From the Archives
The source material for my recent post on Rubbish Rallies.
Today’s Sunday Reads is going to be slightly different than our standard programming for a few reasons. The first is that I did not have as much time this week to focus on the Sunday Reads because I’m preparing for what is set to be a very busy (but exciting) upcoming week where I’ll be recording a Bloomberg Odd Lots podcast on the Spanish Flu / Black Death, recording the first piece of content for my online financial history course, and hosting the BlockWorks Group Webinar with Morgan Housel and Dan Rasmussen on Bear Market Rallies & Investor Amnesia. Exciting times!
However, there is also so much going on in the world that there was no way I could fail to deliver the historical goods on this beautiful Sunday morning. We have shares of bankrupt companies soaring, the number of bankruptcies rising, what looks like the potential beginning of a COVID-19 second wave, and a company with no product boasting a market capitalization of $25 Billion ($NKLA). So, this week I’m going to re-link some important pieces that I’ve previously shared that touch upon a few of these major themes and recent developments, including:
- Booming Speculation
- Rubbish Rallies
- Bankruptcy and Corporate Bond Defaults
- The Political Implications of COVID-19
- COVID-19 and A Second Wave?
Also, since it’s so relevant to the crazy behavior of markets over recent weeks, I’ve included my intro to the recent Sunday Reads I posted on Speculative Booms:
Speculation. For centuries the speculator has been looked down upon by society and the purportedly more ‘respectable’ class known as ‘investors’. While many are familiar with the comparison of Investors and Speculators popularized by Benjamin Graham in The Intelligent Investor, this divide stretches hundreds of years (if not thousands). In fact, the book provided above (written in 1885) in From the Archives includes a chapter titled The Speculator vs. The Investor. However, an even earlier example of looking down upon the speculator is detailed below.
Early instances of anti-speculator sentiment can be found in the 17th century, where market participants on the Amsterdam Stock Exchange referred to the practice of speculating on assets that you did not own as windhandel (wind trading).
As Jason Zweig describes it:
‘The Dutch were also familiar with the word “bubble” (which they presumably borrowed from the English), as you can see here. It was closely related to windhandel, or “dealing in wind,” the Dutch expression for trading in securities that weren’t in the speculator’s possession, as short-sellers do today – and did back then, too. (Windhandel also referred to trading in derivatives like options and futures instead of common stock or physical commodities.) Wind trading is first recorded shortly after the Dutch East East India Company was founded in 1602…
Joseph Penso de la Vega, who in 1688 wrote what is commonly regarded as the world’s earliest book about the stock market, Confusion de Confusiones, described a stratagem used by short-sellers at the Amsterdam exchange:
“they offer for the stocks more than the price of the day (what we call ‘inflating’ the price). They influence the price this way in order to sell [short] at the higher figure and thus to gain in the end. God with one breath breathed life into Adam, whereas the bears take the life of many people by inflating the price [of the shares]…”
This image – pumping up prices by puffing them full of air – is the most logical and likely derivation of the financial term “bubble”…
After several bubbles blew up and burst almost simultaneously, windhandel acquired a more scatological meaning. An explicit Dutch engraving from 1720, “Arelquyn Actionist,” or “Harlequin the Stockbroker,” shows securities dealers selling their offerings to a speculative mob through a unique distribution system: by breaking wind. Customers snatch stock certificates from the streams of gas blasting out of the brokers’ posteriors – a fitting metaphor for investments that ended up too foul to touch.’
What Drives Speculation?
While no period in history is exactly the same, there are often identifiable themes that tend to repeat themselves.
History is riddled with evidence of technological innovations that permanently changed society, with the internet and smartphone are obvious examples in recent decades.
As discussed in the article The Telegraphic Transmission of Financial Asset Prices and Orders to Trade below, the Telegraph had a similarly profound impact:
‘Large scale manufacturers such as James Duke and Andrew Carnegie used the telegraph to coordinate the inflow of raw materials and outflow of manufactured product in a manner that increased capacity utilization rates and amortized the holding costs of this capital over a larger flow volume of output. In wholesale and retail distribution the telegraph net permitted the increase in the rate of inventory turnover that made possible the advent of mass merchandising in the form of the department store and mail order house.
