THE TEN COMMANDMENTS FOR OPTIMIZING VALUE-AT-RISK AND DAILY CAPITAL CHARGES

Abstract.  Credit risk is the most important type of risk in terms of monetary value. Another key risk measure is market risk, which is concerned with stocks and bonds, and related financial derivatives, as well as exchange rates and interest rates. This paper is concerned with market risk management and monitoring under the Basel II Accord, and presents Ten Commandments for optimizing value-at-risk (VaR) and daily capital charges, based on choosing wisely from (1) conditional, stochastic and realized volatility; (2) symmetry, asymmetry and leverage; (3) dynamic correlations and dynamic covariances; (4) single index and portfolio models; (5) parametric, semi-parametric and non-parametric models; (6) estimation, simulation and calibration of parameters; (7) assumptions, regularity conditions and statistical properties; (8) accuracy in calculating moments and forecasts; (9) optimizing threshold violations and economic benefits; and (10) optimizing private and public benefits of risk management. For practical purposes, it is found that the Basel II Accord would seem to encourage excessive risk taking at the expense of providing accurate measures and forecasts of risk and VaR.     

Has the Basel Accord improved risk management during the global financial crisis?

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 realised losses exceed the estimated VaR. In this paper we define risk management in terms of choosing from a variety of risk models, and discuss the selection of optimal risk models. A new approach to model selection for predicting VaR is proposed, consisting of combining alternative risk models, and we compare conservative and aggressive strategies for choosing between VaR models. We then examine how different risk management strategies performed during the 2008–09 global financial crisis. These issues are illustrated using Standard and Poor's 500 Composite Index.     

Downside risk management and VaR-based optimal portfolios for precious metals,oil and stocks

Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals (Portfolio #1) as the least efficient.     

Bayesian loss given default estimation for European sovereign bonds

We develop and apply a Bayesian model for the loss rates given defaults (LGDs) of European Sovereigns. Financial institutions are in need of LGD forecasts under Pillar II of the regulatory Basel Accord and the downturn in LGD forecasts under Pillar I. Both are challenging for portfolios with a small number of observations such as sovereigns. Our approach comprises parameter risk and generates LGD forecasts under both regular and downturn conditions. With sovereign-specific rating information, we found that average LGD estimates vary between 0.46 and 0.64, while downturn estimates lay between 0.50 and 0.86.     

Performance assessments of Taiwan’s financial holding companies

This paper uses Risk-Adjusted Return on Capital (RAROC) to assess the performance of 14 financial holding companies (FHCs) in Taiwan. RAROC value indicates a firm’s performance after considering the market risk effect, and gives a better measurement of the firm’s operational productivity than traditional methods. We use the full valuation methods to calculate Value at Risk (VaR) as the market risk measurement for economic capital. According to the New Basel Capital Accord, the market risk of Internal Model should be adjusted, and the Bank for International Settlement suggests using the backtest to select the best full valuation method for estimating adjusted VaR. Therefore, this paper evaluates the best market risk model, and assesses and compares the performance for each firm before and after its merger and acquisition into the FHC. Overall, we find weak evidence that the performance of 14 FHCs increased over time.     

Transition matrix models of consumer credit ratings

Although the corporate credit risk literature includes many studies modelling the change in the credit risk of corporate bonds over time, there has been far less analysis of the credit risk for portfolios of consumer loans. However, behavioural scores, which are calculated on a monthly basis by most consumer lenders, are the analogues of ratings in corporate credit risk. Motivated by studies of corporate credit risk, we develop a Markov chain model based on behavioural scores for establishing the credit risk of portfolios of consumer loans. Although such models have been used by lenders to develop models for the Basel Accord, nothing has been published in the literature on them. The model which we suggest differs in many respects from the corporate credit ones based on Markov chains — such as the need for a second order Markov chain, the inclusion of economic variables and the age of the loan. The model is applied using data on a credit card portfolio from a major UK bank.     

BANK CAPITAL REQUIREMENTS, BUSINESS CYCLE FLUCTUATIONS AND THE BASEL ACCORDS: A SYNTHESIS

Abstract.  In order to survey the mechanisms through which the introduction of Basel II bank capital requirements is likely to accentuate the procyclical tendencies of banking, this paper brings together the theoretical literature on the bank capital channel of propagation of exogenous shocks and the literature on the regulatory framework of capital requirements under the Basel Accords. We conclude that the theoretical models that revisit the bank capital channel under the new accord generally support the Basel II procyclicality hypothesis and that the magnitude of the procyclical effects essentially depends on (i) the composition of banks' asset portfolios, (ii) the approach adopted by banks to compute their minimum capital requirements, (iii) the nature of the rating system used by banks, (iv) the view adopted concerning how credit risk evolves through time, (v) the capital buffers over the regulatory minimum held by the banking institutions, (vi) the improvements in credit risk management and (vii) the supervisor and market intervention under Basel II. The recent events and instability in financial markets all over the world have led the procyclicality issue to enter the agendas of several political international  fora  and some measures to mitigate procyclicality are being put forward. The bank capital channel literature should now play an important role in evaluating their effectiveness.     

