Data availability is something of a double-edged sword in today’s financial markets. On the one hand, we now have a nearly unlimited supply of research, opinions, back-tests and historical simulations with which to base our investment views upon. On the other hand, the fact that we have more information available at our fingertips than ever before can lead to an over-reliance on how we use it to make decisions.
Over-reliance often leads to overconfidence, which is one of the best ways to go bust in the markets if you’re not careful. There are two arguments I see on a regular basis that show up as a result of data overload:
- …because that’s never happened before.
- …because that’s what’s always happened before.
The problem with this line of thinking is that it can lead investors to fall into what I like to call the certainty trap. It’s this all-or-nothing line of thinking that causes so many to constantly attach extremes to every single market move or data point they see. The beginning of the recovery or the end of the world is always right around the corner. The assumption is that we’re always either at a top or a bottom when most of the time the markets are probably somewhere in the middle.
The certainty trap is so easy to fall for because historical data can feel so safe and reassuring.
Look here, my data says that this has never (always) happened in the past. Surely this trend will continue. I’ll just sit here and wait for my profits to start rolling in.
‘Never’ and ‘always’ have no place in the markets because no one really knows what’s going to happen next. ‘Most of the time’ is a much more reasonable goal, because nothing works forever and always in the markets. If it did everyone would simply invest that way. I think a much more levelheaded approach is to follow the Jason Zweig 10 word investment philosophy:
Anything is possible, and the unexpected is inevitable. Proceed accordingly.
To disregard the potential for the unexpected is the height of arrogance and arrogance is rarely rewarded for long in the ever-changing markets. Don’t get me wrong, I’m not saying you shouldn’t take on high probability bets based on the weight of historical evidence and your current views. That’s exactly what you should do.
But probabilities take into account the fact that there’s always the possibility that we might see the minority situation occur. In fact the best you can hope for is a high probability for success because luck plays such a large role in shaping the outcomes in the markets. I’ve always liked the old adage that it’s better to be roughly right than precisely wrong.
My feeling has always been that historical data is a great way to view the inherently risky nature of the markets, but that doesn’t mean the data always does a great job at predicting exactly what’s going to happen in the future. Investors have to remember that market data does a much better job of forecasting potential risk than it does potential return.
There are no certainties in the markets. Otherwise, there would be no such thing as risk.
Nothing works all the time. Otherwise, it would never work in the first place.
There’s no room for ‘never’ or ‘always’ in the financial markets. Otherwise, you’re sure to be surprised in the future.
Further Reading:
On The Merits of Being a Financial Historian
Data overload? Consider this 17-page private equity performance report for CalPERS, one of the largest and most sophisticated private equity investors.
On page 7, it states that ‘All [PE] strategies have demonstrated volatility over the time periods measured, with Opportunistic being the most volatile.’ But nowhere in the report is volatility quantified, meaning that measures of risk-adjusted return such as Sharpe ratio aren’t reported either.
https://www.calpers.ca.gov/docs/board-agendas/201508/invest/item06b-03.pdf
Volatility and Sharpe ratio are basic data that public investors find on the fact sheet of every ETF and mutual fund.
VIX spiked to 50 last month. What’s happening to the volatility of highly-leveraged buyout companies, as credit spreads ratchet up? Evidently, some big PE investors haven’t the slightest clue. Sharpe ratio, duh, what’s that?
This is a byproduct of data overload — not knowing which data to use. It is pretty amazing how poor their governance and fund oversight is at these huge funds. That should be job number 1. This is why I think “sophisticated” is a misnomer in the investment business.
I’m of the opinion that market timing can work if people are learned enough, but it seems the time required to study the data is not worth the marginal bump it can give to ROI, so most (including myself) are probably better off just buying regularly and waiting 10+ years.
That said, I would be super interested if you would curate a list of all the indicators people use to judge whether or not stocks are at a buying opportunity (P/E, Sharpe, etc). Obviously, there is no one indicator that always works, but it would be fun to see which are at historic highs, which aren’t, and why most people shouldn’t really care.
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