Similarly, the telegraph revolutionized the distribution of fresh meat and vegetables at a relatively early time in the nation’s history. Just in time inventory control, and other advances in what is known today as supply chain management, often popularly attributed to the Japanese, were in fact pioneered by Americans in the late nineteenth century. Here were real payoffs to the investment in the telegraph. From these standpoints, one can view the device as an archetypal physical capital saving innovation of a type to which economic historians have paid relatively little attention.’
Yet like the internet and smartphone, there were repercussions from the telegraph’s invention. Regarding investor behavior and speculation, the increased flow of information and democratized access to financial markets made it easier than ever to make speculative bets.
Simply put, speculation increases when the barriers to speculating are reduced or removed by technology. For instance, the ability to place buy/sell orders through an app on our phone in just a few clicks makes it all too easy for panicked investors to overreact.
Until recently, however, there was still a financial cost to placing these trades on your phone in the form of trade commissions. As most readers will know, this changed last year with the introduction of commission-free trading on almost all major brokerage platforms. The immediate impact of this decision on investor’s behavior is abundantly clear in the chart below from a recent Wall Street Journal article:
By removing the financial barrier to over-trading, speculation exploded. Not only did this move encourage more speculative behavior for existing investors, but also provided access to financial markets for a large number of first-time investors. The WSJ article stated:
‘TD Ameritrade said last week that retail clients opened a record 608,000 new funded accounts in the quarter ended March 31, with more than two-thirds of those opened in March. E*Trade saw a net gain of 363,000 accounts in the quarter—a company record—around 90% of which were retail. Charles Schwab Corp. reported a record 609,000 new brokerage accounts in the quarter, including individuals’ self-directed accounts and those managed by financial advisers.’
That said, the articles in today’s Sunday Reads will focus on the impact of a previous revolutionary technology on financial markets, and how investor’s behavior was altered.
Credit & Low Yields
One of the most common phenomenons in financial history is ‘reaching for yield’, where investors needing a source of income are forced into higher yielding-but riskier-instruments as a result of low bond yields. A few well-known examples of this are found in the Panic of 1825 and The Panic of 1890, which both stemmed from the particularly low yield on British Consols. In both periods, British investors poured their funds into foreign debt that offered yields up to 7 or 8 times higher than British Consols.
In these low yield environments, where investors are pushed into riskier assets to obtain their desired yield, fraudulent behavior abounds as scam artists seize upon the heightened levels of speculation. A similar dynamic unfolds when access to cheap credit fuels a boom in risky new ventures and questionable business practices. For example, the 17th century IPO Bubble in London saw 70% of the publicly listed stocks operating in 1694 get wiped out by the turn of the century.
Now let’s dive in!
My first new article on Investor Amnesia in almost a year! This post looks at a rally in the 19th century that is even more ludicrous and illogical than the recent boom in Hertz shares. The mania took place in 1825, a notorious year for bubbles, scams, and frauds:
‘From this time ‘bubble schemes came out in shoals like herring from the Polar Seas’, illustrated by the fact that the number of bills coming before Parliament for forming new companies shot up from 30 in March to 250 in April.
All manner of companies were ﬂoated. Many were related to Assurance; there were also some novel ventures such as the Metropolitan Bath Company which aimed to pump seawater to London so that poor Londoners could experience seawater bathing, and the London Umbrella Company which intended to set up umbrella stations all over the capital.
Many ventures, however, were arrant swindles designed to test investor credulity. Such examples include the Resurrection Metal Company, which intended to salvage underwater cannonballs that had been used at Trafalgar and other naval battles, and a company (possibly a parody) which was set up ‘to drain the Red Sea, in search of the gold and jewels left by the Egyptians, in their passage after the Israelites’.”
‘We study the relationship between credit, stock trading and asset prices. There is a wide array of channels through which credit provision can fuel stock prices. On one extreme, cheap credit reduces the cost of capital (discount rate) and boosts prices without trading or wealth transfers. On the other extreme, extrapolators use credit to ride a bubble and lose money. We construct a novel database containing every individual stock transaction for three major British companies during 1720 South Sea Bubble. We link each trader’s stock transactions to daily margin loan positions and subscriptions of new share issues. We find that margin loan holders are more likely to buy (sell) following high (low) returns. Loan holders also sign up to buy new shares of overvalued companies and incur large trading losses as a result of the bubble.’
