Online pornography is an immense enterprise. Almost 92bn porn videos were viewed on Pornhub, the world’s largest free internet porn site, in 2016 — more than 12 videos for every person on earth. Nearly half of Pornhub viewers visit the site between 9am-6pm.
The US is the biggest consumer of online pornography per capita, and the UK is the third (Iceland, perhaps surprisingly, is number two). Increasingly, porn is viewed on mobile devices. In the US last year, mobile accounted for 70 per cent of hits on online pornography. “I don’t know a single guy who hasn’t looked at porn at work,” says one man who worked in the City of London, describing colleagues taking their phones on periodic “bathroom breaks” during the working day.
A while ago I put up a post that may have gone a little off the deep end. It likened investing to a spiritual journey and drew heavily on the example of Bridgewater Associates.
Barry Ritholtz has a neat Bloomberg View piece up summarizing some takeaways from a recent interview with Bridgewater founder Ray Dalio. I love this thinking and it is why I keep an investing journal:
Throughout the book, and in a recent conversation we had, Dalio insists the key to his turnaround was revisiting failure and learning from it. He is enamored of the framework described in Joseph Campbell’s “The Hero with a Thousand Faces.” Campbell’s book examined the evolution of mythological figures, whose failure leads to discovering new wisdom that they use to achieve their goals. Dalio wanted his failures to have the same results, so he created a broad set of rules to do so:
- View mistakes as opportunities to improve. He calls this “mistake-based learning.”
- Own your errors. Never hide them, but bring them forward to create a learning opportunity. His advice is to “fail well.”
- Pain + reflection = progress. The “pain of failure” should lead to reflection, from which your wisdom derives.
- Track what you do; keep systemizing what you learn from your mistakes.
- There are many more principles, but this gives you an idea of some of the basics.
Dalio does things that most ordinary people don’t do. Set aside for a minute his remarkable track record as an investor and note the following unusual business behavior: He writes down and reflects on everything he does. Then he systemizes it, eventually turning these into algorithms that his firm’s computer systems help backtest against earlier eras. The end result of this is a hybrid of human creativity and machine learning that produces results better than either could separately.
I have been having some interesting conversations recently regarding the latest trials and travails of cryptocurrency investors. The issue many of them are facing is what to do now having made returns of 5x, 10x, or more.
Do you let it ride and shoot for 1000x?
Do you lock in your profits now?
In traditional markets, such as equity and fixed income, fundamental analysis helps with these issues. If you own Proctor & Gamble (PG) stock, and one day PG falls 50% for no reason other than that traders are bouncing the stock price around, you either: a) do nothing, or b) buy more. Although the market price has plummeted, there is no change in the intrinsic value of what you own (a slice of PG cash flows). In this case your valuation anchors you on what is important (intrinsic value) instead of the noise (the change in market price).
The challenge with cryptocurrency is that there is no intrinsic value for you to anchor on–at least not in the conventional sense. Holding forever and collecting your cash flows is not an option. There are no cash flows to collect. All you’ve got are supply and demand, and supply and demand are notoriously fickle over short time periods.
I have a pet theory that despite the meteoric rise in the price of Bitcoin, the average investor return is much, much lower. This would be consistent with investor behavior in traditional financial markets:
Of the municipal bond category, Morningstar’s Russ Kinnell wrote:
It’s surprising that the rather stable muni-bond fund group could be so misused, but it has been going on for a while. The problem here is that there are very risk-averse investors and a sector with scary headlines. The good news rarely makes headlines. Rather, investors hear about Puerto Rico’s crushing debt and Meredith Whitney’s ill-informed doomsday call. Those news events spurred muni investors to sell, which led to a drop in muni-bond prices and a spike in yields. Thus, they created a buying opportunity just as investors were fleeing. This speaks to the downside of trying to time the market and the benefit of staying focused on the long term.
I am increasingly involved in discussions about how futures trading will impact the spot price of Bitcoin. While I am far from a Bitcoin bull, I have attacked the notion that futures trading will somehow trigger a major correction in spot Bitcoin prices. This post will explain why.
First things first.
This is an intellectual exercise. It is not an investment recommendation. Do not under any circumstances make any decisions with real money (crypto or fiat) based on what you read here. See also my disclaimer at right. If you are serious about putting money into cryptocurrency, do you yourself a big favor and consult with a professional advisor who can provide guidance based on your unique circumstances.
Also, if you are not familiar with futures terminology, you are going to have to bone up on the following:
- Term Structure of Futures
- Futures Arbitrage
Khan Academy has a series of videos that looks decent. I simply don’t have the time to post a comprehensive introduction to futures on this blog. And frankly, if you are not willing to invest some time learning about markets and investing, you probably shouldn’t be spending time reading about digital lottery tickets in the first place.
Now, if you can explain to me why there is no arbitrage opportunity available on a 1-year Bitcoin forward priced at $12,600 with spot Bitcoin at $12,000, assuming a riskfree interest rate of 5%, you will follow my argument.
Why Bitcoin Futures Trading Will Not Trigger A Selloff
Whether the addition of futures trading will be bullish or bearish for Bitcoin depends entirely on the marginal trader of Bitcoin futures. The bear case assumes the market for Bitcoin futures will be dominated by hedgers and short speculators, and that this in turn will exert downward pressure on spot Bitcoin prices.
I disagree for two reasons:
First, market sentiment is euphoric. While there are certainly Bitcoin bears out there, it is difficult to imagine that they will dominate in futures trading. More likely futures will be viewed as a cheap way to get (leveraged) exposure to Bitcoin without the custody issues associated with owning Bitcoin outright in the spot market. I simply do not believe a bunch of professional traders are going to come out of the woodwork to short an asset with no intrinsic value, that people feel justified owning at $10 or $400,000. As a directional short Bitcoin is potentially lethal. Doubly so due to the leverage embedded in futures trading.
