Category Archives: ideas

Who’s Better at Picking Stocks: r/WallStreetBets or a Goldfish?

Michael Reeves has carved out a unique niche in the online world through his comedy-tech videos, combining his programming skills and love of modern technology with rapid fire jokes and satire.

In his latest production, he's taken on the world of meme investing, as represented by the favorite stocks pitched by top contributors to r/WallStreetBets, and pitted them against pure random selection, as represented by the stock picks of his pet goldfish. In the following 15-minute video (featuring some NSFW language and visual humor), he explains how he did it and presents his experimental results:

Our favorite part is when he pitches the "FISH" system to potential investors.

Reeves' experiment makes sense in the light of the real results of the Wall Street Journal's long-running investment dartboard challenge, in which the performance of stocks picked by professional investors competed against stocks picked by WSJ reporters who threw darts at the newspaper's stock listings to pick stocks at random. Superficially, it appeared the pros beat the darts, but that was because they benefitted from two secret advantages that were hidden in plain sight:

Professor Burton Malkiel of Princeton University, who for decades has been arguing that you can't beat the market, and a colleague found that the stocks the experts picked were risky. They were far more volatile than those the reporters picked using darts or the stocks that make up the S&P 500. When the stocks of the three groups are adjusted for risk, the returns of the experts fall precipitously below those of the dartboard or the index.

Professor Malkiel goes further. He argues that the unadjusted returns of the experts were higher because Wall Street Journal readers noted the selections after they were published and then bid them higher. Had the experts chosen their stocks on the day the stock picks were published instead of the day before, their return would fall a whopping 3 percentage points!!!

All in all, Reeves' goldfish-based investing system is a fun way to revisit those old results.

Previously on Political Calculations

What Should the Value of the S&P 500 Be?

Since the S&P 500 (Index: SPX) peaked at 4,796.56 on 3 January 2022, the index has dropped by 18.2% of that record high value. But that simple observation raises a question. What should the value of the S&P 500 be?

We have a couple of interesting ways to approach answering that question, the first of which relies upon how investors set the average level of the index with respect to its trailing year dividends per share during periods of relative order in the U.S. stock market. The following chart illustrates the five major periods of order the S&P 500 has experienced since December 1991, which have been periodically interrupted by periods of relative chaos.

S&P 500 Average Monthly Index Value vs Trailing Year Dividends per Share, December 1991-May 2022 (through 18 May 2022)

In the chart, we show the mathematical relationships that have applied during those relative periods of order, which connects the average monthly value of stock prices (y) with the level of the index' trailing year dividends per share (x). We've built the following tool to do the related math to see how investors would set the value of the S&P 500 for the period of order you select for the trailing year dividends per share you enter. If you're accessing this article on a site that republishes our RSS news feed, you may need to click through to our site to access a working version of the tool.

Alternate S&P 500 Valuation Criteria
Input Data Values
Relative Period of Order
Trailing Year Dividends per Share

Projected S&P 500 Index Value
Estimated Results Values
Index Value Corresponding to Selected Period of Order

Using the default selection of the most recent period of order, which lasted from December 2018 through February 2020, until the arrival of the coronavirus pandemic initiated a period of chaos for the U.S. stock market, we find that with May 2022's estimated $62.90 for trailing year dividends per share, the corresponding value of the S&P 500 would be $3,777.

Or rather, that's what the math suggests would be a reasonable level for the S&P 500 had that relative period of order continued to the present. Since that value is below the current level of the index, this result suggests stock prices still have room to fall, but it's important to note that this level is neither a ceiling nor a floor. It simply represents the mean to which stock prices would revert during this particular previous relative period of order.

That mean level is visualized as the extended trajectory for this relative period of order in the chart above, where you can see the chaotic impact the arrival of the coronavirus pandemic had in March 2020, followed by the bubble inflated by the COVID stimulus programs of 2020 and President Biden's inflation-generating American Rescue Plan Act stimulus program of March 2021. That bubble entered its deflation phase after December 2021, which is still underway today.

