June 15, 2017
What We’re Reading This Week
Passive vs. Active
Financial services articles generally fall into one of four categories: Trump related, Bitcoin/Blockchain related, fraud related, and active/passive investing related. When it comes to active vs. passive, both sides tend to (mis)use the data to support their own means. For example, in 2016 roughly $286.5 billion flowed to U.S. ETFs, $162 billion of which went into U.S. equity ETFs. Passive investing proponents would say this is an example of “passive” strategies gaining credence. “Active” investment managers would point to other data. The average holding period for SPY, a widely held U.S. equity ETF, was 10 days in 2016. You could conclude that the massive amount of money flowing to ETFs comes from active, institutional money managers.
The arguments against each other range from the benign to the ludicrous. Renaud de Planta, the chairman of Pictet Asset Management thinks passive investing “could threaten the free-market economy.” Pictet Asset Management is an active investment manager…obviously. All opponents to passive investing eventually adopt one of two perspectives. Either index funds are creating monopolies or index funds are Marxism. De Planta thinks it’s the former. He also thinks it needs to stop:
“De Planta would prefer passive investing to remain a minority pursuit. ‘If the majority of us embrace them, index-trackers threaten to sabotage the entire economic system,’ he concludes.”
The main argument here is that lumping investors together into a predetermined mix of stocks erodes competition. For instance, if stock A is purchased, not because people like the stock, but because it’s included in a popular index, the price of the stock would become artificially inflated and cease to reflect market conditions. Sort of like what happened with Southwest a month or so ago.
Personally, I think most changes in the way people invest reflect a trend towards making things more efficient. People have always purchased stocks because they were included in an index. Providing a fund that simply allows investors to click one button to buy all the stocks in that index just makes this easier for investors. Of course, there is a subset of investment managers that don’t want things to be easier for investors. I call it the Wizard of Oz approach. Hey, don’t look behind the curtain; we don’t want you to realize that you could do this yourself!
Speaking of active vs. passive, The Economist wrote a nice piece on “Quant” investors. A quant is someone that tries to use market inefficiencies to beat market prices. As far as investing literature goes, it’s a breath of fresh air, if only because it’s honest.
“One notion, says Antti Ilmanen, a former academic who now works for AQR, a fund-management company, is that markets are ‘efficiently inefficient.’ In other words, the average Joe has no hope of beating the market. But if you devote enough capital and computer power to the effort, you can succeed.”
This is a real bummer for “average Joes” and you can sort of understand why most firms that invest money for the average retail investor (Vanguard) focus on simple, passive investment strategies. It is also why Gainplan’s investment model is based on principles used by institutional money managers. We want to bring real, professional money management to retail clients. Unfortunately, no one really talks about how you can beat the market; they just focus on how most people can’t beat the market. Think about it like this. Take investing out of the quote of above and replace it with something else:
“The average Joe has no hope of building an airplane. But if you devote enough capital and computer power to the effort, you can succeed.”
“The average Joe has no hope of building a self-driving car. But if you devote enough capital and computer power to the effort, you can succeed.”
This makes sense, right? And as technology becomes more affordable, advanced investing strategies will be available to the “average Joe.” Currently we refer to this as smart beta. These funds use computer algorithms to mirror advanced trading strategies a human investment manager might use. The problem here (for me) is known as the Observer Effect in physics. Essentially, when you measure something, you change it. The common example is measuring the air in your tires. It cannot be done without letting out a little air and thus, changing the air pressure.
“Whether these funds will prosper depends on why the anomalies have been profitable in the past. There are three possibilities. The first is that the anomalies are statistical quirks; interrogate the data for long enough and you may find that stocks outperform on wet Mondays in April. That does not mean they will continue to do so.
The second possibility is that the excess returns are compensation for risk. Smaller companies can deliver outsize returns but their shares are less liquid, and thus more difficult to sell when you need to; the firms are also more likely to go bust. Two academics, Eugene Fama and Kenneth French, have argued that most anomalies can be explained by three factors: a company’s size; its price relative to its assets (the value effect); and its volatility.
The third possibility is that the returns reflect some quirk of behavior. The outsize returns of momentum stocks may have been because investors were slow to realize that a company’s fortunes had improved. But behavior can change; Mr. Wadhwani says share prices are moving more on the day of earnings announcements, relative to subsequent days, than they were 20 years ago. In other words, investors are reacting faster. The carry trade is also less profitable than it used to be. Mr. Ilmanen says it is likely that returns from smart-beta factors will be lower, now that the strategies are more popular.”
If something allows for a market anomaly, finding it and measuring it will have an effect. If we all trade on the anomaly, the effect is amplified, likely reducing the arbitrage available in the anomaly. I look at algorithm trading as a fairly basic model: numbers go into a computer and trades come out. When all the numbers go into all of the computers, we will all make the same trades. When we all make the same trades, we no longer have anomalies. It stands to reason that some other anomaly will exist. That means investing in smart beta is the stock market equivalent of being late to the party. You are investing in yesterday’s inefficiencies. If the trend continues, we will eventually find ourselves in some kind of cycle where buying and holding an individual stock becomes some form of market arbitrage. The more advanced our computers trade, the more effective unsophisticated trades will become. At some point, the cutting edge of investment management will involve trading paper certificates at some kind of auction under a buttonwood tree!
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