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Tag Archives: Quantitative Investing
Q3 2017 is now behind us. Time to update some performance numbers. In this post I update the quant portfolio performance stats for through Q3 2017. Below are the 2017 YTD total return (through Sep 30, 2017) and max drawdown numbers for the various quant strategies I track. For explanations of the various quant strategies see the portfolios page. All equity portfolios consist of 25 stocks and were formed at the end of 2016. No changes in the holdings since that time (except for the TAA Bond strategy and the Pure Momentum strategy which re-balance every 4 weeks). Like last quarter’s post … Continue reading
Keep it sweet and simple. That’s the fit-for-publishing version of KISS. And it is critical for being successful in the long term with quant investing. The biggest mistake I see new quant investors make is over complicating things. This just leads to failure. By focusing on a few high impact factors a quant strategy can still significantly outperform while being relatively easy to maintain. In today’s post I will present a KISS quant strategy has provided plenty of outperformance while being easy to maintain. Before I dive into the KISS quant strategy let me throw some stats at you. I … Continue reading
What would you think of a quant strategy that only invests in the most profitable companies? Would it under perform the market or beat the market? If you’re an efficient market person you may think that higher profitability must be priced into equities and therefore at best the strategy would match the market. Not so. Turns out that profitability is quite a durable factor and is only beaten by momentum and value. In this post I’ll take a look at some of the data on the profitability factor and how it can be applied in a simple quant strategy. First, … Continue reading
It’s time to get back to talking about quant portfolios. I haven’t posted on any quant related stuff in a while. Doesn’t mean anything. I’ve just been focused on other things. And my quant portfolios require very little maintenance so once they’re up and running there is not much to do. At least there shouldn’t be much to do. The temptation to fiddle and tweak is quite strong but usually leads to worse results in my experience. Anyway I have some more quant posts coming out over the next few weeks which will kind of re-balance the postings in the … Continue reading
In quant investing there is always an urge to continuously look for ways to improve a model. Trying better ways of doing things can be a worthy and profitable endeavor. After all, markets do change. You learn new things, etc… But it can also be fraught with pitfalls. Data mining is a constant worry. With these caveats in mind in this post I’ll take a look at a potential new value composite metric and it’s performance over the last 16 years. My idea for a new value composite comes from Professor Damodaran at NYU, his blog is at Musing on Markets. His academic … Continue reading
Here are the Q1 2017 total return and max drawdown numbers for the various quant strategies I track. For explanations of the various quant strategies see the portfolios page. All equity portfolios consist of 25 stocks and were formed at the end of 2016. No changes in the holdings since that time (except for the TAA Bond strategy which re-balances every 4 weeks). In the table below I list various quant strategies along with their YTD performance and drawdowns. Also, listed are various benchmark indices. All performance numbers are from Portfolio123.com. Overall, the equity quant strategies underperformed both domestic and foreign stock … Continue reading
Update: I updated the charts and some of the performance results on March 28, 2017. I found and corrected an error in the performance calculations. Conclusions remain the same. It’s finally time to start turning all the economic indicator stuff I’ve been posting on into something useful for investors. In this post I’ll introduce the SPY-COMP indicator and how it works as tool for entering and exiting investments. The mechanics of the SPY-COMP system are similar to the SPY-UI system I’ve posted on previously. The only difference is that the new system uses a composite of the top 6 economic … Continue reading
The performance of value factors varies over time. Sometimes value is in favor. Sometimes it is out of favor. But overall value overall is one of the two single factors, along with momentum, that has withstood the test of time. But what if one way of expressing value in stocks has simply stopped working or is just nor working as well as in the past? That’s is what I’ll consider in this brief post. In particular, I’ll look at whether it is still worthwhile to use P/B in individual quant stock portfolios. Many of the quant stock models discussed on … Continue reading
Recently, Jim O’Shaughnessy, the author of What Works On Wall Street, took to Twitter with his first tweet storm (basically a short post in a series of tweets). In it he spoke about his thoughts on active management. I thought I should capture it for future reference. I’ll add comments and links throughout. What Works On Wall Street (4th edition) is basically 681 pages on a handful of factors; mainly value and momentum, with minor roles played by small-cap, equal-weighting, and quality. The lack of ability to focus on the long term is the number one behavioral issue that prevents … Continue reading
Note: All the data tables have been updated to include the TAA bond strategy. Thanks to AllocateSmartly, P123, and Stockcharts.com, I was able to gather 2016 performance data much sooner than last year. This post updates the portfolio statistics, through 2016, for all the various portfolios I track that I have data for going back to 1973. It is not comprehensive by any means but contains a good sample of various diversified global buy and hold portfolios, tactical asset allocation portfolios, and quant portfolios, as well as the popular benchmarks, in particular the 60/40 portfolio for US investors. Last year’s … Continue reading