Market Risk Management Research Articles

Market risk management in a post-Basel II regulatory environment

We propose a novel method of Mean-Capital Requirement portfolio optimization. The optimization is performed using a parallel framework for optimization based on the Nondominated Sorting Genetic Algorithm II. Capital requirements for market risk include an additional stress component introduced by the recent Basel 2.5 regulation. Our optimization with the Basel 2.5 formula in the objective function produces superior results to those of the old (Basel II) formula in stress scenarios in which the correlations of asset returns change considerably. These improvements are achieved at the expense of reduced cardinality of Pareto-optimal portfolios. This reduced cardinality (and thus portfolio diversification) in periods of relatively low market volatility may have unintended consequences for banks’ risk exposure.

Stanovení Value at Risk a Conditional Value at Risk za předpokladu eliptických rozdělení pravděpodobnosti

The importance of risk management is nowadays one of the most important activities of financial institutions. One of the most commonly used methods for measuring and managing market risk is the indicator of Value at Risk (the minimum predicted loss for given significant level and time horizon) and Conditional Value at Risk (the average of expected losses that exceed the value of the Value at Risk). The aim of submitted article is the estimation of Value at Risk and Conditional Value at Risk for given shares of stock's portfolio assuming elliptical distribution of probability. Significant level is determined for 15 %, 10 %, 5%, 1% and 0.5 % for time horizon one day. Firstly, fitting probability of time series will be estimated. It can be assumed that the least appropriate type of distribution for the time series will be the normal distribution. Next, VaR and CVaR will be calculated for all given probability distribution. Due to the fact that it is assumed that empirical time series and portfolio time series will correspond to either Student or Laplace distribution then the most appropriate model for estimating VaR and CVaR will be these two distributions.

Influence of Hedging Cost upon Weather Derivatives Pricing

Weather derivatives play a major role in risk management of non-catastrophic weather market. The healthy development of the derivatives market is inseparable from the reasonable pricing of the product itself. As non-traditional financial derivatives, weather derivatives can provide a good risk hedging. Meanwhile, in the weather derivatives market, brokers play an even more important part than in the traditional financial derivatives market. Therefore, when pricing weather derivatives, we must take two factors into consideration, namely, brokers as market makers as well as the impact of their hedging cost on weather derivatives pricing. Based on the expected claims and risk payment of basic derivatives contracts, this paper is going to discuss weather derivatives pricing on the basis of hedging costs, while taking into account the impact of market makers’ hedging costs, risk aversion and existing positions.

Vector at Risk와 대안적인 VaR

The most useful method for financial market risk management may be Value at Risk (VaR) which estimates the maximum loss amount statistically. The VaR is used as a risk measure for one industry. Many real cases estimate VaRs for many industries or nationwide industries; consequently, it is necessary to estimate the VaR for multivariate distributions when a specific portfolio is established. In this paper, the multivariate quantile vector is proposed to estimate VaR for multivariate distribution, and the Vector at Risk for multivariate space is defined based on the quantile vector. When a weight vector for a specific portfolio is given, one point among Vector at Risk could be found as the best VaR which is called as an alternative VaR. The alternative VaR proposed in this work is compared with the VaR of Morgan with bivariate and trivariate examples; in addition, some properties of the alternative VaR are also explored.

Social protection during recessions: evidence from Chile

This article analyzes the main labor market risk management strategies adopted by the Chilean Government during the 1999 recession that was initially related to the Asian financial crisis. Their successes and failures can suggest innovative social protection solutions for other countries. It seems that the 1999–2001 labor reforms and a three-year plan to increase the minimum wage intensified the recession’s effects on unemployment. Probit models indicate that households coped with the recession’s effects by increasing wives’ labor supply but not by withdrawing children from schools. The expansion of employment programs probably helped households to adopt these coping strategies.

