Looks like everyone's gone passive...

The Active vs Passive Debate – Part 3

Here is the final instalment in my three part series attempting to synthesise the active vs passive management.

The reasons for indexing that we considered in part one left us cold. They’re not convincing because they don’t apply in a lot of circumstances. In part two, we got a little warmer, focusing on the conflict between the activity of investing and investing as a business. In part three, we get red hot, focusing on the strongest reasons for indexing. They are:

  1. You can’t control your behaviour. For example, you are impatient, you follow the herd or you don’t really know what you’re doing.

  2. Indexing will help you to outperform 60-90 per cent of your competitors because they are almost certain to behave badly (even if you don’t).

  3. Indexing makes fewer decisions and therefore fewer mistakes.

  4. Cost matters more than ever in a low return environment.

  5. The paradox of skill.

  6. You get to spend more time thinking about the really important stuff, such as objectives, asset allocation and education.

Read more…

Other Posts in This Series

Thank You!

I want to give a big, big thank you to everyone that has phoned, tweeted, emailed and messaged to offer encouragement, ask a question or express a different opinion.

YOU are the reasons that I write. The web is an amazing place to meet interesting people and exchange ideas. I feel privileged and lucky to know that you’re reading. Let’s keep the conversation going!

Also, be sure to check out i3 Insights on the web:  www.i3invest.com/insights  or on Twitter @i3invest  for lots more interesting content.

Please share my post on Linkedin or Twitter if you like it!

Effective Benchmarking for Individual Investors – A Case Study

In an earlier post, I described my approach to benchmarking for individual investors. It’s centred on three main ideas:

  1. Comparisons matter. Chosen benchmarks must facilitate “apples to apples” comparisons.
  2. Creating meaningful feedback. Investors need to dig a little deeper and create feedback at the decision-level, not just the overall portfolio level.
  3. Chunking. break your performance down into “chunks” that represent the key investment decisions that you make.

The table below summarises the main “chunks” that I use when benchmarking my personal portfolio. These chunks work for me. Ideally each investor will develop their own “chunks” that align with their investment process and time horizon.

Chunks

I have been running a small personal portfolio of US stocks for a little over twelve months. The portfolio currently contains 6 stocks. (I aim to keep my portfolios between 6-15 stocks).

I would be lying if I said that I didn’t look at my performance daily. It’s a bad habit and I’m trying to quit. But I only formally assess the performance of my portfolio once every 12 months. This is when I break down my performance into the five criteria or “chunks” to identify what I can improve.

The following charts and comments are a small sample taken from this exercise. Hopefully they will give individual investors some ideas on how to benchmark their performance.

Opportunity Cost

The charts below are taken from Google Finance. They show the dollar-weighted profit and loss (not the total portfolio value) of my portfolio (top panel) and a notional portfolio featuring the SPDR® S&P 500® ETF (SPY). Values are in USD.

Dollar Weighted P&L

Two things stand out. Firstly, I under-performed the SPY by approximately $2,000. Secondly, my portfolio returns are more volatile than the SPY ETF.

Am I bothered by this result? No, not really. It is no surprise to see that a 6 stock portfolio (which only became a 6 stock portfolio 9 months into the year) is more volatile than an ETF tracking the S&P 500.

The whole point of owning a 6-stock portfolio is for it to perform differently to the market (see portfolio construction)Naturally this is a two-edged sword. Sometimes “different” will mean under-performing the market over the short-to-medium term.

Even the best fund managers routinely get 40-60% of their decisions wrong. Take the Tiger cubs, some of the most well-known hedge funds, as an example. According to NOVUS, their batting average is 56.92% (but who cares with a 2.6 to 1 win/loss ratio!).

Tiger.png

12 months is too short a time frame to assess my skill level. It doesn’t allow enough time to learn from my mistakes and improve as I go along.

Importantly, 12 months isn’t enough time for me to become desensitised to making mistakes. Every investor needs to learn for themselves, by experience, that it’s the performance of the portfolio that counts. This mindset doesn’t come naturally, especially to perfectionists with a competitive streak such as yours truly.

