the left and right tails of the distribution of returns must be modelled thus var for traders having both long and short positions is not adequately modelled using usual normal or student distributions we suggest using an aparch model based on the skewed student distribution to fully take into account the fat left and right tails of the returns distribution this allows for an adequate modelling of large returns defined on long and short trading positions the performances of all models are assessed on daily data for the cac40 dax nasdaq nikkei and smi stock indexes we also compute the expected short fall and the average multiple of tail event to risk measure for the new model

finite sample properties of a qml estimator of stochastic volatility models with long memory abstract we analyse the finite sample properties of a qml estimator of lmsv models we show up its poor performance for realistic parameter values we discuss an identification problem when the volatility has a unit root an empirical analysis illustrates our findings