Flirting with Models

The Research Library of Newfound Research

Category: Uncategorized (Page 1 of 35)

Machine Learning, Subset Resampling, and Portfolio Optimization

We two novel algorithms, one based on machine learning and the other based on simulation, to manage estimation risk in portfolio optimization.

Risk Parity: How Much Data Should We Use When Estimating Volatilities and Correlations?

We explore whether more sensitive volatility estimates (less data) or more stable volatility estimates (more data) produce better risk parity results.

Embracing Conflict in Asset Allocation

Embracing conflict in asset allocation by using multiple approaches can help investors harvest the sizable benefits of process diversification.

4 Lessons from the Ritholtz Wealth Evidence-Based Investing Conference

Concrete takeaways and action steps I learned from the 2016 Ritholtz Wealth Evidence-Based Investing conference in New York City.

Look at Data with a Discerning Eye

Visualizing data can lead to wrong conclusions if the analysis is done incorrectly, but understanding common pitfalls can help avoid costly mistakes.

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