What is he best known for?
The fields of study he is best known for:
- Finance
- Econometrics
- Financial economics
Wayne E. Ferson mainly investigates Econometrics, Capital asset pricing model, Financial economics, Sample and Portfolio.
His work carried out in the field of Econometrics brings together such families of science as Bond and Risk aversion.
His Capital asset pricing model research includes themes of Risk premium and Common stock.
Security market line and Consumption-based capital asset pricing model are the subjects of his Financial economics studies.
His biological study spans a wide range of topics, including Performance measurement and Equity.
In general Equity study, his work on Equity risk often relates to the realm of Investment performance and Economic information, thereby connecting several areas of interest.
His most cited work include:
- THE VARIATION OF ECONOMIC RISK PREMIUMS (1314 citations)
- Measuring Fund Strategy and Performance in Changing Economic Conditions (1289 citations)
- The Risk and Predictability of International Equity Returns (881 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Econometrics, Capital asset pricing model, Financial economics, Portfolio and Equity.
The study incorporates disciplines such as Performance measurement and Market timing in addition to Econometrics.
In his research, Common stock is intimately related to Risk premium, which falls under the overarching field of Capital asset pricing model.
His work on Security market line as part of his general Financial economics study is frequently connected to Predictability, thereby bridging the divide between different branches of science.
His Portfolio study combines topics from a wide range of disciplines, such as Stochastic discount factor, Actuarial science and Variance.
His Equity research incorporates themes from Earnings and Pension fund.
He most often published in these fields:
- Econometrics (90.61%)
- Capital asset pricing model (62.43%)
- Financial economics (44.20%)
What were the highlights of his more recent work (between 2012-2021)?
- Econometrics (90.61%)
- Performance measurement (20.99%)
- Capital asset pricing model (62.43%)
In recent papers he was focusing on the following fields of study:
Wayne E. Ferson spends much of his time researching Econometrics, Performance measurement, Capital asset pricing model, Financial economics and Alpha.
Wayne E. Ferson has researched Econometrics in several fields, including Equity, Mutual fund and Portfolio.
His research integrates issues of Leverage, Price/cash flow ratio, Operating cash flow and Low-volatility anomaly in his study of Equity.
His Portfolio study integrates concerns from other disciplines, such as Volatility and Market timing.
Wayne E. Ferson connects Capital asset pricing model with Consumption in his research.
Wayne E. Ferson frequently studies issues relating to Cash flow and Financial economics.
Between 2012 and 2021, his most popular works were:
- The "Out of Sample" Performance of Long-run Risk Models (40 citations)
- Alpha and Performance Measurement: The Effects of Investor Disagreement and Heterogeneity (34 citations)
- Performance measurement with selectivity, market and volatility timing (34 citations)
In his most recent research, the most cited papers focused on:
- Finance
- Econometrics
- Financial economics
His primary areas of investigation include Econometrics, Performance measurement, Financial economics, Alpha and Flow response.
His Econometrics research integrates issues from Maturity and Momentum.
His work on Market timing expands to the thematically related Financial economics.
His Flow response investigation overlaps with other areas such as Attractiveness, Investor profile and Function.
His work on Investor profile is being expanded to include thematically relevant topics such as Open-end fund.
His study in Open-end fund is interdisciplinary in nature, drawing from both Actuarial science, Global assets under management and Finance.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
