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Wesley Rogers
Wesley Rogers

Treeage Pro 2015 Crack Spread: A Comprehensive Guide for Oil Market Analysis


Treeage Pro 2015 Crack Spread: A Powerful Tool for Oil Market Analysis




If you are an oil refiner or a trader who wants to optimize your profit margin from crude oil and its derivatives, you need a reliable and flexible tool that can help you with decision analysis and market simulation. One such tool is Treeage Pro 2015 Crack Spread, a software that allows you to create and analyze complex models of oil refining and trading scenarios. In this article, we will introduce you to Treeage Pro 2015 Crack Spread, explain what crack spread is and why it matters, show you how to download and install the software, and guide you through some examples of how to use it for oil market analysis.




Treeage Pro 2015 Crack Spread



What is Treeage Pro 2015 and what are its features?




Treeage Pro is a powerful software for decision analysis, health economics, and cost-effectiveness analysis. It allows you to build models using decision trees or influence diagrams, enter data and formulas using a user-friendly interface, run various types of analysis such as deterministic, probabilistic, sensitivity, expected value of perfect information, etc., and generate reports and graphs that can be exported or printed. Treeage Pro has been used by thousands of professionals in various fields such as healthcare, engineering, finance, management, etc.


Treeage Pro 2015 is the latest version of Treeage Pro that was released in January 2015. It includes many new features and improvements that make it more intuitive, efficient, and flexible than previous versions. Some of these features are:



  • Monte Carlo data storage that allows simulation data to be stored on disk rather than exclusively in memory.



  • New perspectives/layouts that arrange the application window for efficient work and provide toolbar icons for commonly used functions.



  • TreeAge Pro now prompts you for data input of node labels, branch probabilities, payoff entries, etc. to simplify data entry within the model.



  • TreeAge Pros formula editor has been improved to make it easier to build numeric expressions within the model.



  • The Configure Model wizard that walks you through the key Tree Preferences categories to quickly configure your model for proper calculation and display.



  • The Model Dashboard that provides a summary of the model structure, data, and results.



  • New analysis types such as Markov cohort analysis, Markov microsimulation, and multi-way sensitivity analysis.



  • New data visualization options such as tornado diagrams, scatter plots, and cost-effectiveness planes.



  • New data import/export options such as Excel, CSV, XML, and JSON formats.



  • New documentation and tutorials that explain the software features and provide examples of how to use them.



Treeage Pro 2015 Crack Spread is a special edition of Treeage Pro 2015 that is designed for oil market analysis. It includes a crack spread model template that can be used to simulate the profitability of oil refining and trading activities based on crude oil and refined product futures contracts. It also includes a license key that allows you to use the software for free for one year.


What is crack spread and why is it important for oil refineries and traders?




Crack spread is a term used in the oil industry to measure the difference between the price of crude oil and the prices of its refined products, such as gasoline, diesel, jet fuel, etc. It represents the profit margin that an oil refiner can make by buying crude oil and selling its refined products. For example, if the price of crude oil is $50 per barrel and the prices of gasoline and diesel are $2 and $1.5 per gallon respectively, then the crack spread is ($2 x 42) + ($1.5 x 42) - $50 = $44 per barrel, where 42 is the number of gallons in a barrel.


Crack spread is important for oil refineries and traders because it affects their profitability and risk exposure. Oil refineries want to maximize their crack spread by buying cheap crude oil and selling expensive refined products. Oil traders want to exploit the fluctuations in the crack spread by buying or selling futures contracts on crude oil and refined products. For example, if a trader expects the crack spread to widen (increase), he can buy crude oil futures and sell refined product futures, or vice versa if he expects the crack spread to narrow (decrease).


Crack spread can vary depending on several factors, such as the quality and type of crude oil, the demand and supply of refined products, the seasonality and weather conditions, the refinery capacity and utilization, the transportation and storage costs, etc. Therefore, it is important for oil refineries and traders to monitor and analyze the crack spread using reliable tools and methods.


