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What’s the best way for individual investors to benchmark their performance? I was recently asked this question by a fellow member of the Australian Shareholders Association. I’m lucky to see how professional investors do this thanks to my day job as a portfolio manager. But most individual investors don’t have a post-graduate level education in quantitative methods. They’ve have never heard of GIPS, nor can they can afford to access a quantitative risk model.
The best way to answer this question and “keep it real” was to think about how I benchmark the performance of my personal portfolio. Obviously, the way that I analyse my performance has been shaped by my professional experience. I’d be foolish not to apply what I’ve learned from working with some of the best fund managers from around the world. That said, the pros don’t have it all their way. Yes, they may have knowledge, skills and resources that aren’t available to ordinary investors. But they are analysing performance not only to learn and improve their investment process but also to report to their clients.
Institutional investors demand as much information as they can get as often as they can get it. This is because they are usually part of a heavily regulated chain of principal and agent relationships (point 4). Each link in the chain has to account for its results to the next link in the chain and so on. This results in information overload. It also and increases the likelihood that results are dominated by short-term “noise”.
In contrast, individual investors only answer to themselves. They aren’t competing with anyone else and they aren’t trying to justify the fees that they charge. All that individual investors need to benchmark themselves are: an internet connection, a spreadsheet, a little effort and knowing what to look for.
So how should individual investors benchmark themselves? They need to find a set of measurements that help them to improve their investing through deliberate practice. I’ve raised the idea of deliberate practice before in my earlier post on regret. In fact, it’s trying to manage the negative effects of regret that lead me to thinking deeply about how I should benchmark my own portfolio.
Readers of my post on regret will remember two key points:
- Regret is a comparative emotion. So, it’s really important that we make the right comparisons.
- It doesn’t have to be negative. Regret can be a positive if it motivates us to learn and improve.
It’s worth elaborating on what makes a bad, as opposed to a good, comparison. We can illustrate the difference with a few examples. Bad comparisons include:
- Short time periods (less than 12 months)
- Market benchmarks
- Time-weighted returns
- Comparisons that ignore real world costs and taxes
Bad Comparisons Don’t Teach
Short time periods reveal almost nothing about future performance and may even be harmful to our wealth for two reasons:
- “Noise” dominates over short time periods
- We are prone to over-reacting to noise due to our behavioural biases
What’s wrong with using a market index? It’s not an investable strategy. It ignores dividends (unless you use a total return index). It ignores brokerage costs and it ignores taxes. But most importantly, it is completely backward-looking. It tells you almost nothing about what your future returns will be. That said, there is a “right” way to use market indices which we’ll consider later on.
Another reason why market benchmarks may be inappropriate is that an investor may have personal risk or return objectives that are quite different from the risk and return profile of the market.
Most of the published investment returns that we see are time-weighted. They make a key assumption: a constant or fixed investment amount for the entire period. Nobody invests this way. Our invested capital changes over time as we add or subtract funds from our portfolio or if we reinvest dividends.
Looking at time weighted returns ignores any asset allocation decisions that we make. This has a huge impact on the dollar performance that we earn. Remember we can only spend dollars, not returns, which is why looking at time-weighted returns isn’t that helpful. This is also another reason why using a market index (without making some adjustments to facilitate an “apples-to-apples” comparison) is a bad idea.
You can find more information on the differences between time-weighted and dollar weighted returns here.
Costs matter. We can illustrate why with the following analogy. Imagine that you had to measure a car’s power output, would you measure it at the engine or at the wheels? One measures the pure power output of the engine, while the other measures the power that’s available for the driver to use. Ultimately, what matters is the power that’s there when the rubber hits the road. In a similar way, it’s important to factor in the impact of brokerage, taxes and other frictional costs that detract from performance.
Good Comparisons Promote Learning
Good comparisons have the following attributes:
- Long-term (minimum of 12 months, ideally much longer)
- Take into account our objectives and goals
- If market-based, they use a simple, low-cost, and investable strategy to create an “apples-to-apples” comparison.
- Dollar-weighted returns
- Create feedback
- Consider real world frictions such as costs and taxes
We’ve already covered the reasons why it’s important to have a long-term horizon (see above). Active investment strategies can have performance cycles lasting several years. Very few investors have that kind of patience. Still, it’s a good idea to periodically check and see how your portfolio is tracking relative to your expectations. This is particularly helpful if you’ve set your benchmarking up to create feedback to help you learn and improve.
It’s impossible to select an appropriate benchmark without clearly identifying your objectives first. You can find some helpful suggestions on how to do this here.
