Adapting Moving Averages To Market Volatility

Stocks & Commodities V. 10:3 (108-114): Adapting Moving Averages To Market Volatility by Tushar S. Chande, Ph.D. Adapting Moving Averages To Market Volatility by Tushar S. Chande, Ph.D. If a market is active, it has volatility: that cannot be avoided. And because the market is continuously changing, an indicator that attempts to predict market activity must itself adapt and change. How? Tushar Chande presents a dynamic—not static—indicators: a variable-length moving average, which adapts to the volatility in question by exponentially smoothing data based on standard deviation. T echnicians can be trend followers or contrarians. Trend followers use price-based indicators, such as moving averages, while contrarians prefer oscillators such as overbought-oversold indicators. But the market never does quite the same thing twice, and so no indicator works all the time. The market is dynamic, adjusting rapidly to information: a continuous tug of war between greed and fear, fact and fiction. Technical indicators, on the other hand, are static, mechanically applying the same formula to the relevant data. What is needed is a combination, dynamic indicators that will automatically adapt to the changing nature of markets, a new class of dynamic indicators that combine exponential moving averages with other technical indicators to adapt automatically to changing price behavior. What is needed is an exponential moving average with a continuously variable smoothing index that adjusts rapidly to changes in price behavior. The smoothing index can be tied to any market variable. It is the continuous, not discrete, changes in the smoothing index that increases the sensitivity of these moving averages to changes in price behavior. These new dynamic exponential averages can be referred to a variable index dynamic average (VIDYA ). Let us first examine exponential moving ave