The Foreign Exchange Matrix. Barbara Rockefeller

of 89.53. During key stress points of the euro zone peripheral crisis, the VIX topped out a bit below 50 on two occasions, first at 48.20 in May 2010 and again at 48.00 in early August 2011. The velocity of the VIX rise or fall can be a factor affecting risk also. On 8 August 2011, when the VIX topped out at 48.00, the index rose 50% in a single day.

      The VIX and the S&P 500 do not always move in lockstep with each other; there is often a sizeable time lag. In October 2008, the VIX topped out close to 89.00 and subsequently edged lower into the end of 2008 and early 2009, suggesting diminishing risk aversion. In contrast, the S&P 500 continued to decline into late 2008 and early 2009, bottoming at 666.92 only in March 2009 (VIX closed at 49.33 that day). A trader trying to buy US stocks cheaply in late 2008/early 2009, thinking they had bottomed, would have experienced buyer’s remorse by getting in too early. The lesson to be learned is that while the VIX can be considered a good predictor of future direction of the S&P 500, a turn in market sentiment suggested by a drop or rise in VIX volatility may not translate to an immediate shift in stock positioning.

      Currency traders use swings in the VIX as a gauge of risk appetite for US and global stocks and, depending upon the FX link at the time, buy and sell currencies accordingly. Starting in September 2010, the CBOE began to offer weekly options (both puts and calls) on VIX futures, which allowed investors to bet on VIX direction for the first time. In the past, if an FX trader saw the VIX falling sharply, he would conclude that US stocks might also fall and drag the dollar with it. More recently, since the US and euro zone financial crises, a falling VIX would suggest risk friendly positions were being pared and red flag the potential for safe-haven demand. Under this scenario, the dollar might firm on safe-haven demand.

      It’s not only FX traders that use VIX as a risk gauge. Figure 2.3 shows VIX against the oil futures contract. Oil led the VIX up from 2004 to 2008 and as oil crashed at end-2008 so did the VIX. In fact, VIX stayed low as oil resumed its rise, except for spikes in both 2010 and 2011. The correlation is not very strong and it lags, but fear of equity market volatility arises from economic conditions and in turn has economic implications that affect perceived demand for oil. It can be bit head-spinning, but it’s not without a certain logic. Since FX traders watch oil prices as well as VIX, when they are both signalling rising risk we can expect magnification of a pro-dollar bias.

      Figure 2.3 – VIX and Crude Oil Futures (monthly)

      2. Risk reversals

      Another measure of bias or directional preference used by currency traders involves risk reversals. Market players, especially those trading FX options, watch the skew in option risk reversals to see which way sentiment is leaning in a given pair. A risk reversal is the difference between the implied volatility of an OTM (out of the money) call (right to buy a currency) and that of a put (right to sell a currency) option of similar maturities. Typically, 25-Delta calls and 25-Delta puts are tracked by the market players.

      If a risk reversal is positive (calls are more expensive than puts) it means that for a given maturity (one-month, two-months, three-months, etc.) buying option protection or insurance in the event of a currency move higher is more expensive than buying protection for a move lower. Conversely, if a risk reversal is negative, then it means that buying insurance to protect against a currency move lower is more expensive than buying insurance to protect against a currency move higher. When risk reversals hit extended levels, it may indicate that a directional expectation has become excessive.

      “This bias helps in assessing the excessive sentiment toward a directional preference and the common wisdom is to use it as a contrarian indicator,” explains Bashar Azzouz, Founder and Managing Director of 2 Rivers Consulting. Azzouz, who manages money and educates on option strategies, says the common practice is to generate two sets of observations from positive and negative risk reversals. The upper limit will be the mean (pick a historical time frame such as six months or a year) of the positive observations, plus one standard deviation of the positive observation. If the upper limit is exceeded, then the bias indicates excessive bullishness and therefore can be viewed as overbought. The lower limit will be the mean of the negative observations, minus one standard deviation of the negative observations. If the lower limit is exceeded, then the bias is indicating excessive bearishness and can be deemed oversold.

      Risk reversals and their ranges can vary greatly between FX pairs. These instruments are quoted like forward foreign currency swap rates, typically from one week to one year, with the most attention paid to the one-month risk reversal. There are occasions where one period suggests future bullishness and another future bearishness. “When there is a divergence in the skew, say one-month (risk reversals) shows calls are bid over puts, while three-months shows puts are bid over calls, this may indicate a corrective short-term bullish outlook in a longer-term bearish trend,” Azzouz suggests.

      3. Federal Reserve stress indexes

      Currency traders seeking a more detailed picture look beyond the one dimensionality of the CBOE’s VIX and seek out other risk indicators that factor in multiple variables, such as Federal Reserve stress indexes. The Federal Reserve Banks of Kansas City and Cleveland release monthly Financial Stress Indexes (FSIs) and the Federal Reserve Bank of St. Louis releases a weekly Financial Stress Index (FSI). These Fed risk gauges are becoming more popular as FX tools. With all stress indicators, the higher the stress, the more pro-dollar bias we see in the FX market.

      Kansas City Federal Reserve Financial Stress Index (KCFSI)

      The Kansas City Federal Reserve Bank describes its FSI as “a monthly measure of stress in the US financial system based on 11 financial market variables.” These variables are: the three-month LIBOR/T-Bill spread (TED spread), the two-year swap spread, off-the run/on the run 10-year Treasury spread, Aaa/10-year Treasury spread, Baa/Aaa spread, high-yield bond/Baa spread, consumer ABS/5-year Treasury spread, the negative value of correlation between stock and Treasury returns, the implied volatility of overall stock prices (VIX), idiosyncratic volatility (IVOL) of bank stock prices, and a cross-section dispersion (CSD) of bank stock returns. “A positive value indicates that financial stress is above the long-run average, while a negative value signifies that financial stress is below the long-run average.” ^[6]

      The Kansas City Fed explains the root causes of financial stress as arising from:

       increased uncertainty about fundamental value of assets

       increased uncertainty about behaviour of other investors

       increased asymmetry of information

       decreased willingness to hold risky assets (flight to quality)

       decreased willingness to hold illiquid assets (flight to liquidity)

      In discussing the uncertainty about the fundamental value of assets, the Kansas City Fed observed that financial innovations can “make it difficult for lenders and investors to even assign probabilities to different outcomes. This kind of uncertainty, in which risk is viewed as unknown and unmeasurable, is often referred to as Knightian uncertainty.” As example of financial innovation, the Fed pointed to “complex structured products such as collateralised debt obligations (CDOs) in the recent subprime crisis, or program trading in the Long-Term Capital Management crisis of 1998.”

      On the issue of transparency the Kansas City Fed stated, “asymmetry of information is said to exist when borrowers know more about their true financial condition than lenders, or when sellers know more about the true quality of the assets they hold than buyers.” These information gaps can “lead to problems of adverse selection or moral hazard, boosting the average cost of borrowing for firms and households, and reducing the average price of assets on secondary markets.”

      In the past 15 years, the KCFSI flashed warning signals on several occasions. See Figure 2.4. In the period from October 1998 to October 2002, the KCFSI saw six distinct peaks in a short period of time. The index peaked in the wake of the