Skośność Rozkładu a Estymacja Kwantylowych Miar Ryzyka – Przypadek Rynku Metali

Krężołek, Dominik

doi:10.22630/mibe.2017.18.4.57

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…There are few studies considering an analysis of precious metals from the investment point of view, so this study fills the gap in this field. Giot and Laurent (2003) and Krężołek (2015;2017a) have shown that the time series in the metals market exhibit similar characteristics as the financial time series. The clustering of variance, asymmetry, leptokurtosis, and heavy tails was observed in empirical distributions.…”

Section: Literature Reviewmentioning

confidence: 93%

“…This hypothesis was tested for those who invested their funds in PLN, finally, however, it was not confirmed. In the papers of Krężołek (2017a;2017b) and Krężołek and Trzpiot (2017), an investment risk assessment was carried out in the metals market using quantile risk measures. They observed significant differences in these assessments determined by the class of risk measures.…”

Section: Literature Reviewmentioning

confidence: 99%

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Volatility Factors of Returns and Risk Analysis Using Quantile Risk Measures in the Gold and Silver Market

Krężołek

2021

Folia Oeconomica

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The aim of the paper is to identify unobservable factors that may significantly determine the level of gold and silver returns and to assess the risk of investment in these metals. To measure risk, the value at risk and other, less popular measures are used: the ES, MS, Rachev ratio and GlueVaR risk measure. Normal and Student’s t‑distributions are used as theoretical distributions. The results of the study show that we can identify latent factors based on observable variables that have a significant impact on the level of gold and silver returns. In addition, it was observed that the risk measures would vary depending on the period of research. It was shown that the estimates of the risk measures using Student’s t‑distribution have a lower estimation error than those based on the normal distribution.

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Section: Literature Reviewmentioning

confidence: 93%

Section: Literature Reviewmentioning

confidence: 99%

Volatility Factors of Returns and Risk Analysis Using Quantile Risk Measures in the Gold and Silver Market

Krężołek

2021

Folia Oeconomica

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“…Najczęstsza prawidłowość jest taka, że im bardziej złożone jest zjawisko rynkowe, tym większa niepewność i nieprzewidywalność dotycząca jego realizacji w przyszłości. Pojawia się bowiem ryzyko, że oczekiwania okażą się odmienne od nieznanej rzeczywistości (Krężołek, 2020).…”

Section: Pomiar Ryzyka Rynkowego Z Wykorzystaniem Miar Wrażliwościunclassified

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2023

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estate appraisers. On the basis of empirical analyses covering 405 residential land properties in Szczecin, individually valued by appraisers for the purpose of the study, the authors propose four types of dependency coefficients and their partial values. They also propose four methods of considering these coefficients in the SAMWN procedure. Additionally, the authors assess the application of six weighting methods for the proposed measures. They obtain an optimal combination of the considered variants of the SAMWN algorithm by calculating the appraisal error measures, then followed by linear ordering procedures. The study shows that the valuation results are most affected by the formula used to calculate the weights of the influence of individual attributes on the value of the property in SAMWN. This confirms the usefulness of the analysed algorithm in practice, but at the same time the need to adapt its procedure to the specifics of the valued property.

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Skośność Rozkładu a Estymacja Kwantylowych Miar Ryzyka – Przypadek Rynku Metali

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Cited by 2 publications

References 5 publications

Volatility Factors of Returns and Risk Analysis Using Quantile Risk Measures in the Gold and Silver Market

Volatility Factors of Returns and Risk Analysis Using Quantile Risk Measures in the Gold and Silver Market

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