The Application of Statistics in Computational Finance
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E5: Financial Mathematics".
Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 434
Special Issue Editors
Interests: nonlinear time series; data science; applied mathematics; computational statistics; econophysics
Special Issue Information
Dear Colleagues,
Uncertainty, chaos and complexity are hallmarks of financial markets everywhere. Over the past 70 years, methods from both statistics and statistical physics have proven invaluable in analyzing, describing and forecasting financial market trends to make sense of uncertainty. Univariate time series analysis and parametric models have helped researchers understand volatility, while multivariate time series analysis has illuminated collective behaviors that underlie the movement of many stocks simultaneously. The intersection of statistics, operations research and machine learning has provided numerous advances in portfolio optimization and selection, as well as predictive power.
The purpose of this Special Issue is to collate articles that reflect the importance of statistics and statistical physics in economics, econometrics and finance. Both theoretical and experimental papers that showcase and advance the use of statistics to compute quantities of interest such as volatility forecasts, descriptive statistics, portfolio weights, and so on, are welcome, both in a univariate or multivariate setting. We would be interested in receiving papers concerning any financial instrument, not limited to equities, fixed income, foreign exchange, options and derivatives, cryptocurrencies.
Dr. Nick James
Dr. Max Menzies
Guest Editors
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Keywords
- computational statistics
- statistical mechanics
- parametric and nonparametric statistical modeling
- volatility clustering
- clustering methods
- statistical algorithms
- time series analysis and forecasting
- cryptocurrencies
- collective behaviours
- portfolio optimization
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