A Discussion of Quantitative Analysis

When I was growing up, I never really considered myself a “math” person.

Mind you - I did very well in my math courses. Consistently got “A” s and was among the top students in any of the courses.

But I was not one of THOSE "math" people!

The kind that thrived off figuring out differential equations and complex algorithms. All that stuff interested me, but I was much more interested in what I would consider “applied” mathematics.

I was less interested in the problem and figuring out the solution and much more interested in how the solution could help me accomplish something I wanted to achieve.

Think of it as not caring to show all the work, just wanting the answer, and then figuring out how to use it!

That being said, I have always been mathematically inclined.

With all the volatility in my childhood, math had an element of certainty that appealed to me. There was little I could control in my life, but figuring out this equation was one small victory in the chaos of my childhood.

Math gave me some degree of comfort. I wasn't interested in figuring out advanced algorithms, but I loved applying math to whatever I was working on to help me find a solution.

As many of you know, I was a massive collector of comic books and sports cards. I still have copies of "spreadsheets" that I put together on word processing documents where I listed my collection and then updated the price (and portfolio value) every month when the price guides would come out.

In that sense, I have always been REALLY into math!

This kind of mentality fits very well in the business of money management. One of the aspects that appealed to me about this profession was the ability to “keep score.”

Every day, you have a scorecard about your success or failure. There are no opinions. Only data and results.

This has always been how I was wired and approached problems.

When I started my money management career in the mid-1990s, this approach was surprisingly not very popular.

Most of the industry focused on "fundamental" analysis and "value.” They looked at many numbers regarding the company's operations and the prices and values of their portfolios, but there was little analysis of any of the rest of the data.

What surprised me was that there was no objective analysis of how we made money in our portfolios.

The managers would see that a particular stock was making or losing money. They also knew which ones were the big losers or gainers.

Beyond that, though, the idea was always to stick to the fundamental story and value, and that is what counted…

I was a young analyst and portfolio manager in my first couple of firms and did what I was told. However, it seemed to me to be a terrible waste of an opportunity.

We had TONS of data, and I knew there could be ways to improve our process.

Figure out where we were losing money and how to do less of that, and figure out where we were making money most often and do MORE of that!

It wasn't until about three years into running my first stand-alone hedge fund – Stadia Capital – that I began putting many of these ideas into our process.

We had a large investor out of Chicago with several $100 million invested with us. They had been with us for about eighteen months and had consistently asked for data.

We believed strongly in complete transparency, so we provided that data and periodically had meetings with them, and they were always great. They were supportive and continued to add capital.

Then, one day, they called us with some unwelcome news. They were reducing their allocation to our strategy. Not only that, but they said it was likely they would pull the entire stake.

This was not a small amount of money for our firm.

We quickly got on a call with them to ask them, "Why"? Our returns were acceptable then; we grew our team, added other investors, and had good momentum.

They didn't have any definitive answers other than that they had done some internal analysis and didn't think our strategy was right for them.

This intrigued (and frustrated) me, so I pushed them on the analysis and what it said, but they were reluctant to share the data.

When faced with situations like this throughout my career, I have had one response that has worked very well. I got on a plane, flew to their offices unannounced, and said, "Hey, can we sit down and go through this data?"

While they were slightly surprised, they were incredibly cool and impressed. They had never had a manager do anything like that.

Over the next few hours, they took me through several data sets that they used to analyze manager performance.

In their experience, they had found that while many managers were successful – very few of them understood exactly how and why they were making money. Even more so, they didn't understand how and why they were LOSING money.

Our performance scored well on most of their measures, but one "yellow" flag led them to pull the money.

Now you might ask – why pull the money if it was only a “yellow” flag?

Remember, they said they would pull it out in stages and wanted to see if we had improved this analysis.

What was the analysis?

It was pretty simple and was called a "steady state” analysis.

They looked at our portfolio snapshots at the beginning of each month and each quarter. Then they ran a “model” portfolio where they asked how we would have performed had we done NOTHING and not made a single trade, just left what we had and kept it for the month or quarter.

They saw that we were systematically and materially underperforming our "steady state” portfolio. We had good (excellent) stock picks, but our trading activity detracted from our performance. Sometimes by a lot.

Remember that action does not always equal progress. In our case, it meant going backward!

There were many other analyses, but this was their key one.

There is more to the story as we put the process in place internally to try to keep them as investors. However, several of our portfolio managers couldn’t adhere to the discipline. We lost the investor…

The point of the story, though, is that looking at the data or "quantitative" analysis does not have to be as sophisticated as what Jim Simons did. Sometimes, it can be a straightforward analysis to improve your investing and trading.

We encourage you to try this analysis.

Take whatever you owned one month, a quarter, and a year ago. “Freeze” that portfolio and see how it would have done through today.

Then, compare how you ACTUALLY performed. We think you might be surprised by the answer!

Once you have it, figure out what you did poorly and do less of that, and figure out what you did well and do MORE of that!

Looking at the data made Jim Simons the most outstanding money manager of all time, made me a much better money manager, and can also help your returns.

How do you look at the data behind your investment performance? Send us your thoughts via email at [email protected] or in the comments section on our website.