Realized Measures to Explain Volatility Changes over Time
| Autor: | Christos Floros, Christoforos Konstantatos, Athanasios Tsagkanos, Konstantinos Gkillas |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
G24
Realized variance lcsh:Risk in industry. Risk management volatility Frequency data Boom Hardware_GENERAL 0502 economics and business lcsh:Finance lcsh:HG1-9999 ddc:330 Econometrics Economics P500 G11 S& G12 050207 economics Hardware_MEMORYSTRUCTURES 050208 finance realized measures 05 social sciences Leverage effect FTSE100 Estimator lcsh:HD61 ComputingMilieux_GENERAL Feedback effect F65 Volatility (finance) statistical properties S& P500 high frequency data |
| Zdroj: | Journal of Risk and Financial Management, Vol 13, Iss 125, p 125 (2020) Journal of Risk and Financial Management Volume 13 Issue 6 |
| ISSN: | 1911-8066 1911-8074 |
| Popis: | We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain volatility changes over time for both the S& P500 and FTSE100 indices. The period of analysis spanned from January 2000 to June 2017 incorporating various market phases, such as booms and crashes. Based on the estimated regressions, we found evidence that the returns of S& P500 and FTSE100 indices were well explained by a specific group of realized measure estimators, and the returns negatively affected realized volatility. These results are highly recommended to financial analysts dealing with high frequency data and volatility modelling. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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