Market Risk: Sizing the Scope & Timing of Market Risk Reversals via Cross Market Correlations

We assert that the historically unique pattern of correlation exhibited by the 21day correlation of daily returns between the S&P 500 (SPX) and the U.S. 10Yr Treasury (UST 10Y), the (RVSL) since 2007 both informs on a secular shift in liquid markets trading and can be enlisted as a key metric to gauge the timing and scope of periodic market shocks such as the May 2010, August 2011, October 2012, October 2014 and August 2015 *risk-off moves. *risk-off loosely defined as a sharp decline in Equities of 5% or more.Secular Shift: As the graph in our report illustrates, the vast majority (67%) of *outlier negative correlations since 1962 have been concentrated in just the past eight years. Anecdotal and empirical study suggests that several factors outlined in our Market Risk Management Framework piece have conspired to foster the instances of elevated correlations. A summary of these factors include increased banking and securities regulation, a decrease in the number of liquidity providers and the persistence of aggressive monetary policy globally by Central Banks.We note that our analysis of other risk and return measures (not shown here) including the VIX, credit spreads and stock dispersions, do not demonstrate the same level of persistent and outsized clustering.

Natural gas storage valuation, optimization, market and credit risk management

This paper presents a method for optimizing, pricing and hedging gas storage facilities and leasing contracts in the presence of counter-party credit risk (CCR). A reduced factor, time-independent and Markovian representation of the forward curve is developed that explains 99% of the curve dynamics and incorporates implied volatility seasonality. A system of partial differential equations for valuation and optimization is derived. The resulting PDEs are solved using a specialized implementation of the radial basis function (RBF) technique. The combination of the time-independent, Markovian, framework facilitates the optimization of high-deliverability storage contracts. In addition, as a by-product of the RBF-PDE solution process, a series of analytic RBF expansions for the value of the gas storage contract is produced. These expansions can be differentiated analytically at virtually no cost to obtain hedging statistics. These expansions can also facilitate the millions of individual contract valuations required to price and hedge CCR.

Improving new product development performance by risk management

Purpose The principal aim of this study is to investigate the relationship between technological, marketing, organizational and commercialization risk management on new product development (NPD) performance. Design/methodology/approach Based on questionnaire, the data were collected from a sample of general automotive industry in Iran. Based on theoretical considerations, a model was proposed and descriptive statistic and hierarchical regression were used to measure the relationship between risk management factors and NPD performance. Findings Data analysis revealed that if organization can amplify their knowledge and information about risk and main factors that affect NPD process, not only can they do their work better but can also increase their ability to predict future happenings that affect performance. Research limitations/implications First, due to the relatively small sample size, caution should be exercised when interpreting the results. Second, the data were collected from automotive producer in Iran, which may restrict to some extent generalizability of the findings. Practical implications The results suggest that managers should consider more attention to risk management. If managers spread the risk management in all aspects of the NPD project, total performance will be increased and it can develop the probability of NPD success. Also organizations should perform great market research due to best commercialization. Originality/value Past researches have presented complete information about NPD process. But identifying and considering the effect of the risk management parameters that are connected to the NPD process were the main thrusts to perform the study. In this paper, based on past research about risk management of NPD, the extra aspect of process that can improve total performance of NPD has been examined.

Predicting Systemic Risk with Entropic Indicators

This paper concentrates on quantifying the behavioral aspects of systemic risk by using a novel approach based on entropy. More specifically, we study aggregate market expectations and the predictability of systemic risk before and during the financial crisis in 2008. Two underlying signals for estimating entropic risk measures are considered: (i) skewness premium of deepest out‐of‐the‐money options; and (ii) implied volatility ratio in regard to deepest out‐of‐the‐money options. The findings confirm the predictive and contemporaneous usefulness of our entropy setting in market risk management. The degree of predictability is closely linked to both the type of entropy and the nature of the underlying signal. Copyright © 2016 John Wiley & Sons, Ltd.

Market Risk Management in a Post-Basel II Regulatory Environment

We propose a novel method of Mean-Capital Requirement portfolio optimization. The optimization is performed using a parallel framework for optimization based on the Non-dominated Sorting Genetic Algorithm II. Capital requirements for market risk include an additional stress component introduced by the recent Basel 2.5 regulation. Our optimization with the Basel 2.5 formula in the objective function produces superior results to those of the old (Basel II) formula in stress scenarios in which the correlations of asset returns change considerably. These improvements are achieved at the expense of reduced cardinality of Pareto-optimal portfolios. This reduced cardinality (and thus portfolio diversification) in periods of relatively low market volatility may have unintended consequences for banks’ risk exposure.

