What is he best known for?
The fields of study he is best known for:
- Statistics
- Finance
- Financial economics
Michael Rockinger mainly focuses on Econometrics, Autoregressive conditional heteroskedasticity, Stock market, Financial economics and Kurtosis.
His work in the fields of Volatility and Valuation of options overlaps with other areas such as Stock market index.
His study brings together the fields of Autoregressive model and Autoregressive conditional heteroskedasticity.
Michael Rockinger studies Financial economics, namely Investment theory.
His Kurtosis study necessitates a more in-depth grasp of Statistics.
His work on Shape parameter, Skewness and Spurious relationship as part of general Statistics study is frequently linked to D'Agostino's K-squared test, bridging the gap between disciplines.
His most cited work include:
- The Copula-GARCH model of conditional dependencies: An international stock market application (564 citations)
- Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications (427 citations)
- Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements (352 citations)
What are the main themes of his work throughout his whole career to date?
Econometrics, Volatility, Autoregressive conditional heteroskedasticity, Kurtosis and Financial economics are his primary areas of study.
His Econometrics research incorporates themes from Extreme value theory and Asset allocation.
His work carried out in the field of Asset allocation brings together such families of science as Portfolio allocation and Microeconomics.
As a part of the same scientific family, Michael Rockinger mostly works in the field of Volatility, focusing on Portfolio and, on occasion, Expected utility hypothesis, Normality, Actuarial science and Pension.
As a member of one scientific family, Michael Rockinger mostly works in the field of Autoregressive conditional heteroskedasticity, focusing on Copula and, on occasion, Predetermined variables.
His Kurtosis research integrates issues from Skewness and Applied mathematics.
He most often published in these fields:
- Econometrics (82.69%)
- Volatility (59.62%)
- Autoregressive conditional heteroskedasticity (46.63%)
What were the highlights of his more recent work (between 2013-2020)?
- Actuarial science (17.31%)
- Econometrics (82.69%)
- Pension (10.58%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Actuarial science, Econometrics, Pension, Portfolio and Volatility.
Michael Rockinger specializes in Econometrics, namely Skewness.
The concepts of his Pension study are interwoven with issues in Life insurance, Payment and Asset allocation.
His study focuses on the intersection of Asset allocation and fields such as Rate of return on a portfolio with connections in the field of Hedge.
His work in Volatility addresses subjects such as Expected return, which are connected to disciplines such as Bond.
Kurtosis is a subfield of Statistics that he studies.
Between 2013 and 2020, his most popular works were:
- Moment Component Analysis: An Illustration With International Stock Markets (21 citations)
- Systemic Risk in Europe (17 citations)
- Systemic Risk in Europe (17 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Finance
- Mathematical analysis
Michael Rockinger focuses on Econometrics, Volatility, Transaction price, Systemic risk and Financial economics.
Michael Rockinger is involved in the study of Econometrics that focuses on Skewness in particular.
He has researched Systemic risk in several fields, including Taxpayer, Financial institution and Financial system.
His research on Kurtosis concerns the broader Statistics.
In his work, Michael Rockinger performs multidisciplinary research in Principal component analysis and Asset.
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