Decay factor optimisation in time weighted simulation — Evaluating VaR performance

We propose an optimisation approach for determining the optimal decay factor in time weighted (BRW) simulation. The backtesting of the BRW simulation, which involves different decay factors, together with a broad range of competing VaR models, has been performed on a sample of seven stock indexes and two commodities: gold and WTI oil. The results obtained show that the BRW simulation with an optimised decay factor relative to the Lopez (1998) size-adjusted function is among the best performing VaR models, second only to the conditional extreme value approach (McNeil & Frey, 2000). The optimised decay factors are sufficiently stable over time, giving economic justification to the optimisation because they do not change over longer time periods. Unlike most of the VaR models tested, in the large majority of cases, the optimised BRW model passes the Basel II criteria but yields significantly lower VaR forecasts than the extreme value approaches, thus resulting in a lower idle capital, i.e. lower costs.     

Value at risk models for volatile emerging markets equity portfolios

This paper investigates the issue of market risk quantification for emerging and developed market equity portfolios. A very wide spectrum of popular and widely used in practice Value at Risk (VaR) models are evaluated and compared with Extreme Value Theory (EVT) and adaptive filtered models, during normal, crises, and post-crises periods. The results are interesting and indicate that despite the documented differences between emerging and developed markets, the most successful VaR models are common for both asset classes. Furthermore, in the case of the (fatter tailed) emerging market equity portfolios, most VaR models turn out to yield conservative risk forecasts, in contrast to developed market equity portfolios, where most models underestimate the realized VaR. VaR estimation during periods of financial turmoil seems to be a difficult task, particularly in the case of emerging markets and especially for the higher loss quantiles. VaR models seem to be affected less by crises periods in the case of developed markets. The performance of the parametric (non-parametric) VaR models improves (deteriorates) during post-crises periods due to the inclusion of extreme events in the estimation sample.     

商业银行市场风险管理中的VAR模型

巴塞尔新资本协议规定金融机构满足资本充足率的要求,并将风险分为信用风险、市场风险和操作风险。针对市场风险的管理,本文着重介绍VAR模型的概念、VAR的种类以及主要特点,并指出VAR面临的主要问题及其在我国金融应用的前景。     

Impact of value-at-risk models on market stability

Financial institutions around the world use value-at-risk (VaR) models to manage their market risk and calculate their capital requirements under Basel Accords. VaR models, as any other risk management system, are meant to keep financial institutions out of trouble by, among other things, guiding investment decisions within established risk limits so that the viability of a business is not put unduly at risk in a sharp market downturn. However, some researchers have warned that the widespread use of VaR models creates negative externalities in financial markets, as it can feed market instability and result in what has been called endogenous risk, that is, risk caused and amplified by the system itself, rather than being the result of an exogenous shock. This paper aims at analyzing the potential of VaR systems to amplify market disturbances with an agent-based model of fundamentalist and technical traders which manage their risk with a simple VaR model and must reduce their positions when the risk of their portfolio goes above a given threshold. We analyse the impact of the widespread use of VaR systems on different financial instability indicators and confirm that VaR models may induce a particular price dynamics that rises market volatility. These dynamics, which we have called `VaR cycles’, take place when a sufficient number of traders reach their VaR limit and are forced to simultaneously reduce their portfolio; the reductions cause a sudden price movement, raise volatility and force even more traders to liquidate part of their positions. The model shows that market is more prone to suffer VaR cycles when investors use a short-term horizon to calculate asset volatility or a not-too-extreme value for their risk threshold.     

Reducing estimation risk in optimal portfolio selection when short sales are allowed

The issue of estimation risk is of particular interest to the decision‐making processes of portfolio managers who use long–short investment strategies. Accordingly, our paper explores the question of whether a VaR constraint reduces estimation risk when short sales are allowed. We find that such a constraint notably decreases errors in estimates of the expected return, standard deviation, and VaR of optimal portfolios. Furthermore, optimal portfolios in the presence of the constraint are substantially closer to the ‘true’ efficient frontier than those in its absence. Finally, we provide VaR bounds and confidence levels for the constraint that lead to the best out‐of‐sample performance. Copyright © 2008 John Wiley & Sons, Ltd.     