High performance computing in multi-scale modeling, graph science and meta-heuristic optimization

One of the main activities within the Group for Scientific Computing at the Faculty of Science are methods for efficiently utilizing real parallel architectures, typically clusters of SMP nodes, shared-memory systems, and GPUs. Focus is on the design, development and implementation of parallel algorithms and data structures for fundamental scientific and engineering problems. Message Passing Interface (MPI) is an important paradigm that still poses interesting design and implementation problems, especially combined with other programming models, like CUDA. In addition to standard HPC (High Performance Computing) technology stack, the Group also utilizes computing stacks like Hadoop and Spark. In this paper we present a short review of the recent research of the Group, focused on large-scale applications in various research fields with references to original articles. The first part considers multi-scale muscle modeling in mixed MPI-CUDA environment. In our approach, a finite element macro model is coupled with the microscopic Huxley kinetics model. The original approach in scheduling tasks within multi-scale simulation ensures good load balance, leading to speed-up of over two orders of magnitude and high scalability. The second part considers application of HPC in graph science for the task of establishing the basic structural features of the minimum-ABC index trees. In order to analyze large amounts of data (all trees of certain order) we utilize grid computing services like storage and computing in order to reduce analysis time up to three orders of magnitude. The last part presents WoBinGO framework for solving optimization problems on HPC resources. It overcomes the shortcomings of earlier static pilot-job frameworks by providing elastic resource provisioning using adaptive allocation of jobs with limited lifetime. The obtained results show that despite WoBinGO's adaptive and frugal allocation of computing resources, it provides significant speed-up when dealing with problems with computationally expensive evaluations, as found in hydro-informatics and market risk management.

Influence of Hedging Cost upon Weather Derivatives Pricing

Weather derivatives play a major role in risk management of non-catastrophic weather market. The healthy development of the derivatives market is inseparable from the reasonable pricing of the product itself. As non-traditional financial derivatives, weather derivatives can provide a good risk hedging. Meanwhile, in the weather derivatives market, brokers play an even more important part than in the traditional financial derivatives market. Therefore, when pricing weather derivatives, we must take two factors into consideration, namely, brokers as market makers as well as the impact of their hedging cost on weather derivatives pricing. Based on the expected claims and risk payment of basic derivatives contracts, this paper is going to discuss weather derivatives pricing on the basis of hedging costs, while taking into account the impact of market makers’ hedging costs, risk aversion and existing positions.

Backtesting Value-at-Risk: A Generalized Markov Framework

Testing the validity of Value-at-Risk (VaR) forecasts, or backtesting, is an integral part of modern market risk management and regulation. This is often done by applying independence and coverage tests developed in Christoffersen (1998) to so-called hit-sequences derived from VaR forecasts and realized losses. However, as pointed out in the literature, see Christoffersen (2004), these aforementioned tests suffer from low rejection frequencies, or (empirical) power, when applied to hit-sequences derived from simulations matching empirical stylized characteristics of return data. One key observation of the studies is that non-Markovian behavior in the hit-sequences may cause the observed lower power performance. To allow for non-Markovian behavior, we propose to generalize the backtest framework for Value-at-Risk forecasts, by extending the original first order dependence of Christoffersen (1998) to allow for a higher, or k’th, order dependence. We provide closed form expressions for the tests as well as asymptotic theory. Not only do the generalized tests have power against k’th order dependence by definition, but also included simulations indicate improved power performance when replicating the aforementioned studies.

