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Applications in Finance

1. Applications in Finance

Simulations are highly popular in the field of finance. Models are built for a wide variety of purposes and in some cases, the builders of these models have gained huge fame, even going on to win the Nobel prize. While the field of finance has a rich history of using simulation to understand market dynamics, in this lesson, we will only scratch the surface.

2. Applications in Finance

Simulation is used in a number of areas within finance. Here are some broad categories. Simulation is quite heavily used in pricing options and other financial instruments. In the corporate world, simulation is used for project finance. We've seen examples of this in earlier chapters, it's very similar to the application of simulation in business decision-making. Finally, simulation is used in evaluating portfolios. Typically portfolio managers want to understand the consequences of having different asset mixes in their portfolio so that they can quantify the risk involved in the decision.

3. Portfolio Simulation

At it's very core, the idea of using simulation for portfolio evaluation is very simple. You build a data generating model to capture uncertainty. Then you vary the inputs to the model and simulate multiple outcomes. Finally, you analyze the outcomes to make your decision. In this case, you are analyzing a portfolio with a principal or initial investment of $10,000. You are interested in understanding the returns of your portfolio after 10 years. Given your current mix of assets, your portfolio is stock heavy. A stock-heavy portfolio has a high expected rate of return, but also has high volatility. Stock heavy portfolios are usually risky, but good for people who are investing for the longer term.

4. Portfolio Simulation

In addition to the stock heavy portfolio, you also have the option of rebalancing your portfolio to add more bonds. A bond heavy portfolio has a lower expected rate of return, but also lower volatility, implying more assured returns. Such a portfolio is typically good for people close to retirement. To compare these two strategies, all you need to do is simulate multiple outcomes from each scenario and analyze the returns. If you are conservative in your approach, you might look at the lower percentile of the distribution of returns in each case to see how much return you are assured of with a high probability.

5. Let's practice!

It is my hope that after completing this final exercise, you could modify it to analyze your own portfolio. With that in mind, let's jump into the code!