Mathematical and Statistical Methods for Actuarial Sciences and Finance (eBook, PDF)
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The interaction between mathematicians and statisticians working in the actuarial and financial fields is producing numerous meaningful scientific results. This volume, comprising a series of four-page papers, gathers new ideas relating to mathematical and statistical methods in the actuarial sciences and finance.The book covers a variety of topics of interest from both theoretical and applied perspectives, including: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit-scoring approaches; data envelopment ...
The interaction between mathematicians and statisticians working in the actuarial and financial fields is producing numerous meaningful scientific results. This volume, comprising a series of four-page papers, gathers new ideas relating to mathematical and statistical methods in the actuarial sciences and finance.
The book covers a variety of topics of interest from both theoretical and applied perspectives, including: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit-scoring approaches; data envelopment analysis; dynamic stochastic programming; financial contagion models; financial ratios; intelligent financial trading systems; mixture normality approaches; Monte Carlo-based methodologies; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; and time series analysis tools.
This book will be of value for academics, PhD students, practitioners, professionals, and researchers. It will also be of interest to other readers with some quantitative background knowledge.
The book covers a variety of topics of interest from both theoretical and applied perspectives, including: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit-scoring approaches; data envelopment analysis; dynamic stochastic programming; financial contagion models; financial ratios; intelligent financial trading systems; mixture normality approaches; Monte Carlo-based methodologies; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; and time series analysis tools.
This book will be of value for academics, PhD students, practitioners, professionals, and researchers. It will also be of interest to other readers with some quantitative background knowledge.
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