Quantitative Methods for Economics and Finance
Trinidad-Segovia, J.E.
Quantitative Methods for Economics and Finance - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (418 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-0197-0 9783036501963 9783036501970
10.3390/books978-3-0365-0197-0 doi
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& 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
Quantitative Methods for Economics and Finance - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (418 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-0197-0 9783036501963 9783036501970
10.3390/books978-3-0365-0197-0 doi
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& 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