Leading Indicators To Improve Decision Making in Oil Trading for TVC:USOIL by GMR-Capital

As you know, trading is a game of probabilities and navigating the financial markets is not always easy.

Different strategies that we use, such as Elliott wave analysis and pattern trading, can provide different scenarios for market movements.

However, market conditions are often uncertain and can extend beyond what is predicted by these strategies. In such cases, it is useful to have access to scientifically proven tools that can help us better assess the probabilities of different scenarios. One such tool is the use of leading indicators.

In this educational idea, we will explore the use of a leading indicator for Wti prices that embodies information from futures term spread and Relative Inventories.

Correlation with Relative Inventories is due to the basic supply and demand dynamics of the market. When inventories are high, there is an oversupply of oil which puts downward pressure on prices. Conversely, when inventories are low, there is a shortage of oil which puts upward pressure on prices.

Another useful metric for predicting oil prices is the term spread. The term spread refers to the difference between the prices of two oil contracts with different delivery dates. Researchers have found that changes in the term spread can be a leading indicator of future prices. The relationship between the term spread and oil prices comes from the fact that the term spread reflects changes in market expectations about future supply and demand for oil .

Studies have confirmed the predictive power of both relative inventories and the term spread. Starting in a seminar paper by Hamilton (1983), it was demonstrated that changes in inventories had a significant impact on future oil prices. Similarly, other research has shown that changes in the term spread have a strong correlation with future oil price movements (e.g., Kilian and Murphy, 2009), and now there are a vastity of academic paper that explores that correlations and the predictive possibilities.

Here another couple of references:

https://www.sciencedirect.com/science/ar…

https://gupea.ub.gu.se/bitstream/handle/…

Now, I want to bring you an example of how these empirical result can be exploited and used in trading.

In the main chart indeed I show an indicator constructed to reproduce the forecasting model proposed in the last article that I linked (Larsson, 2018).

This Forecasting Model is a time series ARIMA model that uses both relative inventories and term spread between 3-months ahead contract and the 40-months ahead contract, together with squared relative inventories to capture non linearities in the relation between inventories and wti price.

You can see the forecasted model in the red line, while the blue line is the weekly oil closing price.

I will report again here the chart for clarity:

After the uptrend ended, in which the forecasting model overshooted before crossing back, we can see that every time the red line (forecasting model) retested the blue line (actual price) the retest was followed by a strong decrease in price.
This was use for us as confirmation for our bearish scenario on oil , that we are still trading.

I hope you can find this post useful!

If you have any comment, please share, we will be happy!

Cheers, GMR