TST Live Pilot – Oil Stocks Ranking Model
Site Overview
See Pilots Home Page for background on this pilot. Energy Coverage Evolution is the manager’s plan to extend the system coverage to natural gas and petrochemical stocks after the pilot. Model Framework describes the two main components of the system: the Macro System for forecasting oil prices and the Stock Ranking System for ranking the stocks.
The Dynamic Drivers Sub-Model is the pilot model that the manager will use to learn how to picture his thought process and lay the foundation for advancing to the longer term project of building out his custom TST Energy Stocks System. The Common Risks Model and the Dynamic Drivers Categories Model are models which our THINKSheet team manages to help the manager develop the best framework and judgments for his pilot model — with the fewest number of hours invested on his part.
Unique Swan Approach describes our unique swans approach together with a link to the generic description of the Swans Approach under the Platform menu. US Shale Production – Swans Watch Matrix is an example of the matrices we provide to help the manager make the most accurate decisions with respect to the dynamic drivers and judgments in the Dynamic Drivers Sub-Model.
Energy Coverage Extension Plan
The manager’s plan is to start with oil stocks and then extend the system to cover natural gas and petrochemical stocks. The stocks below are his initial test coverage to get a sense of how the model works.
Initial Test Coverage
Energy Stocks – S&P 500
Stock Ranking System
The manager’s objective is to anticipate and prepare for major price movements for each stock by forecasting the price of oil and then identifying the cheapest stocks with the best fundamentals that have a near-term, positive catalyst, low risk, and beneficial X-factors. The Stock Ranking System combines (1) a Macro System — TST Oil Prices — using a template co-developed with Energeia, our TST Energy Systems partners, and (2) a Stock Ranking System using the template originally developed for and used by Morgan Stanley and then used at Evercore Partners and several other firms.
Oil Price Macro System Generates Oil Price Assumptions
See TST LIve Oil & TST Oil Prices for TST Oil Prices Macro System that forecasts oil prices. The oil price forecast generates the oil price assumed in the Stock Ranking System. NOTE: The price forecast time horizon for the Oil Trading System modeled in Live Oil is 1 week. The forecast for this Oil Stocks Model is 12 months. However, the manager also uses the shorter time frames in Live Oil to make sure his stocks are not subject to an excessive increase or decline during his 12 month holding period.
Stock Ranking Model Framework
The Stock Ranking Model has two components: Fixed Drivers & Dynamic Drivers as illustrated below. The Fixed Drivers — Valuation & Financials — are quantitative whose overall scores are generated by their sub-models — and the Dynamic Drivers — Catalysts, Risks and X Factors — are qualitative based on subjective judgments input by the manager. The Dynamic Drivers enable him to react to new conditions faster than the Fixed Drivers because they are broader and more versatile and dynamic.
Stock Ranking Framework
Our standard procedure is to start with the Dynamic Drivers Sub-Model because (1) it involves a new approach to modeling and provides clients with a competitive advantage over their peers who cannot model their QL factors in the “language of the market” and (2) our clients usually have their own QT models. We then help them synthesize their QL & QT models into one seamless model of their whole thought process.
USER DOCUMENTATION NOTE: To keep everyone focused on the models and analysis, we use separate sites for the manager’s user documentation. You can access the user documentation for (1) the TST model framework at Model Framework, (2) methodology, metrics and definitions and at TMethod + Metrics and (3) an example of a complete case study at TST Equities – Morgan Stanley Section.
Unique Swans Approach
The manager is using our unique swans approach to forecast major price moves. We use swans to refer collectively to black swans, gray swans, white swans, catalysts and drivers. THINKSheet helps the manager systematically — yet intuitively and dynamically — identify and quantify the swans using an array of proprietary tools, such as the US Shale Production Matrix below.
THINKSheet is a semantics-driven platform designed to help our clients communicate the greatest meaning in the fewest words. For detailed descriptions of the swans and their gradations, see Swans Approach.
THINKSheet Models
The 3 models that follow work together: Dynamic Drivers Sub-Model, Framework Organizational Tool and Dynamic Drivers.Categories Model.
