A Volatility Estimator of Stock Market Indices Based on the Intrinsic Entropy Model
| Autor: | Claudiu Vințe, Marcel Ausloos, Titus Felix Furtuna |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Index (economics)
Science QC1-999 General Physics and Astronomy Astrophysics 01 natural sciences Article 010305 fluids & plasmas FOS: Economics and business Entropy (classical thermodynamics) Order (exchange) 0502 economics and business 0103 physical sciences Range (statistics) Econometrics historical volatility Price level volatility estimators Mathematics 050208 finance Physics 05 social sciences Estimator Mathematical Finance (q-fin.MF) Stock market index QB460-466 Quantitative Finance - Mathematical Finance Volatility (finance) intrinsic entropy model |
| Zdroj: | Entropy Volume 23 Issue 4 Entropy, Vol 23, Iss 484, p 484 (2021) |
| ISSN: | 1099-4300 |
| DOI: | 10.3390/e23040484 |
| Popis: | Grasping the historical volatility of stock market indices and accurately estimating are two of the major focuses of those involved in the financial securities industry and derivative instruments pricing. This paper presents the results of employing the intrinsic entropy model as a substitute for estimating the volatility of stock market indices. Diverging from the widely used volatility models that take into account only the elements related to the traded prices, namely the open, high, low, and close prices of a trading day (OHLC), the intrinsic entropy model takes into account the traded volumes during the considered time frame as well. We adjust the intraday intrinsic entropy model that we introduced earlier for exchange-traded securities in order to connect daily OHLC prices with the ratio of the corresponding daily volume to the overall volume traded in the considered period. The intrinsic entropy model conceptualizes this ratio as entropic probability or market credence assigned to the corresponding price level. The intrinsic entropy is computed using historical daily data for traded market indices (S& P 500, Dow 30, NYSE Composite, NASDAQ Composite, Nikkei 225, and Hang Seng Index). We compare the results produced by the intrinsic entropy model with the volatility estimates obtained for the same data sets using widely employed industry volatility estimators. The intrinsic entropy model proves to consistently deliver reliable estimates for various time frames while showing peculiarly high values for the coefficient of variation, with the estimates falling in a significantly lower interval range compared with those provided by the other advanced volatility estimators. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
| Nepřihlášeným uživatelům se plný text nezobrazuje | K zobrazení výsledku je třeba se přihlásit. |