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Book
Quantitative Methods for Economics and Finance
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Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.

Keywords

Coins, banknotes, medals, seals (numismatics) --- academic cheating --- tax evasion --- informality --- pairs trading --- hurst exponent --- financial markets --- long memory --- co-movement --- cointegration --- risk --- delay --- decision-making process --- probability --- discount --- detection --- mean square error --- multicollinearity --- raise regression --- variance inflation factor --- derivation --- intertemporal choice --- decreasing impatience --- elasticity --- GARCH --- EGARCH --- VaR --- historical simulation approach --- peaks-over-threshold --- EVT --- student t-copula --- generalized Pareto distribution --- centered model --- noncentered model --- intercept --- essential multicollinearity --- nonessential multicollinearity --- commodity prices --- futures prices --- number of factors --- eigenvalues --- volatility cluster --- Hurst exponent --- FD4 approach --- volatility series --- probability of volatility cluster --- S&amp --- P500 --- Bitcoin --- Ethereum --- Ripple --- bitcoin --- deep learning --- deep recurrent convolutional neural networks --- forecasting --- asset pricing --- financial distress prediction --- unconstrained distributed lag model --- multiple periods --- Chinese listed companies --- cash flow management --- corporate prudential risk --- the financial accelerator --- financial distress --- induced risk aversion --- liquidity constraints --- liquidity risk --- macroeconomic propagation --- multiperiod financial management --- non-linear macroeconomic modelling --- Tobin’s q --- precautionary savings --- pharmaceutical industry --- scale economies --- profitability --- biotechnological firms --- non-parametric efficiency --- productivity --- DEA --- dispersion trading --- option arbitrage --- volatility trading --- correlation risk premium --- econometrics --- computational finance --- ensemble empirical mode decomposition (EEMD) --- autoregressive integrated moving average (ARIMA) --- support vector regression (SVR) --- genetic algorithm (GA) --- energy consumption --- cryptocurrency --- gold --- P 500 --- DCC --- copula --- copulas --- Markov Chain Monte Carlo simulation --- local optima vs. local minima --- SRA approach --- foreign direct investment --- bilateral investment treaties --- regional trade agreements --- structural gravity model --- policy uncertainty --- stock prices --- dynamically simulated autoregressive distributed lag (DYS-ARDL) --- threshold regression --- United States


Book
Quantitative Methods for Economics and Finance
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

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Bookmark

Abstract

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.

Keywords

Coins, banknotes, medals, seals (numismatics) --- academic cheating --- tax evasion --- informality --- pairs trading --- hurst exponent --- financial markets --- long memory --- co-movement --- cointegration --- risk --- delay --- decision-making process --- probability --- discount --- detection --- mean square error --- multicollinearity --- raise regression --- variance inflation factor --- derivation --- intertemporal choice --- decreasing impatience --- elasticity --- GARCH --- EGARCH --- VaR --- historical simulation approach --- peaks-over-threshold --- EVT --- student t-copula --- generalized Pareto distribution --- centered model --- noncentered model --- intercept --- essential multicollinearity --- nonessential multicollinearity --- commodity prices --- futures prices --- number of factors --- eigenvalues --- volatility cluster --- Hurst exponent --- FD4 approach --- volatility series --- probability of volatility cluster --- S&amp --- P500 --- Bitcoin --- Ethereum --- Ripple --- bitcoin --- deep learning --- deep recurrent convolutional neural networks --- forecasting --- asset pricing --- financial distress prediction --- unconstrained distributed lag model --- multiple periods --- Chinese listed companies --- cash flow management --- corporate prudential risk --- the financial accelerator --- financial distress --- induced risk aversion --- liquidity constraints --- liquidity risk --- macroeconomic propagation --- multiperiod financial management --- non-linear macroeconomic modelling --- Tobin’s q --- precautionary savings --- pharmaceutical industry --- scale economies --- profitability --- biotechnological firms --- non-parametric efficiency --- productivity --- DEA --- dispersion trading --- option arbitrage --- volatility trading --- correlation risk premium --- econometrics --- computational finance --- ensemble empirical mode decomposition (EEMD) --- autoregressive integrated moving average (ARIMA) --- support vector regression (SVR) --- genetic algorithm (GA) --- energy consumption --- cryptocurrency --- gold --- P 500 --- DCC --- copula --- copulas --- Markov Chain Monte Carlo simulation --- local optima vs. local minima --- SRA approach --- foreign direct investment --- bilateral investment treaties --- regional trade agreements --- structural gravity model --- policy uncertainty --- stock prices --- dynamically simulated autoregressive distributed lag (DYS-ARDL) --- threshold regression --- United States


Book
Quantitative Methods for Economics and Finance
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.