As a general rule: When credit is cheap, speculators are a dime a dozen.
For example, the chart below exhibits the Bank of England’s gross loan issuance in 1720, the year of the South Sea Bubble:
Looking into these loans further, the authors show that 79% of these loan holders were taking speculative positions in the popular stocks of that time: The South Sea Company, Royal African Company, and East India Company.
Knowing that there was rampant levels of speculation in 1720 London, this paper analyzes the behavior of speculators through an exciting new dataset:
‘We construct a novel database containing every individual stock transaction for three major British companies during 1720 South Sea Bubble. We link each trader’s stock transactions to daily margin loan positions and subscriptions of new share issues.’
Their results show that these speculative margin loan holders largely follow the herd by buying at the top, and selling out at the bottom. In addition, these loan holders were twice as likely to ‘buy new shares of overvalued companies’ at peak prices. We see similar scenarios unfold in modern times with retail investors piling into flashy but overpriced IPOs.
The outcome of all this is predictable: poor performance.
‘Even without taking returns on these share subscription positions into account, loan holders incur large trading losses. A margin loan holder realizes a 14 to 23 percentage point lower return than the average investor.‘
In short, margin holders buy and sell at exactly the wrong time, purchase new offerings at peak prices, and generated returns noticeably lower than the average investor. So who were these margin loan holders?
‘Less experienced individuals, investors who trade a lot and male investors are more likely to take margin loans. In the current finance literature, male investors and frequently trading investors are often associated with poor trading performance.’
The authors’ conclude the article by writing:
‘We collect every single stock transaction with buyer and seller identities for three large British companies during the classical 1720 South Sea Bubble. In May 1720, the Bank of England grants its shareholders the right to borrow cash by collateralizing their shares. Each investor can borrow up to the nominal value of the share and loans are recorded in the stock ledger books of the Bank. The meticulous documentation of the transactions allows us to link, on a daily basis, each investor’s share trading to her loan positions. Our data documents the daily equity transactions of about 50% of the British market capitalization over the course of the bubble and five years before.
We find that the marginal borrower displays speculative trading behavior. First, we document that a loan holder acts as an extrapolator by buying stocks that have experienced high returns in the recent past. Second, we find that borrowers realize lower returns than investors without a loan. Third, we find that margin loan holders are more likely to subscribe to new share offerings at peak prices. This strategy is extremely risky and we can ex-post determine that it leads to negative returns. Finally, we show that there is a positive relation between loan holder buying pressure and stock prices during the bubble.’
For those seeking a more U.S. focused article on the impact of Spanish Influenza, this paper from the Federal Reserve Bank of St. Louis is for you. You should take the time to read the entire paper, but their research concludes:
“Most of the evidence indicates that the economic effects of the 1918 influenza pandemic were short-term. Many businesses, especially those in the service and entertainment industries, suffered double-digit losses in revenue. Other businesses that specialized in health care products experienced an increase in revenues. Some academic research suggests that the 1918 influenza pandemic caused a shortage of labor that resulted in higher wages (at least temporarily) for workers, though no reasonable argument can be made that this benefit outweighed the costs from the tremendous loss of life and overall economic activity. Research also suggests that the 1918 influenza caused reductions in human capital for those individuals in utero during the pandemic, therefore having implications for economic activity occurring decades after the pandemic.”
However, some states were hit much harder than others:
In one of the most interesting sections of the paper, the authors provide excerpts from local newspapers describing the economic impact of influenza in their community. The quotes below are all taken from a newspaper article in Little Rock, Arkansas:
- “How Influenza Affects Business.” (The Arkansas Gazette, Oct. 1918)
- Merchants in Little Rock say their business has declined 40 percent. Others estimate the decrease at 70 percent.
- The retail grocery business has been reduced by one-third.
- One department store, which has a business of $15,000 daily ($200,265 in 2006 dollars), is not doing more than half that.
- Bed rest is emphasized in the treatment of influenza. As a result, there has been an increase in demand for beds, mattresses and springs.
