Value at Risk Research Papers (original) (raw)

For risk analyses not only knowledge about the impact of different types of hazards, but also information about the elements and values at risk is necessary. This article introduces a methodology for a countrywide estimation of asset... more

For risk analyses not only knowledge about the impact of different types of hazards, but also information about the elements and values at risk is necessary. This article introduces a methodology for a countrywide estimation of asset values for commercial and industrial properties using Germany as an example. It consists of a financial appraisal of asset values on the municipal level and a further disaggregation by means of land use data. Novelties are the distinction of 60 economic activities, the consideration of production site sizes and the application of a dasymetric mapping technique for a sector-specific estimation and disaggregation of asset values. A validation with empirical data confirms the feasibility of the calculation. The resulting maps can be used for loss estimations e.g. in the framework of cost–benefit analyses that aim to evaluate hazard mitigation measures or for portfolio analyses by banks and insurance companies. The approach can be used for other countries if the necessary data is available (mainly in industrialized countries). In any case, it reveals the critical points when estimating commercial and industrial asset values.

Extreme returns in stock returns need to be captured for a successful risk management function to estimate unexpected loss in portfolio. Traditional value-at-risk models based on parametric models are not able to capture the extremes in... more

Extreme returns in stock returns need to be captured for a successful risk management function to estimate unexpected loss in portfolio. Traditional value-at-risk models based on parametric models are not able to capture the extremes in emerging markets where high volatility and nonlinear behaviors in returns are observed. The Extreme Value Theory (EVT) with conditional quantile proposed by McNeil and Frey (2000) is based on the central limit theorem applied to the extremes rater than mean of the return distribution. It limits the distribution of extreme returns always has the same form without relying on the distribution of the parent variable. This paper uses 8 filtered EVT models created with conditional quantile to estimate value-at-risk for the Istanbul Stock Exchange (ISE). The performances of the filtered expected shortfall models are compared to those of GARCH, GARCH with student-t distribution, GARCH with skewed student-t distribution and FIGARCH by using alternative back-t...

The aim of this paper was to accurately and efficiently forecast from multivariate generalized autoregressive conditional heteroscedastic models. The Rotated Dynamic Conditional Correlation (RDCC) model with the Normal, Student’s-t and... more

The aim of this paper was to accurately and efficiently forecast from multivariate generalized autoregressive conditional heteroscedastic models. The Rotated Dynamic Conditional Correlation (RDCC) model with the Normal, Student’s-t and Multivariate Exponential Power distributions for errors were used to account for heavy tails commonly observed in financial time series data. The daily stock price data of Karachi, Bombay, Kuala Lumpur and Singapore stock exchanges from January 2008 to December 2017 were used. The predictive capability of RDCC models, with various error distributions, in forecasting one-day-ahead Value-at-Risk (VaR) was assessed by several back-testing procedures. The empirical results of the study revealed that the RDCC model with Student’s-t distribution produced more accurate and reliable risk forecasts than other competing models. To cite this article [Farid, S. & Iqbal, F. (2020). Forecasting Value-at-Risk of Asian Stock Markets Using the RDCC-GARCH Model Under D...

Modeling and forecasting the volatility of Brazilian asset returns: a realized

Default probabilities (PDs) and correlations play a crucial role in the New Basel Capital Accord. In commercial credit risk models they are an important constituent. Yet, modeling and estimation of PDs and correlations is still under... more

Default probabilities (PDs) and correlations play a crucial role in the New Basel Capital Accord. In commercial credit risk models they are an important constituent. Yet, modeling and estimation of PDs and correlations is still under active discussion. We show how the Basel II one factor model which is used to calibrate risk weights can be extended to a model for estimating PDs and correlations. The important advantage of this model is that it uses actual information about the point in time of the credit cycle. Thus, uncertainties about the parameters which are needed for Value-at-Risk calculations in portfolio models may be substantially reduced. First empirical evidence for the appropriateness of the models and underlying risk factors is given with S&P data.

