Introduction to Supply & Demand

It is paramount that you understand as a speculator that supply and demand is only a theory based model. How physical markets filter into financial oil price movements is limited, and it does so via a pricing system using 3_rd_ party indexes and tendering windows that only a few of the biggest oil traders in the world participate in, and only for a subset of physical supply depending on the contract being priced. The financial price at settlement for a specific oil contract (of which there are hundreds) can therefore be substantially distorted away from the wider physical transactions taking place around the world. It is therefore imperative to also analyse trader positioning, sentiment and other technical signals alongside supply and demand analysis.

What Is a Supply & Demand Model?

A supply and demand model in oil markets seeks to explain and predict over supply or deficits. The net result is a build-up, or draw, of oil stocks around the world. Supply and demand modelling can be done for the global crude market, but also by product like gasoline, diesel and propane etc.

Supply and demand modelling can, and does, go deeper and deeper into the physical world. This can be by product and region, which will need accounting of where cargos go from and to, as well as pipeline flows. It is important to remember that this work is being done to a very detailed level by all the major oil companies around the world, and they spend a lot of money doing it. Trying to build one yourself to compete with the analysis out there that is done will be difficult, especially as the costs of sourcing the data that goes into minute detail is astronomical.

The good news is that with so much of this analysis being done, there is a lot of group think and therefore it is straight forward to find out the thinking of the majority of the market. You can also see the result if their thinking by analysing their actions in the financial oil market, making trader positioning analysis part of the astute speculators repertoire. It should also be noted that it is becoming easier and easier (and cheaper) to access top level supply and demand modelling.

To understand how traders track supply and demand, the following steps are a rough guide:

Step 1: Understand the Components of Supply & Demand

Supply:

• Crude Oil Production: Track output from key producers, such as OPEC countries, the US, and Russia. Production levels can fluctuate due to policy decisions, resource availability, and infrastructure capacity.

• Spare Capacity: Monitor the additional production capacity that can be brought online during times of increased demand or supply disruptions. Spare capacity acts as a buffer and influences market stability.

• Exports and Imports: Analyse global trade flows, focusing on major exporters and importers, to understand regional supply dynamics.

• Inventories: Include data on commercial and strategic stockpiles. Inventory levels often act as a barometer for short-term supply-demand imbalances.

Demand:

• Global Consumption Trends: Evaluate the main drivers of oil consumption, such as industrial activity, transportation, and heating. Emerging markets are particularly important as they often drive demand growth.

• Seasonality: Account for seasonal variations, such as increased demand for heating oil in winter or gasoline during summer travel seasons.

• Economic Indicators: Use GDP growth, industrial output, and consumer spending data to gauge future demand trends.

Step 2: Incorporate External Influences

Newman’s analysis highlights the importance of external factors that can disrupt the traditional supply-demand balance:

Geopolitical Factors:

• Sanctions, conflicts, and trade restrictions can disrupt supply chains and create volatility.

• Political decisions by organisations like OPEC significantly impact production levels.

Financial Market Activity:

• Speculative trading in oil derivatives, such as futures and options, can amplify price movements. Track speculative positions and open interest in major markets.

• The forward curve (contango or backwardation) reflects market sentiment about future supply and demand balances.

Macroeconomic Factors:

• Currency fluctuations, particularly in the US dollar (the currency for oil trading), affect global oil prices.

• Economic growth or contraction directly impacts oil consumption.

Step 3: Gather & Analyse Data:

Data Sources:

• Production Data: Obtain from OPEC reports, US Energy Information Administration (EIA), and International Energy Agency (IEA).

• Consumption Data: Use reports from the IEA, BP Statistical Review, or national energy agencies.

• Inventory Reports: Track weekly or monthly inventory levels from the EIA or regional agencies.

• Geopolitical Updates: Monitor news and updates on sanctions, conflicts, and trade agreements.

• Market Sentiment: Analyse futures market data and speculative positioning from sources like the Commodity Futures Trading Commission (CFTC).

Quantitative Analysis:

• Develop a supply-demand balance sheet that accounts for production, consumption, and inventories.

• Use statistical tools to identify trends and anomalies in historical data.

Step 4: Build the Model

Mathematical Framework:

• Basic Equation: Where is price, is quantity supplied, and is quantity demanded.

• Elasticities: Include price elasticity of supply and demand to model how sensitive producers and consumers are to price changes.

• Equilibrium: Solve for the price where supply equals demand:

• Dynamic Adjustments: Use time-series data to model lag effects, such as the time it takes for production to respond to price changes.

Implementation Tools:

• Spreadsheets: Use Excel for basic modelling and visualisation.

• Programming: Employ Python, R, or MATLAB for more advanced models and forecasts.

• APIs: Integrate real-time data feeds for continuous updates.

Step 5: Test & Refine the Model:

• Backtesting: Evaluate the model’s accuracy using historical data.

• Scenario Analysis: Test how the model responds to hypothetical scenarios, such as a sudden production cut or demand surge.

• Ongoing Updates: Regularly update the model with the latest data to maintain accuracy.

Step 6: Use the Model to Predict Markets

Applications:

• Identify Trends: Use the model to forecast price trends based on expected changes in supply and demand.

• Spot Opportunities: Detect potential price spikes or drops due to imbalances.

• Risk Management: Anticipate market volatility and adjust trading strategies accordingly.