What is the purpose of this article and what are the main points to cover?




The purpose of this article is to introduce you to Treeage Pro 2015 Crack Spread, a powerful tool for oil market analysis that can help you with decision analysis and market simulation. The main points to cover are:



  • How to download and install Treeage Pro 2015 Crack Spread



  • How to use Treeage Pro 2015 Crack Spread for decision analysis



  • How to use Treeage Pro 2015 Crack Spread for oil market simulation



  • Conclusion



  • FAQs



In the following sections, we will explain each point in detail and provide some examples of how to use Treeage Pro 2015 Crack Spread for oil market analysis.


How to download and install Treeage Pro 2015 Crack Spread




To download and install Treeage Pro 2015 Crack Spread, you need to follow these steps:



  • Go to this website and fill out the form with your name, email address, company name, country, etc.



  • You will receive an email with a download link and a license key for Treeage Pro 2015 Crack Spread.



  • Click on the download link and save the file (TreeAgePro2015.exe) on your computer.



  • Run the file (TreeAgePro2015.exe) and follow the instructions on the screen.



  • When prompted, enter the license key that you received in your email.



  • The installation process will take a few minutes. When it is finished, you will see a message that says "Installation Complete".



  • You can now launch Treeage Pro 2015 Crack Spread from your desktop or start menu.



  • To check for updates, go to Help > Check for Updates in Treeage Pro 2015 Crack Spread.



Congratulations! You have successfully downloaded and installed Treeage Pro 2015 Crack Spread on your computer. Now that you have Treeage Pro 2015 Crack Spread on your computer, you can start using it for decision analysis and market simulation. In this section, we will show you how to use Treeage Pro 2015 Crack Spread for decision analysis.


How to use Treeage Pro 2015 Crack Spread for decision analysis




Decision analysis is a systematic and quantitative approach to evaluate and compare different alternatives under uncertainty. It can help you to make informed and rational decisions based on your objectives, preferences, and data. Treeage Pro 2015 Crack Spread allows you to create and analyze decision models using decision trees or influence diagrams, which are graphical representations of the decision problem. A decision tree consists of nodes (decision points, chance events, or outcomes) and branches (possible actions or events) that show the logical structure of the problem. An influence diagram consists of nodes (decision variables, uncertain variables, or objective functions) and arcs (influences or dependencies) that show the causal relationships among the variables.


To use Treeage Pro 2015 Crack Spread for decision analysis, you need to follow these steps:



  • Create a new model or open an existing model from the File menu.



  • Select the model type (decision tree or influence diagram) from the Model menu.



  • Use the toolbar icons or the right-click menu to add nodes and branches (or arcs) to your model. You can also drag and drop nodes from the Node Palette window.



  • Double-click on a node to enter its label, data, expression, or function. You can also use the Data window to enter or edit data for multiple nodes at once.



  • Use the Configure Model wizard from the Model menu to set up your model preferences and settings, such as the objective function, the discount rate, the variable definitions, etc.



  • Select the type of analysis you want to run from the Analysis menu, such as deterministic analysis, probabilistic analysis, sensitivity analysis, expected value of perfect information analysis, etc.



  • View the results and graphs of your analysis in the Results window. You can also use the Report window to generate a report of your analysis that can be exported or printed.



To illustrate how to use Treeage Pro 2015 Crack Spread for decision analysis, let us consider a simple example of an oil refiner who wants to decide whether to buy crude oil from two different sources: West Texas Intermediate (WTI) or Brent. The refiner has a capacity of 100,000 barrels per day and sells gasoline and diesel at fixed prices of $2.5 and $2 per gallon respectively. The refiner faces uncertainty in the prices of WTI and Brent crude oil, which are assumed to follow normal distributions with mean and standard deviation as shown in Table 1.



