Blame the Quants
Thanks to their armies of elite scientists, quant funds can model the markets and predict their future behavior, goes the undoubted conventional wisdom.
Pablo Triana, Lecturing Birds on Flying. Can Mathematical Theories
Destroy the Financial Markets? (xxi, Wiley 2009)
It is common, perhaps natural, to attribute increases in the volatility of security prices to improvements in technology. After all, technology reduces the cost of trading, and large price movements are often accompanied by large volumes. It does not seem unreasonable that new technology amplifies the impact of ideas, particularly expectations, on trading volumes and prices.
Certainly, there have been great technological advances. On May 23, 1962, the ticker at the New York Stock Exchange fell 143 minutes behind trades, the longest lag in history to that time except October 24, 1929. It ran late 124 times in 1966, unable to keep pace with daily volumes that sometimes exceeded 10 million shares. The major exchanges closed Wednesdays from June to December 1968 to catch up on paper work. The computer has since made much greater volumes routine: daily trades hit 50 million shares in 1978, 1 billion in 1997, and 14 billion on July 19, 2007; 5 billion is now a slow trading day.
The new technology enables trades of blocks of securities triggered by relative price movements. This program trading accounts for more than a third of the NYSE’s volume, and is especially active during the triple witching hours that occur on the third Fridays of March, June, September, and December, which are the expiration days of stock options, index options, and index futures. Wikipedia tells us that these “simultaneous expirations generally increase the trading volumes of options, futures and the underlying stocks, and occasionally increase the volatility of prices of related securities.”
Pablo Triana has responded to the recent financial crisis with a book which argues that the implementation of recent financial theories made possible by the new technology “drastically moves” (xxv) and is destroying the financial markets. Both pillars of the argument are imaginary. I begin with theory, which is an attempt to understand events, for example, price movements. Triana’s observations that the Black-Scholes-Merton (BSM) option-pricing model (the book’s chief culprit), is unrealistic and a poor predictor are redundant. Theories must be simplified to be understood; the “real” world cannot be modeled. Their inability to predict in fact supports efficient-market pricing theories, which assert that prices incorporate information so that future price movements are random. Furthermore, most traders don’t apply the theory. Nevertheless, Triana claims that the crash of October 19, 1987, and later crashes, were caused by “computationally charged stock-trading strategies directly inspired by the mathematical spirit of the Black-Scholes formula” (p. xlviii).
It is in principle possible that such “inspired strategies” have been guilty of any number of evils, including increases in volatility. However, the latter has not occurred. The belief in a positive correlation between volatility and technology finds no support in the data. Financial theories are innocent even of a second-hand cause of volatility.
It is also reasonable to believe that technology reduces volatility. Kenneth Garbade and William Silber (1978) reported that the overland telegraph greatly reduced spreads between security prices in New York, Philadelphia, and New Orleans in the 1840s; a result repeated by the Atlantic cable for prices in New York and London in the 1860s. This implies reductions in volatility to the extent that the effects of location-specific shocks are spread over the greater areas made possible by improved communications and lower transaction costs. Thick markets are associated with low volatility.
However, in December 1857, the Merchants’ Magazine and Commercial Review identified the recent invention of the telegraph, “by means of which bad news, such as the failure or embarrassment of a bank … was immediately communicated to all the cities and large towns of the United States,” as the immediate cause of the panic” (Jalil 2009).
The proof is in the pudding. Our view of the correlation between technology and volatility ought to depend on the data, which predominately points to zero. A strong and well-known example is the history of the volatility of stock prices depicted in the figure (with standard-deviations derived from data through Robert Shiller’s homepage). Many believe that stock and other asset prices are “too volatile” for consistency with the rest of financial theory (Shiller 2000), but there has been little headway in explaining changes in volatility. The figure shows the absence of a trend in the volatility of American stock prices since 1875. The outlier of the 1930s has encouraged investigations of the effects of variations in the volatility of monetary policy (Bordo 2001), company news (Goonatilake 2007; Schwert 1989), and derivatives trading, including triple witches (Edwards 1988), with insubstantial results. The almost continuous advance in technology (exacerbated or not by new financial theories) has had no effect.
Optimistic expectations, excessive leverage, and volatile episodes are as old as the financial markets. The Extraordinary Popular Delusions and the Madness of Crowds (Mackay 1841) during the tulipomania of the 1630s, the collapses of the Mississippi scheme and the South Sea bubble in France and Britain in 1720, and many later booms and busts occurred without computers or sophisticated financial theories. We are told that history will teach people to never again say “this time is different.”
The four most dangerous words in finance are “this time is different.” Thanks to this masterpiece by Carmen Reinhart and Kenneth Rogoff, no one can doubt this again.
Martin Wolf, Financial Times, review (Sept 28, 2009) of This Time is Different:
Eight Centuries of Financial Folly (Princeton U. Press 2009)
Don’t bet on it.
Bordo, Michael, Michael Dueker, and David Wheelock. 2001. “Aggregate price shocks and financial instability: A historical analysis,” WP 2000-005B. Federal Reserve Bank of St. Louis.
Edwards, Franklin. 1988. “Does futures trading increase stock return volatility?” Financial Analysts J., Feb.
Garbade, Kenneth, and William Silber. 1978. “Technology, communication, and the performance of financial markets: 1840-1975,” J. Finance, June.
Goonatilake, Rohitha.and Susantha Herath. 2007. “The volatility of the stock market and news,” International Research J. of Finance and Economics, 11.
Jalil, Andrew. 2009. “A new history of banking panics in the U.S., 1825-1929,” Univ. of California, Berkeley.
Mackey, Charles. 1841. Extraordinary Popular Delusions and the Madness of Crowds. London: Richard Bentley.
Schwert, William. 1989. “Why does stock market volatility change over time?” J. Finance, Dec.
Shiller, Robert. 2000. Irrational Exuberance. Princeton Univ. Press.