It was May 10th, 1996, when Twister hit the box office, a popular action-packed thriller that was the second highest-grossing film of the year. This fictional flick sparked the popularity of “storm chasing” across the country.
Fun Fact: Twister was the first film to be released on DVD in the US.
Some twenty-six years later and the enamor for storm chasing has not faded. A number of travel companies even specialize in storm chasing-led-adventure tours. Throughout tornado alley, local news outlets highlight the collateral damage caused by storm chasers. The influx of traffic and lack of local law enforcement – distracted by the tornado at hand – leads these chasers to blow through stop signs, run red lights, and drive distracted by their various weather devices, often resulting in fatal accidents.
Rick Smith with the National Weather Service speaks out against these amateur chasers, “It is a serious situation in that anytime you have a severe storm, the storm itself is bad enough, and these storms can be very serious. It’s important for people to know it’s not like watching television it’s not a video game. These storms can really hurt you, they can kill you, they can damage your vehicle,”
We are talking about ill-equipped amateurs seeking a thrill and relying on their limited experience and know-how to go out and “play” with tornadoes. This is just downright foolish, no? When it comes to weather, we call these folks storm chasers; when it comes to investing, we call these folks performance chasers.
Today we will dive into the wild world of performance chasing and the financial wreckage this common pastime can cause.
And off we go…
The Fine Print
They try to tell us. They really do try to warn us. The disclaimer is right there. Whether it’s in the fine print or not, we all know what it says. We’ve all memorized it: Past performance is not indicative of future results.
This warning is about as useless as the warning on a pack of cigarettes, “Caution: Cigarette Smoking May Be Hazardous to Your Health.” Primarily because the warning is never heeded.
What do most people do when they are choosing their 401(k) elections? They look at the list of available options, run their finger down the results column that lists the past performance, and choose their allocations based on the best-performing strategy of yesteryear.
What do most wholesalers (salespeople representing an investment management firm) do when they are visiting an advisor’s office? They pitch the en vogue strategy, the one or two funds in their lineup that are sparkling at the moment.
When I got introduced to the industry, I worked in a call center with a full population of other brand-new advisors. The timeline from certification to being client-facing was a short one. These new advisors – myself included – were responsible for building investment allocation proposals. The technology we used to build out proposals would have us select from a long list of funds for each allocation (large cap, small cap, emerging markets, bonds, etc.). What was the habit of most advisors in that call center? They’d organize each list of selections by the best performing strategy over the last 5 years and select that fund to allocate to. This approach made for a very impressive backward-looking performance on the proposal, the problem is that no client actually experienced those rearview mirror results.
All this to say, we are all prone to this naughty shortcut of filtering our decisions based on past results.
Results DO Matter
Don’t misunderstand me here, performance does absolutely matter. My primary concern is that most folks that engage in conversations on performance are not well equipped with what questions to ask and what specific data to zoom in on.
Institutional investors dive deep into performance history to understand a manager’s batting average or persistence. These analysts seek to understand attribution, asking questions like, “Was there one particular investment that was driving a lot of the fund’s success?” They dive into the analysis of the risk that was taken for the reward that was achieved and ask, “Was this risk/reward ratio prudent?” Even further, an analyst would focus on the economic landscape and the current environment we find ourselves in, inquiring, “How might a strategy like this typically perform in these conditions?” These would be the type of questions asked, along with a thorough review of a handful of other key metrics and data points.
Ultimately though, each investment needs to be objective driven. Every dollar allocated should have a purpose and fulfill an objective in the financial plan. One should not just seek investments that seem exciting or attractive, each investment should fit cleanly into the puzzle of the financial plan. Not only are investments assessed based on their own merits, but also how they complement the other parts of the broader portfolio.
Marketing Material vs. What Materialized
Again, today’s conversation was birthed out of a concern I have for those shopping for an investment manager; I believe the presentation of past performance can often be misleading.
Here’s the tension point – investors want to see strong/impressive past performance numbers, and for this reason, advisors want to share strong/impressive past performance data. The important thing to remember is that this data lives on a spreadsheet, a proposal, and/or a fund fact card, but it doesn’t mean that an actual investor experienced those results.
During the dot-com bubble, there was a common anecdote being recounted in many of the financial news outlets. A very popular investment fund had posted some incredible return figures, one of the top-performing funds for the period observed. The interesting thing was the performance of the average investor in that fund compared to the published performance of the fund. The fund had a track record that reflected double-digit returns for the specified time period, while the average investor in the fund had a negative return. At first read, this seems like a head-scratcher, so let me explain. The early strong performance of the fund attracted a lot of investors (dollars), and when the fund was experiencing a negative season (a drawdown), many investors exited the fund. This is the gap between time-weighted returns (published on a fact card) and dollar-weighted returns, which represent the average investor’s experience. A classic case of storm chasing – I mean performance chasing – gone wrong.