With more than one previous relative period of order to choose from, there's a lot of room for interpretation. Other selectable options, such as the one for the early 1990s, may suggest the S&P 500 is greatly undervalued for the dividends per share you enter. One of the cool things about this tool is you can do the math for any level of trailing year dividends per share you choose, so you can find out how stock prices could alternatively been set during the days of the Dot Com Bubble, if that's your area of interest, or during any of the other periods in between. Go ahead and take the tool for a test drive to explore the world of alternate S&P 500 valuations!

Can you project where the S&P 500 could go during periods of chaos?

We know what you're thinking. Wouldn't it be nice if you could project what a reasonable level for the S&P 500 would look like during periods of chaos for the stock market? It would indeed, and we have you covered there as well.

Alternative Futures - S&P 500 - 2022Q2 with m=-2.5 from 20210616 - Snapshot on 20220518

If you know what the expectations are for changes in the growth rate of dividends at different points of time in the future, and you know how far into the future investors are focusing their forward-looking attention as they set current day stock prices, you can reasonably project the level for the S&P 500 even during periods of chaos in the stock market. It has been possible since April 2009 and became practical to accomplish after November 2009, when the CBOE introduced modern quarterly dividend futures for the S&P 500.

Why You Should Read Terrible Books

Alan Moore has written some highly influential works. Many of which have gone from the page to both the big and small screens, inspiring several generations of storytellers along the way.

He has some interesting advice for anyone seeing to become a good writer:

Alan Moore believes every aspiring writer should read terrible books. Watch and find out why this is an integral part of developing your own style as a writer.

Here's the less than one-and-a-half minute video, which is from Moore’s BBC Maestro storytelling course:

Now, if you're looking for inspiration for terrible books to read, we'll point you to a podcast we mentioned several weeks ago: 372 Pages We'll Never Get Back (Patreon for the freshest episodes, delayed episodes available wherever you get podcasts), which specializes in analyzing what makes the books they read bad while having a lot of fun doing it.

But if you want to read terrible books on your own and you're looking for a list of really badly written books to read, Wikipedia's "List of books considered the worst might serve up some inspiration for you.

How Gamestop’s Stock Price Was Squeezed

The story of how Gamestop (NYSE: GME) went from a value of $11.01 per share on 13 November 2020 to reach $325.00 per share on 29 January 2021 has become a stock market legend.

It has also become the subject of a fascinating academic study, where a new paper by Lorenzo Lucchini, Luca Maria Aiello, Laura Alessandretti, Gianmarco De Francisci Morales, Michele Starnini and Andrea Baronchelli investigated how social media contributed to the short squeeze that made GME into *the* prototype meme stock.

If you're not familiar with the story, here's the paper's summary of how the GME short squeeze was made, in which Reddit's r/wallstreetbets (WSB) plays a prominent role (we've added the bullet list formatting to make it easier to follow):

GameStop (GME) is a US video game retailer which was at the centre of the short squeeze in January 2021. The timeline of the events around the squeeze is summarized in table 1, and it unfolded as follows.

  • In 2019, Reddit user u/DeepFuckingValue entered a long position on GME, i.e. he bought shares of the GME stock, and started sharing regular updates in WSB.
  • On 27 October 2020, Reddit user u/Stonksflyingup shared a video explaining how a short position held by Melvin Capital, a hedge fund, could be used to trigger a short squeeze.
  • On 11 January 2021, GME announced a renewed Board of Directors, which included experts in e-commerce. This move was widely regarded as positive for the company, and sparked some initial chatter on WSB.
  • On 19 January, Citron Research (an investment website focused on shorting stocks) released a prediction that GME’s stock price would decrease rapidly.
  • On 22 January, users of WSB initiated the short squeeze.
  • By 26 January, the stock price increased more than 600%, and its trading was halted several times due to its high volatility. On that same date, business magnate Elon Musk tweeted ‘Gamestonk!!’ along with a link to WSB.
  • On 28 January, GME reached its all-time intra-day highest price, and more than 1 million of its shares were deemed failed-to-deliver, which sealed the success of the squeeze. A failure to deliver is the inability of a party to deliver a tradable asset, or meet a contractual obligation; a typical example is the failure to deliver shares as part of a short transaction.
  • On 28 January, the financial service company Robinhood, whose trading application was popular among WSB users, halted all the purchases of GME stocks.
  • On 1 and 2 February, the stock price declined substantially.

