Value At Risk: Recent Advances

Khindanova, Irina; Rachev, Svetlozar T.

doi:10.1201/9780429123610-18

Cited by 5 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In more specific applications such as the field of medical physics, fixed terms of model and code, the lack of data for adjusting the models, and the complexity of combining different disciplines in a single computational tool all limit the use of Monte Carlo simulations [23]. In the value-at-risk area, Monte Carlo simulations lack the ability to keenly capture the phenomena observed in financial data, such as timevarying fluctuations and long-term dependence [24].…”

Section: Limitationsmentioning

confidence: 99%

“…As a popular research method or data processing method, future research should focus on the integration with other methods and fields. For instance, in the field of nuclear physics, the currents in the effective field theory (EFT) yield constructed new insights into the reactions of light and medium-mass nuclei, neutron matter, and electroweak atoms [24]. In the field of medical physics, emission tomography system is modified on Monte Carlo simulations of core-based imaging systems [25].…”

Section: Future Outlooksmentioning

confidence: 99%

See 1 more Smart Citation

Principle and Applications of Monte-Carlo Simulation in Forecasting, Algorithm and Health Risk Assessment

Dou

2024

HSET

View full text Add to dashboard Cite

Monte Carlo simulation, as a technique to reverse parameters by random sampling in known data, is widely used in many fields such as finance, computer and engineering. While introducing the basic concepts and related principles of Monte Carlo simulation, this paper will focus on three new applications of Monte Carlo simulation in electricity price prediction, algorithm and health risk assessment. The limitations and future development of the Monte Carlo simulation are discussed later. Future research should solve the defects of Monte Carlo simulation with long computing consumption time, lack of evaluation method and strict sampling requirements, and enhance the adaptability of this method by combining the problems worth research in various fields. This paper hopes to provide the reader with the relevant background knowledge of Monte Carlo simulations to facilitate the application of Monte Carlo simulation to complex problems in more domains. Overall, these results shed light on guiding further exploration of applications based on Monte Carlo Simulations.

show abstract

Section: Limitationsmentioning

confidence: 99%

Section: Future Outlooksmentioning

confidence: 99%

Principle and Applications of Monte-Carlo Simulation in Forecasting, Algorithm and Health Risk Assessment

Dou

2024

HSET

View full text Add to dashboard Cite

show abstract

“…Where ( is the quantile to of standard Student-t distribution with degrees of freedom , and is the number of data observations, and assuming a negative value to a smallest . (Tsay, 2005;Hu, 2008;Khindanova, 2000).…”

Section: Value-at-risk Of Standard Student-t Approachmentioning

confidence: 99%

Risk Analysis on Foreign Exchange Using Value-at-Risk Parametric Approach

Susanto

Riaman²

2022

ijgor

View full text Add to dashboard Cite

Foreign Exchange or usually known as Forex are one of the most famous investment objects. When investing in Forex, it is necessary to know the movements of the foreign exchange price as well as the risk that might happen. The purpose of this study is to predict the level of risk, seeing the characteristics of foreign exchange, and compare which foreign exchange is better to invest in. The Value-At-Risk (VaR) models used to predict the risk of the foreign exchange are VaR of standard normal distribution approach, VaR of Student-t distribution approach, and Modified VaR normal. Based on the research, the potential loss for AUD is Rp 9,445.26, CAD is Rp 7,972.62, CHF is Rp 7,073.74, EUR is Rp 6281.90, GBP is Rp 9,234.37, JPY is Rp 10,971.68, SGD is Rp 3,988.65, and USD is Rp 2,896.47 with an assumption that an investor invests as much as Rp 1,000,000.00 to each foreign exchange. USD is the best foreign exchange to choose because it has the lowest potential risk based on its VaR.

show abstract

“…The 1988 Basel Committee signed by G-10 countries imposed risk management on banks, which have motivated the use of some VaR methodology to comply with regulations (Jorion, 2001). Several United States government agencies such as the Federal Reserve and the Security and Exchange Commision (SEC) use or advocate the use of VaR (Khindanova et al, 2000). In the Brazilian context, the Brazilian's Central Bank, requires financial institutions to manage risks based on VaR.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A GARCH-VaR Investigation on the Brazilian Sectoral Stock Indices

et al. 2019

View full text Add to dashboard Cite

In this paper, we have explored operational risk in Brazil by considering different sectoral indices of the Brazilian economy and the GACH Value-at-Risk (GARCH-VaR) estimation approach. We have carried a statistical evaluation of the eight Brazilian sectoral stock indices during different time ranges so that VaR methodologies could be chosen according to the data. We have analyzed the sectoral Brazilian indices during a common time range where we have realized VaR backtests using recent data. The results of the study reveals that VaR may be an effective tool on minimizing risk exposure and potentially to avoid losses when trading in the Brazilian stock market. Furthermore, we have showed that different sectors of the Brazilian economy have significantly different risk behavior. In particular, the consumption and industrial sectoral indices presented the best risk performance. In this sense, we highlight that this type of analysis would be useful to small lenders/investors in evaluating the attractiveness of lending/investing on the Brazilian stock market.

show abstract

Value At Risk: Recent Advances

Cited by 5 publications

References 0 publications

Principle and Applications of Monte-Carlo Simulation in Forecasting, Algorithm and Health Risk Assessment

Principle and Applications of Monte-Carlo Simulation in Forecasting, Algorithm and Health Risk Assessment

Risk Analysis on Foreign Exchange Using Value-at-Risk Parametric Approach

A GARCH-VaR Investigation on the Brazilian Sectoral Stock Indices

Contact Info

Product

Resources

About