Beware of the Backtest
Obviously, over the last few decades, we’ve seen a rise in the influence of technology across many industries, and the finance industry has not been immune to this evolution. It seems like quantitative strategies, rules-based approaches, Robo-advisors, artificial intelligence, and the such have really gained traction and interest amongst the investment community.
These types of “evolutionary” investment management approaches can further amplify the concern I expressed above – fund results vs. investor results. Now, not only do you need to be cautious of results that few investors ever experienced, but you also need to be cognizant of track records that only exist in a financial data laboratory. Say hello to backtesting.
I don’t desire to get too granular here, but backtesting introduces a lot of new issues. Imagine if I was crafting a strategy that just sought to own stocks of companies that started with the letter “A.” This is laughable, right? So, what if I made it sound more sophisticated and I based our hypothetical strategy on other rules that seemed intelligible or used a language of finance that sounded more highbrow? With this proposed investment solution, you might be more inclined to hear me out. Here’s the truth, though, in a backtest, both of these approaches – our letter “A” approach or the other – could potentially show amazing results.
As I mentioned, investment managers, wholesalers, advisors, and the entire industry desire nothing more than to impress you with past results. So, what do financial data miners do? They test and test and test until they find something that looks good in the rearview mirror, and then they make minor adjustments and tweaks to polish the results even more – in the world of data modeling, we call this overfitting. Again, this puts the burden on the amateur storm chaser to be equipped to ask those appropriate next questions, “How has this strategy done out of sample?” Or “Does this model rely on data points that were unknowable?” For example, running a backtest based on earnings growth and then telling the model to buy at the beginning of the year whatever companies had the best end-of-year earnings growth – mining data that based on time-and-place that was unknowable for an investor in real-time. You will often find issues with backtests dealing with smaller capitalization companies, so you might ask, “Are there any issues with trading frictions or volume that would make this model difficult to recreate in real life?” Just a few inquiries one might pose if you were vetting out a new quant strategy.
And just like that, voila! Even you can create a beautiful backtest that any marketing department would fall in love with. My encouragement, performance chasers, heed the advice from Aesop’s Fables, “Be careful what you wish for, lest it comes true!”
Benchmarks, Contentment, & Conclusions
Much of this performance-chasing culture is driven by (1) our access to a whole lot of data via the internet and (2) our growing desire to constantly compare ourselves to our neighbors, also potentially driven by the internet. Naturally, we regularly find ourselves “benchmarking” our results. Now, is it wise to have some sort of an anchor point to measure our investment outcomes? Yes, of course. Next question, if you search hard enough, will you always find a benchmark that you wish you would’ve owned? Absolutely. One year perhaps you wish you would’ve owned bitcoin, another oil futures, another cash, another foreign stocks, and on and on and on – this is the neverending revolving door of I-wish-I-would’ve-owned-this-or-that. Like I always say, if I had a time machine, I’d be the best investor of all time.
So, let me help you out with how you should benchmark. If you are taking on a new investment strategy, why not measure this strategy versus what you did own prior to the switch or the other strategy you rejected in favor of the strategy you chose. Now, to be fair, you will want to make sure you are benchmarking here with apples-to-apples comparisons. These two strategies you are comparing should have similar characteristics of risk, liquidity, etc. To help, I’d partner with a professional to assist you with crafting these comparatives. Remember, part of this process will be determining the appropriate time periods to apply these comparisons. I’ll give you a hint, one day, one month, and one year will not be a sufficient sample size.
I’ve never chased storms myself, but I imagine whether you are a professional or a rookie, there will always be a desire to see a bigger tornado from a closer vantage point. These types of risk takers are never satiated. Again, never quite big enough, never quite close enough, always chasing after that next storm. This attitude is the antithesis of contentment, which is a key trait of successful investors. Let’s keep this simple, your financial plan has a target rate of return, and this is the target you should strive for. At the same time, I promise you this, you will ALWAYS be able to find an investor that did a little better than you. The challenge will be if you can be content with the outcomes you achieve. My advice, resist the desire to over-compare and stay the course.
These will be the type of behavioral/psychological obstacles we all face. Most often, we will find that we are our own greatest nemesis. Sometimes we just have to get out of our own way.