시장위험관리와 감사품질의 융합을 통한 공정가치 서열체계의 자본비용에 미치는 영향에 대한 연구

The data of fair value hierarchy is expected to contain different degree of measurement error, information asymmetry, and information risk by the level of hierarchy. Thus, this study examines how hierarchy of fair value discriminately influences on companies’ cost of capital. Through regression analysis of corporations listed from 2011 to 2014, it turns out that the regression coefficient of level 1 and 2 of fair value variable vary their rank by cost of capital types, while level 3 contains the highest regression coefficient for every cost of capital variable. In addition, further study of how the relevance between cost of capital and the fair value hierarchy gets affected by market risk management level and audit quality finds no consistent results. However, by analyzing the effect of coincident interaction through the convergence of market risk management and audit quality, when audit quality and market risk management level are high, the effect of relieving cost of capital of Level 3 gets the highest. In conclusion, fair value hierarchy data seems to affect discriminately on cost of capital by involved information risk, and the information risk could decrease by the level of market risk management and audit quality. •

ANALISIS TINGKAT KESEHATAN BANK SYARIAH MANDIRI PERIODE 2011-2013 DALAM PERSPEKTIF RASIO CAMELS

This study aims to measure the health of commercial banks based on Islamic principles by using CAMELS ratio. Contributions from the application of the CAMELS ratio against the Bank Syariah Mandiri in order to assess the factors Capital, Assets, Management, Profitability, Liquidity and Sensitivity. If Bank Syariah Mandiri attention to the ratio of C (Capital) maintain and anticipate emerging risks. Additionally, using the ratio of A (Asset) anticipate the risk of default of the financing provided. The ratio of M (Management) to manage and run the business in accordance with the principles of risk management and capital adequacy of the precautionary principle. The ratio E (Earnings) address the problem of losses, raising capital in creating a profit during a predetermined period and can control the operating expenses to operating income. Then, the ratio L (Liquidity) keeping and maintaining a sufficient level of liquidity, and the latter ratio S (Sensitivity) made into a very low market risk and market risk management is carried out effectively and consistently.
 In this case, the study of Bank Syariah Mandiri period 2011-2013 using CAMELS ratio obtains a good picture of the plight, healthy or not healthy cycle of Bank Syariah Mandiri or financial position of the Bank Syariah Mandiri. Researcher expects that Bank Syariah Mandiri can predict bankruptcy and financial benefit ratio test in predicting a good profit in the period 2011-2013 and the future.

Methods and Models of Market Risk Stress-Testing of the Portfolio of Financial Instruments

Amid instability of financial markets and macroeconomic situation the necessity of improving bank risk-management instrument arises. New economic reality defines the need for searching for more advanced approaches of estimating banks vulnerability to exceptional, but plausible events. Stress-testing belongs to such instruments. The paper reviews and compares the models of market risk stress-testing of the portfolio of different financial instruments. These days the topic of the paper is highly acute due to the fact that now stress-testing is becoming an integral part of anticrisis risk-management amid macroeconomic instability and appearance of new risks together with close interest to the problem of risk-aggregation. The paper outlines the notion of stress-testing and gives coverage of goals, functions of stress-tests and main criteria for market risk stress-testing classification. The paper also stresses special aspects of scenario analysis. Novelty of the research is explained by elaborating the programme of aggregated complex multifactor stress-testing of the portfolio risk based on scenario analysis. The paper highlights modern Russian and foreign models of stress-testing both on solo-basis and complex. The paper lays emphasis on the results of stress-testing and revaluations of positions for all three complex models: methodology of the Central Bank of stress-testing portfolio risk, model relying on correlations analysis and copula model. The models of stress-testing on solo-basis are different for each financial instrument. Parametric StressVaR model is applicable to shares and options stress-testing;model based on "Grek" indicators is used for options; for euroobligation regional factor model is used. Finally some theoretical recommendations about managing market risk of the portfolio are given.

Economic Capital for Market Risk

The interaction of capital and risk for trading and treasury units is of primary interest in the corporate governance of banks as it links operational profitability and strategic risk management. During the financial crisis, several banks’ trading units suffered significantly higher losses than their risk capital charged based on value-at-risk constraints. There is a structural inconsistency between strategic risk management with a one-year internal capital adequacy assessment process and operating risk management with a ten-day risk horizon for trading units.A new risk budgeting scheme aligns bank risk appetite on an annual basis with operating short-term risk limits. A bank assigns an annual risk budget to its market risk managers. The annual risk budget equals the probability of an annual loss that is higher than a predefined capital-at-risk. Managers’ risk consumption equals the probability of a year-to-date loss in excess of the capital-at-risk at the 10-day risk horizon. As soon as the risk manager has completely consumed his annual risk budget, he immediately has to hedge his positions. The more risk a manager takes and consumes today, the more likely he will be restricted in the future. This relation forces the risk taker to run market risk in a conscious and far-sighted manner.

