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The use of Value-at-Risk methodology in the assessment of investor’s risk attitudes on the precious metals market

100%
Krężołek D.
Econometrics. Ekonometria. Advances in Applied Data Analytics
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2017
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issue 3 (57)
101-112
EN
The decision making process is directly associated with risk, no matter what area of interest it is. In the case of financial investments we can define a special type of risk called investment risk. Taking into account the financial time series of assets’ characteristics (prices, returns), small deviations of future values comparing to their expected level are not a major threat to the investor’s portfolio. In contrast, if the changes in prices/returns are significant, unpredictable and result from unexpected and adverse events, one should pay attention to the proper risk measurement. The topic of this article refers to the new family of risk measures related to investments in assets on the precious metals market. These risk measures are called the GlueVaR risk measures. The name itself suggests that the GlueVaR is related to the commonly used measure of risk – VaR. As will be presented in the article, the family of the GlueVaR risk measures may be expressed as a linear combination of VaR and conditional VaR for fixed tolerance levels. Moreover, the new risk measure allows for assessing risk more personally, taking into account the investor’s attitudes towards risk. If portfolio investments are of interest, the GlueVaR risk measures meet the assumption of subadditivity. This property of risk measure is required, as it is strongly related to the diver-sification problem.
2
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The Gluevar Risk Measure and Investor’s Attitudes to Risk–An Application to the Non-Ferrous Metals Market

100%
Krężołek D.
Statistics in Transition new series
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2016
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vol. 17
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issue 2
305-316
EN
Investing in the economic world, characterized by a high level of uncertainty and volatility, entails a higher level of risk related to investment. One of the most commonly used risk measure is Value-at-Risk. However, despite the ease of calculation and interpretation, this measure suffers from a significant drawback – it is not subadditive. This property is the key issue in terms of portfolio diversification. Another risk measure, which meets this assumption, has been proposed – Conditional Value-at-Risk, defined as a conditional loss beyond Value-at-Risk. However, the choice of a risk measure is an individual decision of an investor and it is directly related to his attitudes to risk. In this paper the new risk measure is proposed – the GlueVaR risk measure, which can be defined as a linear combination of VaR and GlueVaR. It allows for calculating the level of investment loss depending on investment’s attitudes to risk. Moreover, GlueVaR meets the subadditivity property, therefore it may be used in portfolio risk assessment. The application of the GlueVaR risk measure is presented for the non-ferrous metals market.
3
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The Effectiveness of the GlueVaR Risk Measure on the Metals Market – the Application of Omega Performance Measure

99%
Krężołek D., Trzpiot G.
Acta Universitatis Lodziensis. Folia Oeconomica
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2017
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vol. 5
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issue 331
153-167
PL
Podejmowanie decyzji inwestycyjnych jest indywidualną kwestią każdego inwestora. Strategia, jaką przyjmuje, znajduje swoje odzwierciedlenie w poziomie akceptowalnego ryzyka. Niemniej jednak każdy z inwestorów dąży do minimalizacji dużych strat przy jednoczesnej maksymalizacji zysku. Istnieje wiele miar ryzyka, a każda z nich przekazuje inną informację. W artykule poddano ocenie efektywność dwóch nieklasycznych miar ryzyka: wskaźnika Omega oraz koherentnej miary GlueVaR. Cechą wspólną obu tych mierników jest konieczność ustalenia pewnego punktu progowego określającego, kiedy podjęta inwestycja rozumiana jest jako strata. Efektywność miar ryzyka przeanalizowano na przykładzie inwestycji podejmowanych na rynku metali.
EN
Decision‑making process is an individual matter for each investor and the strategy they choose, reflects the level of accepted risk. Nevertheless, any investor wants to minimize huge losses while maximizing profits. As far as the measure of risk is concerned, literature is full of examples of tools which help to evaluate the risk. However, the level of the risk usually differs, depending on circumstances. In this paper we present two non‑classical risk measures: Omega performance risk measure and GlueVaR risk measure. Both of them require a threshold to be set, which reflects the starting point for the investment to be considered as a loss. The effectiveness of the Omega and GlueVaR risk measures is compared using the example of metals market investments.
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