I’ve made some changes to my investment strategy that have improved my performance. These changes a as direct result of feedback that I’ve createdThey have resulted in improved performance so this year.

Its impossible to learn how to manage your behaviour by reading a book. The only way is to get out there and do it! I’m hopeful that I’ll continue to refine my investment strategy and improve my results. I think of my under-performance as the”tuition fee” for learning how to become a better investor.

But if I significantly under-perform over a period of 3-5 years then I should think seriously about sacking myself and investing in a passive index fund. 

My under-performance was primarily due to two reasons. Higher than normal trading costs explain almost a third of the under-performance (see Efficiency).

The rest was due to two small speculative positions and a core position in which I averaged down (increased my position as the price fell). These positions lost -17.14%, -21.00% and -23.98% respectively (see selection and portfolio construction).

Efficiency

There were 13 trades (11 buys and 2 sells) in my portfolio. This is more than I would ordinarily trade since I started with 100% cash on day one and had to purchase stock to construct my portfolio.

My notional SPY portfolio had only 8 trades (8 buys). The brokerage paid on the additional 5 trades explains approximately 28.2% of the under-performance between my portfolio and the notional portfolio.

The lesson that I took from this feedback is this: unless I have an edge, each time I trade, I shift the odds in favour of the passive ETF benchmark.

Tax wasn’t really an issue as the two sales were both at a loss.

I expect that this year’s brokerage costs will be lower due to starting with an established portfolio.  However, the feedback on my trading costs has prompted me to review my brokerage arrangements which will hopefully make a big difference.

Selection

Selection refers to checking if the stocks that I invest in are consistent with the types of opportunities that my investment strategy is designed to identify. I learned a few things by going over my investment strategy. For example, last year I carved my portfolio up into two buckets:

  • Good companies at a fair price
  • Special situations – distressed companies, turnarounds, deep value, etc.

The detractors to my performance came mainly from the special situations category. I discovered that I don’t really have an edge investing in these companies because:

  • The lower hit rate means that comes with this sort of investing means that a more diversified (at least 30 stocks) portfolio is appropriate.
  • Splitting my portfolio up into smaller lot sizes (which I would need to do to manage risk) would significantly increase my transaction costs.
  • Portfolio turnover is higher which increase brokerage costs and taxes (if I’m successful).
  • Special situations require more a lot more work and ongoing monitoring.
  • I simply don’t have the time to analyse and cover more than a handful of stocks at the moment.

My portfolio is currently mostly made up of good companies at a fair price and a large allocation to cash.

The lesson here is the importance of honest self-examination. It’s the only way to learn the boundaries of your circle of competence.

Portfolio Construction

I use daily closing prices of the stocks in my portfolio and the S&P 500 to calculate the following summary statistics for my portfolio.

Stats

As you can see, my portfolio was riskier than the market (higher beta and volatility). Performance was also less consistent: 13 more down days and 12 fewer up days. This doesn’t tell me much other than I need to keep digging to understand why.

The next chart shows the evolution of my portfolio allocations over time. One of the reasons for the higher volatility/lower consistency of returns was that I took a few months to diversify across 6 stocks. Two of my early purchases were the small speculative positions that later exited at a loss.

Allocations over time

Here is the composition of my portfolio at the end of 12 months. By this time the portfolio is more diversified. Equal weighting is a good default but I’m happy to have a larger position in a stock where I have high conviction.  For example, the stock shown in orange is almost 30% of my portfolio.

Allocations

I dug further to better understand the higher volatility/lower consistency of returns by looking at the daily return contribution of each stock to the overall portfolio.

Daily Return Contribution

This yielded some interesting insights:

  • Stock H (brown) generated a lot of volatility, even though it was a small position.
  • Stock F (green) shows two large downward spikes. Here the stock price was reacting to disappointing quarterly results.
  • Stock E (light blue) generated a lot of volatility in the early part of the year because it was one of only 3 stocks held as I was building the portfolio.

The chart below repeats this analysis over a 20-day (roughly a month of trading days) horizon. This highlight just how much of the variability of results was generated by stocks H (brown) and F (green).

