Blog #29 Shock Markets

In my previous two blogs, I highlighted the works of two eminent behavioral economists: Nobel laureates Richard Thaler and Daniel Kahneman. Thaler taught us that we need be nudged to do things today that are good for our future financial well being, like starting to save early for retirement. Danny Kahneman taught us that most people are loss-averse, unwilling to take risk for fear of losing money. Or if they do invest, they cash out too early, thus missing out on the bounteous reward of long-term investing.

Today, I want to pay tribute to a third behavioral economist: professor Robert Shiller of Yale University. Shiller shared the Nobel Prize in 2013 with Eugene Fama and Lars Hansen, both from the University of Chicago. Fama popularized the idea that stock markets are “efficient”, meaning that the market prices stocks so precisely that on average, the price of a stock is “just right”, being neither underpriced or overpriced compared to its fundamentals.

2013 Nobel

Claims that the stock market is efficient gives Shiller the goose bumps. I can almost imagine him saying: “I don’t buy this efficient market stuff.  Investors are human, and you don’t have to be an economist to know that humans often make gross errors of judgement when they invest in stocks, commodities, real estate or whatever…”

What are Shiller’s main contributions to behavioral finance?  I think there are two. First, in an influential 1981 academic paper, Shiller showed that historically, US stock prices were  too volatile to be explained by economic fundamentals. This has significant  implications of how investors should manage risk. More of that later.

Second, Shiller is best remembered by the general public for two uncannily accurate predictions about the US financial market. The first prediction appeared in his bestseller, Irrational Exuberance (2000) which warned that the stock market in March 2000 has become a bubble, led by tech stocks. As it turned out, March 2000 was indeed the height of the stock market, with the tech-heavy NASDAQ stock index reaching a peak on March 10, 2000. It took 15 years from that peak for the NASDAQ index to recover to its pre-crash level.

Image result for shiller irrational exuberance 2000

Shiller was in prediction mode again in August 2006 when he wrote in the Wall Street Journal warning of an imminent crisis in the US housing market and that “there is a significant risk of a very bad period…, and a possible recession sooner than most of us expected“. Two years later, this prediction came to pass, triggering the global financial crisis of 2008 -2010.

I want to return to Shiller’s 1981 paper and see what we can learn from his research on stock market volatility. Shiller’s paper appeared the prestigious journal, American Economic Review with the title:

Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?

When you see titles like this, you know the answer. Using data from 1871 to 2002, Shiller showed that US stock prices were too volatile to be explained by reasonable forecasts of stock dividends or discount rates. I will skip the methodological details of the paper and zoom in on the main message. The main message is that the stock market was not pricing stocks rationally because if it was, stock prices would not jump around as much as they did. After all, dividends tend to increase rather smoothly and the rational discount rates that Shiller computed were nowhere as volatile as actual stock prices. The following graph expresses the essence of Shiller’s argument.


In this above plot, the bold jiggly line traces the S&P 500 index deflated by inflation. The various thin lines are proxies of how the index should move if stock prices were rational based on forecasts of future dividends and reasonable discount rates. Clearly, this graph shows that actual stock prices are excessively volatile compared to fundamentals as reflected by the thin lines.

Why is the market so volatile?  One reason is that speculators are the ones causing most of the volatility. Speculators, by definition, care little about fundamentals. All they care about is how to get rich quick by buying low and selling high. But when everyone buys the same stocks, those stocks will become overpriced compared to what they are intrinsically worth. Since what goes up must eventually come down, there will be a day of reckoning. When the day arrives, the most overpriced stocks will fall like dominoes.

This story is mine, not Shiller’s but readers of Shiller’s other writings will know that he is sympathetic to the view that stock prices are often sentiment-driven. Shiller likes to use a more colorful term: animal spirits for market sentiment. Animal spirits is also the main title of a book Shiller co-wrote with Nobelist George Akerlof. The subtitle of the book: “How human psychology drives the economy and why it matters for global capitalism”says it all.

A volatile market means there must be days or months when stock prices experience unusually big moves either up or down. The fancy term for such big moves is outliers.  This leads me to three questions:

Q1. How much of the market’s overall volatility is due to outliers? 

Answer: for the US stock market, half of the market’s volatility is explained by just 20% of the returns. These largest 20% returns may be considered as outliers. My result is based on a long sample of monthly returns on the US stock market from 1926 to 2017. The data was downloaded from Shiller’s website at

Q2. How do outliers affect the market’s average return?

Answer: if we drop the best 10% and worst 10% monthly returns from the sample, the average return goes up from 11.2% to 13.2%.  This tells us that bad outliers have a greater impact on the market than good outliers.

Q3. Can investors predict when bad outliers will hit the market?

Answer: While it is every investor’s dream to avoid the worst months, the reality is that you only know the worst months after the fact. Attempts to predict future bad outliers based on past returns are doomed to fail. To see this, look at the plot below. It shows how the worst 10% returns is spaced out over time (vertical axis, in number of months).

Worst 10 percent

Notice that bad outliers are scattered widely in time. Thus one bad month is rarely followed soon after by another bad month. This makes accurate predictions of bad outliers tough. The picture for good outliers (the 10% best returns) isn’t much better (see next plot).

Best 10 percent

Similar to bad outliers, a good month is rarely followed soon after by another good month. Bottom line: there are no easy ways to predict these market movers and shakers.

What then should you do in a market like this?  You have two options. Option #1: park your money in cash and escape the market’s volatility. Option #2: try to catch the best months and avoid the worst months. Finally, Option #3: park your money in the stock market and ignore the market’s volatility.

Please read the above paragraph again slowly.

To escape volatility by holding cash speaks of extreme loss-aversion that isn’t the most productive use of your hard earned savings. Option #2 (market timing) is wishful thinking given the difficulty of predicting outliers.

This leaves Option #3. The most prudent way to grow your wealth is to invest long-term as a buy-and-hold investor. By holding a diversified stock portfolio over decades rather than months, you are making a long-term commitment to ride through volatility and get rewarded for that. You are also tuning out short-term noises that add to volatility. The longer you stay invested, the more likely you will encounter outliers, both good and bad. Learn to take the bad ones in stride. Better still, use every major market correction as opportunity to add to your holdings. Never waste a crash :0


Further reading (for nerds only)
An academic paper on why the stock market is inefficient.


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s