# Negative derivatives pricing

In my “Properties of Stock Options” lecture note, a particularly important theorem relates to the notion that derivatives (options) prices must be non-negative.  Interestingly, back in April 2020, prices for oil futures contracts actually turned negative; see the Wall Street Journal article entitled “U.S. Oil Costs Less Than Zero After a Sharp Monday Selloff” (an ungated PDF version is available at https://bit.ly/oilpriceshock). Quoting from that article, “The unusually large difference in price between oil for delivery in May and later has traders filling up tankers and setting them adrift.” Basically, if you had the means to store oil in the meantime, (e.g., offshore in a very large crude carrier) it made a lot of financial sense to be paid to assume ownership of the (negatively priced) May 2020 contract, and sell a later dated futures contract at which time you could deliver the goods! Apparently, somewhere off the coast of South Africa was an especially popular place to anchor due to its relatively equidistant access to markets in Asia, Europe, and the Americas.

In closing, the following related video from wsj.com is well worth 95 seconds of everyone’s time!

U.S. oil futures plunged below zero for the first time in history, signaling the little storage capacity there is. WSJ’s Spencer Jakab explains how we got here and what to expect next.

# A Random Walk Down Wall Street

If you were to read only one book about finance, it would have to be “A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing” by Burton G. Malkiel. Malkiel’s book (now in its 12th edition) provides a compelling argument in favor of efficient markets theory and investing in (passively managed) index funds.

The efficient market theory implies that stock prices follow a random walk. These ideas were originally conceived of by Professors Paul Samuelson and Eugene Fama in the 1960s, and subsequently popularized by folks like Professor Malkiel. In Finance 4366, we rely extensively upon the notion that prices of speculative assets (e.g., stocks, bonds, commodities, foreign exchange, etc.) follow random walks as we consider the technical details associated with pricing and hedging risk using financial derivatives.

# The Real Force Driving the GameStop Revolution

Jason Zweig’s Intelligent Investor article referenced below, entitled “The Real Force Driving the GameStop Revolution” should be required reading for all students of finance. Among other things, the article provides its readers much needed historical context for last week’s GME, AMC, and Blackberry bubbles!
wsj.com
Individual traders banded together this past week to move markets like never before. But the buildup to this remarkable moment has been happening for decades.

# The 17 equations that changed the course of history (spoiler alert: we use 4 of these equations in Finance 4366!)

I especially like the fact that Ian Stewart includes the famous Black-Scholes equation (equation #17) on his list of the 17 equations that changed the course of history; Equations (2), (3), (7), and (17) play particularly important roles in Finance 4366!

From Ian Stewart’s book, these 17 math equations changed the course of human history.

# Calculus, Probability and Statistics, and a preview of future topics in Finance 4366

Probability and statistics, along with the basic calculus principles covered last Thursday, are foundational for the theory of pricing and managing risk with financial derivatives, which is what this course is all about. During yesterday’s class meeting, we introduced discrete and continuous probability distributions, calculated parameters such as expected value, variance, standard deviation, covariance, and correlation, and applied these concepts to measure expected returns and risks for portfolios comprising risky assets. During tomorrow’s class meeting, we will take a deeper dive into discrete and continuous probability distributions, in which the binomial and normal distributions will be showcased.

On Tuesday, February 2, we will introduce and describe the nature of financial derivatives, and motivate their study with examples of forwards, futures, and options. Derivatives are so named because they derive their values from one or more underlying assets. Underlying assets typically involve traded financial assets such as stocks, bonds, currencies, or other derivatives, but derivatives can derive value from pretty much anything. For example, the Chicago Mercantile Exchange (CME) offers exchange-traded weather futures and options contracts (see “Market Futures: Introduction To Weather Derivatives“). There are also so-called “prediction” markets in which derivatives based upon the outcome of political events are actively traded (see “Prediction Market“).

Besides introducing financial derivatives and discussing various institutional aspects of markets in which they are traded, we’ll consider various properties of forward and option contracts, since virtually all financial derivatives feature payoffs that are isomorphic to either or both schemes. For example, a futures contract is simply an exchange-traded version of a forward contract. Similarly, since swaps involve exchanges between counter-parties of payment streams over time, these instruments essentially represent a series of forward contracts. In the option space, besides traded stock options, many corporate securities feature “embedded” options; e.g., a convertible bond represents a combination of a non-convertible bond plus a call option on company stock. Similarly, when a company makes an investment, so-called “real” options to expand or abandon the investment at some future is often present.

Perhaps the most important (pre-Midterm 1) idea that we’ll introduce is the concept of a so-called “arbitrage-free” price for a financial derivative. While details will follow, the basic idea is that one can replicate the payoffs on a forward or option by forming a portfolio comprising the underlying asset and a riskless bond. This portfolio is called the “replicating” portfolio, since, by design, it replicates the payoffs on the forward or option. Since the forward or option and it’s replicating portfolio produce the same payoffs, then they must also have the same value. However, suppose the replicating portfolio (forward or option) is more expensive than the forward or option (replicating portfolio). If this occurs, then one can earn a riskless arbitrage profit by simply selling the replicating portfolio (forward or option) and buying the forward or option (replicating portfolio). However, competition will ensure that opportunities for riskless arbitrage profits vanish quickly. Thus the forward or option will be priced such that one cannot earn arbitrage profit from playing this game.

# Also featured as one of “50 Things That Made the Modern Economy”: The Index Fund

Besides insurance, Tim Harford also features the index fund in his “Fifty Things That Made the Modern Economy” radio and podcast series. This 9-minute long podcast lays out the history of the development of the index fund in particular and the evolution of so-called passive portfolio strategies in general. Much of the content of this podcast is sourced from Vanguard founder Jack Bogle’s September 2011 WSJ article entitled “How the Index Fund Was Born” (available at https://www.wsj.com/articles/SB10001424053111904583204576544681577401622). Here’s the description of this podcast:

“Warren Buffett is the world’s most successful investor. In a letter he wrote to his wife, advising her how to invest after he dies, he offers some clear advice: put almost everything into “a very low-cost S&P 500 index fund”. Index funds passively track the market as a whole by buying a little of everything, rather than trying to beat the market with clever stock picks – the kind of clever stock picks that Warren Buffett himself has been making for more than half a century. Index funds now seem completely natural. But as recently as 1976 they didn’t exist. And, as Tim Harford explains, they have become very important indeed – and not only to Mrs. Buffett.”

Warren Buffett is one of the world’s great investors. His advice? Invest in an index fund

# Insurance featured as one of “50 Things That Made the Modern Economy”

From November 2016 through October 2017, Financial Times writer Tim Harford presented an economic history documentary radio and podcast series called 50 Things That Made the Modern Economy. This same information is available in book form under the title “Fifty Inventions That Shaped the Modern Economy“. While I recommend listening to the entire series of podcasts (as well as reading the book), I would like to call your attention to Mr. Harford’s episode on the topic of insurance, which I link below. This 9-minute long podcast lays out the history of the development of the various institutions which exist today for the sharing and trading of risk, including markets for financial derivatives as well as for insurance.

“Legally and culturally, there’s a clear distinction between gambling and insurance. Economically, the difference is not so easy to see. Both the gambler and the insurer agree that money will change hands depending on what transpires in some unknowable future. Today the biggest insurance market of all – financial derivatives – blurs the line between insuring and gambling more than ever. Tim Harford tells the story of insurance; an idea as old as gambling but one which is fundamental to the way the modern economy works.”

# Bullish Stock Bets Explode as Major Indexes Repeatedly Set Records

This is a fascinating WSJ  article about recent (historically unprecedented) trading volumes in options markets. The article features a 21-year-old student at Syracuse University named Ben Austin, who apparently “… primarily trades calls to position for big events that have the potential to lift stocks”, and attributes the following quote to Mr. Austin: “There’s way more potential for higher gains in a shorter amount of time.” While this is technically correct (after all, as we shall soon learn in Finance 4366, call options represent leveraged bets on stocks), there’s also way more potential for larger losses in a shorter amount of time, particularly since Mr. Austin is probably not hedging his options positions with positions in the stocks against which the call options are written.
wsj.com
“Options activity in January is building on 2020’s record volumes in the latest sign of optimism.”

# On the ancient origin of the word “algorithm”

The January 26th assigned reading entitled “The New Religion of Risk Management” (by Peter Bernstein, March-April 1996 issue of Harvard Business Review) provides a succinct synopsis of the same author’s 1996 book entitled “Against the Gods: The Remarkable Story of Risk“. Here’s a fascinating quote from page 33 which explains the ancient origin of the word “algorithm”:

“The earliest known work in Arabic arithmetic was written by al­Khowarizmi, a mathematician who lived around 825, some four hun­dred years before Fibonacci. Although few beneficiaries of his work are likely to have heard of him, most of us know of him indirectly. Try saying “al­Khowarizmi” fast. That’s where we get the word “algo­rithm,” which means rules for computing.”

Note: The book cover shown above is a copy of a 1633 oil-on-canvas painting by the Dutch Golden Age painter Rembrandt van Rijn.

# On the relationship between the S&P 500 and the CBOE Volatility Index (VIX)

Besides going over the course syllabus during the first day of class on Tuesday, January 19, we will also discuss a particularly important “real world” example of financial risk. Specifically, we will look at the relationship between stock market returns (as indicated by daily percentage changes in the SP500 stock market index) and stock market volatility (as indicated by daily percentage changes in the CBOE Volatility Index (VIX)):

As indicated by this graph from page 22 of the lecture note for the first day of class, daily percentage changes on closing prices for VIX (which is the x-axis variable) and the SP500 (which is the y-axis variable) are strongly negatively correlated. The blue points represent 7,712 daily observations on these two variables, spanning the time period from January 3, 1990, through August 10, 2020. When we fit a regression line through this scatter diagram, we obtain the following equation:

${R_{SP500}} = 0.0594 - 0.1126{R_{VIX}}$,

where ${R_{SP500}}$ corresponds to the daily return on the SP500 index and ${R_{VIX}}$ corresponds to the daily return on the VIX index. The slope of this line (-0.1156) indicates that on average, daily VIX returns during this time period were inversely related to the contemporaneous daily return on the SP500; i.e., when volatility, as measured by VIX, went down (up), then the stock market return as indicated by SP500 typically went up (down). Nearly half of the variation in the stock market return during this time period (specifically, 48.75%) can be statistically “explained” by changes in volatility, and the correlation between ${R_{SP500}}$ and ${R_{VIX}}$ comes out to -0.698. While a correlation of -0.698 does not imply that ${R_{SP500}}$ and ${R_{VIX}}$ always move in opposite directions, it does suggest that this will be the case more often than not. Indeed, closing daily returns on ${R_{SP500}}$ and ${R_{VIX}}$ during this period moved inversely 78.62% of the time.