**Using Volatility to Forecast Market Activity**

Option volatilities measure the rate and magnitude of the changes in a currency's price. Implied option volatilities on the other hand measure the expected fluctuation of a currency's price over a given period of time based upon historical fluctuations. Volatility calculations typically involve the historic annual standard deviation of daily price changes. (Find out everything you need to know about option volatility in the

*.)*

*Option Volatility Tutorial*Option volatility information is readily availabl from a variety of sources. In using volatility to forecast market activity, the trader needs to make certain comparisons. Although the most reliable comparison is implied versus actual, the availability of actual data is limited. Alternatively, comparing historical implied volatilities is also effective. One-month and three-month implied volatilities are two of the most commonly benchmarked time frames used for comparison (the numbers below represent percentages).

Figure 1 Source: IFR Market News Plug-in |

- If short-term option volatilities are significantly lower than long-term volatilities, expect a potential breakout.
- If short-term option volatilities are significantly higher than long-term volatilities, expect reversion to range trading.

Breakout traders, on the other hand, can also monitor option volatilities to make sure that they are not buying or selling into a false breakout. If volatility is at average levels, the likelihood of a false breakout increases. Alternatively, if volatility is very low, the probability of a real breakout increases. These guidelines generally work well, but traders also have to be careful. Volatilities can have long downward trends during which time volatilities can be misleading. Traders need to look for sharp movements in volatilities, not a gradual one.

The following is a chart of USD/JPY. The green line represents short-term volatility, the red line long-term volatility and the blue line price action. The arrows with no labels are pointing to periods when short-term volatility rose significantly above long-term volatility. You can see such divergence in volatility tends to be followed by periods of range trading. The "1M implied" arrow is pointing to a period when short-term volatility dips below long-term volatility. At price action above that, a breakout occurs when short-term volatility reverts back toward long-term volatility.

Figure 2 |

Source: StockCharts.com |

**Using Delta to Calculate Spot Probabilities**

*What Is Delta?*

Options price can be seen as a representation of the market's expectation of the future distribution of spot prices. The delta of an option can be thought of roughly as the probability of the option finishing in the money. For example, given a one-month USD/JPY call option struck at 104 with a delta of 50, the probability of USD/JPY finishing above 104 one month from now would be approximately 50%.

*Calculating Spot Probabilities*

With information on deltas, one can approximate the market's expectation of the likelihood of different spot levels over time. When the probability indicates that the spot will finish above a certain level, call-option deltas are used; when the probability indicates that the spot will finish below a certain level, put-option deltas are used.

The key to calculating expected spot levels is using conditional probability. Given two events, A and B, the probability of A and B occurring is calculated as follows:

P(A and B) = P(A)*P(B|A) |

*given*the occurrence of A.

Here is the formula applied to the problem of calculating the probability that spot will touch a certain level:

P(touching and finishing above spot level) = P (touching spot level) * P(finishing above spot | touched spot level) |

*given*that is has already touched that level.

ExampleSay we want to know the probability of the EUR/USD touching 1.26 in the next two weeks. Because we are interested in spot finishing above this level, we look at the EUR call option. Given current spot and volatilities, the delta of this option is 30. Therefore, the market\'s view is that the odds of EUR/USD finishing above 1.26 in two weeks are roughly 30%. If we assume that EUR/USD does touch 1.26, the option delta then would become 50. By definition an at-the-money option has a delta of 50, and thus has a one-in-two chance of finishing in the money. Here is the calculation using the above equation: 0.3 = P(touching 1.26) * 0.5 This means the odds of EUR/USD touching 1.26 in two weeks equals 60% (0.3/ 0.5). The market\'s "best guess" then is that EUR/USD has a 60% chance of touching 1.26 in two weeks, given the information from options. |

*The rule-of-thumb this methodology yields is that the probability of spot touching a certain level is roughly equivalent to two times the delta of an option struck at that level.*

**Using Gamma to Predict Trading Environments**

*What Is Gamma?*

Gamma represents the change in delta for a given change in the spot rate. In trading terms, players become long gamma when they buy standard puts or calls, and short gamma when they sell them. When commentators speak of the entire market being long or short gamma, they are usually referring to market makers in the interbank market.

