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Books > Business & Economics > Industry & industrial studies > Service industries > Financial services industry
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Mathematical and Statistical Methods for Actuarial Sciences and Finance - eMAF2020 (Hardcover, 1st ed. 2021)
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Mathematical and Statistical Methods for Actuarial Sciences and Finance - eMAF2020 (Hardcover, 1st ed. 2021)
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The cooperation and contamination between mathematicians,
statisticians and econometricians working in actuarial sciences and
finance is improving the research on these topics and producing
numerous meaningful scientific results. This volume presents new
ideas, in the form of four- to six-page papers, presented at the
International Conference eMAF2020 - Mathematical and Statistical
Methods for Actuarial Sciences and Finance. Due to the now sadly
famous COVID-19 pandemic, the conference was held remotely through
the Zoom platform offered by the Department of Economics of the Ca'
Foscari University of Venice on September 18, 22 and 25, 2020.
eMAF2020 is the ninth edition of an international biennial series
of scientific meetings, started in 2004 at the initiative of the
Department of Economics and Statistics of the University of
Salerno. The effectiveness of this idea has been proven by wide
participation in all editions, which have been held in Salerno
(2004, 2006, 2010 and 2014), Venice (2008, 2012 and 2020), Paris
(2016) and Madrid (2018). This book covers a wide variety of
subjects: artificial intelligence and machine learning in finance
and insurance, behavioral finance, credit risk methods and models,
dynamic optimization in finance, financial data analytics,
forecasting dynamics of actuarial and financial phenomena, foreign
exchange markets, insurance models, interest rate models, longevity
risk, models and methods for financial time series analysis,
multivariate techniques for financial markets analysis, pension
systems, portfolio selection and management, real-world finance,
risk analysis and management, trading systems, and others. This
volume is a valuable resource for academics, PhD students,
practitioners, professionals and researchers. Moreover, it is also
of interest to other readers with quantitative background
knowledge.
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