Dow Jones Stock Index Analysis - part 7

Introduction

I go on with the definition of the ARMA-GARCH model for Dow Jones Industrial Average (DJIA) daily log-returns.

Packages

The packages being used in this post series are herein listed.

suppressPackageStartupMessages(library(lubridate))
suppressPackageStartupMessages(library(fBasics))
suppressPackageStartupMessages(library(lmtest))
suppressPackageStartupMessages(library(urca))
suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(quantmod))
suppressPackageStartupMessages(library(PerformanceAnalytics))
suppressPackageStartupMessages(library(rugarch))
suppressPackageStartupMessages(library(FinTS))
suppressPackageStartupMessages(library(forecast))
suppressPackageStartupMessages(library(strucchange))
suppressPackageStartupMessages(library(TSA))

Getting Data

We upload the environment status as saved at the end of part 2.

load(file='DowEnvironment.RData')

Volatility Analysis

Line plots of conditional volatility by year are shown.

par(mfrow=c(6,2))
pl <- lapply(2007:2018, function(x) { plot(cond_volatility[as.character(x)], main = "DJIA Daily Log returns conditional volatility")})
pl

Conditional volatility box-plots by year are shown.

par(mfrow=c(1,1))
cond_volatility_df <- xts_to_dataframe(cond_volatility)
dataframe_boxplot(cond_volatility_df, "Dow Jones Daily Log-returns conditional Volatility 2007-2018")

Afterwards 2008, the volatility basically tend to decrease. On year 2017 the volatility was lower with respect any other year under analysis. On the contrary, on year 2018 we experienced a remarkable increase of volatility with respect year 2017.

References

[1] Dow Jones Industrial Average [https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average]

[2] Skewness [https://en.wikipedia.org/wiki/Skewness]

[3] Kurtosis [https://en.wikipedia.org/wiki/Kurtosis]

[4] An introduction to analysis of financial data with R, Wiley, Ruey S. Tsay [https://www.wiley.com/en-us/An+Introduction+to+Analysis+of+Financial+Data+with+R-p-9780470890813]

[5] Time series analysis and its applications, Springer ed., R.H. Shumway, D.S. Stoffer [https://www.springer.com/gp/book/9783319524511]

[6] Applied Econometric Time Series, Wiley, W. Enders, 4th ed. [https://www.wiley.com/en-us/Applied+Econometric+Time+Series%2C+4th+Edition-p-9781118808566]

[7] Forecasting - Principle and Practice, Texts, R.J. Hyndman [https://otexts.org/fpp2/]

[8] Options, Futures and other Derivatives, Pearson ed., J.C. Hull[https://www.pearson.com/us/higher-education/product/Hull-Options-Futures-and-Other-Derivatives-9th-Edition/9780133456318.html]

[9] An introduction to rugarch package [https://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf]

[10] Applied Econometrics with R, Achim Zeileis, Christian Kleiber - Springer Ed. [http://www.springer.com/la/book/9780387773162]

[11] GARCH modeling: diagnostic tests [https://logicalerrors.wordpress.com/2017/08/14/garch-modeling-conditional-variance-useful-diagnostic-tests/]

Disclaimer

Any securities or databases referred in this post are solely for illustration purposes, and under no regard should the findings presented here be interpreted as investment advice or a promotion of any particular security or source.