Flirting with Models

Research Library of Newfound Research

Author: Justin Sibears (Page 1 of 11)

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.

Separating Ingredients and Recipe in Factor Investing

Factor portfolio construction has two key elements: ingredients (the signals used to pick investments) and recipe (the rules used to translate those signals into allocations). While the ingredients often get the most focus, the recipe can have just as large of an impact on returns.

Failing Slow, Failing Fast, and Failing Very Fast

Failure to meet your financial objectives can take one of two forms: fast failure and slow failure. Failing fast involves suffering large losses at the wrong time as the result of taking too much risk. Failing slow involves achieving insufficient growth due to taking too little risk.

Three ETF-Based Ways to Leverage Your 60/40 Without Margin

We explore three ETF-Based ways to leverage your 60/40 without margin. We explore high beta ETFs, levered ETFs, and derivative-based ETNs as potential tools and look at the benefits and risks of each approach.

Presidential Stock Market Leaderboard

Page 1 of 11

You are about to leave thinknewfound.com and are being redirected to the website for Newfound Research Funds.