Sep 22

## R Code For Statistics and Finance: An Introduction

Posted by abiao at 19:28 | Code » Code site | Comments(6) | Reads(11212)
Statistics and Finance: An Introduction is a useful book emphasizing the applications of statistics and probability to finance, such as regression, ARMA and GARCH models, the bootstrapping, and nonparametric regression using splines. For an easier learning and application, the author also public the R codes and examples at http://www.stat.tamu.edu/~ljin/Finance/stat689-R.htm.

Possible interesting sections:
Fig 2.11 & R Code: Comparison on normal and heavy-tailed distributions.
Fig 2.12 & R Code: Survival function of a Pareto distribution with c=0.25 and a=1.1 and of normal and exp distribution on being greater than 0.25.
Fig4.1  &  R Code: Autocorrelation functions of AR(1) processes with r equal to 0.95 , 0.75,0.2 and -0.9
Fig4.2  &  R Code: Simulations of 200 Observations from AR(1) processes with various parameters. The white noise process is the same for all four AR(1) Processes.
Fig4.7  &  R Code: Time series plot of the 3 month Treasury bill rates, plot of first differences, and ACFs.  The data set contains monthly values of the 3 month rates from Jan 1950 until Mar 1996.
Model Fit Examples R Codes: Fit GE Daily log return using AR(1),AR(6), MA(2), ARMA(2,1) and log price using ARIMA(2,1,0) Model
Fig4.9  &  R Code: Time series plot of the daily GE log Prices with forecasts from an ARIMA(1,1,0) Model.
Fig5.3  &  R Code: Expected frontier and tangency portfolio with different r.
Fig5.4 : Efficient frontier (solid) plotted for N=3 assets.
Tangency portfolio with the constraints R Code:
R Code  Volatility smiles and polynomial regressionpage 283-284
Fig 8.15: Ratio of Log Return on a call to log return on the underlying stock. Page 291.
Fig 9.4 : Polynomial and spline estimates of forward rates of U.S. Treasury bonds.
Fig 10.5 : Actual efficient frontier for the sample (optimal) and bootstrap efficient frontier (achieved) for each of six bootstrap resamples.
Fig 10.6:  Results from 400 bootstrap resamples. For each resample, the efficient portfolio with a mean return of 0.012 is estimated. In the upper subplot, the actual mean return and standard deviation of the return are plotted as a small dot. The large dot is the point on the efficient frontier with mean return of 0.012.
Model Fit:
** R Code:  GARCH Model Fit, Page 373.

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Hello,

The above link for R codes for the Stats and Finance is not working. I bought the book and was mid way through learning some of this stuff in R. Would greatly appreciate you could tell me any alternate site for this.

Regards,
Vinay
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