What is he best known for?
The fields of study he is best known for:
- Operating system
- Statistics
- Mathematical analysis
David H. Bailey mainly focuses on Algorithm, Parallel computing, Computation, Floating point and Extended precision.
His studies deal with areas such as Transcendental function, Number theory, Arithmetic, Experimental mathematics and Subroutine as well as Algorithm.
His Parallel computing study incorporates themes from Fast Fourier transform, Latency and Scalability.
His Computation research integrates issues from Software, Computer engineering and Code.
The various areas that David H. Bailey examines in his Extended precision study include Arbitrary-precision arithmetic and Computational science.
His biological study spans a wide range of topics, including Applied research, Set and Parallel processing.
His most cited work include:
- The Nas Parallel Benchmarks (2023 citations)
- IEEE Standard for Floating-Point Arithmetic (610 citations)
- The NAS parallel benchmarks—summary and preliminary results (433 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Computation, Experimental mathematics, Parallel computing, Sharpe ratio and Econometrics.
His Computation study also includes fields such as
- Software which intersects with area such as Language translation,
- Computer engineering which is related to area like Floating point.
David H. Bailey combines subjects such as Theoretical computer science, Algebraic number and Quantum field theory with his study of Experimental mathematics.
His work carried out in the field of Parallel computing brings together such families of science as Fast Fourier transform and Set.
His Sharpe ratio research is multidisciplinary, relying on both Multiple comparisons problem and Selection bias.
His Arbitrary-precision arithmetic research entails a greater understanding of Algorithm.
He most often published in these fields:
- Computation (16.90%)
- Experimental mathematics (14.14%)
- Parallel computing (11.38%)
What were the highlights of his more recent work (between 2013-2020)?
- Sharpe ratio (18.62%)
- Overfitting (13.79%)
- Econometrics (16.90%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Sharpe ratio, Overfitting, Econometrics, Investment strategy and Computation.
The study incorporates disciplines such as Multiple comparisons problem, Modern portfolio theory and Selection bias in addition to Sharpe ratio.
His work in the fields of Econometrics, such as Econometric methods, overlaps with other areas such as Market forecast.
His research integrates issues of Numerical integration, Algebra, Arithmetic and Pure mathematics in his study of Computation.
A large part of his Arithmetic studies is devoted to Arbitrary-precision arithmetic.
His Experimental mathematics research includes elements of Theoretical computer science and Calculus.
Between 2013 and 2020, his most popular works were:
- Enhancing reproducibility for computational methods. (179 citations)
- PSEUDO-MATHEMATICS AND FINANCIAL CHARLATANISM: THE EFFECTS OF BACKTEST OVERFITTING ON OUT-OF-SAMPLE PERFORMANCE (73 citations)
- The NAS Parallel Benchmarks 2.0 (55 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Statistics
- Mathematical analysis
David H. Bailey mainly focuses on Overfitting, Investment strategy, Sharpe ratio, Econometrics and Context.
His work often combines Overfitting and Investment management studies.
Many of his Investment strategy research pursuits overlap with Finance, Small number and Out of sample.
David H. Bailey has researched Econometrics in several fields, including Selection bias and Portfolio.
His Portfolio research is multidisciplinary, incorporating elements of Market data, Nonparametric statistics and Regression.
His Context research spans across into areas like Minifloat, Mathematical physics, Arbitrary-precision arithmetic, Arithmetic and Empirical data.
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