This paper studies a strategy that minimizes the risk of a position in a zero coupon bond by buying a percentage of a put option, subject to a fixed budget available for hedging. We consider two popular risk measures: Value-at-Risk(VaR)... more

This paper studies a strategy that minimizes the risk of a position in a zero coupon bond by buying a percentage of a put option, subject to a fixed budget available for hedging. We consider two popular risk measures: Value-at-Risk(VaR) and Tail Value-at-Risk (TVaR). We elaborate a formula for determining the optimal strike price for this put option in case of a Hull-White stochastic interest rate model. We calibrate the Hull-White model parameters to a set of cap prices, in order to provide a credible numerical illustration. We demonstrate the relevance of searching the optimal strike price, since moving away from the optimum implies a loss, due to an increased (T)VaR. In this way, we extend the results of [Ahn et al., 1999], who minimize VaR for a position in a share.

Le rôle du traitement de l’information dans le cadre de l’intermédiation bancaire est de première importance. La banque peut accéder à différents types d’information pour appréhender la gestion du risque par couverture de la Value at Risk... more

Le rôle du traitement de l’information dans le cadre de l’intermédiation bancaire est de première importance. La banque peut accéder à différents types d’information pour appréhender la gestion du risque par couverture de la Value at Risk par allocation de fonds propres. L’information hard, contenue dans les documents comptables et produite grâce à des modèles de score, est quantitative et

El presente Trabajo Fin de Master plantea como objetivo la aplicación práctica del modelo GARCH y distribuciones de colas anchas en el cálculo del riesgo de mercado, mediante metodología VeR Paramétrica, en una cartera de renta variable... more

El presente Trabajo Fin de Master plantea como objetivo la aplicación práctica del modelo GARCH y distribuciones de colas anchas en el cálculo del riesgo de mercado, mediante metodología VeR Paramétrica, en una cartera de renta variable en el periodo de 1/1/2014 al 31/12/2018 para los principales títulos del sector bancario y financiero que cotizan en el mercado bursátil español y que pertenecen al IBEX-35. Se escogen los valores cotizados de Santander, BBVA, CaixaBank, Sabadell y Bankia. Se realiza metodología empírica mediante técnicas matemáticas, estadísticas y econométricas. Se comparan resultados obtenidos entre distribución normal y distribución T-Student (colas anchas), y según la forma de cálculo de la volatilidad (Estándar o GARCH). Finalmente se realiza el Backtesting en el periodo de 1/1/2019 al 30/6/2019 para los resultados de la cartera y se establecen las conclusiones finales del estudio.

Value at risk is currently the standard in risk reporting. In this document we will describe methods to more accurately assess the risk in a portfolio with derivatives like options. We will describe the delta-gamma method and Monte Carlo... more

Value at risk is currently the standard in risk reporting. In this document we will describe methods to more accurately assess the risk in a portfolio with derivatives like options. We will describe the delta-gamma method and Monte Carlo simulation. These specifications can be used to enhance a classical Value at Risk model. To show the practical implementation we also give some VBA pseudo-code structures that can be used in a program like Excel

Dalam penulisan ini akan dilakukan pembahsan menganai pembentkan portofolio optimum yang berisi sejumlah saham yang tergolong dalam LQ45. Pemilihan saham kategori LQ45 karena liquiditas saham yang tergolong LQ45 sangat liquid dan banyak... more

Dalam penulisan ini akan dilakukan pembahsan menganai pembentkan portofolio optimum yang berisi sejumlah saham yang tergolong dalam LQ45. Pemilihan saham kategori LQ45 karena liquiditas saham yang tergolong LQ45 sangat liquid dan banyak peminat di pasar saham. Data yang digunakan dalam penelitian ini data saham yang digunakan adalah periode 1 january 2016 – 31 maret 2016 data harian sebagai sampel dalam penghitungan besaran risiko ( variance),expected return dari masing-masing saham , dan nilai VaR dengan metode historical price dan penentuan portofolio yang optimal. Dari hasil pengolahan data ditemukan bahwa kombinasi dua saham yang memberikan risiko terendah berdasarkan rumus VaR untuk portofolio kombinasi dua saham adalah portofolio dengan saham HMSP dan BBCAdimana nilai VaR portofolio yang ditanggung oleh investor jika menginvestasikan dana portofolio ini sebesar Rp35,973,642.78 dari total dana 1M.

