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Persistent link: https://www.econbiz.de/10012203181
Emerging markets often go through periods of financial turbulence and the estimation of market risk measures may be problematic. Online search queries and implied volatility may (or may not) improve the model estimates. In these situations a step-by-step analysis with R and Russian market data...
Persistent link: https://www.econbiz.de/10012591721
This paper investigates the intraday volatility pattern of the E-mini SP500, quoted at the Chicago Mercantile Exchange, one of the most traded American Stock Index futures. The data set consists of round-the-clock hourly returns. The squared (and absolute) returns are characterized by long...
Persistent link: https://www.econbiz.de/10008665276
Persistent link: https://www.econbiz.de/10011417840
This paper investigates the intraday volatility pattern of the E-mini SP500 hourly returns. In order to account for the observed long memory and periodicity in returns volatility we introduce the Fractionally Integrated Periodic EGARCH and the Seasonal Fractional Integrated Periodic EGARCH. For...
Persistent link: https://www.econbiz.de/10014204671
Daul et al. (2003), Demarta and McNeil (2005) and Mcneil et al. (2005) underlined the ability of the grouped t-copula to take the tail dependence present in a large set of financial assets into account, particularly when the assumption of one global parameter for the degrees of freedom (as for...
Persistent link: https://www.econbiz.de/10013134397
In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the daily range incorporates all the information...
Persistent link: https://www.econbiz.de/10014350946