Miha Kralj
90d5638008
- LTMA (Linear Trend Moving Average): Introduces a predictive moving average using dual cascaded EMAs for trend estimation. - MCNMA (McNicholl EMA): Implements a zero-lag TEMA using a cascaded EMA structure for enhanced responsiveness. - NLMA (Non-Lag Moving Average): Utilizes a damped cosine kernel to achieve reduced lag in moving averages. - NMA (Natural Moving Average): Adapts smoothing based on volatility profiles using a square-root kernel. - NYQMA (Nyquist Moving Average): Applies the Nyquist-Shannon theorem to prevent aliasing in cascaded moving averages. - RAIN (Rainbow Moving Average): Combines multiple SMA layers with weighted averages for multi-scale smoothing. - TRAMA (Trend Regularity Adaptive Moving Average): Adapts smoothing based on the frequency of new highs and lows in price data.
3.6 KiB
QSTICK: Qstick Indicator
"The average candlestick body reveals the market's true conviction."
The Qstick indicator, developed by Tushar Chande, computes a moving average of the close-minus-open difference over a lookback period, quantifying whether bars are predominantly bullish or bearish. Positive values indicate closes above opens (buying pressure); negative values indicate closes below opens (selling pressure). It supports both SMA (O(N) space via ring buffer) and EMA (O(1) space) smoothing modes and requires TBar input for open/close access.
Historical Context
Tushar Chande introduced Qstick as part of his candlestick quantification work in The New Technical Trader (1994, co-authored with Stanley Kroll). Traditional candlestick analysis relies on visual pattern recognition; Qstick reduces bar body direction and magnitude to a single continuous number suitable for systematic tracking. The indicator addresses a specific gap: close-to-close momentum indicators miss intrabar dynamics captured by the open-to-close differential. The name "Qstick" reflects the "quick stick" reading of candlestick conviction.
Architecture & Physics
1. Body Difference
d_t = \text{Close}_t - \text{Open}_t
Positive d_t represents a bullish bar (close above open), negative represents bearish, zero represents a doji.
2. Moving Average Smoothing
SMA mode: Maintains a ring buffer of N differences and a running sum for O(1) incremental updates:
\text{Qstick}_t = \frac{1}{N} \sum_{i=0}^{N-1} d_{t-i}
EMA mode: Standard recursive filter with decay \alpha = 2/(N+1):
\text{Qstick}_t = \alpha \cdot d_t + (1 - \alpha) \cdot \text{Qstick}_{t-1}
EMA mode uses O(1) space but weights recent bars more heavily than SMA.
3. Complexity
| Metric | SMA Mode | EMA Mode |
|---|---|---|
| Time | O(1) per bar | O(1) per bar |
| Space | O(N) ring buffer | O(1) |
| Ops | 1 add, 1 sub, 1 div | 1 sub, 1 mul, 1 FMA |
Mathematical Foundation
Parameters
| Parameter | Type | Default | Constraint | Description |
|---|---|---|---|---|
| period | int | 14 | > 0 | Lookback period for moving average |
| useEma | bool | false | — | Use EMA (true) or SMA (false) |
Pseudo-code
QSTICK(bar, period=14, useEma=false):
diff = bar.Close - bar.Open
if useEma:
// EMA mode
alpha = 2.0 / (period + 1)
if count == 0:
ema_val = diff
else:
ema_val = FMA(alpha, diff - ema_val, ema_val) // alpha*(diff-ema)+ema
result = ema_val
else:
// SMA mode with ring buffer
if buffer is full:
running_sum -= buffer.oldest
buffer.add(diff)
running_sum += diff
result = running_sum / min(count, period)
return result
Zero-Crossing Interpretation
| Condition | Meaning |
|---|---|
| Qstick > 0 | Closes above opens dominate (net buying pressure) |
| Qstick < 0 | Closes below opens dominate (net selling pressure) |
| Qstick crosses zero | Shift in intrabar momentum direction |
| Qstick rising | Increasing bullish pressure regardless of sign |
| Qstick falling | Increasing bearish pressure regardless of sign |
Scale Dependence
Qstick values are in absolute price units, not normalized. Cross-instrument comparison requires normalization (e.g., divide by ATR or price level). Short periods (5-8) suit trading signals; longer periods (20+) suit trend identification.
Resources
- Chande, T. S. & Kroll, S. (1994). The New Technical Trader. John Wiley and Sons.
- Kirkpatrick, C. D. & Dahlquist, J. R. (2015). Technical Analysis: The Complete Resource for Financial Market Technicians. FT Press.