scholarly journals PERHITUNGAN VALUE AT RISK KUNJUNGAN WISATAWAN ASING KE BALI

2020 ◽  
Vol 9 (1) ◽  
pp. 69
Author(s):  
AGUS PUTU SURYAWAN ◽  
KOMANG DHARMAWAN ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Rapid Development ◽  
Tourism Industry ◽  
Provincial Government ◽  
Confidence Levels ◽  
Tourism Promotion ◽  
Natural Beauty

The development of the tourism industry in Bali is very fast compared to other regions in Indonesia. This is due to the fascination of Bali which fascinates tourists, such as culture, customs and natural beauty. The rapid development of tourism in Bali requires tourism risk management. The purpose of this study is to calculate the Value At Risk (VaR) of Chinese, British and American tourists visiting Bali. The study was conducted using the VaR method with the GARCH (1,1) and GJR (1,1) models. Chinese tourist visit data is homocedasticity so it cannot proceed to GARCH (1.1) and GJR (1.1) modeling. VaR value of British and American tourist visits using the GARCH (1.1) and GJR (1.1) models at 95% confidence levels respectively -69.2% and -43.6 with an average VaR value of -56, 4%, and -69.3% and -44.7% with an average VaR of -57%. This means that if the Bali Government targets the number of tourist visits to be 7,100,000 people with a tourism promotion cost of Rp.134.1 per person, then there will be at least 4,004,400 people visiting Bali. So the investment costs incurred by the Provincial Government of Bali for tourism promotion of Rp. 536,990,040.

scholarly journals Value at Risk and Market Risk: Case of the Regional Securities Exchange

2020 ◽  
Vol 7 (6) ◽  
pp. 19
Author(s):  
Mouhamadou Saliou Diallo
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Financial Crisis ◽  
Value At Risk ◽  
Composite Index ◽  
Market Risk ◽  
Management Approach ◽  
Portfolio Risk ◽  
Confidence Levels ◽  
Determining Factor

The study of the BRVM market risk using the VaR method is a determining factor in assessing the performance of our equity portfolio composed of the BRVM composite index and the BRVM10 index. It has enabled us, with the help of Basel regulations, to use backtesting to determine the minimum amount of capital that an investor must hold per day to protect against risk. The kupiec test enables us to determine the reliability of VaR calculated at different confidence levels. The result of our study confirms, using the extreme VaR method, the robustness of our threshold-based portfolio risk management approach. It also confirms the problem of market attractiveness during times of financial crisis.

Volatility Forecast by Volatility Index and Its Use as a Risk Management Tool Under a Value-at-Risk Approach

2018 ◽  
Vol 21 (02) ◽  
pp. 1850010 ◽  
Author(s):  
Yam Wing Siu
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Risk Premium ◽  
Value At Risk ◽  
Realized Volatility ◽  
Management Tool ◽  
Spot Price ◽  
Pricing Options ◽  
Significance Levels ◽  
Risk Approach

This paper examines the predicting power of the volatility indexes of VIX and VHSI on the future volatilities (or called realized volatility, [Formula: see text] of their respective underlying indexes of S&P500 Index, SPX and Hang Seng Index, HSI. It is found that volatilities indexes of VIX and VHSI, on average, are numerically greater than the realized volatilities of SPX and HSI, respectively. Further analysis indicates that realized volatility, if used for pricing options, would, on some occasions, result in greatest losses of 2.21% and 1.91% of the spot price of SPX and HSI, respectively while the greatest profits are 2.56% and 2.93% of the spot price of SPX and HSI, respectively, making it not an ideal benchmark for validating volatility forecasting techniques in relation to option pricing. Hence, a new benchmark (fair volatility, [Formula: see text] that considers the premium of option and the cost of dynamic hedging the position is proposed accordingly. It reveals that, on average, options priced by volatility indexes contain a risk premium demanded by the option sellers. However, the options could, on some occasions, result in greatest losses of 4.85% and 3.60% of the spot price of SPX and HSI, respectively while the greatest profits are 4.60% and 5.49% of the spot price of SPX and HSI, respectively. Nevertheless, it can still be a valuable tool for risk management. [Formula: see text]-values of various significance levels for value-at-risk and conditional value-at-value have been statistically determined for US, Hong Kong, Australia, India, Japan and Korea markets.

