文件名称：computational-finance-and-financial-econometrics-with-r:计算金融和金融计量经济学与 r
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更新时间：2024-06-20 13:27:31
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计算金融和金融计量经济学与 r 计算金融和金融计量经济学与 r
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computational-finance-and-financial-econometrics-with-r-master
----Lab-5---Analyzing-Stock-Returns()
--------Return distribution comparison(354B)
--------Create graphical summary for a return series(548B)
--------Getting the financial data(1KB)
--------Compute univariate descriptive statistics(527B)
--------Annualized monthly estimates(278B)
--------Calculating the returns(442B)
--------Plotting financial data with PerformanceAnalytics(789B)
--------Bivariate graphical analysis(241B)
----Lab-2---Random-Variables-and-Probability-Distributions()
--------Compute simple total returns and dividend yields(194B)
--------Determine the value-at-risk of simple monthly returns(232B)
--------Compute continuously compounded monthly returns(151B)
--------Compute annual returns(196B)
--------3(176B)
--------Compute probabilities(275B)
--------Compute quantiles(175B)
--------Determine the value-at-risk of continuously compounded monthly returns(262B)
--------Compute simple monthly returns(150B)
--------Add second normal curve(350B)
----Lab-8---Computing-efficient-portfolios-using-matrix-algebra()
--------The CER model(454B)
--------The efficient frontier(347B)
--------The tangency portfolio(605B)
--------Loading in your data set(557B)
--------The global minimum variance portfolio - Part Two(436B)
--------The global minimum variance portfolio - Part One(348B)
--------An efficient portfolio(532B)
--------The global minimum variance portfolio - End game(261B)
----README.md(114B)
----Compute probabilities(274B)
----Lab-6---Constant-expected-return-model()
--------Normality of the asset returns(148B)
--------Download the data and calculate the returns(1KB)
--------Estimate the standard error of the correlation parameter(380B)
--------Bootstrapping(412B)
--------The standard error of the variances(280B)
--------Hypothesis test for the mean(92B)
--------Hypothesis test for the correlation(165B)
----Return-Calculations()
--------Compare simple and continuously compounded returns.R(525B)
--------Calculate simple returns(343B)
--------Graphically compare the simple and continuously compounded returns(498B)
--------Calculate growth of $1 invested in SBUX(399B)
--------Add dates to simple return vector(498B)
--------Compute continuously compounded 1-month returns(536B)
----Lab-4---Simulating-Time-Series-Data()
--------A different MA(1) model(688B)
--------Simulate data from a MA(1) model(145B)
--------Plotting the theoretical and the sample ACF(728B)
--------An AR(1) model(677B)
--------Plot the data from the simulated MA(1) model(296B)
----Lab-3---Bivariate-Distributions()
--------Simulate data(329B)
--------Plot the simulated data(215B)
--------Uncorrelated random variables(862B)
--------Compute a joint probability(535B)
--------Negatively correlated random variables(868B)
--------Covariance matrix(240B)
--------Add lines to the plot(274B)
----Lab-7---Introduction-to-portfolio-theory()
--------The CER model(720B)
--------Tangency Portfolio(415B)
--------Global Minimum Variance Portfolio(978B)
--------An Efficient Portfolio with 30% Tangency(1KB)
--------The Sharpe Slope(188B)
--------Loading in your data set(230B)
--------Tangency portfolio and T-bills(1KB)
--------Adding T-bills to your portfolios(886B)
--------A portfolio of Boeing and Microsoft stock(871B)