Monthly Return Contribution

Stocks F and H were the two small speculative positions that I sold out of during the year. After that the variability of my results reduced.

The analysis illustrated above is a good visual check on my portfolio construction. I didn’t realise just how much my smallest and speculative (i.e. risky) ideas were driving performance and volatility. That’s not good when running a concentrated portfolio.

Behaviour

I also track each individual buy, sell and hold decision. I do this in three ways:

  1. Keeping track of the absolute number of buy and sell decisions that I get right (batting average or win/loss ratio). I keep a tally both in absolute (loss vs gain) and relative (vs S&P 500).
  2. My dollar win/loss ratio. In other words, the percentage of my portfolio allocated to winning vs losing stocks. Once again, I track this in absolute (loss vs gain) and relative (vs S&P 500).
  3. Investigating the impact of my behaviour (buying, selling and holding decisions) when managing each individual position.

The table below shows the win/loss and dollar win/loss ratios for all of my buy decisions.

Buys

As you can see:

  • Only 45.5% of my buy decisions or stock picks resulted in an investment return greater than zero and only 36.4% beat the S&P 500.
  • My dollar win/loss ratio was much better. 57.9% (win/loss ratio = 1.37) of the money that I invested earned a return greater than zero and 45.6% (win/loss ratio = 1.20) beat the market.

How do I interpret this? My picking was bad but my ability to size positions was good as I invested more money in the best performing stocks. 

Once again, the impact of the two speculative stocks can be seen. Had I not invested in these stocks, my batting average and win/loss ratio would look like this:

  • 62.5% of my buy decisions or stock picks resulted in an investment return greater than zero and 50% beat the S&P 500.
  • My dollar win/loss ratio was much better. 68.5% (win/loss ratio = 2.17) of the money that I invested earned a return greater than zero and 53.9% (win/loss ratio = 1.17) beat the market.

This reinforces the conclusion that it’s too soon to draw any firm conclusions. A handful of investment decisions is too small a sample size.

I create charts to analyse my trading behaviour in response to changes in price, absolute and relative performance. Here’s how to interpret the charts:

  • Dark blue line (left axis) shows the cumulative holding performance (price only) of the stock over the year. A dark blue line above (below) zero means the absolute performance of the stock is positive (negative).
  • Dotted black line (left axis) is the cumulative performance (price only) of the S&P 500. The stock is out(under)-performing the S&P 500 if the dark blue line is above (below) this line.
  • Grey shaded area (left axis) represents performance spread between the stock and the S&P 500. The stock is out(under)-performing the S&P 500 if the are is above (below) zero.
  • Yellow dashed line (right axis) shows the number of shares held.

You could also create similar charts examining other variables, for example price-to-earnings ratios. Whatever helps you to analyse the decisions that you’re making.

Stock A

The chart above is for Stock A, my best performing position. I initiated my position in Stock A in May and held it through the rest of the year. The stock was very cheap relative to its fundamentals at the time of purchase. In fact, it continues to look cheap relative to the market, especially if you strip out its large cash balance.

The question that I take away from this chart is this: Why didn’t I buy more around December 2016/January 2017?

I had identified this stock as a core long-term holding (i.e. not a speculative or relative value opportunity), the outlook was improving, the fundamentals remained solid, market momentum was positive and the valuation was still cheap (although not as cheap as before). So why didn’t I buy more? My guess is that the disposition effect got the better of me. Like many people, I find it very hard to buy more of a stock once it goes up. It just felt wrong, even though it was the right thing to do.

So what’s the lesson? Peter Lynch’s was right.

Peter’s Principle #11
The best stock to buy may be the one you already own.

Many stocks which later became major holdings started out as minor purchases by Magellan. Often it is unnecessary to run around looking for the perfect stock, you may already have it in your portfolio, so buy more! It goes back to principle number 9, the number of really brilliant companies is finite, so when you do have one it might be better to buy more than to go out to find something else.