- Little Rock businesses are losing $10,000 a day on average ($133,500 in 2006 dollars). This is actual loss, not a decrease in business that may be covered by an increase in sales when the quarantine order is over. Certain items cannot be sold later.
- The only business in Little Rock in which there has been an increase in activity is the drug store.
This piece on ticker subscriptions and price efficiency is one of the most fascinating articles I’ve read in months because of its implications for markets today, particularly as it relates to passive investing and price discovery.
While the parallel is not immediately obvious, the period covered in this paper and recent decades both involve the rise of a new ‘technology’ with the potential to affect pricing efficiency and co-movements in prices.
For example, this quote from Michael Green in a recent article on passive investing states:
‘Each new dollar invested into passive index funds must purchase the securities in the benchmark index. These purchases exert an inexorable influence on the underlying securities. Per Sharpe’s own work, these are not passive investors – they are mindless systematic active investors with zero interest in the fundamentals of the securities they purchase.
If incremental investor dollars were increasingly flowing into market capitalization indices, we would expect to see two clear phenomena. First, we would expect to see momentum rewarded as securities that rose in price would capture an increasing fraction of each incremental investment dollar. Second, we would expect to see a rise in correlation as securities become increasingly traded as a group.’
In that same vein, the authors of this article looks at some of these same issues in relation to the ticker:
‘How does access to information affect price efficiency? We address this question by studying the stock ticker; a device that disseminated price changes to brokerage offices with a ticker subscription. We find that an increased number of ticker subscriptions in a state strengthened the return continuation and return co-movement of firms headquartered in the state. Therefore, the increased dissemination of price changes appears to have decreased price efficiency by increasing uninformed trend chasing. Our results challenge the assumption that greater access to information improves price efficiency.‘
The article specifically looks at ‘return co-movement to determine whether uninformed trading explains return continuation.’
‘The positive β1 coefficients in Panel A of Table 7 indicate that an increased number of ticker subscriptions in a state increases the average local beta of firms in the state, which indicates greater return co-movement among local stocks… This positive coefficient indicates that greater price dissemination in a state is associated with higher return co-movement in the state.’
Their analysis also yielded an interesting insight on ‘local’ investment biases:
‘The positive state-level relation between ticker subscriptions and return co-movement also suggests that the stock ticker did not mitigate local investment bias. Instead, investors appear to have continued to focus their trading on “familiar” local firms despite gaining exposure to non-local firms via the stock ticker. Note that the ticker subscription did not confer any informational advantage that would justify the continuation of local investment bias.’
The authors conclude:
‘In summary, recall that the stock ticker disseminated price changes, not information on fundamentals. Furthermore, any decrease in trading costs associated with ticker subscriptions is predicted to increase informed trading by facilitating arbitrage activity and therefore lowering return co-movement. Overall, the positive relation between ticker subscriptions and return co-movement indicates that greater uninformed trend chasing, not greater liquidity, explains the positive impact of ticker subscriptions on return continuation.‘
There is an even more direct linkage between the Ticker and Passive Funds: Cost. Tell me this doesn’t sound familiar:
‘Ticker subscriptions had an inverse relation with the cost of transmitting data to the ticker’s location. We find that lower operating costs for a stock ticker increased ticker subscriptions and strengthened both the return continuation as well as the return co-movement of firms in the state. Intuitively, lower data transmission costs reduced price efficiency as the associated increase in investor access to price changes increased trend chasing.’
In other words, lower costs increased the prevalence of tickers, which increased uninformed trading, which decreased price discovery and increased co-movement in returns.
You can see how easy it would be for one to apply this logic to passive funds today. With access to low-cost (or even free) passive ETFs or mutual funds, assets in passive vehicles have exploded. In turn, critics argue that this has produced a ‘momentum’ effect and increased in return co-movements. Food for thought.
‘Overall, the instrumental variable procedure confirms that increasing the access of investors to price changes decreases price efficiency by increasing trend chasing.’
Definitely take the time to read this article.
(Above Graph: ‘Dots represent city-level 1918 influenza mortality and manufacturing employment growth around the 1918 Flu Pandemic. Green (red) dots are cities with non-pharmaceutical intervention (NPI) days above (below) the median fall 1918.’)
