Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

Sources of Bank Interest Rate Risk

We investigate bank stocks'sensitivity to changes in interest rates and the factors affecting this sensitivity. We focus on whether the exposure of commercial banks to interest rate risk is conditioned on certain balance sheet and income statement ratios. We find a significantly negative relation between bank stock returns and changes in interest rates over the period 1991–1996. We also find that bank characteristics measured from basic financial statement information explain bank stocks'sensitivity to interest rate changes. These results suggest that bank managers, analysts, and regulators can use this information to assess the relative risk exposure of banks.     

浅谈我国银行内部审计的发展

银行内部审计随着银行业务的扩大，越来越受到高层管理者的重视，它是由相对独立、较为超胶铁稽核部门来执行的一种再监督。加入WTO以后，银行稽核工作从观念到工作方法都将发生重大变革。首先是观念的变革，银行内部审计的重点将由事后审计向事前审计转移，突出表现为检查风险向控制风险转移，内容由财务收支、资产质量等专项稽核向整体评价转移，更加注重绩效审计，同时加强对风险评估和管理方面的审计；其次是工作方法的变化，手段上充分利用计算机处理原始数据，方法上改变过去被动地接受稽核项目，按稽核方案对所辖行实施无差别的稽核，转为利用内部控制评价结果有区别地决定稽核对象、稽核频率、现场稽核的检查面。     

Use of minimum risk approach in the estimation of regression models with missing observations

This article considers a linear regression model with some missing observations on the response variable and presents two estimators of regression coefficients employing the approach of minimum risk estimation. Small disturbance asymptotic properties of these estimators along with the traditional unbiased estimator are analyzed and conditions, that are easy to check in practice, for the superiority of one estimator over the other are derived. Received May 2001     

Initial Margin Requirements, Volatility, and the Individual Investor: Insights from Japan

Initial margin requirements represent: (1) a cost impediment to the wealth constrained investor and (2) a potential way of mitigating excessive volatility. However, prior empirical research finds that margins are not an effective tool in reducing volatility. We consider the possibility that margins primarily affect certain stocks and investors. Specifically, we test whether margins affect individuals who, as a group, we believe to be the investors most affected when margin requirements change. Our initial empirical tests, however, do not support this contention.     

From T-Bills to Stocks: Seasonal Anomalies Revisited

This paper employed eleven data series which consist of stocks, bonds, bills, equity premiums, term premiums, and various default premiums to investigate whether January seasonality reported in existing literature is robust across different states of the economy as this has important trading implications. For the periods 1926–1990, small stocks, small stock premiums, low grade bonds, and default premiums (spread between high grade, low grade and government bonds) reveal January seasonality and that the seasonality is robust across different states of the economy except for low grade bond returns and default premiums. January seasonality for low grade bond returns and low grade bond default premiums are primarily driven by results found during periods of economic expansion. Overall, January seasonality is more evident during the economic expansion periods although the magnitude of default premiums is larger during periods of economic contraction. Furthermore, prior findings of strong summer equity returns are primarily driven by the results found during the periods of economic contraction. It is also found that equity returns are generally higher during periods of economic expansion.     

Credit risk and sustainable debt: a model and estimations of why the Euro is stable in the long-run

Sustainable debt has become the key issue in rating of private as well as sovereign debtors. The problem of how to estimate sustainable debt has also been at the center of the debate over the Asian 1997–1998 financial crisis. If the external value of the currency depends on the external debt of a country, it is necessary to estimate the creditworthiness of the country. This paper studies credit risk and sustainable debt in the context of a dynamic model. For a dynamic growth model with an additional equation for the evolution of debt, we demonstrate of how to compute sustainable debt and creditworthiness. The model is estimated by employing time series data for the core countries of the Euro-area. The computations show that the Euro-area has large external assets. Using time series methods, the sustainability of external debt (assets) is estimated for those core countries of the Euro-area. Those estimations show that the Euro will be a stable currency in the long-run.     

Likelihood-based specification analysis of continuous-time models of the short-term interest rate

An extensive collection of continuous-time models of the short-term interest rate is evaluated over data sets that have appeared previously in the literature. The analysis, which uses the simulated maximum likelihood procedure proposed by Durham and Gallant (2002), provides new insights regarding several previously unresolved questions. For single factor models, I find that the volatility, not the drift, is the critical component in model specification. Allowing for additional flexibility beyond a constant term in the drift provides negligible benefit. While constant drift would appear to imply that the short rate is nonstationary, in fact, stationarity is volatility-induced. The simple constant elasticity of volatility model fits weekly observations of the three-month Treasury bill rate remarkably well but is easily rejected when compared with more flexible volatility specifications over daily data. The methodology of Durham and Gallant can also be used to estimate stochastic volatility models. While adding the latent volatility component provides a large improvement in the likelihood for the physical process, it does little to improve bond-pricing performance.     

Analysing Perceived Downside Risk: the Component Value‐at‐Risk Framework

Multinational companies face increasing risks arising from external risk factors, e.g. exchange rates, interest rates and commodity prices, which they have learned to hedge using derivatives. However, despite increasing disclosure requirements, a firm's net risk profile may not be transparent to shareholders. We develop the ‘Component Value‐at‐Risk (VaR)’ framework for companies to identify the multi‐dimensional downside risk profile as perceived by shareholders. This framework allows for decomposing downside risk into components that are attributable to each of the underlying risk factors. The firm can compare this perceived VaR, including its composition and dynamics, to an internal VaR based on net exposures as it is known to the company. Any differences may lead to surprises at times of earnings announcements and thus constitute a litigation threat to the firm. It may reduce this information asymmetry through targeted communication efforts.