I now have a rule where I don’t add a stock to my portfolio without first checking to see if I should be adding to an existing holding. Analysing my performance has given me a vivid example of why this is important. Hopefully this gives me the nudge that I need to buy more of a stock if it’s the right thing to do, even if the price is now higher.

Losses often result in the best lessons. Here’s the chart for Stock H. Stock H was a small speculative holding. The company was a serial acquirer that had recently been embroiled in several scandals. It was also highly-indebted. Stock H had suffered a precipitous decline. The largest investor had finally capitulated and sold out for a massive loss.

Stock B

Why would I buy such a diseased company? I don’t have a problem with allocating a small part of my portfolio to turnarounds and other speculative opportunities; provided that I go into them with my eyes open. My opinion was always that Stock H was a long shot. It had a high probability of going to zero and a small probability of increasing 2-3x in value in a short time. So I made sure to:

  • keep my position small
  • pre-committed to a definite stop loss

I assumed that most of the bad news was probably reflected in the price. Nearly all of the management team and the board had been replaced. Some of the acquired businesses were profitable and there was a plan in place to reduce debt by selling several business units. If they could pull it off, their might be upside. So I bought a small position in August. The market reacted favourably to several announcements by the company, so I increased my position in September.

Then things took a turn for the worse. Despite assurances from management, Stock H’s scandalous behaviour continued. The company struck a deal with creditors to capitalise interest, further increasing its debt. The asset sales that were supposed to reduce debt now looked less certain. Investors were also voting with their feet and the stock price reversed and was now falling just as quickly as it had bounced.

I sold out in November, as the news surrounding the company deteriorated and the stock price was nearing my stop. I booked a 17.4% loss, but I avoided the almost 70% loss I would have suffered if I continued to hold the stock!

I am more proud of my behaviour with Stock H than I am of Stock A. Why? Because selling as a loss is hard to do (disposition effect and regret aversion) and because I stuck to my investment process. Stock H is a visceral reminder of the importance of being honest with myself (am I investing or speculating?) and risk management.

Yes, you could argue that I probably shouldn’t have invested in a long-shot (and you’d be right). But at least I protected myself by using a clearly defined risk management strategy and I dealt with my mistake quickly before it blew up my portfolio.

Conclusion

I have a lot of areas to improve on. More importantly, I have a clear understanding of what those areas are and a plan to work on them. I couldn’t have done this without the feedback that comes from creating meaningful comparisons.

So don’t just compare your performance to a benchmark, you need to make one that you can learn from!

 

I hope you’ve found this post interesting and helpful. Please share it with your friends on Twitter or LinkedIn!

Why my Mum Beats all CIOs

The following is a guest post (of sorts). Its a speech delivered to an industry audience by a friend of mine back in 2009.

Some of the specifics may be a little dated after 8 years (e.g. whatever happened to Intech?) but each of the 27 question’s posed by my friend’s “mum” remain as relevant as ever. They remain pertinent because, after 8 year, most superannuation funds still invest this way.

My friend’s mum doesn’t have to worry about any of those things. All she has to worry about is achieving a total return after taxes without taking any unnecessary risk.

Some reader’s may find these views provocative (to say the least). That is understandable because they threaten the status quo. But sometimes we need to ask the difficult questions. In the words of Socrates, “every great and noble steed who is tardy in his motions owing to his very size” requires a “gadfly” to be “stirred into life”.

Without further ado; here’s why my friend’s mum is a better investor than most CIOs.

Why my Mum Beats all CIOs

My initial view is that the way super is managed in Australia is not well aligned to members interests and that it doesn’t surprise me that the results are both ordinary and not necessarily what the members want. For example:

  • A cash plus strategy to a layman means cash plus!
  • Super returns over longer periods of time do not seem to have significantly outperformed cash.
  • I’m pretty sure that most members would gladly accept lower returns in the good times for some protection in the bad times.
  • It appears that there is very little excess return and what there is is unlikely to be true alpha

What I am going to highlight today is a number of issues that I have encountered and some potential solutions.

Even though I am expressing my concerns in a tongue-in-cheek manner and using my mum as a hypothetical retail investor, the issues in my view are nevertheless pertinent and real.