As the number of COVID-19 cases begin to rise again in some of the states that had reopened, the most important question on everyone’s mind is if we are starting to see the start of Wave 2. This is an alarming prospect because in the case of the Spanish Flu, it was the second wave that was the worst of all three waves. That said, it seems like a good time to re-share this piece on public health interventions and the economy.
What is the tradeoff between public health policy and economic health? Scores of retail businesses and small business owners are getting crushed by these guidelines, and in many instances it is leading to social unrest. This paper looks at the historical evidence for how public health interventions affect the economy:
‘What are the economic consequences of an influenza pandemic? And given the pandemic, what are the economic costs and benefits of non-pharmaceutical interventions (NPI)? Using geographic variation in mortality during the 1918 Flu Pandemic in the U.S., we find that more exposed areas experience a sharp and persistent decline in economic activity. The estimates imply that the pandemic reduced manufacturing output by 18%. The downturn is driven by both supply and demand-side channels. Further, building on findings from the epidemiology literature establishing that NPIs decrease influenza mortality, we use variation in the timing and intensity of NPIs across U.S. cities to study their economic effects. We find that cities that intervened earlier and more aggressively do not perform worse and, if anything, grow faster after the pandemic is over. Our findings thus indicate that NPIs not only lower mortality; they may also mitigate the adverse economic consequences of a pandemic.‘
The Wall Street Journal recently wrote about the boom in U.S. bankruptcies:
‘Corporate bankruptcies spiked during May as the coronavirus pandemic slammed the U.S. economy, pushing the number of filings to levels recorded in the wake of the 2007-09 recession.
U.S. courts recorded 722 businesses nationwide filing for chapter 11 protection last month, a yearly increase of 48%, according to figures from legal-services firm Epiq Global. In May 2019, a total of 487 businesses filed for that type of bankruptcy, which lets corporations resolve their financial problems and continue operating.’
As this uptick in bankruptcies is likely to persist, it is worth looking at the 150-year history of corporate bond default risk.
“We study corporate bond default rates using an extensive new data set spanning the 1866–2008 period. We find that the corporate bond market has repeatedly suffered clustered default events much worse than those experienced during the Great Depression. For example, during the railroad crisis of 1873–1875, total defaults amounted to 36 percent of the par value of the entire corporate bond market. We examine whether corporate default rates are best forecast by structural, reduced-form, or macroeconomic credit models and find that variables suggested by structural models outperform the others. Default events are only weakly correlated with business downturns. We find that over the long term, credit spreads are roughly twice as large as default losses, resulting in an average credit risk premium of about 80 basis points. We also find that credit spreads do not adjust in response to realized default rates.”
In this article, there is a section on the Panic of 1873 that offers interesting parallels with markets today. The 1870s were highlighted by the exciting and rapid growth of new technology: railroads. With this exciting technology came booming debt markets:
‘The growth in economic activity was accompanied by a rapid expansion in the corporate bond market. For example, the number of bond issuers listed in the Commercial and Financial Chronicle was 158 in 1866, but quickly reached 421 by 1872. The Commercial and Financial Chronicle from this period is often filled with enthusiastic accounts about the promise of new technology:
‘Every well-built railroad if suitably located becomes a productive machine which adds to the wealth of the whole country… Our new railroads increase the value of farms and open new markets for their products. They lessen the time and cost of travel. They give a value to commodities otherwise almost worthless. They concentrate population, stimulate production and raise wages by making labor more efficient. Our existing railroads are computed to create more wealth every year than is absorbed for the construction of new railroads.” (January 11, 1873).’
Yet, eventually, this exuberance must face reality.
‘However, later in the same year there was a major panic which led to a default rate of 14.3 percent in 1873. Contrast the buoyant spirit reflected in the previous quote with that evidenced by the following quote from the Commercial and Financial Chronicle exactly one year later.