Dynamic Drivers Sub-Model
The objective of this model is to identify the stocks with the most positive catalysts, lowest common risks and most positive x factors.
Framework Organizational Tool – Common Risks Model
This framework organizational model is designed to help the manager identify the 3 most serious risks common to all of the stocks that most differentiate them. The criteria are that the risks (1) are common to the group, (2) have great impact on price, (3) are least efficiently priced in, (4) differentiate the stocks, and (5) are not covered in the other specifically-defined stock ranking model categories or in the macro model that generates the forecasted oil price. Macro Model Answer is the oil price which is the most important, differentiated common risk.
Dynamic Drivers Categories Model
The Dynamic Drivers Categories Model below works together with the Dynamic Drivers Sub-Model. The objective is to identify the most important and dynamic categories of drivers of the stock prices for the group to help the manager correctly input the 7 drivers and their weights, impacts & probabilities. The categories are dynamic – i.e., the categories and their rankings are constantly changing as market conditions change.
US Shale Production
To help the manager accurately identify the dynamic drivers for US shale oil production, we have provided the swans watch matrix below. (The financial professionals on our team developed the Financing category and a petroleum engineer the Production Costs and Wells & Rigs categories.) The matrix provides an organized checklist for the manager to consider when making his judgments about the US shale oil production drivers. Once the manager progresses beyond the pilot, he assumes a far more active role in updating the matrix — but with our ongoing support.
Swans Watch Matrix
Energy Geopolitics
Why is Putin in Syria?
How are the great powers realigning?
What’s holding up the Power of Siberia pipeline?
What is the impact of the New Maritime Silk Road?
What are the risks to the Saudi oil infrastructure?
How are the great powers shifting alliances and opposition?
The manager uses the swans watch matrix below to make judgments about the geopolitical forces and risks facing the largest producers, such as the above. He also uses the Middle East Geopolitics section of our TST Oil Price Trading System in the Live Oil/Sample Scenarios site cross-linked to this site.
Swans Watch Matrix
The tables below summarize the largest oil & gas producers & consumer impacted by energy geopolitics.
Largest Oil Producers
Largest Natural Gas Producers & Consumers
Russian Gas Exports To Europe
The table below indicates why Putin is so strongly motivated to protect his leverage over Europe in terms of gas delivery.
The map below shows the strategic geographical location of Syria in terms of the two major gas pipelines from the Middle East producers to Europe. The Islamic Pipeline would deliver gas from Iran & Iraq through Syria to Europe. The Qatar-Turkey pipeline would deliver gas from the Gulf States to Europe. These are the best routes from the Middle East to Europe and are subject to great contention among the great energy powers. They provide an opportunity for Russia to partner with Iran and Iraq and a threat from the Gulf States for the Europe customers anxious to wean themselves from Russia’s gas leverage.
Strategic Gas Pipelines to Europe with Routes through Syria
Threats to Saudi Oil Infrastructure
There are numerous threats to Saudi Arabia’s oil infrasturue, particularly because of the close proximity of the main fields, processing facilities, and port terminals for the world’s largest exporter and its close location to Iran and the Strait of Hormutz and in the Eastern Province, the home of the disenfranchised Shiites.. The threats come from ISIS, Al Quaeda, lone wolfs, all as detailed in the Security Threats to Saudi Arabia’s Oil Infrastructure paper by the Institute for Gulf Affairs, a think tank in Washington D.C.
TST Models under Construction: Putin Pipeline Strategy & Synthesis Swans
Two TST model are under construction: Putin Pipeline Strategy and Synthesis Swans. Putin Pipeline Strategy models our team’s view of Putin’s pipeline strategy for Europe and East Asia. Oil Stocks Synthesis Swans is the synthesis of the factors that drive oil stock prices in the TST Stock Ranking Model. Synthesis is a key concept that separates THINKSheet output from traditional models. Go to Interconnections can be Black Swans in Platform/Swans Approach site to see Nassim Taleb explanation of why interconnections can be black swans. The explanation is particularly compelling because Taleb’s example was the financial crisis of 2007-10 before it occurred.
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