How did retail traders do in the summer of 2020?

(Note: I published, then deleted, this story realizing the data source was wrong. The nice folks at medium restored it for me after I thought I had resolved it, however I’m not entirely confident I have done so, so note well this might be wrong.)

If you follow the financial media, social, new, or legacy, you’ll probably have encountered stories about the influx of normal people into the stock market during the pandemic summer of 2020. Thus you’ll have read about posters on r/wallstreetbets using Robinhood, a low-fee brokerage, to buy almost certainly worthless options with their stimulus checks, in the hope that stonks (stocks) go up, that tendies (ten dollar bills) may be stacked.

There are several reasons to be interested in this story. You might, to use yet more of the lingo, be seeking alpha (a good investing strategy), you might be interested in the sociology of such behaviour, or you might just be interested in finding patterns in data (I’m writing this from a combination of all three).

I’m not sure if an exactly similar phenomenon exists in the UK. Ironically, while gambling is legal in the UK, options are marginally available for the average person (they’re not very tax efficient, is my understanding of the gap; it’s ironic because in the US, again as far as I know, gambling is mostly illegal but options, an instrument very suitable for gambling, are seemingly fine). And we didn’t really have stimulus checks.

But I was nevertheless curious. There exists similar ‘retail’ markets for stocks in the UK. The app I use is Freetrade (which I recommend, although I haven’t used any others). On Freetrade, one can buy stocks and bonds and efts, and fractions thereof (one can’t buy options, commodities, forex, crypto, or CFDs, which are the tax-efficient derivatives available in the UK.) As its name suggests, Freetrade doesn’t explicitly have transaction fees, but instead offers a freemium model.

Moreover, each Friday, it posts on Twitter a list of the most popular stocks that week. This made me wonder: does the list contain any interesting collected wisdom? Can one derive from it a good investment strategy? One might think obviously not, that this represents ‘dumb’ money, that it would simply represent people buying in late such that over time mean-reversion (or something more fancy I don’t know about) would gradually whittle away money to nothing.

At the same time, Freetrade customers presumably have a relatively unique socio-cultural role. Beneficiaries of low barriers to entry, with an interest in making money but without gobs of wealth, and without any fiduciary requirements to anyone but themselves, they might possess insights and capacities wealthier or institutional traders don’t. It’s worth exploring.

So I did some exploring. The disappointing answer, both to the questions of the penultimate paragraph, and to the title of my post, is: I don’t know how good Freetraders are. However, I can give you both a partial answer, and, more importantly, some relatively clean data you can use to find ask work better answers for yourself.

The Silly Question I asked

Here’s a question: say one were to buy, each week, the most popular stocks per the Freetrade list, and sell them the next week and buy the most popular stocks of that next week, how would one do?

My initial guess was: badly. By operating in that way, one would be buying at the top, and likely over time to lose money. And, in fact, subject to the very important caveat that I didn’t mess anything up (highly likely; I’m releasing this to the world in the hope that my mistakes will become evident, and also because this is a weekend project and the weekend is almost over), it seems like the answer is indeed: badly.

In particular, assume that you start with £100, that you always invest all of it, that you invest in ten stocks each week, that you divide any capital you have equally between all ten stocks, and that any gains you reinvest, then following the above simplistic strategy yields the following graph, with a final amount of £23.59 (NOTE: If the live sheet shows something different, I’m pretty sure it’s owing to a failure on the part of googlefinance. If you go to the live version of the sheet, and columns j and l differ, that means googlefinance is being screwy). Ouch!

What can we conclude from this, assuming I haven’t made a mistake? Well, not much: that a silly on the face of it strategy is, in fact, silly. But the real interest lies not so much in this fact, as in what else might be lurking in the data. You can find the data here. (For those curious, I got it from Twitter by the very advanced technique of ‘copy and paste’ (the API wasn’t working on any of my bots), then regex’d it into shape, pulling the historical financial data from thesheets in-built function googlefinance.)

I’m sure I messed a bunch of stuff up. I work off opening data from the Friday in question, which is before Freetrade posts their list; I suck at maths; if a stock is in the list in two subsequent weeks, it is sold and then bought back, introducing unnecessary transaction costs (if not fees); googlefinance is depreciated and for at least a couple of stocks, thus probably for others, gives wrong data (also, if you go to the sheet, you might see #N/A with an error message about googlefinance); and probably lots more, all of which would need to be seen to before one could even slightly rely on this. All lectors should cavere.

Let me just end by noting the slightly obscure structure of the sheet (this screenshot is from a slightly older, since debugged version — the accurate data is to be found at the live link above):

The ‘direction’ field is a cool feature of the data Freetrade gives us, letting us know if the stock has moved up the top ten (UP), down (take a guess), whether it has reappeared having occurred in a previous but not the immediately previous week (BACK), or whether it’s new to the top ten (again, guess). The Price field gives the price on the date, the subsequent one the price 7 days later, then the percentage change is worked out, and the overall percentage change subsequently. The balance, at a given week, is a function of the previous balance and the percentage increase this week. The Vanguard s&p eft is just for comparison.

An interesting thing to try, which I might, is see whether balancing one’s portfolio in terms of the direction variable yields better or more interesting results. Another interesting thing would be to check out the viability of more sensible buy and hold strategies — take an arbitrary list, and see how it’s doing 2/3/6 months later. That’s easily done; but for another weekend.