By the end of January 2021, Melvin Capital, which had heavily shorted GameStop, declared to have covered its short position (i.e. closed it by buying the underlying stock). As a result, it lost 30% of its value since the start of 2021, and suffered a loss of 53% of its investments, i.e. more than 4 billion USD.

While the paper's summary indicates a substantial decline in value, we'll point out that since it peaked at $325 per share, GME bottomed at $40.69 per share on 18 February 2022 before climbing back up to $300 per share on 8 June 2021, before dropping back toward the middle of that range. The following chart shows its stock price history:

GME Stock Price History: 12 October 2020 - 14 April 2022

That's all the "what happened", but it's the "why it happened" we find fascinating. The authors identify one key element in the postings of the WSB redditors that established their credibility, separating their postings from the ordinary run of the mill comments that dominate discussions on many other stock investing discussion sites, which they describe in the paper's introduction:

In this paper, we analyse discussions on WSB from 27 November 2020 to 3 February 2021 (table 1) and investigate how they translated into collective action before and during the squeeze that was initiated on 22 January and lasted until 2 February. Motivated by recent theoretical [10,11] and experimental [12] evidence that minorities of committed individuals may mobilize large fractions of a population [10,1315] even when they are extremely small [16], we investigate whether committed users on WSB had a role in triggering the collective action. To this aim, we operationalize the commitment of a user as an exhibited proof that the user has financial stakes in the asset.

We won't keep you in suspense. Here's the summary of what they found:

We show that a sustained commitment activity systematically pre-dates the increase of GameStop share returns, while simple measures of public attention towards the phenomenon cannot predict the share increase. Additionally, we also show that the success of the squeeze operation determines a growth of the social identity of WSB participants, despite the continuous flow of new users into the group. Finally, we find that users who committed early occupy a central position in the discussion network, as reconstructed by WSB posts and comments, during the weeks preceding the stock price surge, while more peripheral users show commitment only in the last phases of the saga.

The last part is to say that the early influencers who effectively established their credibility continued to be influential within the network. We think that continued influence is attibutable to their success, which had the short squeeze of GME's stock not occurred, would have led other WSB participants to discount the information value of their postings. People with opinions about a company's investment worthiness are a dime a dozen on a stock discussion board, but people who back up their talk with hard evidence of their bets that go on to pay off were granted credibility.

Much of the authors' study focuses on the dynamics between this "core" group of GME redditors and others who were on the periphery of the investing activity, which they describe as a "behavioural cascade" event. The core group attained a critical point of credibility, sweeping up peripheral redditors who transitioned from observers to participants as the short squeeze cascaded into a legendary event.


As for the hedge fund that lost billions on its attempted short of GME, the firm is considering returning what's left of the capital it controls to its remaining investors as its future with its current structure is in doubt. The fund lost 39% of its capital in 2021, with another 21% of losses to date in 2022. It's management would launch a new fund to replace it.


Lorenzo Lucchini, Luca Maria Aiello, Laura Alessandretti, Gianmarco De Francisci Morales, Michele Starnini and Andrea Baronchelli. From Reddit to Wall Street: the role of committed minorities in financial collective action. Royal Society Open Science. Volume 9, Number 4. 6 April 2022. DOI: 10.1098/rsos.211488.

Better Ways to Sort Out What the U.S. Treasury Yield Curve Is Saying

Part of the U.S. Treasury yield curve inverted and all we got was lousy analysis!

Examples of U.S. Treasury Yield Curve, Inverted and Normal

That's actually something of an understatement. There has been an explosion of reporting about the inversion of the U.S. treasury yield curve in recent weeks. If you read any of it, you likely found it leaves a lot to be desired. Here's a random selection of recent headlines:

It's not any better if you read what academic economists have been writing either, much of which has the intellectual consistency of muddled hash. In fact, if all that analysis were laid out end to end, the last thing you'd ever reach from reviewing it all is a conclusion. You'd think achieving some sort of clarity would be both desirable and a priority because the inversion of the Treasury yield curve is believed to portend recession in the future for the economy.

