is not responding only to the factors, but to the quickly disappearing probability of making a profit from the existing short position.
This is the sense in which the market is not always right, as the old law has it. The market is always right in the sense that every trader has to accept the prices offered and a single trader cannot change the market’s mind about what is the correct price. The market can be dead wrong about factor analysis but it doesn’t matter. You have to trade the prices in front of you, not what you think prices should be.
Making sense of the information
Now enter the poor retail trader, who often has no idea that FX trading is not easy, as the TV and website ads proclaim. Retail FX trading is rapidly expanding, hot on the heels of professional asset managers diversifying their base. How do these new traders make sense of the market? FX commentary is keeping pace, but much of it is of dubious quality.
One book author asserts the Canadian dollar is 40% correlated with the price of oil – without naming the time period over which the statistic was calculated, rendering it literally useless. In practice, you can manipulate the CAD to be correlated with the price of oil to any number that suits your argument by changing the correlation timeframe. In the funniest case, a publisher was so eager to get a book in print and capitalise on the demand for market commentary that it failed to notice a whole chapter and multiple other references devoted to “rouge” traders (when “rogue” was the intent).
The lesson here is to be careful what conclusions you draw from what you read. And also, to come back to our matrix, that single-factor explanations of FX market behaviour are always wrong. To explain a move, you need:
1 fundamental factors;
2 technical measurement of the sentiment derived from those factors;
3 technical dynamics, and
4 existing positions of the key players.
Once you have these four things and decide which weight each should have, you can begin filling out your matrix and deciding how best to position yourself for a move. In the chapters ahead, we will go deeper into the specific factors that drive currencies.
It’s probably fair to say that very few, if any, highly sophisticated FX market players have programmed a matrix to include all the factors or succeeded in figuring out how a change in one fundamental feeds the technicals and then how the resulting positions create a feedback effect on other technicals and sometimes the fundamentals themselves. A computer program that is capable of taking new data and have it light up the relevant variables in some kind of logical order and have it all result in a price deduction would be a splendid machine, indeed. If some advanced hedge fund or sovereign fund has created a working matrix, they are keeping it a deep, dark secret.
Until such a thing can be devised, we mere mortals must struggle with the sets of variables the old-fashioned way, using our brains. It should come as no surprise that some of the best traders are fairly ignorant of economics and historical context, but are cracker-jack at game theory. In the chapters that follow, we do not actually mention the matrix very often. Instead our goal is to describe the FX market in ways that will be useful to the reader in creating his own matrix in his imagination, if not in programming code.
Endnotes
1 Matthew C. Harding, ‘Application of Random Matrix Theory to Economics, Finance and Political Science’, Department of Economics, MIT Institute for Quantitative Social Science, Harvard University, SEA’06 MIT: 12 July 2006 (web.mit.edu/sea06/agenda/talks/Harding.pdf). [return to text]
2 Robert Slater, Soros, The Unauthorized Biography, The Life, Times and Trading Secrets of the World’s Greatest Investor (McGraw-Hill, 1995). [return to text]
3 James Burke, The Pinball Effect (Little Brown, 1996). [return to text]
Chapter 2 – Review of Risks
“If this were a logical world, men would ride sidesaddle.”
Ron Frost, Agricultural Markets Manager, Chicago Mercantile Exchange
Markets are increasingly global in scope, so that a Mumbai investor can trade a US equity issue or the euro/dollar exchange rate with equal ease of execution (although we may question whether he should). A symptom of this globalisation is that global financial markets move together in a way that they did not before; events in one market have repercussions for others.
There are many risk indicators that players watch to try to help them understand the risk that movements in one market will affect another they are interested in, but we do not yet have a single risk index to explain market behaviour.
In this chapter, after discussing the globalisation of FX markets and contagion, we move on to the tools the market uses to gauge risk. We discuss VIX, the highly-watched fear-factor gauge, risk reversals, stress indexes, and credit default swaps.
Risk and contagion
Contagion arises from the Asian Crisis
Before the Asian Crisis of 1997-98, a big risk event was fairly well contained to the country in question; now a Brazilian limit on foreign investor inflows has a spillover effect not only on the Mexican peso, but also the Korean won. The Asian Crisis was the first time we saw the attitude toward risk shifting from a single country basis to a global basis. What began as a run on the Thai baht in May 1997 (leading to devaluation in July 1997) spread to investor selling of the Malaysian ringgit, Philippine peso and Indonesian rupiah, among others. In the autumn of 1997 and early 1998, Asian currency jitters sent shock waves around the world, with other emerging market currencies feeling the heat as investors exited existing emerging market long positions and sought safe-haven currencies.
By May 1998, the Russian stock and bond market had collapsed, along with the Russian ruble. Russian officials were forced to triple interest rates to 150% to prevent the ruble from falling further. In June of that year, the Japanese yen succumbed to downward pressure, with the Bank of Japan and the US Federal Reserve intervening to prevent further yen weakness. The dollar-yen topped out at ¥147.65 before ending the year at ¥113.45.
By August 1998, the Dow Jones Industrial Average had fallen over 500 points and, by September, Federal Reserve Chairman Greenspan promised to lower US interest rates as the Nikkei 225 hit a 14-year low and other global stock indices also fell dramatically. In addition, troubled US hedge fund Long-Term Capital Management (LTCM) received a $3.5 billion bailout. LTCM had been counting on the convergence spread in fixed income to make tiny arbitrage gains magnified by high leverage, a strategy designed by not one, but two, Nobel Prize winners. Like others, they had never heard of contagion on this scale.
In the autumn of 2008, the Fed initiated a series of interest rate cuts to stabilise US financial markets. The International Monetary Fund (IMF) announced bailout packages for Russia and Brazil. The market began to stabilise in the first quarter of 1999 and the Dow Jones Industrial Average climbed back to over 10,000. Investors breathed the first sigh of relief in nearly two years. While traumatic, the events of that period provided investors with a valuable education. They learned the hard way that, as New York Times columnist Thomas Friedman would later write, “The World is Flat.”
Globalisation of risk
While