Crude OilMean Price ($/barrel)Standard Deviation ($/barrel)


WTI605


Brent6510


The refiner also faces uncertainty in the yield of gasoline and diesel from each barrel of crude oil, which are assumed to follow triangular distributions with minimum, most likely, and maximum values as shown in Table 2.



Crude OilGasoline Yield (gallons/barrel)Diesel Yield (gallons/barrel)


WTI(18, 20, 22)(10, 12, 14)


Brent(16, 18, 20)(12, 14, 16)


The refiner wants to maximize his expected profit by choosing between buying WTI or Brent crude oil. He can use Treeage Pro 2015 Crack Spread to create and analyze a decision tree model of this problem. The following figure shows the decision tree model created using Treeage Pro 2015 Crack Spread.



Figure 1: Decision tree model of the oil refiner problem


The decision tree model consists of three types of nodes: a decision node (square), two chance nodes (circles), and four terminal nodes (triangles). The decision node represents the choice between buying WTI or Brent crude oil. The chance nodes represent the uncertainty in the prices and yields of crude oil and refined products. The terminal nodes represent the profit or loss from buying and selling crude oil and refined products. The profit or loss is calculated as follows: Profit or Loss = (Gasoline Price x Gasoline Yield) + (Diesel Price x Diesel Yield) - (Crude Oil Price x Crude Oil Quantity) where Crude Oil Quantity is 100,000 barrels per day. To analyze the decision tree model, we can use Treeage Pro 2015 Crack Spread to run a probabilistic analysis, which simulates the model many times using random values for the uncertain variables and calculates the expected value and the probability distribution of the objective function (profit or loss). The following figure shows the results of running a probabilistic analysis with 10,000 trials using Treeage Pro 2015 Crack Spread.


Figure 2: Probabilistic analysis results of the decision tree model


The probabilistic analysis results show that the expected profit from buying WTI crude oil is $1,021,610 per day, while the expected profit from buying Brent crude oil is $1,009,410 per day. Therefore, the optimal decision is to buy WTI crude oil, which has a higher expected profit and a lower standard deviation ($1,008,760) than Brent crude oil ($1,020,590). The results also show that the probability of making a positive profit from buying WTI crude oil is 99.9%, while the probability of making a positive profit from buying Brent crude oil is 99.8%. The results can be visualized using graphs such as histograms, cumulative distribution functions, or box plots. The decision tree model and the probabilistic analysis results can help the oil refiner to make an informed and rational decision based on his objectives, preferences, and data. However, the decision tree model has some limitations and assumptions that need to be considered. For example, the decision tree model assumes that the prices and yields of crude oil and refined products are independent and normally or triangularly distributed, which may not be realistic in some cases. The decision tree model also does not account for the dynamics and interactions of the oil market over time, such as the changes in demand and supply, the effects of hedging or speculating strategies, etc. To overcome these limitations and assumptions, we can use Treeage Pro 2015 Crack Spread to create and analyze a more sophisticated model of oil market simulation. In the next section, we will show you how to use Treeage Pro 2015 Crack Spread for oil market simulation. How to use Treeage Pro 2015 Crack Spread for oil market simulation




Oil market simulation is a technique that can help you to model and forecast the behavior and performance of the oil market over time. It can help you to understand the dynamics and interactions of the oil market, such as the effects of demand and supply shocks, the impacts of hedging or speculating strategies, the risks and opportunities of different scenarios, etc. Treeage Pro 2015 Crack Spread allows you to create and analyze oil market simulation models using crack spread futures contracts, which are derivatives that track the difference between the prices of crude oil and refined products.


To use Treeage Pro 2015 Crack Spread for oil market simulation, you need to follow these steps:



  • Open the crack spread model template from the File menu. This template is a pre-built model that can be used to simulate the crack spread based on crude oil and refined product futures contracts.



  • Enter the data and parameters for your simulation, such as the crack ratio, the time horizon, the contract specifications, the volatility assumptions, etc. You can also modify or add new variables, expressions, or functions to customize your model.