I warn you in advance that there are some very good reasons why you should take what I say with a grain of salt.

Not the ordinary disclaimer where I say that the views expressed are mine alone (which they are) and that I wasn’t here, you weren’t here and I didn’t say anything but more something like “my views are so aberrant that many think that I’m a complete crackpot”…

… Additionally, it is part of my job description to be negative. Whereas a business development manager is mostly telling a good story (maybe a fairy tale) suggesting that one should invest with his organisation my job is to say no to over 95% of the opportunities that are presented.

I wonder what came first, the chicken or the egg?  Has my job made me a glass half empty kind of guy? Or was I always this way and therefore suited to being a CIO?

There is perhaps one good reason that you may want to hear what I have to say and that is that this. Sometimes my strategies do work and my record of investing over 30 years is pretty good…

… My mother is an excellent investor. She doesn’t listen to me but maybe does pay some attention to my dad…

… Sometimes she does some strange things, like buys shares in Arnotts just because she liked getting a large biscuit tin every Christmas.

But mostly she just makes sound, sensible, long-term investment decisions that are totally aligned to her needs and have worked in the past and in my view will continue to work.

My mother is a zoologist and a mathematician who has spent many years raising 4 children and helping with 10 grandchildren. She is layman in relation to finance.

So how come she had had much better results than most, if not all, superannuation funds?

Is it because she is so good or because the funds have just over-complicated and over-engineered something that should be straightforward.

I put forward the hypothesis that it’s the latter.

Here are a number of issues that I have identified where I think super funds could do better and the 20 (actually 27, my lucky number, buts what’s a few more between friends) questions that my mother might ask.

Why do most super funds look so similar, namely 70/30?

Surely a 70/30 fund is not appropriate for all that many members?

Surely one should have an eye on future retirement income (similar to liabilities for a DB fund) and employ some form of liability driven investing?

Maybe DB style investing with its longer term horizon is a better way of managing super?

Why do funds continue to use active managers in traditional asset classes when the data conclusively shows that at least 75% underperform before fees?

Why play a game when the odds are worse than even money?

In the case of some alternative asset classes despite the attraction of higher potential alpha the odds are even more stacked against you.

For example, only the top 10% of private equity managers achieve results that are superior to listed markets.

Why do funds emphasise relative returns?

After all, you can’t eat them!

More importantly, why do funds give out mandates where losing 40% of a client’s money when the index falls 50% is seen as good? (i.e. we can’t blame the manager in this instance who has lived up to his end of the bargain).

Why do funds classify high-yield credit as fixed interest and within ‘defensive assets’?

High yield credit is clearly a de facto equity bet and my data suggests a correlation (r-squared) of between 0.6 and 0.7.

So if one did like credit why not classify it as a ‘growth asset’? (Assuming of course positive returns!)

And, why not think about investing in equities instead of high-yield credit?

(Usually I think equities are a better bet but right now I prefer credit to equity on a risk-adjusted basis. Maybe credit will even outperform equities in an absolute sense over the next short while?).

If managers can tell cheap and expensive stocks then why can’t they tell cheap and expensive asset classes?

The Frank Russell used group used to say “Son, its time in the market, not market timing!”

Now, even they have a strategist to look at selective tilting.

Surely it makes sense to buy low, sell high and therefore not to buy high!

Why do super funds listen to mathematicians?

After all, they would say that on average we all have one testicle!

More importantly and seriously quantitative analysis suggested that high valuations (high equity prices and low credit spreads) were OK given low volatility and low default rates.

If only they had read a history book and realised that the period 2002-2007 was the outlier and that pre 2002 and post 2007 are more usual.

However, I am glad that pointy heads were embraced by funds management as how else would they get laid.

Why do funds pay active fees for portfolios that have large amounts of redundancy and are de facto at least 50% passive?

Our analysis of a standard multi-manager portfolio suggests that upwards of 50% is redundant. I’m sure you can understand why we would replace an expensive, underperforming, redundant portfolio with a large amount in a passive management style.

Why do funds invest in hedge fund-of-funds?

