A market tends to move swiftly from periods of price consolidation to new levels. Here's how to recognize the setup before a market moves out of a short-term consolidation, from the authors of Street Smarts: High Probability Short-Term Trading Strategies. By Laurence A. Connors and Linda Bradford Raschke In Street Smarts , we introduced a trading strategy we use to pinpoint which markets are likely to move dramatically. In this article, we will share this strategy with you. Markets oscillate from periods of low volatility to high volatility and back. Our research indicates that after periods of extremely low volatility, volatility tends to increase and price may move sharply. This increase in volatility tends to correlate with the beginning of short- to intermediate-term moves in price. We have found that we can identify which markets are about to make such a move by measuring the historical volatility and the application of pattern recognition. But before we go further, let's define a few concepts, beginning with our measurement of volatility. A FEW DEFINITIONS Historical volatility is the standard deviation of day-to-day logarithmic closing price changes (see sidebar, "Calculating historical volatility"), expressed as an annualized percentage. In simple terms, historical volatility is the degree to which prices fluctuate over a period. For example, a six-day historical volatility reading of 10% for a security trading at a price of $100 means that for the past six days, its annualized range would have been between $110 and $90 one standard deviation (68%) of the time. A high-volatility reading indicates that the security is very volatile, while a low-volatility reading signals the lack of volatility. You can use different lookback periods. Often, in short-term lookbacks, such as six days, the historical volatility will fluctuate while the longer-term analysis, such as 100 days, will remain relatively stable. We have found that large price moves occur when the six-day historical volatility reading is less than 50% of the 100-day reading. |
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