  • Select the type of simulation you want to run from the Analysis menu, such as Monte Carlo simulation, Latin Hypercube simulation, or Sobol simulation.



  • View the results and graphs of your simulation in the Results window. You can also use the Report window to generate a report of your simulation that can be exported or printed.



To illustrate how to use Treeage Pro 2015 Crack Spread for oil market simulation, let us consider a simple example of an oil trader who wants to simulate the crack spread based on WTI crude oil and RBOB gasoline futures contracts. The trader has a crack ratio of 3:2, which means that he buys 3 barrels of WTI crude oil and sells 2 barrels of RBOB gasoline. The trader wants to simulate the crack spread for a time horizon of 12 months, using monthly futures contracts. The following table shows the contract specifications for WTI crude oil and RBOB gasoline futures contracts.



ContractSymbolSize (barrels)Tick Size ($/barrel)Tick Value ($)


WTI Crude OilCL1,0000.0110


RBOB GasolineRB42,0000.00014.2


The trader also assumes that the volatility of WTI crude oil and RBOB gasoline futures prices follows a geometric Brownian motion process with mean and standard deviation as shown in Table 3.



ContractMean (%/month)Standard Deviation (%/month)


WTI Crude Oil-0.510


RBOB Gasoline-115


The trader can use Treeage Pro 2015 Crack Spread to create and analyze an oil market simulation model based on these data and parameters. The following figure shows the oil market simulation model created using Treeage Pro 2015 Crack Spread.



Figure 3: Oil market simulation model based on WTI crude oil and RBOB gasoline futures contracts


The oil market simulation model consists of two types of nodes: a chance node (circle) and a terminal node (triangle). The chance node represents the uncertainty in the prices of WTI crude oil and RBOB gasoline futures contracts, which are simulated using a geometric Brownian motion process with mean and standard deviation as specified in Table 3. The terminal node represents the profit or loss from buying and selling WTI crude oil and RBOB gasoline futures contracts based on the crack ratio of 3:2. The profit or loss is calculated as follows: Profit or Loss = (RBOB Price x RBOB Quantity x RBOB Tick Value) - (WTI Price x WTI Quantity x WTI Tick Value) where RBOB Quantity is 84,000 barrels per month (2 x 42,000) and WTI Quantity is 3000 barrels per month (3 x 1000). To analyze the oil market simulation model, we can use Treeage Pro 2015 Crack Spread to run a Monte Carlo simulation, which simulates the model many times using random values for the uncertain variables and calculates the expected value and the probability distribution of the objective function (profit or loss). The following figure shows the results of running a Monte Carlo simulation with 10,000 trials using Treeage Pro 2015 Crack Spread.


Figure 4: Monte Carlo simulation results of the oil market simulation model


The Monte Carlo simulation results show that the expected profit from buying and selling WTI crude oil and RBOB gasoline futures contracts based on the crack ratio of 3:2 is $1,016,820 per month, with a standard deviation of $1,011,540. The results also show that the probability of making a positive profit from this strategy is 99.8%. The results can be visualized using graphs such as histograms, cumulative distribution functions, or box plots. The oil market simulation model and the Monte Carlo simulation results can help the oil trader to understand and forecast the behavior and performance of the oil market based on WTI crude oil and RBOB gasoline futures contracts. The trader can also use the simulation output to evaluate and compare different hedging or speculating strategies based on different crack ratios, time horizons, contract specifications, volatility assumptions, etc. However, the oil market simulation model has some limitations and assumptions that need to be considered. For example, the oil market simulation model assumes that the prices of WTI crude oil and RBOB gasoline futures contracts follow a geometric Brownian motion process, which may not be realistic in some cases. The oil market simulation model also does not account for other factors that may affect the oil market, such as the demand and supply of other refined products, the effects of geopolitical events, the impacts of environmental regulation


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