“After such a panic as has, the past year, swept over the country, it becomes a kind of melancholy pleasure to look over the field and find that there are not quite so many dead and wounded lying about as was anticipated. It was a fearful storm while it lasted, and although every one of course can say now that he knew it was coming, yet the real truth is, its breaking was terribly sudden and unexpected… There are few people who allow themselves to remember long the lessons experience would teach them. If this were not so, there would be many less failures in the world… Almost all felt they were carrying too much debt; they would henceforth be out of it. There are now, however, very evident signs that these resolutions have been mostly forgotten. Over-trading, as it is called, is an evil that has ever existed, and pretty much the same epitaph can be written above each business prostration—here lies the result of an attempt to do too much with too little capital. Must history necessarily repeat itself?” (January 10, 1874).”‘
There is no shortage of political divisiveness and anger in the United States. Add in a recession, market crash, and global pandemic? We’re in store for a political nightmare and the presidential election is fast approaching. Remember that whole thing?
In addition to the existing partisanship rampant across America, which can affect how one views Trump’s response to the crisis, the bailout of industries like Airlines have stirred some of the anti-executive / anti-Wall Street sentiments prevalent in the Great Financial Crisis of 2008. The 2008 crisis spurred the Occupy Wall Street movement, the rise of the Tea Party, and some would argue global populism in general.
This article provides helpful context on the historical relationship between political movements and financial crises / market crashes. Across 20 developed countries, this paper assesses the political consequences of financial crises over the last 140 years through studying more than 800 general elections. Their analysis finds that ‘On average, far-right parties increase their vote share by 30% after a financial crisis.’
Equally interesting is their conclusion that only Financial Crises have this large impact on the political process:
‘Financial crises are politically disruptive, even when compared to other economic crises. Indeed, we find no (or only slight) political effects of normal recessions and different responses in severe crises not involving a financial crash. In the latter, right wing votes do not increase as strongly and people rally behind the government. In the light of modern history, political radicalization, declining government majorities and increasing street protests appear to be the hallmark of financial crises.’
In so far as people blame central banks for exacerbating inequality through quantitative easing, the authors end their article by acknowledging this argument:
‘As a consequence, regulators and central bankers carry a big responsibility for political stability when overseeing financial markets. Preventing financial crises also means reducing the probability of a political disaster.’
Now that the NBER reported the United States officially entered a recession in February, what are the implications for the presidential election in November? This paper analyzes almost 200 years of data to study the relationship between elections and the U.S. economy:
‘The influence of the economy on presidential elections has been well documented. However, citing the substantial growth of the federal government and the enactment of legislation such as the Employment Act of 1946, the majority of the literature focuses on the effect of the economy only on modern presidents. While some scholars study the influence of the economy on presidents starting in 1913 or even the late nineteenth century, few, if any, scholars study the effect of the economy on earlier presidents. This paper examines the extent to which the U.S. economy affected presidential election from the early 19th century to the present day. Arguing that the federal government’s role in the national economy changed dramatically during the middle of the twentieth century, we present evidence that price stability was positively associated with incumbent party electoral success from 1828 to 1948 and that income growth was directly related to incumbent party electoral success in the subsequent years. While the nature of the economic effects on presidential elections have varied over time, economic conditions have clearly played a role in national elections since the early years of the American republic.‘
Interestingly, the evolving role of the Federal Reserve suggests that there may have been a shift in exactly what evidence supported a ‘strong economy’, and how this helped/hurt the incumbent during elections:
‘Though the Federal Reserve System was established in 1913, it did not enjoy its current level of policymaking independence until the Accord with the Treasury Department in 1951 . Prior to the Accord, the Federal Reserve helped to keep interest rates low in order to support government bond prices as was desired by the Treasury Department. However, after the war, inflation began to increase and the Federal Reserve‘s purchase of Treasury issues to maintain government bond prices led to more inflation… In other words, the operation of the Federal Reserve was no longer fully tied with the goals of the Treasury. Thus, until 1952, the executive branch had significantly more control over monetary policy—and the value of the currency—than it did following the Accord.‘
Therefore, there seem to be two separate periods worth studying: Pre-1952 and Post-1952.
‘The concomitant transformation of the position of the federal government in the national economy and the increase in the independence of the Federal Reserve suggests the following hypotheses related to the role of economic circumstances in presidential elections:
- Prior to 1952, price stability was positively associated with the share of the vote received by the incumbent president (or his fellow partisan).
- From 1952 to the present, income growth was positively associated with the share of the vote received by the incumbent president (or his fellow partisan).’
The findings in this paper largely support these two hypotheses.
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