Part of the problem is because the U.S. Treasury yield curve has more than one part to it than can become inverted. A lot of people will focus on some select parts of it, without taking what's going on in the rest of it into account.

That realization lies behind some more interesting analysis by MetricT at r/dataisbeautiful that offers a path to reach the kind of conclusions you'd want to reach whenever the treasury yield curve becomes inverted. Here's that original analysis from 28 March 2022, which has been updated with charts showing yield curve data through 15 April 2022 (in addition to some other minor tweaks):

Mean Yield Spread across all US Treasury Maturities as a (slightly) better recession gauge than the 10y/2y and 10y/3m yield curve spreads

The US Treasury yield curve spread (most commonly the 10 yr/2 yr and 10 yr/3mo spreads) are popular gauges of incoming recession. But those measures aren't perfect. In particular:

  • There is a noticable false positive from Sep 1966 - Feb 1967 where the 10 yr/3 mo yield curve inverted but no recession followed.
  • A "is it or isn't it?" event in 1998 where the yield curve almost inverted before returning to normal. This caused a lot of consternation at the time until it was subsequently shown to be another false positive.
  • Another "is it or isn't it?" event in 2019 where the yield curve inverted, but pundits wondered if it "inverted enough" to trigger a recession. Narrator: It did...

I've been looking at ways to improve the traditional yield curve measures. A few months ago I posted R code to graph the percent of all yield curve spreads that are inverted, which made it much more obvious that a recession was the likely outcome in 2019.

So the idea occured to me: There are (at present) 55 different yield curve combinations. What would the average of all yield curve combinations look like? That should give us a better measure of how distorted the yield curve is than looking at a single pair of spreads.

As it turns out, the average does perform a bit more accurately than the 10y/2y and 10y/3m yield curves. In particular, it fails to invert in 1998, meaning our "is it or isn't it?" has a much clearer "no" answer. And it did invert during the similar "is it or isn't it?" event in 2019 and correctly predict a recession. So it sends a clearer signal than the better known 10y/2y and 10y/3m curves.

Graph 1:

Graph 1

Top: The US Treasury yield curve as of April 15 2022. A healthy yield curve should be upward sloping. Notice the obvious bear flattening between 3 yr <-> 10 yr Treasuries. There are already inversions between several longer-duration Treasuries (inverted points highlighted in red). There is currently a technical inversion in the 30yr/20yr curve due to a preference for 30 year Treasuries due to the relative newness of 20 yr Treasuries.

Middle: The usual 10y/2y and 10y/3m spread alongside the average yield spread for all maturity combinations. Notice that while the 10y/2y is rapidly nosediving (and getting a lot of press in doing so), the average is still relatively stable, though that may or may not last much longer. So keep an eye on things, but don't overreact just because the 10y/2y curve inverts.

Bottom: Shows the percent of all Treasury combinations that are inverted. It's graphed as a percent because the total number of maturities has changed over time (for instance, the Fed introduced 7 yr Treasuries in 2009), so graphing the percent allows you to do an apples-to-apples comparison. The color scheme is simply "blue if the average yield curve spread is < 0, red if it's > 0".

Graph 2:

Graph 2

Graphs the Federal Funds Rate since 1985 and highlights times when the average yield curve is inverted. As you can see, Fed tightening has come to a screeching halt almost immediately once the average YC is inverted, and quickly starts heading downward. It suggests the Fed is going to have great difficulty raising the Fed rate, as they probably only have a few months before the average inverts.

I'll clean the code up and eventually post it on my Github repo, though it will probably take a few days.

There are two bits of good news. First, MetricT's code is available! Second, through 15 April 2022, the average of all yield curve combinations hasn't changed the low probability of recession signal of MetricT's original analysis from 28 March 2022.

We're not the only ones who recognize there's a lot lacking in current day analysis of the treasury yield curve. For additional discussion, we'll recommend adding Scott Grannis' exploration of better measures of the yield curve to your reading list as well.

Previously on Political Calculations