Results 11 to 20 of about 4,544 (205)
, 2000 With the implementation of Value-at-Risk (VaR) models a new chapter of risk management was opened. Their ultimate goal is to quantify the uncertainty about the amount that may be lost or gained on a portfolio over a given period of time. Most generally, the uncertainty is expressed by a forecast distribution P t+1 for period t+1 associated with the ...
Härdle, Wolfgang, Stahl, Gerhard
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A K-Means Classification and Entropy Pooling Portfolio Strategy for Small and Large Capitalization Cryptocurrencies [PDF]
Entropy, 2023 In this study, we propose three portfolio strategies: allocation based on the normality assumption, the skewed-Student t distribution, and the entropy pooling (EP) method for 14 small- and large-capitalization (cap) cryptocurrencies.
Jules Clement Mba +1 more
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Backtesting the Expected Shortfall [PDF]
, 2021 Backtesting of risk measure estimates is an integral part for an effective risk management. With the growing importance of the Expected Shortfall (ES) to potentially replace the Value at Risk (VaR) as a primary measure for market risk this also calls for
Spring, Konstantin
core +3 more sources
Studying the effects of USING GARCH-EVT-COPULA METHOD TO ESTIMATE VALUE AT RISK OF PORTFOLIO [PDF]
Iranian Journal of Finance, 1999 Value at Risk (VaR) plays a central role in risk management. There are several approaches for the estimation of VaR, such as historical simulation, the variance-covariance and the Monte Carlo approaches. This work presents portfolio VaR using an approach
Ghodratollah Emamverdi
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The Accuracy of Risk Measurement Models on Bitcoin Market during COVID-19 Pandemic
Risks, 2021 Since late 2019, during one of the largest pandemics in history, COVID-19, global economic recession has continued. Therefore, investors seek an alternative investment that generates profits during this financially risky situation.
Danai Likitratcharoen +3 more
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A review of backtesting and backtesting procedures [PDF]
The Journal of Risk, 2005 This paper reviews a variety of backtests that examine the adequacy of Value-at-Risk (VaR) measures. These backtesting procedures are reviewed from both a statistical and risk management perspective. The properties of unconditional coverage and independence are defined and their relation to backtesting procedures is discussed.
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The Adjustment of VaR to the Empirical Distribution of Returns [PDF]
Theoretical and Applied Economics, 2006 Basel II Recommendations concerning internal rating based models approach for financial institutions and the success of RiskMetrics made Value-at-Risk (VaR) is the most important risk measurement instrument at international level.
Radu Lupu
doaj +1 more source
The Probability of Backtest Overfitting [PDF]
The Journal of Computational Finance, 2013 Most firms and portfolio managers rely on backtests (or historical simulations of performance) to select investment strategies and allocate them capital. Standard statistical techniques designed to prevent regression over-fitting, such as hold-out, tend to be unreliable and inaccurate in the context of investment backtests.
David H. Bailey +3 more
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ANALYSIS OF THE INVESTMENT ARBITRAGE STRATEGY USING FINANCIAL MULTIPLIERS
Статистика и экономика, 2016 This article describes an algorithm for stock pairs trading using financial multipliers of underlying companies. This algorithm has been tested on historical data and compared with classical Bollinger bands strategy.
Dmitry S. Pashkov
doaj +1 more source
Correctness of backtest engines [PDF]
The Journal of Investment Strategies, 2017 In recent years several trading platforms appeared which provide a backtest engine to calculate historic performance of self designed trading strategies on underlying candle data. The construction of a correct working backtest engine is, however, a subtle task as shown by Maier-Paape and Platen (cf. arXiv:1412.5558 [q-fin.TR]).
Robert L\\\"ow +2 more
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