Modeling Ray Dalio’s Modeling: The Art of Position Concentration

If you’re not failing, then you’re not pushing your limits, and if you’re not pushing your limits then you’re not maximizing you’re potential.” – Ray Dalio

When we first exposed our initial thoughts on this legendary hedge fund manager in Bridgewater Associates: Modeling Ray Dalio’s Modeling, the key finding was that their investment strategy was impersonating that of a macro manager (which historically relied largely on futures) by using ETFs to shoulder the primary market factors. In the chart below, Alphacution presents an illustration of the portion of 13F market value represented by a very short list of ETFs:

Now, having expanded our modeling template (over several other trading firms) to include more analytics – and with the benefit of a couple more 13F reports to update our existing Bridgewater model, there are more key findings to share:

First, the market value of 13F securities reached an all-time high for the 54-quarter period beginning Q4 2005 and ending Q1 2019. This should come as no surprise given widespread media accounts of uniquely strong performance for 2018:

However, what we want to add to the conversation here is a bit more about how Bridgewater is engaging in portfolio construction to execute on their macro-thematic strategy and ultimately achieve such strong performance on such a large (and increasing) capital base.

Alphacution is now tracking portfolio and position concentration – among other similar position sizing and scaling analytics – for all of its 13F dataset modeling. In specific, we are now tracking the top and top 10 largest positions (by value) for each 13F report. In the case of Bridgewater, these latest findings are notable with the largest long position at 19.2% of total 13F portfolio value (which is at a multi-year low) and the top 10 largest positions at 79.1% of total 13F portfolio value (which is also down from highs of ~90%):

Now, other than letting that (surprising) level of concentration sink in for a minute, here’s some additional thinking: Since we can only see US- and equity-centric long positions, there is a big piece of this story that evades us, so I want to be a little careful as we walk out on this limb. However, that said, we have already noticed at least one other big player using increasingly concentrated positioning to enhance performance. See Fidelity’s Concentration Risk for more on that.

We also know that meticulously constructed relative value strategies have capacity constraints that (have historically) come into play well before any manager arrives at the hefty AuM levels north of $100 billion or so that Bridgewater currently enjoys – so, we can conclude that the bigger they get (in terms of AuM) the more (typically long) biased their portfolio becomes by default. And yet, on the other hand, the more biased their portfolio becomes the more the gravitational pull of beta-level performance takes its toll.

This is where all the modeling comes into play: As of Q1-2019, there were only 284 stocks and 19 ETFs on the long side of this portfolio. The ETFs, in total, make up nearly 87% of the portfolio value. This is where the performance needs to be harvested. Security selection and impeccable timing are the key factors for outperformance. At scale, security selection can’t change all that rapidly.

In this case, performance is mainly in the timing – and that’s what all the modeling is for…

More soon.

Watch this space – and inquire about subscription options for deeper learning…

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By | 2019-05-30T01:23:34-04:00 May 30th, 2019|Alphacution Feed|

About the Author:

Paul Rowady is the Director of Research for Alphacution Research Conservatory, a research and strategic advisory platform uniquely focused on modeling and benchmarking the impacts of technology on global financial markets and the businesses of trading, asset management and banking. He is a 30-year veteran of the proprietary, quantitative and derivatives trading arenas. Contact:; Follow: @alphacution.