The edge the financial media and trading gurus provide comes in the form of dumb money needed for systematic and skilled traders to realize alpha.
A few days ago there was an article in a financial website about a coming bull market in some commodity. The article was written by some technical analyst who threw a few lines and moving averages on the chart and based conclusions on those. The next day there was another article in the same website by another technical analyst who used different lines and indicators in support of the claim that the price of the same commodity will fall.
Some will argue: “This is normal because there are always buyers and sellers in the market.”
But what about if the buyer and seller are the same person and the sell comes at a lower price that the buy?
This is not of concern to financial media; they are in the business of making money from clicks and they are happy to present different views.
The problem is that most of these technical opinions are based on simplistic narratives. Since financial media depends on clicks from the public they will avoid publishing articles with quantitative analysis. Most people are told that “there will be no math.”
Math is pain, math is not good for business and math is what some nerds do. These nerds don’t get many offers to publish their work in financial media. They instead choose ArXiv.org or ssrn.com and are usually read by other nerds only, as very few from the audience of financial media get close to those sites.
These are some of the issues with financial media articles about the markets:
- Frequent conflicting narratives
- There are rarely follow-ups
- Rarely articles include measures of risk
- Authors have different objectives
- Most of the time analysis is hopelessly simplistic
The conflicting narratives usually cause cognitive dissonance and readers come back for more in hope of a resolution. This creates more clicks. However, there are rarely follow-ups, or admission of error, just occasional boasting about success. Very infrequently articles present any measure of risk, i.e., how much may be lost in case the analysis is translated to market action although there may be references to uncertainty. Risk is the expected loss due to uncertainty and is not easy to calculate. In fact, most authors have no idea what expectation means and a large number of them confuse averages with expectations but keep in mind that some economists have the same problem.
Authors may have different objectives not revealed in the articles. Some are short-term traders and others are trend-followers. Readers may think someone is looking at a longer-term trade when in fact the analysis is good for a few days but that is not made clear. One major drawback is that most of the time the analysis is hopelessly simplistic because, among other things, analysis will not be published if it contains math. Remember, the financial media does not want to alienate readers with math.
Next, the gurus: I attended a webinar recently just out of curiosity. Someone in front of many screens promised financial independence to a large group of clueless individuals (judged from their comment stream.) The method was so simplistic no one had a chance to make any money other than losing everything but the choice of words and technical jargon made it appear sophisticated. The subscribers, whoever decided to subscribe, were actually paying to learn how to throw money way when there are easier ways: go on a shopping spree, or give the money to charity for example.
The dumb money
The dumb money created by financial media and trading gurus is exactly what professionals need to realize alpha. After the dot com crash, there was a significant decrease in dumb money as many retail traders using technical analysis and other simplistic methods got ruined and some decided to go passive in an effort to break even. Neal Berger made a reference to dumb money recently as the source of alpha and how the reduced flow has affected the profitability of trend-followers.
The reason I believe there is still alpha in the markets is because many resort to simplistic analysis and investing gurus. I do not see any prospects of quantitative trading becoming mainstream in the next 10 or 20 years so quant trading, but not of the “pedestrian” type touted by some popular investing sites, has chances of generating alpha. By “pedestrian” I mean things like these trivial price series and cross-sectional momentum methods and associated articles that cover 10 – 20 pages to tout the results of simplistic rules that do not take more than a few characters, for example P > MA12 (price above the 12-month moving average.) No one knows the risks of these simplistic methods and it is reasonable to assume that the risk is the uncle point. For example, an extended period of sideways stock market could generate devastating losses for price series momentum and even for cross sectional. Essentially, anyone who invests with these methods without paying for insurance is naive and this is fine if the money is personal but quite irresponsible if managing pension money. No 20-page analysis with fancy charts will compensate for the fact that these trivial investing methods carry high risk. Yet, part of the financial media promotes these methods and avoids counter-arguments.
Retail quant traders and small quant funds have an advantage as long as financial media exchanges clicks for noise and large funds resort to high capacity simplistic investment strategies. The low capacity strategy with the idiosyncratic alpha generation mechanism is the future as long as risks are properly quantified and potential sources of bias are eliminated, for example data-snooping, p-hacking, etc. A proper mix of few strategies that rely on idiosyncratic alpha is the key to success. My preference is for a “non-pedestrian” type rotation of key sectors, a long/short equity and a mean-reversion strategy. Note that long/short equity is a drag on alpha during bull markets but can offer significant hedge or even outperformance during bear markets so there is a trade-off there that must be balanced against objectives. In the case of sector rotation, the key is not so much the math but the choice of sectors. Mean-reversion lags recently after a few good years but it is unlikely that it will be arbitraged out of the markets since there are not many alternatives in a market with a small supply of dumb money when passive investing dominates.
If you have any questions or comments, happy to connect on Twitter: @mikeharrisNY
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