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It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value‐at‐risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models.

This article investigates the effect of modeling extreme events on the calculation of minimum capital risk requirements for three LIFFE futures contracts. The use of internal models will be permitted under the European Community Capital Adequacy Directive II and will be widely adopted in the near future for determining capital adequacies. Close scrutiny of competing models is required to avoid a potentially costly misallocation of capital resources, to ensure the safety of the financial system. The authors propose a semi‐parametric approach, for which extreme risks are modeled using a generalized Pareto distribution, and smaller risks are characterized by the empirically observed distribution function. The primary finding of comparing the capital requirements based on this approach with those calculated from both the unconditional density and from a conditional density (a GARCH(1,1) model), is that for both in‐sample and out‐of‐sample tests, the extreme value approach yields superior results. This is attributable to the fact that the other two models do not explicitly model the tails of the return distribution.

This paper examines the cyclical regularities of macroeconomic, financial and property market aggregates in relation to the property stock price cycle in the UK. The Hodrick Prescott filter is employed to fit a long‐term trend to the raw data, and to derive the short‐term cycles of each series. It is found that the cycles of consumer expenditure, total consumption per capita, the dividend yield and the long‐term bond yield are moderately correlated, and mainly coincident, with the property price cycle. There is also evidence that the nominal and real Treasury Bill rates and the interest rate spread lead this cycle by one or two quarters, and therefore that these series can be considered leading indicators of property stock prices. This study recommends that macroeconomic and financial variables can provide useful information to explain and potentially to forecast movements of property‐backed stock returns in the UK.

Investors are now able to analyse more noise-free news to inform their trading decisions than ever before. Their expectation that more information means better performance is not supported by previous psychological experiments which argue that too much information actually impairs performance. The purpose of this paper is to examine whether the degree of information explicitness improves stock market performance.

An experiment is conducted in a computer laboratory to examine a trading simulation manipulated from a real market-shock. Participants’ performance efficiency and effectiveness are measured separately.

The results indicate that the explicitness of information neither improves nor impairs participants’ performance effectiveness from the perspectives of returns, share and cash positions, and trading volumes. However, participants’ performance efficiency is significantly affected by information explicitness.

The novel approach and findings of this research add to the knowledge of the impact of information explicitness on the quality of decision making in a financial market environment.

Dunlop Aircraft Tyres has won the official approval of the Hungarian Civil Aviation Authority for its tyre retreading facilities. This follows a recent contract won by the company to supply new tyres for Malev Hungarian Airlines' fleet of Boeing 767s.

This study aims to extend the literature by extensively investigating the impact of foreign exchange and interest rate changes on the returns and volatility of bank stocks in Saudi Arabia, which is the largest dual banking industry.

This study employs the generalized autoregressive conditional heteroscedasticity (GARCH) model on stock returns of four fully Islamic Saudi banks and eight conventional Saudi banks.

The results showed that the foreign exchange rate return has a positive impact on Saudi conventional bank returns, while it has an adverse impact on Saudi Islamic bank returns. Moreover, a higher interest rate return has a positive impact on Saudi bank stock returns implying that the assets side is more sensitive to changes in interest rates than the liability side. Finally, higher foreign exchange and interest rates volatility increases the volatility of Saudi bank returns, where the former has the largest significant impact. Therefore, Saudi regulators should pay more attention to the risk management of their banks because this could threaten the stability of their financial system.

To the best knowledge of the author, this is the first study that tries to extensively analyze the joint impact of foreign exchange and interest rates on bank stock returns and volatility in Saudi Arabia by applying the GARCH model. The study uses a long data set from 2010 to 2019 that includes all Saudi banks and employs four measures of interest rates to increase the robustness of the results.