Market Risk and Volatility Weighted Historical Simulation after Basel III

2017 ◽  
Author(s):  
Jean-Paul Laurent ◽  
Hassan Omidi Firouzi
Keyword(s):  
Market Risk ◽  
Basel Iii ◽  
Historical Simulation

scholarly journals Dynamics of Risk Factors Affecting the Capital Adequacy Ratio with Special Reference to UCO Bank

2019 ◽  
Vol 8 (2) ◽  
pp. 10-13
Author(s):  
Preeta Sinha ◽  
Protik Basu
Keyword(s):  
Market Risk ◽  
Capital Adequacy ◽  
Basel Iii ◽  
Bank Capital ◽  
Financial Reports ◽  
Factors Affecting ◽  
Operational Risks ◽  
Capital Adequacy Ratio ◽  
Using Data ◽  
Asset Quality

To reinforce the stability of the financial system, policy makers and the Basel committee have proposed Basel accord to ensure that financial institutions maintain sufficient capital buffers. Basel III framework emphasizes on sustained increase in bank capital in order to absorb the potential credit, market and operational risks. The capital adequacy requirement under Basel III norms are directly linked to the PCA (Prompt Corrective action) framework which has disrupted the flow of credit in the economy. Market risk, Credit risk, Operational risk and deposits are some of the factors affecting the capital adequacy ratio (CAR) which influences the bank performances. This study aims at analysing the most important factor responsible for the shrinking liquidity due to adherence of stringent capital adequacy ratio imposed by RBI. Currently 11 public sector Banks out of 21 PSUs under PCA has sequentially shrunk their loan book including UCO Bank. The bank’s asset quality has worsened over the years. Using regression analysis, this paper seeks to study the major determinants of Capital Adequacy ratio using data sets for the period from 2009 to 2018 of UCO bank. The data was collected from the financial reports of the UCO bank for the aforesaid period. Among the parameters considered, it was found that deposits affect the CAR the most and market risk has the lowest impact on CAR.

scholarly journals EVALUATING MEASURES OF MARKET RISK IN CIRCUMSTANCES OF GLOBAL FINANCIAL CRISIS – EMPIRICAL EVIDENCE FROM FIVE COUNTRIES

2013 ◽  
Vol 1 ◽  
pp. 75-81
Author(s):  
Ivica Terzić ◽  
Marko Milojević
Keyword(s):  
Value At Risk ◽  
Global Financial Crisis ◽  
Market Risk ◽  
Var Models ◽  
Risk Models ◽  
Historical Simulation ◽  
Rolling Window ◽  
Independence Properties ◽  
Window Approach ◽  
Metrics Model

The purpose of this paper is to evaluate performance of value-at-risk (VaR) produced by two risk models: historical simulation and Risk Metrics. We perform three backtest: unconditional coverage, independence and conditional coverage. We present results on both VaR 1% and VaR 5% on a one-day horizon for the following indices: S&P 500, DAX, SAX, PX and Belex 15. Our results show that Historical simulation 500 days rolling window approach satisfies unconditional coverage for all tested indices, while Risk Metrics has many rejection cases. On the other hand Risk Metrics model satisfies independence backtest for three indices, while Historical simulation has rejected more times. Based on our strong criteria to accept accuracy of VaR models only if both unconditional coverage and independence properties are satisfied, results indicate that during the crisis period all tested VaR models underestimate the true level of market risk exposure.

scholarly journals Measuring Market Risk of Commercial Banks Implementing VaR with Historical Simulation Approach

2021 ◽  
pp. 79-99
Author(s):  
Minhaz-Ul Haq
Keyword(s):  
Stock Prices ◽  
Commercial Banks ◽  
Value At Risk ◽  
First Generation ◽  
Market Risk ◽  
Jel Classification ◽  
Simulation Approach ◽  
Share Prices ◽  
Historical Simulation ◽  
The Impact

This paper attempts to picture the impact of the market risk of ten commercial banks located in Bangladesh with the help of a non-parametric model known as the Historical Simulation Approach over the course of eight years. These banks' daily stock prices were used as inputs and analyzed in Microsoft Excel by means of Percentile and LN function. The study revealed market risk exposure as third, second-and first-generation banks from the least to the highest. It also pointed out the ups and downs of these banks' share prices in the selected period. Further analysis showed the portfolio VaR estimation for different time intervals. JEL classification numbers: G32. Keywords: Value-at-risk, Historical Simulation, Market Risk, Confidence Interval.

scholarly journals Value-at-Risk Estimation of Equity Market Risk in India

2021 ◽  
Vol 9 (1) ◽  
pp. 1-24
Author(s):  
Jitender
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Moving Average ◽  
Equity Market ◽  
Market Risk ◽  
Financial Instrument ◽  
Historical Simulation ◽  
Distributed Models

Abstract The value-at-risk (Va) method in market risk management is becoming a benchmark for measuring “market risk” for any financial instrument. The present study aims at examining which VaR model best describes the risk arising out of the Indian equity market (Bombay Stock Exchange (BSE) Sensex). Using data from 2006 to 2015, the VaR figures associated with parametric (variance–covariance, Exponentially Weighted Moving Average, Generalized Autoregressive Conditional Heteroskedasticity) and non-parametric (historical simulation and Monte Carlo simulation) methods have been calculated. The study concludes that VaR models based on the assumption of normality underestimate the risk when returns are non-normally distributed. Models that capture fat-tailed behaviour of financial returns (historical simulation) are better able to capture the risk arising out of the financial instrument.

scholarly journals VALUE-AT-RISK (VAR) APPLICATION AT HYPOTHETICAL PORTFOLIOS IN JAKARTA ISLAMIC INDEX

2011 ◽  
Vol 3 (2) ◽  
pp. 153-180
Author(s):  
Dewi Tamara ◽  
Grigory Ryabtsev
Keyword(s):  
At Risk ◽  
Exploratory Study ◽  
Value At Risk ◽  
Market Risk ◽  
Global Crisis ◽  
Historical Simulation ◽  
Level Of Confidence ◽  
Simulation Based ◽  
Increasing Risk

The paper is an exploratory study to apply the method of historical simulation based on the concept of Value at Risk on hypothetical portfolios on Jakarta Islamic Index (JII). Value at Risk is a tool to measure a portfolio’s exposure to market risk. We construct four portfolios based on the frequencies of the companies in Jakarta Islamic Index on the period of 1 January 2008 to 2 August 2010. The portfolio A has 12 companies, Portfolio B has 9 companies, portfolio C has 6 companies and portfolio D has 4 companies. We put the initial investment equivalent to USD 100 and use the rate of 1 USD=Rp 9500. The result of historical simulation applied in the four portfolios shows significant increasing risk on the year 2008 compared to 2009 and 2010. The bigger number of  the member in one portfolio also affects the VaR compared to smaller member. The level of confidence 99% also shows bigger loss compared to 95%. The historical simulation shows the simplest method to estimate the event of increasing risk in Jakarta Islamic Index during the Global Crisis 2008.

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