Introduction to Computational Finance and Financial Econometrics
开始时间: 04/22/2022
持续时间: 10 weeks
课程主页: https://www.coursera.org/course/compfinance
课程评论: 2 个评论
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课程简介
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.
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
课程评论(2条)
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要有光LTBL
2013-08-28 22:35
0 票支持; 0 票反对
前几周难度略低,从第7周左右才真正开始讲有趣的,前面还是概率统计什么的为主。作业基本上属于太简单(当然这是本科课)。。。R的覆盖还是不错的,视频虽然是课上录的但是质量还可以,不过不能下载视频和没有statement of accomplishment是挺讨厌的。
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课程图谱
2013-06-01 21:45
0 票支持; 0 票反对
“计量金融学与金融经济计量学导论” 曾于去年9月份和12月份分别在Coursera上开过,授课老师是华盛顿大学的Eric Zivot教授,他著有一本同名的教材,貌似是国内学计量金融学的必读,具体不太清楚。该课程需要使用R语言来分析金融数据和建立模型,貌似挺有意思的。
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