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HOW

Going Beyond “Modern Portfolio Theory” (MPT) to Deliver Customized Investment Recommendations.

While MPT has been widely used in investment management, it primarily focuses on optimizing portfolio returns based on the trade-off between risk and return, where risk is defined as the standard deviation of portfolio returns. However, we believe that better optimization goes beyond MPT.

Investment advising for data scientists with Story Makers Investment Advisors

Understanding Individuals

We use answers from our detailed client questionnaire to quantify risk aversion, loss aversion, and more, at an individual level. These are used to estimate parameters and arrive at personalized investor utility functions.

Investment advising for data scientists with Story Makers Investment Advisors

Data & Machine Learning

Our models use features engineered from hundreds of data sources to account for trends and changes in asset prices, interest rates, inflation, employment, sentiment, GDP, exchange rates, indices, commodities, and much more.

Investment advising for data scientists with Story Makers Investment Advisors

Risk Measures & Optimization

Our optimization metrics don’t rely on standard deviation of portfolio returns to measure risk. Instead, we use combinations of many risk measures such as downside deviation, value-at-risk, tail-value-at-risk, maximum drawdown, and others.

Investment advising for data scientists with Story Makers Investment Advisors

12-Month Strategy

We deliver an individualized investment and recurring investment strategy expected to be optimal over the next 12 months (for tax, and other reasons). We recommend repeating this process every 12 months.

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