It was obvious that pre 2007 that most FOF exhibited an alarmingly close correlation with each other and with equities.

Was it that by some miracle that all of their uncorrelated alpha with large diversified portfolios yielded such similar results (a 1 in 6 million possibility) or was it that it was just some form of commoditised (exotic) beta?

You work it out!

Believe it or not, one of our managers still insists that there was no beta in its FOF!

Why do managers buy stocks that they don’t like?                                                       

Why did managers buy a lot of expensive alternate assets that didn’t really diversify risk?

As Keynes says, the only thing that rises in a crisis is correlations.

If one adjusts for timing of valuations its pretty clear that many so-called uncorrelated assets are not uncorrelated at all and all that was different was the timing of valuations.

Why do funds believe that assets that are revalued less frequently are less volatile?

How volatile would your home be if it were valued daily?

If you believe that assets with appraisal values are less volatile, have I got a deal for you!

I can provide you with ASX200 returns for no fee with half the volatility of the ASX Just buy into a Macquarie True Index fund and revalue monthly!

Why do managers use the indices that they do?

Why would one use the UBSA All Maturities Composite Bond Index that contains credit and that the more debt that a company or the government issues, the more that it is represented in the index. Does that mean as a company is going under I should buy more debt issued by it?

Why are cap weighted equity indices (where highly priced growth companies are overly represented) a good measure?  No wonder value managers outperform these indices consistently.

Why are managers allowed to take lower quality, riskier, out-of-index bets and call any excess return ‘alpha’?

Isn’t it expected that a portfolio that includes small caps will outperform one without? So why do we applaud a manager that includes riskier, smaller cap assets and then pulls out his thumb and says “what a good boy am I?”

How come, managers rarely ask for a mandate to allow them to buy the less risky safer out-of-index assets?  I’ve never seen a small cap manager ask to be allowed to buy large caps or an EM manager ask to buy developed market stocks!

Doesn’t it therefore follow that fixed interest managers are likely to add credit (and risk) to a portfolio in an attempt to beat their index?

Doesn’t it also follow that we can look back at past performance, suggest that bond managers are ‘one-trick-ponies’ and be sceptical as to whether they exhibited any real skill?

Why do funds invest in bonds with low duration?

How are bonds (often with credit attached) with an average modified duration of 3.21 years) useful in protecting the portfolio of a member with 25+ years to go until retirement?

Why do funds which supposedly manage for the long-term pay so much attention to short-term performance?

My mum has never heard of Mercer or Intech so is not bothered about league tables.

She does however care about her after tax performance relative to CPI & cash.

If one was genuinely a long-term investor then one might hold a value portfolio like DFA for the very long term.

But please remember when taking long-term bets, whether leveraged or not, that as Keynes says “the market can stay irrational longer than you can stay solvent!”

Why don’t super funds manage to an after-tax benchmark?

If the goal was to make CPI +4% after tax then why not lock that when it’s possible.

Why don’t funds differentiate more between mark-to-market and genuine under-performance?

If one holds a duration matched portfolio of semi-government securities with a spread of 100 bps to CGS, then if one holds until maturity then the portfolio will outperform govs by 1%.

Who cares about the marking to market?

Why use a sector specialist model that is so clearly sub-optimal?

It creates artificial barriers that lead to absurdities.

For example, if the situation was such that adding preferred stock improved portfolio outcomes it is very difficult for a sector specialist portfolio construction to accommodate it. The bond guys don’t like it because it has delta and is out-of-index and the equity guys don’t like it because its beta is too low. Go figure!

Additionally it rewards managing against an index (no matter how stupid the index is) without regard to absolute returns or the opportunities in other asset classes.

My job is not to buy any bargains but to buy the best bargains!

I suggest only two asst classes, growth and defensive.

So, why aren’t equity managers keen to buy preferred stock and convertible notes when appropriate?

My guess is that it’s just a bit hard for them to deal with anything outside their very narrow irrelevant view of the world.

Why do people think that when the ASX200 is at 6800 with past low vol it is less risky than when it’s at 3400 with recent high vol?

I think that risk is neither vol nor Var but something more related to valuations.

