The cross-currency hedging performance of implied versus statistical forecasting models

This article examines the ability of several models to generate optimal hedge ratios. Statistical models employed include univariate and multivariate generalized autoregressive conditionally heteroscedastic (GARCH) models, and exponentially weighted and simple moving averages. The variances of the hedged portfolios derived using these hedge ratios are compared with those based on market expectations implied by the prices of traded options. One-month and three-month hedging horizons are considered for four currency pairs. Overall, it has been found that an exponentially weighted moving-average model leads to lower portfolio variances than any of the GARCH-based, implied or time-invariant approaches.

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.

Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.

Forecasting exchange rate volatility using conditional variance models selected by information criteria

This paper uses appropriately modified information criteria to select models from the GARCH family, which are subsequently used for predicting US dollar exchange rate return volatility. The out of sample forecast accuracy of models chosen in this manner compares favourably on mean absolute error grounds, although less favourably on mean squared error grounds, with those generated by the commonly used GARCH(1, 1) model. An examination of the orders of models selected by the criteria reveals that (1, 1) models are typically selected less than 20% of the time.

Episodic nonstationarity in exchange rates

We examine a method recently proposed by Hinich and Patterson (mimeo, University of Texas at Austin, 1995) for testing the validity of specifying a GARCH error structure for financial time series data in the context of a set of ten daily Sterling exchange rates. The results demonstrate that there are statistical structures present in the data that cannot be captured by a GARCH model, or any of its variants. This result has important implications for the interpretation of the recent voluminous literature which attempts to model financial asset returns using this family of models.

Predicting stock index volatility: can market volume help?

This paper explores a number of statistical models for predicting the daily stock return volatility of an aggregate of all stocks traded on the NYSE. An application of linear and non-linear Granger causality tests highlights evidence of bidirectional causality, although the relationship is stronger from volatility to volume than the other way around. The out-of-sample forecasting performance of various linear, GARCH, EGARCH, GJR and neural network models of volatility are evaluated and compared. The models are also augmented by the addition of a measure of lagged volume to form more general ex-ante forecasting models. The results indicate that augmenting models of volatility with measures of lagged volume leads only to very modest improvements, if any, in forecasting performance.

Testing for non-linearity in daily sterling exchange rates

A number of tests for non-linear dependence in time series are presented and implemented on a set of 10 daily sterling exchange rates covering the entire post Bretton-Woods era until the present day. Irrefutable evidence of non-linearity is shown in many of the series, but most of this dependence can apparently be explained by reference to the GARCH family of models. It is suggested that the literature in this area has reached an impasse, with the presence of ARCH effects clearly demonstrated in a large number of papers, but with the tests for non-linearity which are currently available being unable to classify any additional non-linear structure.

How do multilateral institutions influence individual perceptions of international affairs? Evidence from Europe and Asia

To date there has been no systematic study of the relationship between individuals’ opinions of different institutions and their perceptions of world affairs. This article tries to fill this gap by using a large cross-country data set comprising nine EU members and seven Asian nations and instrumental variable bivariate probit regression analysis. Controlling for a host of factors, the article shows that individuals’ confidence in multilateral institutions affects their perceptions of whether or not their country is being treated fairly in international affairs. This finding expands upon both theoretical work on multilateral institutions that has focused on state actors’ rationale for engaging in multilateral cooperation and empirical work that has treated confidence in multilateral institutions as a dependent variable. The article also shows that individuals’ confidence in different international organizations has undifferentiated effects on their perceptions of whether or not their country is being treated fairly in international affairs, though individuals more knowledgeable about international affairs exhibit slightly different attitudes. Finally, the article demonstrates significant differences in opinion across Europe and Asia.