scholarly journals ESTIMATING VALUE-AT-RISK BASED ON NON-NORMAL DISTRIBUTIONS

2015 ◽  
Vol 3 ◽  
pp. 188-195 ◽  
Author(s):  
Mária Bohdalová ◽  
Michal Greguš
Keyword(s):  
At Risk ◽  
Risk Factor ◽  
Value At Risk ◽  
Likelihood Method ◽  
Normal Distributions ◽  
Confidence Levels ◽  
Portfolio Returns ◽  
Distribution Parameters ◽  
Financial Portfolios ◽  
Daily Changes

The article presents a comparative study of parametric linear value-at-risk (VaR) models used for estimating the risk of financial portfolios. We illustrate how to adjust VaR for auto-correlation in portfolio returns. The article presents static and dynamic methodology to compute VaR, based on the assumption that daily changes are independent and identically distributed (normal or non-normal) or auto-correlated in terms of the risk factor dynamics. We estimate the parametric linear VaR over a risk horizon of 1 day and 10 days at 99% and 95% confidence levels for the same data. We compare the parametric VaR and a VaR obtained using Monte Carlo simulations with historical simulations and use the maximum likelihood method to calibrate the distribution parameters of our risk factors. The study investigated whether the parametric linear VaR applies to contemporary risk factor analysis and pertained to selected foreign rates.

scholarly journals Risk management of risk under the Basel Accord: forecasting value‐at‐risk of VIX futures

2011 ◽  
Vol 37 (11) ◽  
pp. 1088-1106 ◽  
Author(s):  
Chia‐lin Chang ◽  
Juan‐Ángel Jiménez‐Martín ◽  
Michael McAleer ◽  
Teodosio Pérez‐Amaral
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Basel Accord ◽  
Vix Futures ◽  
Management Of Risk

Optimal Reciprocal Reinsurance under VaR or TVaR Constraint

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hung-Hsi Huang ◽  
Ching-Ping Wang
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Moral Hazard ◽  
Value At Risk ◽  
Incentive Compatibility ◽  
Regular Form ◽  
Optimal Reinsurance ◽  
The Common ◽  
Risk Constraint ◽  
Management Requirement

Abstract Most existing researches on optimal reinsurance contract are based on an insurer’s viewpoint. However, the optimal reinsurance contract for an insurer is not necessarily to be optimal for a reinsurer. Hence, this study aims to develop the optimal reciprocal reinsurance which satisfies the benefits of both the insurer and reinsurer. Additionally, due to legislative restriction or risk management requirement, the wealth of insurer and reinsurer are frequently imposed upon a VaR (Value-at-Risk) or TVaR (Tail Value-at-Risk) constraint. Therefore, this study develops an optimal reciprocal reinsurance contract which maximizes the common benefits (evaluated by weighted addition of expected utilities) of the insurer and reinsurer subject to their VaR or TVaR constraints. Furthermore, for avoiding moral hazard problem, the developed contract is additionally restricted to a regular form or incentive compatibility (both indemnity schedule and retained loss schedule are continuously nondecreasing).

The Value-at-Risk Methodology of Basel II and Basel III

2014 ◽  
pp. 100-114 ◽  
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Basel Ii ◽  
Risk Measurement ◽  
Capital Adequacy ◽  
Basel Iii ◽  
Regulatory Capital ◽  
Advantages And Disadvantages ◽  
Risk Methodology

This chapter examines the advantages and disadvantages of the risk estimate approach—Value-at-Risk (VaR) which has been extensively embraced by regulators and practitioners in financial markets under the Basel II & III framework as the basis of risk measurement, both for the purpose of ensuring regulatory capital adequacy, and risk management and strategic planning at industry level.

Arbor City Community Foundation (A): The Foundation

2017 ◽  
pp. 1-3 ◽  
Author(s):  
Karl Schmedders ◽  
Russell Walker ◽  
Michael Stritch
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Management Policy ◽  
City Region ◽  
Portfolio Rebalancing ◽  
City Community ◽  
Portfolio Returns ◽  
The Impact ◽  
Community Foundation

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in Illinois in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the value-at-risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses. The questions in Part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF's risk management. In Part (B) the foundation receives a major donation. As a result, the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund's new portfolio and to perform a portfolio rebalancing analysis.Understanding the concept of value at risk (VaR); Calculating daily and monthly VaR by two different methods, the historical and the parametric approach; Interpreting the results of VaR calculations; Understanding the role of diversification for managing risk; Evaluating the impact of portfolio rebalancing on the overall risk of a portfolio.

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