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The Basel II Accord requires that banks and other authorized deposit‐taking institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure value‐at‐risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realized losses exceed the estimated VaR. The purpose of this paper is to address the question of risk management of risk, namely VaR of VIX futures prices.

The authors examine how different risk management strategies performed before, during and after the 2008‐2009 global financial crisis (GFC).

The authors find that an aggressive strategy of choosing the supremum of the univariate model forecasts is preferred to the other alternatives, and is robust during the GFC.

The paper examines how different risk management strategies performed before, during and after the 2008‐2009 GFC, and finds that an aggressive strategy of choosing the supremum of the univariate model forecasts is preferred to the other alternatives, and is robust during the GFC.

The recent 2008–2009 financial crisis has led international financial authorities to review the existing regulation; the Basel Committee on Banking Supervision has been thus induced to review the pillars of the Basel Accord (Basel II) in order to strengthen the risk coverage of capital framework (Basel 2.5 and III). These reforms will help to raise capital requirements for the trading book, which represents a major source of losses for internationally financial institutions, especially during crisis periods. In particular, the Committee has introduced a Stressed Value-at-Risk (SVaR) capital requirement, as a new methodology to evaluate market risk.

This chapter aims to shed some lights on the issues major banks have to face when calculating SVaR in the context of emerging markets, pointing out the differences in adopting an estimation model with respect to another one. Our results show a considerable increase in capital requirements especially when new rules are applied to financial markets with high-risk parameters, such as emerging markets are. The increased cost due to higher capital requirements could be a disincentive to investment in markets with higher risk profiles than the developed markets, taking also into account that diversification benefits deriving from investing in emerging economies have shown a decrease over time. The reduction of institutional investors can thus represent a brake on the process of innovation and evolution of emerging markets.

The purpose of this paper is to investigate the relationship between liquidity and credit risk, and employ the findings to estimate the Incremental Risk Charge (IRC), the new credit risk capital add‐on introduced by the Basel Committee for banks' trading books. The IRC estimates are compared with stressed market risk measures, derived from a sample of corporate bond indices encompassing the recent financial crisis. This can determine the extent to which trading book capital would change in stress conditions, under newly proposed rules.

The Basel II and the proposed Basel III capital requirements for banks' trading books, with a sample of bond portfolios, are implemented.

The findings show that, although the (incremental) credit risk in the trading book may be considerable, the capital needed to absorb market risk‐related losses in stressed scenarios can be more than ten times larger.

The data, methodology and purpose are all original.

The financial crisis has led the Basel Committee to improve the system of capital requirements for market risks. This paper aims to investigate the effects of different models to estimate the market risk in the management of the trading book. The study takes into account the events occurring in the financial markets and the new prudential rules.

The author compares different models and proposes an opportunity cost function able to evaluate the cost related to capital requirements. He identified seven asset classes and studies the effects of different models for estimating VaR simulating financial portfolios with increasing risk. The series consists of the daily return from 01/01/2002 to 06/30/2012.

The results show that it is possible to identify a wide area between aggressive and conservative approach where the bank management must choose. The regulation does not encourage intermediaries to the use of complex models that could better evaluate the risk in financial markets. The revision of the market risk framework increases the capital requirement and reduces the incentive to use models with more predictive power for regulatory purposes.

The work differs from previous contributions for three characteristics: first, it uses a set of extended data and more consistent with the actual operation. Secondly, the author presents an opportunity cost function in order to evaluate the estimation models. Third, he calculates the effect of stressed‐VaR after a year and a half of adoption.

International tourism is a major source of export receipts for many countries worldwide. Although it is not yet one of the most important industries in Taiwan (or the Republic of China), an island in East Asia off the coast of mainland China (or the People's Republic of China), the leading tourism source countries for Taiwan are Japan, followed by USA, Republic of Korea, Malaysia, Singapore, UK, Germany and Australia. These countries reflect short, medium and long haul tourist destinations. Although the People's Republic of China and Hong Kong are large sources of tourism to Taiwan, the political situation is such that tourists from these two sources to Taiwan are reported as domestic tourists. Daily data from 1 January 1990 to 30 June 2007 are obtained from the National Immigration Agency of Taiwan. The heterogeneous autoregressive (HAR) model is used to capture long memory properties in the data. In comparison with the HAR(1) model, the estimated asymmetry coefficients for GJR(1,1) are not statistically significant for the HAR(1,7) and HAR(1,7,28) models, so that their respective GARCH(1,1) counterparts are to be preferred. These empirical results show that the conditional volatility estimates are sensitive to the long memory nature of the conditional mean specifications. Although asymmetry is observed for the HAR(1) model, there is no evidence of leverage. The quasi-maximum likelihood estimators (QMLE) for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for international tourist arrivals to Taiwan are statistically adequate and have sensible interpretations. However, asymmetry (though not leverage) was found only for the HAR(1) model and not for the HAR(1,7) and HAR(1,7,28) models.

