Finance Use Case

Portfolio optimization is the process of selecting the best portfolio (asset distribution), out of the set of all portfolios being considered, according to some objective.

The objective typically maximizes factors such as expected return, and minimizes costs like financial risk.

When optimizing your portfolio, you assign an ‘optimization weight’ for each asset class and all assets within that class. The weight is the percentage of the portfolio that concentrates within any particular class. For example, say we weight stocks at 10% and bonds at 20%.

An optimal portfolio is one that minimizes your risk for a given level of return or maximizes your return for a given level of risk. What it means is that risk and return cannot be seen in isolation. You need to take on higher risk to earn higher returns.

How to Select an Optimal Portfolio

  1. Risk % (Standard Deviation)
  2. As an investor, you can select how much risk is acceptable to you in the portfolio by selecting any other point that lies on the efficient frontier.
  3. Risk/Return Profile.
  4. Risk/Reward Profile.
  5. Risk/Return Table of Optimal Portfolios.
  6. Optimal Portfolio.

Creating an Optimal Portfolio

To create an Optimal Portfolio one of the main aspects is Risk Diversification. It can be achieved by using some technical ideologies. Optimal portfolio is a term used to refer Efficient Frontier with the highest return-to-risk combination given the specific investor’s tolerance for risk:

  • optimisation problem in order to mitigate the risk on the assets and creating a benchmark according to the local stock markets
  • optimisation of portfolio after the structure of the top 100 banks
  • reallocation of the financial asset according to the business financial rules in order to get an optimal portfolio
  • Monte Carlo integration – the process of numerically estimating the mean of a probability distribution by averaging samples: https://cambridgequantum.com/quantum-monte-carlo-integration-the-full-advantage-in-minimal-circuit-depth/

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