In this journal entry, I am going to demonstrate the notion of correlation and how it can be used in trading. We recently published an article about applying correlation to trading strategies which explains the nitty-gritty of price correlation. This journal entry demonstrates it in practice.

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**Assumptions**

The first step in applying correlation to the trading strategies is to identify what underlying assets correlate. One of the ways to do that is to configure charting software so that correlation coefficient is calculated. The value of the coefficient closer to 1 demonstrates strong direct correlation while the value of the coefficient closer to -1 demonstrates strong inverse correlation. The closer the value of the coefficient to the edge values the stronger the correlation between the underlying assets.

For this journal entry I decided to pick two industries where the stock prices could potentially correlate:

- Banking
- Technology

After testing a range of stocks on the matter of correlation, the following ones which correlate have been identified:

- Bank Of America (BAC) <-> Citigroup (C) / Banking industry
- Microsoft (MSFT) <-> Apple (AAPL) / Technology industry

These stocks demonstrate strong direct correlation. So what that means for us? Strong direct correlation means that the changes in the price of one underlying asset show the changes in the price of the correlated underlying asset. The direction of the change depends on whether the correlation is direct or indirect. Taking that into consideration, only one underlying asset can be thoroughly watched while the bet can be done on both ones.

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**Demonstration of correlation**

The correlation was applied to Bollinger Bands strategy. Furthermore, stochastic indicator was used to make the trading signals stronger.

The first trade was done with a pair of **Bank Of America <-> Citigroup**. BAC is the stock which was analysed. These underlying assets showed strong correlation. The coefficient value was nearly 0.9. Moreover, the historical data demonstrated strong direct correlation as well. Stochastic signaled oversold asset. Finally, the price broke the bottom band. All of that signaled about purchasing CALL options which were purchased for both correlated underlying assets – BAC and C.

Unfortunately, the main downward trend turned out to be stronger which led to the options been expired out of the money. By having a glance at broker’s chart, we can see the correlation between prices. There are very similar ups and downs.

The next trade was done with a pair of **Microsoft <-> Apple**. MSFT is the stock which was analysed. The stocks demonstrated strong direct correlation of nearly 0.8. The historical data also showed direct correlation of the stock prices. Stochastic signaled oversold asset and the price broke the bottom band. Taking that into consideration, CALL options were purchased for both underlying assets.

This time, the main downward trend turned out to be prevailing and MSFT option expired out of the money. Luckily, AAPL expired on the edge in the money. The correlation of stock prices can be seen by having a look at broker’s charts. The ups and downs look very similar on the charts.

Another trade that was taken with **Bank Of America <-> Citigroup** pair showed much better results. The pair demonstrated strong direct correlation of above 0.8. As for the stochastic indicator, it helped identify an oversold asset. As we are testing Bollinger Bands strategy with correlation, breaking the bands is considered to be one of the most strong indicators. The price actually broke the upper band making an opportunity to place PUT option for both BAC and C.

Eventually, the prediction turned out to be correct and both trades closed in the money. The amount invested for each trade was $100 with 75% profit which resulted in $150 in total in profit.

The last trade to demonstrate correlation was done with **Bank Of America <-> Citigroup** pair again. The pair demonstrated strong direct correlation (~0.8). Stochastic signaled overbought asset. The price broke the top band. PUT option was purchased for both stocks.

Unfortunately, the trend did not change the direction and the options expired out of the money.

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**Conclusion**

In this journal entry, I demonstrated the notion of correlation and how it can be used with Bollinger bands trading strategy. How do you apply correlation in your trading?

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