000			02459nam a22002417a 4500
999			_c4116 _d4116
005			20221111134543.0
008			221111b ||||| |||| 00| 0 eng d
020			_a9781493938353
082			_a330.015195 _bCAR
100			_aCarmona, Rene _99952
245			_aStatistical analysis of financial data in R
250			_a2nd
260			_bSpringer _aSwitzerland _c2014
300			_axvii, 588 p.
365			_aEURO _b109.99
520			_aAbout this book Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This book fills this gap by addressing some of the most challenging issues facing any financial engineer. It shows how sophisticated mathematics and modern statistical techniques can be used in concrete financial problems. Concerns of risk management are addressed by the control of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Data description techniques such as principal component analysis (PCA), smoothing, and regression are applied to the construction of yield and forward curve. Nonparametric estimation and nonlinear filtering are used for option pricing and earnings prediction. The book is intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. Because it was designed as a teaching vehicle, it is sprinkled with practical examples using market data, and each chapter ends with exercises. Practical examples are solved in the computing environment of R. They illustrate problems occurring in the commodity and energy markets, the fixed income markets as well as the equity markets, and even some new emerging markets like the weather markets. The book can help quantitative analysts by guiding them through the details of statistical model estimation and implementation. It will also be of interest to researchers wishing to manipulate financial data, implement abstract concepts, and test mathematical theories, especially by addressing practical issues that are often neglected in the presentation of the theory.
650			_aR (Computer program language) _91512
650			_aMathematical statistics _9837
650			_aBusiness mathematics _9179
650			_aFinance--Econometric models _91870
650			_aFinance--Mathematical models _9180
942			_2ddc _cBK