Plasma free fatty acids do not provide the link between obesity and insulin resistance or β-cell dysfunction: results of the Reading, Imperial, Surrey, Cambridge, Kings (RISCK) study

Aims To investigate the relationship between adiposity and plasma free fatty acid levels and the influence of total plasma free fatty acid level on insulin sensitivity and β-cell function. Methods An insulin sensitivity index, acute insulin response to glucose and a disposition index, derived from i.v. glucose tolerance minimal model analysis and total fasting plasma free fatty acid levels were available for 533 participants in the Reading, Imperial, Surrey, Cambridge, Kings study. Bivariate correlations were made between insulin sensitivity index, acute insulin response to glucose and disposition index and both adiposity measures (BMI, waist circumference and body fat mass) and total plasma free fatty acid levels. Multivariate linear regression analysis was performed, controlling for age, sex, ethnicity and adiposity. Results After adjustment, all adiposity measures were inversely associated with insulin sensitivity index (BMI: β = −0.357; waist circumference: β = −0.380; body fat mass: β = −0.375) and disposition index (BMI: β = −0.215; waist circumference: β = −0.248; body fat mass: β = −0.221) and positively associated with acute insulin response to glucose [BMI: β = 0.200; waist circumference: β = 0.195; body fat mass β = 0.209 (P values <0.001)]. Adiposity explained 13, 4 and 5% of the variation in insulin sensitivity index, acute insulin response to glucose and disposition index, respectively. After adjustment, no adiposity measure was associated with free fatty acid level, but total plasma free fatty acid level was inversely associated with insulin sensitivity index (β = −0.133), acute insulin response to glucose (β = −0.148) and disposition index [β = −0.218 (P values <0.01)]. Plasma free fatty acid concentration accounted for 1.5, 2 and 4% of the variation in insulin sensitivity index, acute insulin response to glucose and disposition index, respectively. Conclusions Plasma free fatty acid levels have a modest negative association with insulin sensitivity, β-cell secretion and disposition index but no association with adiposity measures. It is unlikely that plasma free fatty acids are the primary mediators of obesity-related insulin resistance or β-cell dysfunction.

Time varying price discovery

We show how multivariate GARCH models can be used to generate a time-varying “information share” (Hasbrouck, 1995) to represent the changing patterns of price discovery in closely related securities. We find that time-varying information shares can improve credit spread predictions.

Low-frequency volatility of real estate securities in relation to macroeconomic risk

Real estate securities have a number of distinct characteristics that differentiate them from stocks generally. Key amongst them is that under-pinning the firms are both real as well as investment assets. The connections between the underlying macro-economy and listed real estate firms is therefore clearly demonstrated and of heightened importance. To consider the linkages with the underlying macro-economic fundamentals we extract the ‘low-frequency’ volatility component from aggregate volatility shocks in 11 international markets over the 1990-2014 period. This is achieved using Engle and Rangel’s (2008) Spline-Generalized Autoregressive Conditional Heteroskedasticity (Spline-GARCH) model. The estimated low-frequency volatility is then examined together with low-frequency macro data in a fixed-effect pooled regression framework. The analysis reveals that the low-frequency volatility of real estate securities has strong and positive association with most of the macroeconomic risk proxies examined. These include interest rates, inflation, GDP and foreign exchange rates.

Firms’ exporting and importing activities: is there a two-way relationship?

The literature on firm heterogeneity and trade has highlighted that most trading firms tend to engage in both importing and exporting activities. This paper provides some evidence that helps understanding to what extent this is the result of a two-way relationship. Using firm-level data for a group of 27 Eastern European and Central Asian countries from the World Bank Business Environment and Enterprise Performance Survey (BEEPS) over the period 2002–2008, we estimate a bivariate probit model of exporting and importing. After controlling for size (and other firm-level characteristics) we find that firms’ exporting activity does not increase the probability of importing, while the latter has a positive effect on foreign sales. This effect is mainly channeled through an increase in firm productivity and product innovation.

Communicating thematic data quality with web map services

Geospatial information of many kinds, from topographic maps to scientific data, is increasingly being made available through web mapping services. These allow georeferenced map images to be served from data stores and displayed in websites and geographic information systems, where they can be integrated with other geographic information. The Open Geospatial Consortium’s Web Map Service (WMS) standard has been widely adopted in diverse communities for sharing data in this way. However, current services typically provide little or no information about the quality or accuracy of the data they serve. In this paper we will describe the design and implementation of a new “quality-enabled” profile of WMS, which we call “WMS-Q”. This describes how information about data quality can be transmitted to the user through WMS. Such information can exist at many levels, from entire datasets to individual measurements, and includes the many different ways in which data uncertainty can be expressed. We also describe proposed extensions to the Symbology Encoding specification, which include provision for visualizing uncertainty in raster data in a number of different ways, including contours, shading and bivariate colour maps. We shall also describe new open-source implementations of the new specifications, which include both clients and servers.