What is he best known for?
The fields of study he is best known for:
- Statistics
- Econometrics
- Finance
His main research concerns Econometrics, Financial economics, Predictability, Statistics and Volatility.
His biological study spans a wide range of topics, including Equity and Regression.
Allan Timmermann interconnects Target date fund, Open-end fund, Interest rate and Stock market, Stock market bubble in the investigation of issues within Financial economics.
His research integrates issues of Algorithmic trading, Dividend, Risk premium, Technical analysis and Trading strategy in his study of Stock market.
The study incorporates disciplines such as Bond, Actuarial science and Asset allocation in addition to Predictability.
His work on Optimal estimation as part of his general Statistics study is frequently connected to Shrinkage estimator, Estimation, Goldfeld–Quandt test and Directional analysis, thereby bridging the divide between different branches of science.
His most cited work include:
- The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling. (887 citations)
- Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap (753 citations)
- Predictability of Stock Returns: Robustness and Economic Significance (745 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Econometrics, Financial economics, Predictability, Portfolio and Volatility.
His studies deal with areas such as Statistics, Inflation and Stock market as well as Econometrics.
His studies in Inflation integrate themes in fields like Economic forecasting, Survey data collection and Realization.
His work carried out in the field of Financial economics brings together such families of science as Dividend and Equity.
The various areas that he examines in his Portfolio study include Money market, Capital asset pricing model, Asset and Market timing.
The Asset allocation study combines topics in areas such as Bond, Pension and Investment.
He most often published in these fields:
- Econometrics (84.94%)
- Financial economics (24.68%)
- Predictability (20.26%)
What were the highlights of his more recent work (between 2015-2021)?
- Econometrics (84.94%)
- Inflation (12.47%)
- Panel data (5.19%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Econometrics, Inflation, Panel data, Predictability and Cash flow.
His Econometrics study combines topics in areas such as Expected loss and Stock market.
His Inflation study also includes fields such as
- Regime switching and related Economic statistics and Threshold model,
- Key that intertwine with fields like Market efficiency, Asset return and Probability distribution.
His Predictability research includes elements of Bond, Yield curve and Asset allocation.
His Cash flow study incorporates themes from Dividend and Capital asset pricing model.
He has researched Economic forecasting in several fields, including Real gross domestic product, Financial economics and Realization.
Between 2015 and 2021, his most popular works were:
- Runs on Money Market Mutual Funds (79 citations)
- Genome-wide association study implicates CHRNA2 in cannabis use disorder. (50 citations)
- Bond Return Predictability: Economic Value and Links to the Macroeconomy (37 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Finance
- Econometrics
Empirical evidence, Econometrics, Ecology, Stochastic volatility and Hummingbird are his primary areas of study.
Allan Timmermann has included themes like Regime switching and Short rate, Yield curve in his Econometrics study.
Allan Timmermann combines subjects such as Bond, Predictability, Inflation and Forward rate with his study of Stochastic volatility.
His work in Hummingbird covers topics such as Specialization which are related to areas like Niche, Species richness and Niche differentiation.
His study in Financial economics is interdisciplinary in nature, drawing from both Demand forecasting, Technology forecasting and Range.
His Volatility research is multidisciplinary, incorporating perspectives in Bayes estimator, Conditional expectation and Gibbs sampling.
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