Keywords

academic cheating --- tax evasion --- informality --- pairs trading --- hurst exponent --- financial markets --- long memory --- co-movement --- cointegration --- risk --- delay --- decision-making process --- probability --- discount --- detection --- mean square error --- multicollinearity --- raise regression --- variance inflation factor --- derivation --- intertemporal choice --- decreasing impatience --- elasticity --- GARCH --- EGARCH --- VaR --- historical simulation approach --- peaks-over-threshold --- EVT --- student t-copula --- generalized Pareto distribution --- centered model --- noncentered model --- intercept --- essential multicollinearity --- nonessential multicollinearity --- commodity prices --- futures prices --- number of factors --- eigenvalues --- volatility cluster --- Hurst exponent --- FD4 approach --- volatility series --- probability of volatility cluster --- S&amp --- P500 --- Bitcoin --- Ethereum --- Ripple --- bitcoin --- deep learning --- deep recurrent convolutional neural networks --- forecasting --- asset pricing --- financial distress prediction --- unconstrained distributed lag model --- multiple periods --- Chinese listed companies --- cash flow management --- corporate prudential risk --- the financial accelerator --- financial distress --- induced risk aversion --- liquidity constraints --- liquidity risk --- macroeconomic propagation --- multiperiod financial management --- non-linear macroeconomic modelling --- Tobin’s q --- precautionary savings --- pharmaceutical industry --- scale economies --- profitability --- biotechnological firms --- non-parametric efficiency --- productivity --- DEA --- dispersion trading --- option arbitrage --- volatility trading --- correlation risk premium --- econometrics --- computational finance --- ensemble empirical mode decomposition (EEMD) --- autoregressive integrated moving average (ARIMA) --- support vector regression (SVR) --- genetic algorithm (GA) --- energy consumption --- cryptocurrency --- gold --- P 500 --- DCC --- copula --- copulas --- Markov Chain Monte Carlo simulation --- local optima vs. local minima --- SRA approach --- foreign direct investment --- bilateral investment treaties --- regional trade agreements --- structural gravity model --- policy uncertainty --- stock prices --- dynamically simulated autoregressive distributed lag (DYS-ARDL) --- threshold regression --- United States


Book
Fractal Dimension for Fractal Structures : With Applications to Finance
Authors: --- --- ---
ISBN: 3030166457 3030166449 Year: 2019 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

This book provides a generalised approach to fractal dimension theory from the standpoint of asymmetric topology by employing the concept of a fractal structure. The fractal dimension is the main invariant of a fractal set, and provides useful information regarding the irregularities it presents when examined at a suitable level of detail. New theoretical models for calculating the fractal dimension of any subset with respect to a fractal structure are posed to generalise both the Hausdorff and box-counting dimensions. Some specific results for self-similar sets are also proved. Unlike classical fractal dimensions, these new models can be used with empirical applications of fractal dimension including non-Euclidean contexts. In addition, the book applies these fractal dimensions to explore long-memory in financial markets. In particular, novel results linking both fractal dimension and the Hurst exponent are provided. As such, the book provides a number of algorithms for properly calculating the self-similarity exponent of a wide range of processes, including (fractional) Brownian motion and Lévy stable processes. The algorithms also make it possible to analyse long-memory in real stocks and international indexes. This book is addressed to those researchers interested in fractal geometry, self-similarity patterns, and computational applications involving fractal dimension and Hurst exponent.

Keywords

Fractal analysis. --- Fractal geometric analysis --- Geometric analysis --- Differentiable dynamical systems. --- Topology. --- Mathematics. --- Distribution (Probability theory. --- Algorithms. --- Dynamical Systems and Ergodic Theory. --- Measure and Integration. --- Probability Theory and Stochastic Processes. --- Mathematical Applications in Computer Science. --- Algorism --- Algebra --- Arithmetic --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Math --- Science --- Analysis situs --- Position analysis --- Rubber-sheet geometry --- Geometry --- Polyhedra --- Set theory --- Algebras, Linear --- Differential dynamical systems --- Dynamical systems, Differentiable --- Dynamics, Differentiable --- Differential equations --- Global analysis (Mathematics) --- Topological dynamics --- Foundations --- Dynamics. --- Ergodic theory. --- Measure theory. --- Probabilities. --- Computer science—Mathematics. --- Computer mathematics. --- Computer mathematics --- Electronic data processing --- Mathematics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Lebesgue measure --- Measurable sets --- Measure of a set --- Algebraic topology --- Integrals, Generalized --- Measure algebras --- Rings (Algebra) --- Ergodic transformations --- Continuous groups --- Mathematical physics --- Measure theory --- Transformations (Mathematics) --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics


Book
Fractal Dimension for Fractal Structures
Authors: --- --- --- ---
ISBN: 9783030166458 Year: 2019 Publisher: Cham Springer International Publishing :Imprint: Springer

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