Here’s what I do instead of using a market index. My portfolio consists entirely of stocks listed in the United States. Most of them feature in the S&P 500 index. That’s why I have selected the SPDR® S&P 500® ETF (SPY) as my simple, cheap and investable benchmark. I create two portfolios using Google Finance (there are other websites that also calculate portfolio performance for you):
- My “actual” portfolio where I capture all of the trades and dividends in the stocks that I own.
- A “opportunity cost” portfolio, where I capture notional trades (equivalent to my actual trades) and dividends in the SPY.
Both portfolios factor in brokerage costs (assumed brokerage for the opportunity cost portfolio) and, in my case, currency conversion. This creates an “apples-to apples”, dollar-weighted comparison of two investable strategies (my portfolio and the SPY), net of costs.
This analysis helps me answer the question of opportunity cost: should I continue trying to pick stocks or would I be better off investing in an index ETF? But it’s purely backward-looking and it doesn’t provide any information to help me learn how to improve my investment process.
Winners Create Feedback
Imagine that you’re the coach of a football team. The season has just ended and now it’s time to begin preparing for the next year. How would you analyse your performance? Would you simply look at you win/loss percentage and call it a day? No, you would probably dig deeper in search of patterns. For example, you might examine how your results differ when playing at home or away. Or you might look at the percentage of games won when your team is in the lead at half-time.
You probably won’t stop there. You’ll keep digging. For example, you might review the performance of specific players, or examine how your team executes specific plays or manages possession of the ball when attacking or defending.
What’s the point of this analogy? Winners create the feedback that they need to learn though deliberate practice. They break the overall result down into its component parts. Winners study each aspect of their performance and look for specific ways to improve. They create an action plan to improve and they make sure that they follow through.
Looking at your performance versus a benchmark or objective is important. But it won’t help you to identify the specific steps that you can take to become a better investor. For that to happen, you’ll need to create your own feedback.
Why Feedback Matters
Investment success requires sticking to an investment process that has an “edge”, that is a process that both facts and logic suggest will work on average over time. The corollary is that there will be frequent specific cases where it doesn’t work. I’ve observed that successful fund managers are often wrong between 40-60 percent of the time. They make a lot of money not because they avoid mistakes completely, but because their wins are much larger than their losses.
The only way we can improve as investors is if we track and hopefully improve our “edge” over time. This is impossible to do without detailed feedback. Historical performance isn’t enough because any strategy with a 40-60% error rate guarantees long stretches of underperformance. How can we identify an expected stretch of underperformance vs a strategy without an edge? Feedback!
The phrase “will work on average over time” is important. It implies that we’re concerned primarily with the quality of our decision making and not necessarily subsequent results. Why do we say this? Because results are a combination of luck and skill. Skill will eventually win out over luck if we make good decisions and we give our process enough time to bear fruit.
Constructing Feedback – An Example
What sort of feedback do we need? We need feedback that helps us measure and assess the quality of our investment decisions.
I create this feedback by breaking my performance down into decision “chunks”. These chunks will vary from investor to investor. That’s OK, the point is to find a categorization that makes sense to you and is appropriate for your investment strategy. Here are the chunks that I group my investment decisions into:
- Opportunity Cost
- Portfolio Construction
Opportunity Cost relates to my objectives and whether or not the evidence suggests that I can reasonably achieve them. It also examines the question of whether or not I’d be better off investing with a different strategy. Efficiency is pretty straightforward. Selection covers decisions such as searching for, evaluating and monitoring investment opportunities. Portfolio construction decisions include the sizing of positions, the timing of cash flows and how I manage the trade-off between concentration and diversification. Behavioural decisions refer to my actions once invested. For example, do I succumb to the disposition effect by selling my winners and letting my losers run?
Breaking my investment decisions down into levels of increasing granularity also helps me to learn faster. I run a concentrated (currently 6 stocks), low turnover portfolio. I might make only 3-4 buy or sell decisions in a year. I can learn from reviewing these decisions but it’s probably true that I could learn faster if I reviewed more investment decisions. That’s why I make sure to review both implicit as well as explicit investment decisions.
Buy and sell decisions are explicit. Every time I buy a stock, I am making an implicit decision not to buy the 3, 5, 10 or however many other stocks that I also considered purchasing. Each day that I hold a stock, I’m making an implicit decision not to sell it. Considering implicit decisions increases the feedback available to learn from.
We need to search for meaningful comparisons to help us learn and improve or investment process. This goes beyond simply benchmarking against a market index. It is possible for individual investors to do this by creating their own feedback. This involves thinking about your investment process, breaking it down into the decisions that determine your results and collecting and analysing as many examples of these decisions as possible. It’s important that the frequency of review aligns with the investment horizon of your strategy. Please don’t do this monthly unless you’re a trader!
I’ll use my own portfolio as an example of how to do this in a future post. In the meantime, I would really appreciate hearing from you, my readers, on how you benchmark your performance.
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