Analysing *Oil, Gold, and Stocks* downloaded from Quandl in *3.91* seconds with the following original description:

Comparison of oil, gold and stock markets. USD.

## Variables

This daily dataset contains *16329* rows and *4* columns with the overall number of *65316* records. As the dataset is made of several variables to analyse, please choose and click on one from the below list for futher univariate analysis:

# Overview

Until then, let us check a line chart of the dataset:

There can be seen the *3* variables on the vertical axis based on the date shown on the horizontal axis.

References:

- Tukey, J. W. (1977).
*Exploratory Data Analysis*, Reading Massachusetts: Addison-Wesley.
- Sarkar, Deepayan (2008)
*Lattice: Multivariate Data Visualization with R*, Springer.

# Pair-wise cross-correlation

We can compare the above visualized time-series for relationships between those by the cross-correlation function that is basically a simple Pearson correlation estimate when the lag is 0. The negative and positive numbers on the x axis below shows a lag or delay on a daily basis, which means that we are looking for a possible temporal effect between the variables.

References:

- Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S*. Fourth Edition. Springer-Verlag.

*Oil* and *Gold*

It seems that the cross-correlation estimate for *Oil* and *Gold* is maximum at lag *-2* being *0.92*. So it seems that *Oil* and *Gold* are correlated.

*Gold* and *S&P500*

It seems that the cross-correlation estimate for *Gold* and *S&P500* is maximum at lag *0* being *0.63*. So it seems that *Gold* and *S&P500* are correlated.