Assignment Develop a trading strategy for this Delta Airlines. Present the results of your strategy. You will submit both a written document (PDF) and your accompanying code (Python script or...

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Assignment Develop a trading strategy for this Delta Airlines. Present the results of your strategy. You will submit both a written document (PDF) and your accompanying code (Python script or IPython/Jupyter Notebook). 1. A brief history of the equity or commodity that you have chosen. • For an equity, it should include the company history (summarized) and any major company events of interest to an investor. It should also include what the company produces and any major foreseeable risks for the company in the near future. It should also include the industry that the company exists in. • For a commodity, it should include the use cases of the commodity, the role it plays in the U.S and World economies, and any other information important to an investor. 2. Plot the historical price of the underlying and describe any major events you observe there. 3. A summarization of your trading strategy. I suggest that you choose a single strategy covered in Chapter 4/class 4. Use the yfinance Python package to pull down current options dates and premiums. Use only underlying and/or European options (no American/Exotic). ● Choose and record actual option expiration dates from when you start your project (this may be easier if you are using a Notebook). ● Include a payoff diagram for your strategy with real market strike prices and premiums (remember bid/ask splits). ● Include a description of why you chose this trading strategy given what you know about the underlying. 4. Describe how you are going to simulate the underlying price using time series and Monte Carlo meth- ods and what assumptions you are making. Calculate and present the statistical moments (mean, median, standard deviation) of the underlying? What time series model will you use to generate your simulations? 5. Estimate the initial time series model (you will use an AR model). Use ar select order (fromstatsmodels) to select the correct model. Collect the errors in the model. Re-sample the errors 1 5000 different times (with replacement) and estimate 5000 additional models. For each model, predict the number periods forward that you need to reach the expiration of your strategy and collect your simulated payoffs for each. 6. Plot the simulations together (include this plot in the document!). 7. Display and discuss some descriptive statistics (mean, median, standard deviation) of the underlying and payoffs across the simulations along with the past 12 months of the observed descriptive statistics of the underlying. These should be displayed in a small, neat looking table. 8. Choose at random (but be consistent!) one of the simulations, plot it, and answer the following questions (pretending this simulation is what happened in reality in the future): ● Do you think the simulation is realistic given what you understand about the underlying? ● What is your payoff is in this specific simulation? ● What you may have ignored in this simplified exercise? ● How you could adjust your strategy (if need be) if you expect this specific scenario to happen more consistently?.