EVT and tail-risk modelling: Evidence from market indices and volatility series

Value-at-Risk (VaR) has become the universally accepted risk metric adopted internationally under the Basel Accords for banking industry internal control, capital adequacy and regulatory reporting. The recent extreme financial market events such as the Global Financial Crisis (GFC) commencing in 2007 and the following developments in European markets mean that there is a great deal of attention paid to risk measurement and risk hedging. In particular, to risk indices and attached derivatives as hedges for equity market risk. The techniques used to model tail risk such as VaR have attracted criticism for their inability to model extreme market conditions. In this paper we discuss tail specific distribution based Extreme Value Theory (EVT) and evaluate different methods that may be used to calculate VaR ranging from well known econometrics models of GARCH and its variants to EVT based models which focus specifically on the tails of the distribution. We apply Univariate Extreme Value Theory to model extreme market risk for the FTSE100 UK Index and S&P-500 US markets indices plus their volatility indices. We show with empirical evidence that EVT can be successfully applied to financial market return series for predicting static VaR, CVaR or Expected Shortfall (ES) and also daily VaR and ES using a GARCH(1,1) and EVT based dynamic approach to these various indices. The behaviour of these indices in their tails have implications for hedging strategies in extreme market conditions.     

Fat tails,VaR and subadditivity

Financial institutions rely heavily on Value-at-Risk (VaR) as a risk measure, even though it is not globally subadditive. First, we theoretically show that the VaR portfolio measure is subadditive in the relevant tail region if asset returns are multivariate regularly varying, thus allowing for dependent returns. Second, we note that VaR estimated from historical simulations may lead to violations of subadditivity. This upset of the theoretical VaR subadditivity in the tail arises because the coarseness of the empirical distribution can affect the apparent fatness of the tails. Finally, we document a dramatic reduction in the frequency of subadditivity violations, by using semi-parametric extreme value techniques for VaR estimation instead of historical simulations.     

商业银行操作风险及其量化管理

本身并不新鲜的操作风险这一话题随着新巴塞尔资本协议的诞生又重新成为了金融界关注的焦点。到底该如何对这一与银行经营形影不离的风险进行管理呢?全世界的银行家们通过对操作风险的定义及其各种具体表现的深刻理解得出了这样的结论:好的操作风险管理能够降低经营成本并提高银行价值。本文从对操作风险的定义和特点出发,讨论了国外操作风险管理的先进经验和协议中给出的操作风险量化管理办法,指出了操作风险的量化在整个操作风险管理过程中的重要意义。     

商业银行总体经济资本测度方法比较研究

总体经济资本测度是商业银行实施《新巴塞尔资本协议》的关键。本文比较研究了商业银行总体经济资本的两种测度方法：资产波动法和收益波动法,分别介绍了两种测度方法的基本原理、计算步骤以及各自的应用范围和侧重点,并对两种方法相对应的经济资本加总技术,如搭积木法、椭圆分布法、Copula连接函数方法、多因子模型和混合多因子模型等进行了比较研究。     

船闸检修期间三峡坝区船舶海事行为管理研究

2012年,三峡船闸和葛洲坝船闸同步检修,船舶在三峡坝区待闸锚地大量积压,船舶海事行为管理有着鲜明的区域性、时间性和社会根源。文章研究分析了船闸同步检修期间的船舶海事行政违法行为概况、成因和防治对策。     

基于省域视角的信用风险模型适应性分析

巴塞尔新资本协议在鼓励银行采用内部评级法评估信用风险以提取资本准备的同时也强化了各国监管机构对内部评级模型绩效检验与审查的要求.CreditMetrics和CreditRisk+是银行业信用风险评估的基准模型.从建模的数学方法看,CreditRisk+是基于违约的判断,而CreditMetrics则是根据等级变化评价.利用江苏省银监局的相关统计数据对信用风险评估模型进行参数特性审查与绩效检验,结果显示这两类常用模型都可以在江苏的商业银行经营实践中稳定地实现根据信贷组合的实际风险状况进行内部资本配置这一目标.     

Basel III liquidity rules: The implications for bank lending growth in Africa

This paper examines the possible loan growth effect of the Basel III NSFR and LCR requirements in Africa and seeks to determine whether the different regions of the continent are affected differently. The paper also offers what is possibly the first investigation of how the interaction between the performance of loan portfolios and the new Basel III liquidity requirements might shape bank loan growth rates. Using a dataset of 361 commercial banks across 38 African countries over the 2005–2015 period, our static and dynamic panel analyses show that both the NSFR and the LCR exert significant positive effects on bank loan growth rates. The results also reveal that the NSFR reduces the impact of the negative effect of poor performance of loan portfolios on bank loan growth rates. Compliance with the Basel III liquidity rules in Africa is therefore likely to have beneficial impacts on policies intended to increase bank lending in the continent.     

我国商业银行操作风险成因及对策分析

2010年底,我国将有第一批商业银行开始实施新巴塞尔协议,这标志着中国银行业的全面风险管理体系建设正式步入轨道。作为商业银行三大主要风险之一的操作风险,因为相关研究起步晚,管理滞后,成为银行业关注的重点。本文结合国内商业银行的实际,深入剖析当前我国商业银行操作风险产生的原因,并提出强化操作风险管理的对策。