Thus, the term structure of Bitcoin futures is likely to be contango. Other than volatility and uncertainty there isn’t much reason for Bitcoin futures to trade in backwardation. If the spot market were wavering there might be an argument otherwise. But as noted above the spot market is euphoric. Therefore, futures traders looking for arbitrage opportunities will most likely be shorting longer dated Bitcoin futures and buying spot Bitcoin as a hedge (the goal being to earn roll yield with no directional exposure to Bitcoin prices). This argues for upward pressure on Bitcoin prices in the short term.
In order for futures trading to pressure spot Bitcoin downward, the term structure of Bitcoin futures will have to backwardate. This will encourage arbitrageurs to sell Bitcoin in the spot market and go long Bitcoin futures, putting downward pressure on spot Bitcoin prices.
What would cause the Bitcoin futures curve to backwardate? The Bitcoin narrative would have to break. Apologies in advance to enthusiasts but Bitcoin doesn’t trade on fundamentals right now. It trades on momentum (a.k.a sentiment). Skilled short sellers are not going to put big positions on unless the narrative breaks and sentiment turns. Otherwise they are going to get squeezed. Hard.
I never, ever, ever get involved in what I would call open-ended situations. . . . I have avoided pie-in-the-sky names. To use an analogy, I’m not interested in climbing into a tree and wrestling the jaguar out of the tree. I’m interested in someone shooting the jaguar out of the tree, and then I will go cut the thing apart once it hits the ground. Instead of open-ended situations, I like to short complete pieces of garbage with fraudulent management and horrifically bad balance sheets. I look for change, I look for ‘if this goes away tomorrow will anyone miss them’?
It is a common refrain these days among investment managers that “fundamentals don’t matter.” The market does what it does because of ________. (possible answers include: easy monetary policy; tech bubble v2.0; passive investing bubble) This makes all stocks go up together. With stocks so highly correlated it is impossible for a stock picker to succeed because “bad stocks” get rewarded just as much as “good stocks.” That is why passive investing is so popular. It is all one big, self-reinforcing bubble. When the pointy reckoning finally arrives all of us fancy active manager types will laugh our way to the bank.
I admit I am guilty of saying some of this stuff myself. Which I suppose makes me extra guilty because I understand correlation and how to interpret the statistic and am still using the term imprecisely.
Here is a good analysis by Aaron Brask on the Alpha Architect blog refuting this argument. He argues from first principles and even conducts a simulation to show that mathematically, correlation does not impact the expected returns of individual stocks. I will steal his chart because it is a convenient summary:
Mathematically, Brask’s argument is irrefutable. That’s the nice thing about mathematics. When you’re right, you’re right.
I will go further and argue that all this confusion about correlation stems from the fact that many finance professionals don’t actually understand it. They use a heuristic: “correlation = perform the same.” That is how they are used to explaining correlation to clients (and each other). The heuristic is fine for generic spiels about portfolio diversification but it can be dangerous when applied to actual portfolio management decisions.
I have encountered this on several occasions. For example, a colleague once asked if there was a mistake in a chart that showed the S&P 500 correlated nearly perfectly with a 50/50 blend of T-Bills and the S&P 500. My colleague was using that heuristic of “correlation = perform the same.” The two portfolios are indeed perfectly correlated. However, the historical return of the blended portfolio is much lower because T-Bills tend to return much less than stocks over time. This is exactly what Brask illustrates in his simulation.
Look again at his chart. Instead of focusing your attention on the return, compare the shapes of the line graphs. Pretty close, right? That visual similarity is indicative of high correlation. That’s because correlation measures similarity in the variation of returns, not similarity in returns themselves.
To illustrate further, here are three more visuals, graphing relative outperformance/underperformance of different portfolios over time.
The first is the S&P 500 versus itself (perfect correlation = 1):
The next is the S&P 500 versus the Bloomberg Barclays Aggregate Bond Index (correlation = basically 0 but in fact is slightly negative):
The final comparison is S&P 500 versus a 50/50 blend of itself and T-Bills (correlation = very near 1) :
Notice how in the first and third charts, the points plot in a straight line, while in the middle chart they are an uncoordinated blob. In this visualization, the more the plotted points resemble a straight line, the higher the correlation. The third chart shows a strong linear relationship but with much higher returns for the S&P 500 over the blended portfolio.
An improved heuristic for correlation is to think about the extent to which two assets share common risk factors. An investment grade bond index is mostly exposed to reinvestment and interest rate risk (seasoned with a pinch of credit risk). A stock index has little direct interest rate risk and almost no reinvestment risk. It is more exposed to the business cycle and economic variables such as real wage growth. Intuitively, you would expect very little correlation between stock index returns and bond index returns.
T-Bills have very little risk of any kind. Some people think of them as risk free. That is not entirely accurate but for this exercise it is a safe assumption. When you combine T-Bills with the S&P 500 the only relevant risk exposures are those of the S&P 500. They will drive 100% of the variation in portfolio returns over time, despite the fact that 50% of the portfolio is risk free. You can therefore expect high correlation with the S&P 500.
So when someone in the investment business says, “high correlations are bad for stock pickers,” she isn’t actually talking about correlation. What she actually means is, “market environments where investors don’t care whether they own good businesses or bad businesses make it difficult for active managers to outperform their benchmarks on a relative basis.” Hopefully she understands the difference intellectually and is just speaking imprecisely, using the “correlation = perform the same” heuristic for convenience. But you never know. People will trot out some pretty silly stuff when billions of dollars of fee revenue are on the line.
(Incidentally, if you are the type of person who likes to give prospective financial advisors quizzes before hiring them, this is a good topic to add to your list)