What is he best known for?
The fields of study he is best known for:
- Statistics
- Finance
- Microeconomics
His primary areas of study are Econometrics, Financial economics, Extreme value theory, Exchange rate and Correlation analysis.
His Econometrics research is multidisciplinary, relying on both Value at risk, Positive economics, Tail index and Statistics.
The study incorporates disciplines such as Quantile and Monte Carlo method in addition to Tail index.
His Financial economics research includes themes of Stock exchange, Stock market and Random variable, Probability mass function.
His Extreme value theory research focuses on subjects like Empirical distribution function, which are linked to Measure, Distribution and Class.
Casper G. de Vries regularly ties together related areas like Systemic risk in his Bond market studies.
His most cited work include:
- The All-Pay Auction with Complete Information (666 citations)
- On the frequency of large stock returns: Putting booms and busts into perspective (446 citations)
- Rigging the lobbying process: An application of the all-pay auction (439 citations)
What are the main themes of his work throughout his whole career to date?
Casper G. de Vries mainly investigates Econometrics, Monetary economics, Financial economics, Extreme value theory and Downside risk.
The various areas that Casper G. de Vries examines in his Econometrics study include Estimator, Futures contract, Beta, Portfolio and Exchange rate.
In his study, Market share and Shape parameter is strongly linked to Tail risk, which falls under the umbrella field of Financial economics.
He has included themes like Value at risk, Risk management, Mathematical economics and Sample in his Extreme value theory study.
The concepts of his Mathematical economics study are interwoven with issues in Common value auction and Symmetric equilibrium.
His Downside risk research incorporates elements of Heavy-tailed distribution, Actuarial science, Portfolio optimization, Diversification and Systemic risk.
He most often published in these fields:
- Econometrics (64.69%)
- Monetary economics (35.66%)
- Financial economics (43.71%)
What were the highlights of his more recent work (between 2009-2021)?
- Econometrics (64.69%)
- Financial economics (43.71%)
- Futures contract (20.63%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Econometrics, Financial economics, Futures contract, Extreme value theory and Sample.
His Econometrics research incorporates themes from Heavy-tailed distribution, Beta, Downside risk and Inflation.
His studies in Downside risk integrate themes in fields like Diversification, Hedge fund and Systemic risk.
His work deals with themes such as Actuarial science, Sharpe ratio and Autocorrelation, which intersect with Systemic risk.
He interconnects Monopolistic competition and Imperfect competition in the investigation of issues within Extreme value theory.
His Sample study also includes fields such as
- Risk management that intertwine with fields like General equilibrium theory,
- Order statistic and related Metric and Quantile.
Between 2009 and 2021, his most popular works were:
- Fat tails, VaR and subadditivity☆ (82 citations)
- Contests with Rank-Order Spillovers (51 citations)
- Risk Measures for Autocorrelated Hedge Fund Returns (34 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Finance
- Microeconomics
Econometrics, Financial economics, Extreme value theory, Tail risk and Sample are his primary areas of study.
His Econometrics research integrates issues from Value at risk, Heavy-tailed distribution, Downside risk, Beta and Systemic risk.
His Systemic risk study frequently draws parallels with other fields, such as Finance.
His study in Extreme value theory is interdisciplinary in nature, drawing from both Productivity, Futures contract, Risk management and General equilibrium theory.
His studies deal with areas such as Pareto principle and Yield curve as well as Sample.
His work on Order statistic and Quantile as part of general Statistics study is frequently linked to Estimation and Selection, therefore connecting diverse disciplines of science.
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