Fundamental analysis Macroeconomic indicators

How does Oil and Gas Affect the US Energy Sector?

Elena Berseneva 21 september 2022 28

In an earlier study, we have looked at WTI impact on the US dollar and other currencies, and have found that as the price of WTI rises, the exchange rates of the US dollar and Japanese yen decline, while the Canadian dollar and Russian ruble rise. No outstripping influence of oil prices on exchange rates has been revealed.

 

The connection of Brent oil with the Canadian dollar, and the Norwegian krone has also been studied. And again it turned out that it would not be possible to make money on the backlog of the Canadian dollar and the Norwegian krone from the oil rate.


Today, let's look at the history, whether oil and gas prices are ahead of the movement of the US energy sector (S&P 500 Energy).

Hypothesis
To conclusion

The rise in oil and gas prices is outpacing the rise in the S&P 500 Energy index. The decline in the S&P 500 Energy falls behind the decline in oil and gas prices.

К выводам
Data used

Timeframe: D1 (Daily)


Financial instruments


Period: September 1989 – August 2022


Signals to enter the market: 20274


Analysis of the obtained results 

 

The presence or absence of a connection between changes in the prices of oil and gas with changes in the S&P 500 Energy index will be determined using the day-to-day correlation coefficient and with shifts of 1, 2, 3, 4 and 5. Consider the entire available history depth, 5 years and separately 2022 year.

 

When determining the strength of the connection, we will focus on the Chaddock scale:



The results are presented in charts (red line - weak connection, yellow - moderate, green - noticeable): 



The day-to-day correlation coefficient (shift 0) shows the presence of:

  • moderate to noticeable direct relationship between changes in oil and the S&P 500 Energy. And in recent years, this relationship has been strengthening.
  • weak direct relationship between changes in gas and the S&P 500 Energy. In recent years, this relationship has also been strengthening.

 

Correlations in shifts indicate the presence of:

  • weak direct relationship, intensified in 2022, between changes in oil and the S&P 500 Energy at a shift of 2 days;
  • weak reverse relationship, intensified in 2022, between changes in oil and the S&P 500 Energy at a shift of 5 days;
  • weak direct relationship, intensified in 2022, between changes in gas and the S&P 500 Energy at shifts of 1, 2 and 3 days.

 

Thus, the correlation in shifts has shown us that with an increase in oil prices today, in 10-12% of cases, the S&P 500 Energy index rises on the 2nd day and decreases on the 5th day. And the upward movement of gas prices in 10-14% of cases coincides with the upward movement of the S&P 500 Energy on the 1st, 2nd and 3rd days.



Let's check whether the profitability analysis confirms the results of the correlation analysis.

 

Strategy

  • If oil prices rise today, open long positions on the S&P 500 Energy at the Open of the 2nd day (direct entry), short positions at the Open of the 5th day (reverse entry).
  • In the event of a decrease in the price of oil today, open short positions on the index at the Open of the 2nd day (direct entry), long positions at the Open of the 5th day (reverse entry).
  • In the event of an increase in the price of gas today, open long positions on the S&P 500 Energy at the Open of the 1st, 2nd and 3rd days.
  • In the event of a decrease in the price of gas today, open short positions on the index at the Open of the 1st, 2nd and 3rd days.

 

Closing positions:

  • at the close of the 1st (current) day after entering the market;
  • at the close of the 2nd day after entering the market;
  • at the close of the 3rd day after entering the market;
  • at the close of the 4th day after entering the market;
  • at the close of the 5th day after entering the market.



The strategy will be evaluated according to the following criteria:

 

  • The average rate of return reflects the relative change in the quotes of financial instruments in percentage. A positive value of the rate of return indicates the profitability of the strategy, a negative one indicates a loss. 


The average rate of return (R) of a financial instrument is calculated using the formula:

where:

n is the number of trades;

 

P (%) – the percentage of change in the quote of a financial instrument at the time of fixing a position, is calculated as follows:

 

for buy positions

P (%) = (position closing price - position opening price) / position opening price * 100%

 

for sell positions

P (%) = (position opening price - position closing price) / position opening price * 100%

 

  • The total rate of return (TR) is the sum of the profits from all trades. The greater the value of the total rate of return, the greater the profit brought by the signal during its testing period. 
  • Maximum drawdown (MaxDD) is the maximum loss in percentage terms from fixing unprofitable trades for the entire testing period. The lower the value of the maximum drawdown, the better the trading signal works.

where:

n – number of trades;

TRn – total rate of return of n trades;

DDn – drawdown at the time of closing the n-th trade;

MaxDD – maximum drawdown.




Let's look at the results of testing the strategy:

 

So, the analysis of the profitability of the strategy throughout history, for 5 years and for 2022 confirms the results of the correlation analysis. In recent years, the reaction of the index to changes in the prices of oil and gas has been increasing.

 


The following strategy parameters have shown a significant rate of return (from 0.3%) (direct entries are highlighted in green, reverse entries are highlighted in orange):


S&P 500 Energy vs
Entry-Exit
Brent
 2-1
 5-2
 5-3
WTI
 2-3
 5-2
 5-3
NG
 1-3
 1-4
 1-5
 2-2
 2-3
 3-1


 

Analysis of the total rate of return and maximum drawdown helps to identify the best parameters of the strategy:


The optimal entry-exit parameters are shown below (direct entries are highlighted in green, reverse entries are highlighted in orange):


S&P 500 Energy vs
Entry-Exit
Brent
 2-1
 5-2
WTI
 2-3
 5-3
NG
 1-3
 2-2


The numbers in the table mean that from January to August 2022, the strategy of buying the S&P 500 Energy at the Open on the 2nd day after the increase in Brent and selling the S&P 500 Energy at the Open on the 2nd day after the decrease in Brent and closing transactions at the Close of the same day (i.e., day 1 in the table) has brought significant profitability with the smallest drawdown.

 

The average rate of return of such a strategy is 0.4% with a drawdown of 13%. The total rate of return was 62%, and the number of market entries was 155.

Conclusion

There is a relationship between changes in the prices of oil and gas and the US Energy Sector Index. This relationship has been growing in recent years.

The correlation in shifts shows that when oil prices rise today, in 10-12% of cases, the S&P 500 Energy index rises on the 2nd day and falls on the 5th day. And the upward movement of gas prices in 10-14% of cases coincides with the upward movement of the S&P 500 Energy on the 1st, 2nd and 3rd days.

The profitability analysis confirms the results of the correlation analysis. And in recent years, the reaction of the index to changes in the prices of oil and gas has been intensifying.



The effectiveness of oil and gas in forecasting the US energy sector has been revealed.


And there is an opportunity to earn on the backlog of the S&P 500 Energy index from oil and gas prices.

Detailed results are shown in the Appendix:

XLSX (0.10 MB)SP 500 Energy vs Brent, WTI, NG.xlsx

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