Preface The functions of business divide into several areas and the general focus of this book is on one of the most important although least understood of these—DISTRIBUTION. The particular focus is on reviewing current practice in distribution costing and on attempting to push the frontiers back a little by suggesting some new approaches to overcome previously defined shortcomings.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

The purpose of this paper is to analyze different behaviors between long-term options’ implied volatilities and realized volatilities.

This paper uses a widely adopted short interest rate model that describes a stochastic process of the short interest rate to capture interest rate risk. Price a long-term option by a system of two stochastic processes to capture both underlying asset and interest rate volatilities. Model capital charges according to the Basel III regulatory specified approach. S&P 500 index and relevant data are used to illustrate how the proposed model works. Coup with the low interest rate scenario by first choosing an optimal time segment obtained by a multiple change-point detection method, and then using the data from the chosen time segment to estimate the CIR model parameters, and finally obtaining the final option price by incorporating the capital charge costs.

Monotonic increase in long-term option implied volatility can be explained mainly by interest rate risk, and the level of implied volatility can be explained by various valuation adjustments, particularly risk capital costs, which differ from existing published literatures that typically explained the differences in behaviors of long-term implied volatilities by the volatility of volatility or risk premium. The empirical results well explain long-term volatility behaviors.

The authors only consider the market risk capital in this paper for demonstration purpose. Dealers may price the long-term options with the credit risk. It appears that other than the market risks such as underlying asset volatility and interest rate volatility, the market risk capital is a main nonmarket risk factor that significantly affects the long-term option prices.

Analysis helps readers and/or users of long-term options to understand why long-term option implied equity volatilities are much higher than observed. The framework offered in the paper provides some guidance if one would like to check if a long-term option is priced reasonable.

It is the first time to analyze mathematically long-term options’ volatility behavior in comparison with historically observed volatility.

The equation of unified knowledge says that S = f (A,P) which means that the practical solution to a given problem is a function of the existing, empirical, actual realities and the future, potential, best possible conditions of general stable equilibrium which both pure and practical reason, exhaustive in the Kantian sense, show as being within the realm of potential realities beyond any doubt. The first classical revolution in economic thinking, included in factor “P” of the equation, conceived the economic and financial problems in terms of a model of ideal conditions of stable equilibrium but neglected the full consideration of the existing, actual conditions. That is the main reason why, in the end, it failed. The second modern revolution, included in factor “A” of the equation, conceived the economic and financial problems in terms of the existing, actual conditions, usually in disequilibrium or unstable equilibrium (in case of stagnation) and neglected the sense of right direction expressed in factor “P” or the realization of general, stable equilibrium. That is the main reason why the modern revolution failed in the past and is failing in front of our eyes in the present. The equation of unified knowledge, perceived as a sui generis synthesis between classical and modern thinking has been applied rigorously and systematically in writing the enclosed American‐British economic, monetary, financial and social stabilization plans. In the final analysis, a new economic philosophy, based on a synthesis between classical and modern thinking, called here the new economics of unified knowledge, is applied to solve the malaise of the twentieth century which resulted from a confusion between thinking in terms of stable equilibrium on the one hand and disequilibrium or unstable equilibrium on the other.

This book is a policy proposal aimed at the democratic left. It is concerned with gradual but radical reform of the socio‐economic system. An integrated policy of industrial and economic democracy, which centres around the establishment of a new sector of employee‐controlled enterprises, is presented. The proposal would retain the mix‐ed economy, but transform it into a much better “mixture”, with increased employee‐power in all sectors. While there is much of enduring value in our liberal western way of life, gross inequalities of wealth and power persist in our society.