March 2019

I've been working hard on making the tools better, in particular on the optimizer, to make sure it produces great results. Keep in mind that studies that use historical returns can only be relied on so much. And we should never be using historical results to tweak the portfolio, because it leads to overfitting. If you are not aware, overfitting is a data science term...

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Machine learning can be used in investing in a variety of ways. This article seeks to show a few of those and describe the basics. Hedge funds have tried for years to use machine learning (or AI) in their funds. Moving on to today, all quantitative funds use some form of machine learning. Some hedge funds even build around machine learning specifically, spurning human intervention. Risk Management Risk...

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In Forbes I found a post about some 'expert' model portfolios. I thought it would be interesting to try optimizing these portfolios using RIAengine smart portfolio optimizer, and seeing what backtests looked like. Here are the results. Buffet 90/10 Portfolio The first portfolio is simple, just 90% allocation to an S&P500 index fund (I chose SPY) and a 10% allocation to Bonds, I used SHY. Here is...

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High quality data is important for a company building investment apps. That's why we're excited to announce that we will soon have a deal with Morningstar, one of the leaders in stock market data. RIAengine uses data to analyze investment portfolios. We use this analysis to help you come up with better portfolios. RIAengine will be launching the smart portfolio optimizer soon to a small beta...

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Investment portfolio risk can be an uncomfortable topic. It’s easy to find articles all over the internet that encourage people to sit tight when things are dropping. Warren Buffet’s famous instructions regarding his wife’s trust are to put 90% of it in the S&P500. And since Warren Buffet says to do it, a lot of people think we should all do the same. (side note, with...

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