Direct Answer
Tushar Chande's VIDYA is an exponential moving average whose smoothing weight is scaled by a volatility index, so it speeds up when volatility is high and slows down when it is low. The scale is commonly the absolute Chande Momentum Oscillator divided by 100. It trails price like other moving averages, but moves faster in directional stretches and flattens when the volatility index is low.
Variable Index Dynamic Average: Formula, Meaning, Signals, Examples and How to Use It
How Is Variable Index Dynamic Average Calculated?
Tushar Chande's VIDYA is an exponential moving average whose smoothing weight is scaled by a volatility index, so it speeds up when volatility is high and slows down when it is low. The scale is commonly the absolute Chande Momentum Oscillator divided by 100.
Formula: VIDYA(t) = alpha * k * Price + (1 - alpha * k) * VIDYA(t-1), alpha = 2 / (n + 1), k = volatility index between 0 and 1
Inputs:
- Prices
- EMA period n
- Volatility index k (commonly |CMO| / 100)
- CMO lookback if CMO is used
Worked example. With a 20-period EMA weight, a volatility index of 0.5, a price of 102 and a prior VIDYA of 100, the new value is 100.095. The inputs are illustrative numbers, not market data.
Reading it. It trails price like other moving averages, but moves faster in directional stretches and flattens when the volatility index is low. Price above a rising VIDYA is read as an uptrend.
Limits. The choice of volatility index changes behavior, and some implementations use standard deviation ratios instead of CMO. The average can stall in low-volatility trends.
What is Variable Index Dynamic Average?
Tushar Chande's VIDYA is an exponential moving average whose smoothing weight is scaled by a volatility index, so it speeds up when volatility is high and slows down when it is low. The scale is commonly the absolute Chande Momentum Oscillator divided by 100.
How to use Variable Index Dynamic Average
It trails price like other moving averages, but moves faster in directional stretches and flattens when the volatility index is low. Price above a rising VIDYA is read as an uptrend. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.
Strengths
- Scaling the smoothing weight by a bounded index between 0 and 1 means the average can never move faster than the base EMA.
- The Chande Momentum Oscillator input uses both up and down changes, so the weight reflects directional movement and not just size.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- The index is recomputed each bar from a short window, so the speed of the average changes quickly and the line can alternate between fast and slow.
- Using the absolute value of a signed oscillator discards direction, so rallies and declines of equal strength speed the line alike.
- Correlated indicators can create false confidence by repeating the same underlying information.
Editorial and risk note
This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance.
Frequently Asked Questions
Is Variable Index Dynamic Average a buy or sell signal?
No. It trails price like other moving averages, but moves faster in directional stretches and flattens when the volatility index is low. The choice of volatility index changes behavior, and some implementations use standard deviation ratios instead of CMO. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions.
What is the best setting for Variable Index Dynamic Average?
Variable Index Dynamic Average takes these inputs: prices; EMA period n; volatility index k (commonly |CMO| / 100). There is no universal best setting for the tunable ones, so test them across instruments, regimes and out-of-sample periods and favor stable parameter regions over one historical winner.
Can Variable Index Dynamic Average be used by itself?
The choice of volatility index changes behavior, and some implementations use standard deviation ratios instead of CMO. The average can stall in low-volatility trends. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Variable Index Dynamic Average work on every timeframe?
The calculation (VIDYA(t) = alpha * k * Price + (1 - alpha * k) * VIDYA(t-1), alpha = 2 / (n + 1), k = volatility index between 0 and 1) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it.
Why does Variable Index Dynamic Average give false signals?
The index is recomputed each bar from a short window, so the speed of the average changes quickly and the line can alternate between fast and slow. Using the absolute value of a signed oscillator discards direction, so rallies and declines of equal strength speed the line alike. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Variable Index Dynamic Average be backtested?
Rebuild Variable Index Dynamic Average from prices using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline.