The Misbehavior of Markets – Exclusive Interview w/ Co-Author Richard Hudson

We’re excited and honored to have a very special guest this week on the podcast, Richard Hudson, co-founder of the London and Brussels-based Science Business Publishing Ltd. He’s the co-author of The (mis)Behavior of Markets: A fractal view of risk, ruin & reward, which he wrote with famed Yale/IBM mathematician Benoit Mandelbrot. Our discussion, frankly, should be required listening for any investor and was recorded in January of 2020 immediately preceding the market crash that occurred just weeks later.

The Misbehavior of Markets

  • The reason people lose money in markets is that they underestimate the risk.
  • The mathematical and financial models that are most commonly used by banks and investment firms around the world are based on faulty assumptions.
  • Their assumptions are flawed and underestimate the potential of major market moves–crashes or booms. Extreme market movements happen much more frequently than the financial models suggest. 

Why Models Haven’t Changed

  • Financial models remain the same–partly because of convenience and partly because, for the most part, during most trading days, these models work.
  • However, in crashes and booms, the models fall apart.
  • These outlier events do not follow the normal path of the models.
  • Markets can be irrational and go beyond models in both directions.

The 2008 Market Crash

  • This problem went on, economically, in Europe for a decade.
  • One result of 2008 was the recognition of the need to improve financial market research by the public sector.
  • Ultimately, if we understand this very volatile system, perhaps we can control it better and, therefore, reduce the harm that it causes when it all blows up.

Market Memory

  • Standard financial models assume that there is no market memory, that from one day to the next, from one trade to the next, it’s just a coin toss.
  • The model assumes that price movements are independent of one another.
  • However, even anecdotally, we know that’s not true — there is a dependence between price movements of successive trading days.
  • Mandelbrot took this a little further using his fractal geometry and hypothesized that there is something called long memory — things that might have happened 20 years ago in the market still have a very faint echo later on.

The Cotton Market Example

  • From Mandelbrot’s research, he determined that when there is a small cause, then you can have a big effect–essentially a feedback loop.
  • In the cotton market, he found that this dynamic, although prices varied over time, was like a fingerprint. Each market has its own unique fingerprint.
  • The cotton market had its own characteristics of volatility, which he could measure and give parameters for.

Advice for Individual Investors

  • Be aware of the risk, and don’t follow the herd.
  • Dig into the math of investment models and understand the assumptions.
  • Persuade governmental bodies that funding should be made available by the public sector to fund research as to how markets work.
  • What we need now is fundamental research to develop a better model to actually understand how markets work.

For more information on Richard, check out Science Business, or pick up a copy of the book we discussed today, The Misbehavior of Markets.

False Belief in the Market

  • One of the biggest false beliefs we see right now out in the market is the idea that markets will rebound.
  • However, we cannot assume what has happened in the past will continue to occur in the same way in the future.
  • We have to have a game plan for more than one market outcome–V-shaped recoveries do not happen every time.

Becoming a Better Trader

  • Every good trader and investor should learn, adapt, and model their behavior based on new information as they learn.
  • When new data presents itself, good investors should be flexible and have the ability to change their strategy.

Our Chosen Strategies

  • Iron butterflies — tails are under-priced and is a defined-risk strategy that worked well in back-testing.
  • A core list of uncorrelated tickers — over time, give us the most diversity in our portfolio for non-crash type markets.
  • VIX hedge – Correlations go out the window when market volatility significantly increases, so we have been diligent in using a VIX hedging strategy to reduce our portfolio risk.

Takeaways from The Misbehavior of Markets

  • The data doesn’t lie — assumptions versus proven realities are put to the test.
  • Very good theories can be crushed under the weight of very good data.
  • Most of the standard financial models that are out there far underestimate the tail risk type of events.
  • You have to keep appropriate levels of risk management in place — be aware of the risk that’s inherent in the market
  • Randomness, even in coin flips, can look complex merely because of the outcome of a random process (i.e., sequencing risk).
  • The fractal nature of market prices explains similarities in volatility and price movement across time frames.
  • Efficient Portfolio Theory — this theory, although effective, relies too heavily on the bell curve.
  • Modern Portfolio Theory — an idea that markets are efficiently priced for all information, markets are independent with no memory, and variance and standard deviation are now the good proxies for risk. This theory is generally good, but still underestimates the tales of the bell curve.
  • The Black-Scholes model is right as long as the assumptions of a bell curve are relevant and that prices move continuously without memory.
  • All of these pricing models work 98% of the time the way that they should–assuming a normal distribution.
  • Modern financial theory assumes, wrongly, that people are rational and self-interested.
  • Scholes and Merton created a fund that searched for options that were priced wrong based on their models. Then, they started taking risky bets on directional prices and bonds with leverage and then blew the fund up in 1998.
  • Two biggest mistakes: being highly focused in one or a few markets, and having a massive amount of leverage.
  • Our brain highlights what it imagines are patterns, and then it disregards contradictory information.

 

Option Trader Q&A w/ Todd

Trader Q&A is our favorite segment of the show because we get to hear from one of our community members and help answer their questions live on the air. Today’s question comes from Todd:

I currently own several stocks and I’ve been selling covered calls on them. But, I came across a strategy called a collar, where they buy a put. But, nothing I found, so far, has exactly explained to me the benefits or the risks of collars. If you could answer that on your Option Alpha Podcast, I would appreciate it. Thank you.

Remember, if you’d like to get your question answered here on the podcast or LIVE on Facebook & Periscope, head over to OptionAlpha.com/ASK and click the big red record button in the middle of the screen and leave me a private voicemail. There’s no software to download or install and it’s incredibly easy.

Thank You for Listening!

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About The Author

Kirk Du Plessis

Kirk founded Option Alpha in early 2007 and currently serves as the Head Trader. In 2018, Option Alpha hit the Inc. 500 list at #215 as one of the fastest growing private companies in the US. Formerly an Investment Banker in the Mergers and Acquisitions Group for Deutsche Bank in New York and REIT Analyst for BB&T Capital Markets in Washington D.C., he's a Full-time Options Trader and Real Estate Investor. He's been interviewed on dozens of investing websites/podcasts and he's been seen in Barron’s Magazine, SmartMoney, and various other financial publications. Kirk currently lives in Pennsylvania (USA) with his beautiful wife and three children.