In this post I update my TAA Batting Averages post from last year. The introduction to that post sums up the intent of this excercise pretty well so I’ll just say the same thing again this year.
In today’s post I want to look at long term TAA model performance in a different way. I think intuitively most investors realize that any strategy they pick will have periods of outperformance and underperformance. But decision making under real circumstances exposes us to all kinds of biases which often cause is to make intuitive, gut decisions based on incomplete or recent data. There are statistical ways to deal with these issues to help us make better decisions, in this case, to maybe choose the TAA strategies that not only perform the best over the long term but do so across different market environments and time periods. Many statistical prediction techniques use base rates . Base rates are basically batting averages. And in general, it is good to pick things with high batting averages – it is an indication that the higher performance (or lower performance) is not luck, that it is persistent, and will continue into the future.
Also, it is important to not that I’m only looking at returns here. I n this piece I’m going to focus on returns which is only one metric to consider in choosing a TAA strategy. Risk adjusted performance, drawdowns, and turnover and other key parameters that need to be considered.
We’re looking at long term data here so the addition of 2019 is not going to change the base rates of the portfolios by much, if at all. But I’ve done a few different things this year. OK, let’s dive right in.
I’m using the longest period I can, 1973 through 2019. and data from various sources but mainly with data from Allocate Smartly . Because of that I’m limited in the number of strategies that I can look at. Ideally, we’re looking for strategies that outperform over all periods. I’ve chosen various buy and hold, TAA strategies, and various time periods. I then compare performance of the TAA strategies over the given period to the 60/40 benchmark portfolio. Underperformance is highlighted in RED. This year, I’ve also added two buy and hold benchmarks, the GAA (global asset allocation) portfolio, and the Vanguard Model, which is Vanguard’s recommended standard allocation. GAA is a much more global version of the US centric 60/40 portfolio, and the Vanguard Model is Vanguard’s take on a more global allocation. I have the allocations for a bunch of buy and hold portfolios here . Here is the updated data table.
Table 1: TAA and Buy and Hold Portfolio Performance Over Various Time Periods
- Avg TAA is the average of the TAA strategies in the table
- Meta is Allocate Smartly’s Meta Strategy which dynamically chooses among the TAA strategies
- NFUSTI is the US Trend Index from Newfound Research , a simple TAA index based on US markets
- SPY-COMP and DM-COMP are two portfolios from my Economic Pulse Newsletter
This year, let’s start with the elephant in the room. During the current bull market from 2009 to 2019, the last 11 years, beating the US centric 60/40 buy and hold portfolio has been a tough task. Even the more diversified, more global buy and hold portfolios have underperformed significantly. Does anyone else find it amazing the even over the last 20 years, the 60/40 portfolio has beat the GAA and the Vanguard Model portfolio? That kind of outperformance also makes performance over the last 3,5, and 10 years, hard to match. But over longer periods of time, especially periods covering bear markets and recessions, more diversified strategies outperform the 60/40 US benchmark and TAA strategies do even better. That’s what they are designed to do. And of course, that’s not even mentioning risk-adjusted performance which I will take a look at in a later post.
Now, let’s look at the base rates. Let’s use ALL rolling 3-year periods and calculate the base rates, the number of periods the strategy outperformed over 60/40 as a percentage of all rolling 3-year periods. The higher number, the higher the batting average, the better. Here is the updated table.
Table 2: Base Rates for Various TAA Portfolios
Not much has changed from last year as we would expect. I’ve chosen 70% as a good base rate (choose your own, I’m probably biased) and highlighted those strategies with 70% or greater base rates. That means that the given strategy outperforms the buy and hold model in at least 7 out of 10 rolling 3 year periods. As you can see, certain strategies are clearly better than others on this metric. VAA, GEM, GTT, SPY-COMP, and DM-COMP have the highest base rates across the different benchmarks.
Now, what about other strategies? I often get asked about other strategies but I’m hesitant to calculate base rates on them if they don’t have enough history. However, there are a few really good TAA strategies that are left out of the comparison above simply because there is not enough data. We could at least look at the performance data over various sub periods over a reasonable long period of time, like 20 years. That is usually my minimum cutoff. If I limit the history to 20 years I can included a few more strategies in the performance table. Here is the updated chart with 6 more strategies. Sorry for the eye chart.
- Avg TAA is the average of the TAA strategies in the table
- AAA is the Adaptive Asset Allocation Stratrgy
- VPC is Varadi’s Percent Channels Strategy
- NFTAA is NewFound Research’s New Global Trend Following Strategy
- EM-COMP, and both WF-COMP strategies are mine from the Economic Pulse Newsletter
Both AAA and VPC will show up again in the analysis on risk-adjusted performance and perform quite high in that regard.
OK, that about covers the update. In summary, base rates are an important tool in analyzing the performance of strategies. The higher the base rate, batting average, the higher the odds are that the strategies outperformance is not a matter of luck. Base rates are not the only criteria in choosing TAA strategies, but I think they are an important one that investors should consider.