How Market Makers View Gamma

How Market Makers View Gamma

Generally, options market makers seek to be delta neutral - that is, they want to hedge their portfolios against movement in the underlying spot rate. The amount by which their delta, or hedge ratio, changes is known as gamma.

If USD/JPY rises to 108, the trader will need to sell another $10 million, this time at 108, as the total delta position becomes $20 million. What happens if USD/JPY goes back to 107? The delta position goes back to $10 million, as before. Because the trader is now short $20 million, he or she will need to buy back $10 million at 107. The net effect then is a 100-pip profit, selling a 108 and buying at 107.

In sum, when traders are long gamma, they are continually buying low and selling high, or vice versa, in order to hedge. When the spot market is very volatile, traders earn a lot of profits through their hedging activity. But these profits are not free, as there is a premium to own the options. In theory, the amount you make from delta hedging should exactly offset the premium. Whether or not this is true in practice depends on the actual volatility of the spot rate.

The reverse is true when a trader has sold options. When short gamma, in order to hedge, the trader must continually buy high and sell low - thus he or she loses money on the hedges, in theory the exact same amount earned in options premium through the sales.

Why Is Gamma Important for Spot Traders?

Why Is Gamma Important for Spot Traders?

But what relevance does all this have for regular spot traders? The answer is that spot movement is increasingly driven by what goes on in the options market. When the market is long gamma, market makers as a whole will be buying spot when it falls and selling spot when the exchange rate rises. This behavior can generally keep the spot rate in a relatively tight range.

When the market is short gamma, however, the spot rate can be prone to wide swings as players are either continually selling when prices fall, or buying when prices rise. A market that is short gamma will exacerbate price movement through its hedging activity. Thus:

- When market makers are long gamma, spot generally trades in a tighter range.
- When market makers are short gamma, spot can be prone to wide swings.

**Using Risk Reversals to Judge Market Positioning**

*What Are Risk Reversals?*

Risk reversals are a representation of the market's expectations on the exchange-rate direction. Filtered properly, risk reversals can generate profitable overbought and oversold signals.

A risk reversal consists of a pair of options, a call and a put, on the same currency, with the same expiration (one month) and sensitivity to the underlying spot rate. Risk reversals are quoted in terms of the difference in volatility between the two options. While in theory these options should have the same implied volatility, in practice they often differ in the market. A positive number indicates that calls are preferred to puts and that the market is expecting a move

*up*in the underlying currency. Likewise, a negative number indicates that puts are preferred to calls and that the market is expecting a move

*down*in the underlying currency.

*While the signals generated by a risk-reversal system will not be completely accurate, they can specify when the market is bullish or bearish.*

How Can Risk Reversals Be Used to Predict Spot Currency Movement?

How Can Risk Reversals Be Used to Predict Spot Currency Movement?

Risk reversals convey the most information when they are at relatively extreme values. These extreme values are commonly defined as one standard deviation beyond the averages of positive and negative values. Therefore, we are looking at values one standard deviation below the average of negative risk-reversal figures, and values one standard deviation above the average of positive risk-reversal figures.

When risk reversals are at these extreme values, they give off contrarian signals; when the entire market is positioned for a rise in a given currency, it makes it that much harder for the currency to rally, and that much easier for it to fall on negative news or events. A large positive risk-reversal number implies an overbought situation, while a large negative risk-reversal number implies an oversold situation. The buy or sell signals produced by risk reversals are not perfect, but they can convey additional information used to make trading decisions.

Figure 3: GBP/USD: Risk reversals can generate reasonably accurate signals at extreme values |

Summary

There are many tools used by seasoned options traders that can also be useful to trading spot FX. Volatility can be used to forecast market activity in the cash component through comparing short-term versus longer term implied volatilities. Delta can help estimate the probability of the spot rate reaching a certain level. And gamma can predict whether spot will trade in a tighter range if it is vulnerable to wider swings. Risk reversals are a representation of the market's expectations on exchange-rate direction. If filtered properly, risk reversals can be used to gauge market sentiment and determine overbought and oversold conditions.