Entrepreneurial failure: Statistical and psychological explanations

Research summary: Entrepreneurial start‐ups suffer high rates of business failure. Previous research on entrepreneurial failure has focused on two kinds of explanations: statistical and psychological. Statistical explanations attribute excess entry to random errors made by boundedly rational entrepreneurs attempting to estimate business opportunities in risky markets. Psychological explanations focus on entrepreneurial overconfidence and competition neglect. These explanations emerged independently and have not been tested or compared in the same study. In this experimental study, we distinguish entrepreneurial markets from other types of markets and test statistical and psychological hypotheses for all market types. We find that excess entry is significantly greater in small, risky markets than in other market types, and that confidence levels account for excess entry, over and above the effects of unbiased statistical errors.Managerial summary: How can we explain the fact that most entrepreneurial ventures fail within five years? Market risk, inadequate capital and inexperienced management certainly play a role. However, from an economic point of view, it seems odd that inexperienced, under‐funded people continue to engage in risky behavior that is widely known to fail. We conducted experiments that tested two explanations of entrepreneurial failure. The first explanation – the statistical hypothesis – argues that entrepreneurship involves high uncertainty, so random errors are inevitable and can produce excess entry (or under‐entry). The second explanation – the psychological hypothesis – says that entrepreneurs' mistakes are not random but skewed heavily toward excess entry; hence, their decisions are distorted by psychological factors such as overconfidence. Our experiments found support for both of these explanations. Random errors under uncertainty explained 60% of the excess entry in our experiments. However, the overconfidence hypothesis correctly predicted that excess entry exceeds under‐entry, and our psychological measures of overconfidence found support in the data. We also found that the markets that most often attract entrepreneurial investment – emerging markets with high uncertainty – were the markets most conducive to excess entry, due to a combination of psychological and market factors. Hence, we conclude that potential entrepreneurs should pay less attention to their own abilities and aspirations, and more attention to the external realities of competition in the marketplace. Copyright © 2015 John Wiley & Sons, Ltd.

Risk management for international portfolios with basket options: A multi-stage stochastic programming approach

The authors consider the problem of active international portfolio management with basket options to achieve optimal asset allocation and combined market risk and currency risk management via multi-stage stochastic programming (MSSP). The authors note particularly the novel consideration and significant benefit of basket options in the context of portfolio optimization and risk management. Extensive empirical tests strongly demonstrate that basket options consistently have more clearly improvement on portfolio performances than a portfolio of vanilla options written on the same underlying assets. The authors further show that the MSSP model provides as a supportive tool for asset allocation, and a suitable test bed to empirically investigate the performance of alternative strategies.

Market Risk and Bank Specific Determinants of Commercial Banks in Malaysia

Market risk is one of the important risks in banking system. With a myriad number of products, market risk happens when change in net asset value due to changes in equity, commodity prices and exchange rate. This paper is an attempt to identify the factors that determine market risk in bank and to compare that risk determinants between conventional and Islamic banking systems in Malaysia. The unique duality banking system in Malaysia, namely the conventional and Islamic banking system would provide comprehensive determinants of market risk in banking sector. The dataset is constructed from 21 conventional banks and 16 Islamic banks with the year of observation within 2008-2014. Total loan/ financing, loan loss provision, total equity, GAP, interest expenses, short term investment, size, non- interest income and management efficiency are factors that were used in this study. Employing panel data analysis, the result revealed that GAP has strong relationship with market risk. Our findings are not only significant to both bank managers as well as investors, since they the findings will enable them to fully assess the effects of different strategic choices on a bank’s risk profile but also contributing in terms of enriching and enhancing literature on market risk management of Islamic and conventional banks. Establishment of a comprehensive market risk management system in both banking system should be a prerequisite as it contributes to overall risk management system of the bank.