Introduction to Computational Finance and Financial Econometrics

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来源：www.coursera.org

10个序列

等级：入门

经济学, 金融

语言：英语

1分

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Learn mathematical and statistical tools and techniques used in quantitative and computational finance. Use the open source R statistical programming language to analyze financial data, estimate statistical models, and construct optimized portfolios. Analyze real world data and solve real world problems.

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课程大纲

Topics covered include:

Computing asset returns
Univariate random variables and distributions

Characteristics of distributions, the normal distribution, linear function of random variables, quantiles of a distribution, Value-at-Risk

Bivariate distributions

Covariance, correlation, autocorrelation, linear combinations of random variables

Time Series concepts

Covariance stationarity, autocorrelations, MA(1) and AR(1) models

Matrix algebra
Descriptive statistics

histograms, sample means, variances, covariances and autocorrelations

The constant expected return model

Monte Carlo simulation, standard errors of estimates, confidence intervals, bootstrapping standard errors and confidence intervals, hypothesis testing , Maximum likelihood estimation, review of unconstrained optimization methods

Introduction to portfolio theory
Portfolio theory with matrix algebra

Review of constrained optimization methods, Markowitz algorithm, Markowitz Algorithm using the solver and matrix algebra

Statistical Analysis of Efficient Portfolios
Risk budgeting

Euler’s theorem, asset contributions to volatility, beta as a measure of portfolio risk

The Single Index Model

Estimation using simple linear regression

教师

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Eric Zivot - Economics Department

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重头开始

Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.