لم تعُد المخاطر قيداّ على الأعمال بل أصبحت مصدراً هاماً من مصادر الميزة التنافسية، حيث باتت المخاطر جزءاً هاماً من بيئة الأعمال بصورة عامة، فبدون مخاطر لا يوجد أرباح، وبالمقابل إن تجاهل المخاطر يمكن أن يهدد أكبر المؤسسات بالفشل والإفلاس،... more

لم تعُد المخاطر قيداّ على الأعمال بل أصبحت مصدراً هاماً من مصادر الميزة التنافسية، حيث باتت المخاطر جزءاً هاماً من بيئة الأعمال بصورة عامة، فبدون مخاطر لا يوجد أرباح، وبالمقابل إن تجاهل المخاطر يمكن أن يهدد أكبر المؤسسات بالفشل والإفلاس، وينعكس هذا التهديد على سمعة المؤسسة واستقرارها المالي واستمرارية وجودها.
هذا وإن موضوع المخاطر وإدارتها من الموضوعات التي شغلت فكر الكثير من الباحثين الأكاديميين والتطبيقيين على حدٍ سواء، نظراً لما لها من أثر جوهري في سلامة واستقرار المنشآت التجارية والمؤسسات المالية، وقد زادت أهمية إدارة المخاطر بعد اندلاع الأزمات المالية المتتالية التي عصفت بالنظام المالي والمصرفي العالمي، ما استوجب ظهور صناعة مالية مبتكرة تحمي المنشآت من المخاطر المختلفة عُرفت بصناعة إدارة المخاطر لها منتجوها وأدواتها وأسواقها.
ومن هنا يأتي هذا الكتاب ليقدم للقارئ أهم موضوعات المخاطر المالية والمصرفية وإدارتها الحديثة وتطبيقها على أرض الواقع، حيث تضمن الفصل الأول لمحة سريعة عن مفهوم إدارة المخاطر ومسبباتها وأنواعها وأساليب إدارتها.
أما الفصل الثاني فقد خُصِصَ للحديث عن المخاطر المالية (خطر الائتمان، خطر سعر الفائدة، خطر سعر الصرف) من حيث التعريف بهذه المخاطر وقياس الخسارة الناتجة عنها باستخدام النماذج الرياضية والاحصائية، واقتراح أساليب وتقنيات داخلية لإدارة هذه المخاطر بشكل ذاتي، مع سرد أمثلة وحالات تطبيقية توضح كيفية استخدام هذه الأساليب والتقنيات.
في حين تضمن الفصل الثالث شرح وتطبيق أدوات الهندسة المالية المصممة لإدارة المخاطر (المشتقات المالية)، المؤلفة من عقود الخيارات والعقود الآجلة والعقود المستقبلية وعقود المبادلات. حيث تم شرح هذه العقود بطريقة مبسطة وتوضيح آلية تطبيقها على أرض الواقع، مع اقتراح استراتيجيات محددة لاستخدام هذه الأدوات بشكل سليم.
أما الفصل الرابع فقد خُصص للحديث عن للمخاطر المصرفية المؤلفة من خطر المحفظة الائتمانية، خطر محفظة السوق، خطر السيولة المصرفية، خطر التشغيل، حيث انطلق الكاتب من شرح القوائم المالية الموحدة للمصارف وتوضيح أهم البنود الرئيسية فيها، ثم ناقش المخاطر المصرفية وأساليب إدارتها بطريقة عملية تضمنت حالات تطبيقية متعددة.
وقد خٌصص الفصل الخامس للحديث عن لجنة بازل للرقابة المصرفية، التي تعد اللاعب الرئيسي في مجال وضع القواعد الاحترازية التي تساعد على تحقيق سلامة النظام المصرفي على المستويين المحلي والعالمي. حيث تم التوسع في شرح الأساليب المقترحة من قبل اللجنة لإدارة المخاطر المصرفية وطرح الحالات العملية والتطبيقية التي توضح كيفية استخدام هذه الأساليب.