Accordingly, when prices are lower and spreads are higher I am inclined to add to holdings.

Why listen to some asset consultants?

I do accept that they provide some level of protection. (CYA)

However, recent implemented consulting results do not inspire confidence.

Why pay managers win, lose or draw? Why offer performance fees which give managers a free option?

Is it any surprise that those on performance fees routinely add risk and those on flat fees routinely index hug and gather assets?

I guess we reap what we sow!

Why hire outperforming managers and terminate underperforming managers?

Surely mean reversion would suggest doing the opposite?

There have been numerous studies which show that the only type of performance that persists is really bad performance. Otherwise past performance is a poor guide to future performance.

Isn’t it interesting that on average recently terminated managers outperform the replacement managers?

Why pay fees based on FUM? Especially if the strategy is not capacity constrained.

Surely it takes the same work to manage or advise upon or provide custody for $100m as for $1 billion.

PS I do accept that there are some additional fees and risks associated with size but do not accept that they are as linear as service providers do.

Why do funds spend 80% of their time looking at manger selection and 20% looking at Strategy and Strategic Asset Allocation?

Surely this is the 80/20 rule completely arse about?

After all, managing beta is risky but is 400x* better than alpha as a tool for increasing portfolio outcomes.

*20 times cheaper and 20 times more important.

So, why not just go back to an old fashioned balanced fund where alpha and beta are both properly managed?

“The more things change, the more they stay the same” or “plus ça change, plus c’est la même chose”

Finally, I’d like to leave you with two thoughts.

  • If history revealed the path to riches, librarians would be in the Forbes 500 (Buffet); and
  • Flat is the new up.

Measuring Up – Effective Benchmarking for Individual Investors

Reading time:  9 minutes

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.

Comparisons Matter

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:

  1. Regret is a comparative emotion. So, it’s really important that we make the right comparisons.
  2. 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:

  1. “Noise” dominates over short time periods
  2. We are prone to over-reacting to noise due to our behavioural biases

See  my latest piece for i3 Insights (point 3) and last month’s column (point 7) for more details.

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):

  1. My “actual” portfolio where I capture all of the trades and dividends in the stocks that I own.
  2. 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
  • Efficiency
  • Selection
  • Portfolio Construction
  • Behaviour

Chunks

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.

Conclusion

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.

 

I hope you’ve found this post interesting and helpful. Please share it with your friends on Twitter or LinkedIn!

 

 

The Active vs Passive Debate Part II

Here is my latest column for i3 insights where I dig into the real reasons why active management so often fails to deliver on its promises.

For those that can’t be bothered reading on, here’s a spoiler: The problem lies with the business of active investing, not the activity. It is definitely possible to beat the market. But for that to happen, investors must avoid common mistakes, such as those featured in this post.

Part 1 of this series: Synthesizing the Active vs Passive debate

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Synthesising the Active vs Passive Debate

I’m a firm believer in the value of active investment management.

I also believe that 95 per cent of institutions should invest passively.

No, I’m not confused or delusional. My apparently contradictory viewpoint is the result of a deliberate effort to synthesise both sides of the active vs passive debate.

Most of the active versus passive debate focuses on the analysis supporting either the active or the passive side. In reality, the correct decision depends on the circumstances (see my earlier post).

This is why synthesising the arguments from both sides of the debate is vital. One of the best examples of the power of synthesis is the legendary Charlie Munger. Here’s a thought-provoking quote from Charlie courtesy of an interesting piece written by the Farnham Street Blog entitled The Work Required to Have an Opinion.

The ability to destroy your ideas rapidly instead of slowly when the occasion is right is one of the most valuable things. You have to work hard on it. Ask yourself what are the arguments on the other side. It’s bad to have an opinion you’re proud of if you can’t state the arguments for the other side better than your opponents. This is a great mental discipline.

I’m going to take up Charlie’s challenge: an active investor presenting the case for indexing better than a passive investor. There’s a lot to cover, so I’ll tackle the subject in three parts:

Read more: Market Fox – Synthesising the Active vs Passive Debate

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