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Developing Financial Analysis Tools
Laying the Foundation of Financial Markets
The Course Overview (1:57)
Performing Time Value of Money in R (8:13)
Evaluating the Equity Markets Using the quantmod Package in R (10:46)
Fundamental and Technical Analysis in R (17:55)
Bond Valuation in R (9:36)
Yield Curve (9:27)
Introduction to Derivatives (10:04)
Introduction to Shiny (10:18)
Financial Data Extraction and Cleaning
Extracting Financial Data from Various Sources (13:35)
Extracting Data from the Web (11:33)
Understanding Tidy Data Using the tidyquant Package (8:02)
Visualizing Financial Data in R (7:19)
Generating a User Interface in Shiny (11:02)
Creating a Shiny Application (7:55)
Basic Statistics Using R
Summarizing Financial Data in R (8:24)
Outlier Analysis in R (5:27)
Calculating Asset Return (8:06)
Understanding Population and Sample Data (6:29)
Evaluating Skewness and Kurtosis in Financial Data in R (6:35)
Probability Distribution of Asset Returns (8:50)
Market Volatility, Correlation, and Covariance in R (7:18)
Introduction to Time Series Modeling
Basic Features of a Time Series (9:13)
Decomposition of Time Series Data (9:07)
Stationarity and Autocorrelation in R (8:29)
Stationarity and Autocorrelation in R (Continued) (7:59)
Time Series Modeling in R
Time Series Modeling in R (Continued) (9:07)
ARIMA in R (12:10)
Advance Topics in Time Series Modeling
Forecasting in R (11:05)
Accuracy of Forecast (10:28)
Cointegration
Cointegration (Continued) (7:12)
Vector Autoregression (VAR) (13:49)
Forecasting in R