Value-at-Risk (VaR) is the most popular tool for risk measurement in ban- king and finance industry today. The study estimates the volatility for mar- ket risk measurement to calculate diversified VaR. Using Multivariate GARCH BEKK... more

Value-at-Risk (VaR) is the most popular tool for risk measurement in ban- king and finance industry today. The study estimates the volatility for mar- ket risk measurement to calculate diversified VaR. Using Multivariate GARCH BEKK proposed by Engle and Kroner (1993) and variance-covariance matrix methods, this paper compares both methods in generating volatility forecast to estimate diversified VaR particularly for market risk. The paper examines three exchange rates: GBP/USD, USD/JPY, and USD/SGD, from the period of 2000 to 2005. The empirical result shows that GARCH BEKK model performs better, though has more sophisticated specification, than variance-covariance matrix method in estimating the volatility. The estimation results are as follows: VaR estimation generated by GARCH BEKK is 0.1388% which leads to capital charge of 5.2063%; while estimation generated by variance-covariance matrix is 0.1982% which leads to capital charge of 7.433%. The results also show that the volatility changes significantly every 125 observations or at least once in three months. This concludes that volatility forecast should be evaluated at least every three months.

Financial time series analysis deals with the understanding of data collected on financial markets. Several parametric distribution models have been entertained for describing, estimating and predicting the dynamics of financial time... more

Financial time series analysis deals with the understanding of data collected on financial markets. Several parametric distribution models have been entertained for describing, estimating and predicting the dynamics of financial time series. Alternatively, this article considers a Bayesian semiparametric approach. In particular, the usual parametric distributional assumptions of the GARCH-type models are relaxed by entertaining the class of location-scale mixtures

Value at Risk (VaR) is a common statistical method that has been used recently to measure market risk. In other word, it is a risk measure which can predict the maximum loss over the portfolio at a certain level of confidence. Value at... more

Value at Risk (VaR) is a common statistical method that has been used recently to measure market risk. In other word, it is a risk measure which can predict the maximum loss over the portfolio at a certain level of confidence. Value at risk, in general, is used by the banks during the calculation process to determine the minimum capital amount against market risks. Furthermore, it can also be exploited to calculate the maximum loss at investment portfolios designated for stock markets. The purpose of this study is to compare the VaR and Markowitz efficient frontier approach in terms of portfolio risks. Along with this angle, we have calculated the optimal portfolio by Portfolio Optimization method based on average variance calculated from the daily closing prices of the ninety-one stocks traded under the Ulusal-100 index of the Istanbul Stock Exchange in 2011. Then, for each of designated portfolios, Monte-Carlo Simulation Method was run for thousand times to calculate the VaR. Finally, we concluded that there is a parallel relationship between the calculated optimum portfolio risks and VaR values of the portfolios.

Copulae provide investors with tools to model the dependency structure among financial products. The choice of copulae plays an important role in successful copula applications. However, selecting copulae usually relies on general... more

Copulae provide investors with tools to model the dependency structure among financial products. The choice of copulae plays an important role in successful copula applications. However, selecting copulae usually relies on general goodness-of-fit (GoF) tests which are independent of the particular financial problem. This paper ¯rst proposes a pair-copula-GARCH model to construct the dependency structure and simulate the joint returns of five U.S. equites. It then discusses copula selection problem from the perspective of downside risk management with the so-called D-vine structure, which considers the Joe-Clayton copula and the Student t copula as building blocks for the vine pair-copula decomposition. Value at risk, expected shortfall, and Omega function are considered as downside risk measures in this study. As an alternative to the traditional bootstrap approaches, the proposed pair-copula-GARCH model provides simulated asset returns for generating future scenarios of portfolio v...