Contents：
主講人：劉念麟 教授(日本東京理科大學)
題 目：Spot covariance estimation with synchronous high-frequency finance data
摘要Abstract:
Empirical studies have pointed out the importance of considering different temporal variations in correlations between asset prices. Currently, high-frequency profiles sampled asynchronously across different assets have mainly applied for integrated covariance estimation but less so for spot covariance estimation. Based on the seminal works of Malliavin and Mancino [1,2] in conjunction with the principle component analysis approach, in this talk, we try to propose a novel spot covariance estimation with synchronous high-frequency finance data. We will point out which kind of high-frequency data we are interested in and briefly explain why we apply the Malliavin-Mancino method to these data.
References
[1] P. Malliavin and M. E. Mancino. Fourier series method for measurement of multivariate volatilities. Finance Stoch., 6(1):49–61, 2002.
[2] P. Malliavin and M. E. Mancino. A Fourier transform method for nonparametric estimation of multivariate volatility. Ann. Statist., 37(4):1983–2010, 2009.
Category：Faculty training in teaching
Time：
2024/02/20 14:10 ~ 2024/02/20 15:00
Registration period：
2024/02/16 09:30 ~ 2024/02/19 12:00
Location：
科學館 S433室
Duration：1.0 hours
Registration Limit：20 (Current Registrants：10）
Attendees：teachers、students