WILEY Mathematics and Statistics for Financial Risk Management

WILEY Mathematics and Statistics for Financial Risk Management By Miller, Michael B. Published by WILEY Publication Date: 2014-02-07 Subject: Business & Economics Finance General, Business & Economics Finance - General, Mathematics Applied, Mathematics Probability & Statistics General, Applied Mathematics, Finance, Finance & Accounting, Probability & Statistics, Finance And The Finance Industry, Probability And Statistics, Hc Wirtschaft Betriebswirtschaft, Business & Economics Finance General, Business & Economics, Finance, General, Finance & Accounting, Hc Wirtschaft Betriebswirtschaft, Hc, Wirtschaft, Betriebswirtschaft, General Finance & Investments, Business Mathematics, Insurance - Risk Assessment & Management Subject Keywords: Michael B. Miller; Michael Miller; Mike Miller; mathematics and statistics for financial risk management; financial risk management; statistical finance; statistical finance in risk management; risk management; risk management mathematics; risk models; applying risk models; developing risk models; popular risk models; popular risk models used by practitioners; practitioner oriented; mixture models; decay factors; risk professionals; financial engineers; corporate risk managers; financial risk managers; financial risk manager; financial risk manager exam; FRM; FRM exam; probability; Bayes' Law; Bayes' Theorem; Bayes rule; expected value; skewness; kurtosis; distributions; Monte Carlo; Monte Carlo simulation; Cholesky decomposition; Cholesky; Principal Component Analysis; PCA; regression; linear regression; optimal hedging; hedging; random walks; drift diffusion; GARCH; jump diffusion; interest rate models; value at risk; VaR; EWMA; Excel examples; spreadsheet examples; Excel; quant; quantitative; quantitative techniques, Michael B. Miller; Michael Miller; Mike Miller; mathematics and statistics for financial risk management; financial risk management; statistical finance; statistical finance in risk management; risk management; risk management mathematics; risk models; applying risk models; developing risk models; popular risk models; popular risk models used by practitioners; practitioner oriented; mixture models; decay factors; risk professionals; financial engineers; corporate risk managers; financial risk managers; financial risk manager; financial risk manager exam; FRM; FRM exam; probability; Bayes' Law; Bayes' Theorem; Bayes rule; expected value; skewness; kurtosis; distributions; Monte Carlo; Monte Carlo simulation; Cholesky decomposition; Cholesky; Principal Component Analysis; PCA; regression; linear regression; optimal hedging; hedging; random walks; drift diffusion; GARCH; jump diffusion; interest rate models; value at risk; VaR; decay factors; EWMA; Excel examples; spreadsheet examples; Excel; quant; quantitative; quantitative techniques Genre: Business & Economics, Finance, General, Finance & Accounting, Hc, Wirtschaft, Betriebswirtschaft Target Audience: Professional and scholarly