Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
8,851 documents
This daily-chart strategy enters long when a fast, double-smoothed exponential moving average crosses above a slower double-smoothed average. It closes on the reverse crossover or when price reaches a hard stop set as a percentage below the average entry…
This strategy combines recent swing sweeps with trend and momentum conditions to generate swing entries. For longs, price must sweep below recent lows and then close bullish above the sweep high, the chart-timeframe Hull Moving Average, and a rising 1-hour…
The strategy combines a local Supertrend direction with an optional higher-timeframe Supertrend agreement filter and a volume threshold. It also calculates prior-bar Donchian channel boundaries and uses ATR-based stop and target levels, with an optional exit…
This strategy combines three Supertrend indicators with different ATR multipliers and lookback periods. A long setup requires all three direction signals to be bullish; a short setup requires all three to be bearish. By default, entries can recur whenever…
This strategy combines an RSI-adjusted T3 moving average with a volatility squeeze and momentum filter. RSI controls the T3 smoothing length: lower RSI produces a longer setting, while higher RSI shortens it. The squeeze component compares Bollinger Bands…
This long-only swing system looks for a close above the prior 50-day closing high, paired with volume at least 1.5 times its 50-day average. It takes the signal only when price is above both the 50- and 200-day simple moving averages and the shorter average…
This indicator fits a straight line over each interval defined by a user-selected timeframe and plots the resulting segments on a lower-timeframe chart. It estimates each segment’s endpoints from weighted and simple moving-average calculations, then measures…
This futures strategy combines three signal components: directional trend conditions based on an EMA and directional indicators, a Donchian-style break of a prior high or low, and a volatility squeeze release confirmed by price relative to the Bollinger…
This indicator estimates trend alignment by recursively applying a selected moving average across multiple levels. It compares the source and each moving-average level pairwise: a fully ordered stack produces the strongest bullish or bearish reading, while…
This strategy combines several technical measures into a composite score intended to represent bullish or bearish conditions. Its components include moving-average relationships and momentum, RSI and Williams %R readings, directional movement strength,…
This example presents a directional strategy that uses a fast and slow exponential moving average to define the prevailing trend. It enters long when RSI crosses above a lower threshold while price is above the fast average, and enters short when RSI crosses…
This strategy combines four Fisher Transform series calculated over different lookback multiples with RSI, the direction of a weighted moving average, and an OBV oscillator. A long signal requires all four Fisher values to be rising, RSI to clear a…
This TradingView strategy combines a weighted score from trend, volume, RSI, and candle direction with ATR-based stop-entry levels. A long score awards points for price above the 200-period EMA, above-average volume, RSI below a threshold, and a bullish…
This strategy uses a fast and slow simple moving average to define trend direction, with three selectable entry styles. Traders can enter after a moving-average cross while a timed window remains open, on a price recross of the fast average in the direction…
This strategy seeks breakouts from short-term trendlines built from recent pivot highs and lows. It projects resistance from the two latest highs and support from the two latest lows, then enters long when price crosses above resistance or short when it…
This long-only daily spot strategy makes confirmed market structure a prerequisite for entries. It tracks swing highs and lows, defines structural trends from higher highs and higher lows or lower highs and lower lows, and detects breaks of the latest…
This strategy uses an ATR-based Supertrend to define direction and generate entries when its state changes. The band is calculated from a chosen price source and an ATR multiple; the ATR can use either the standard method or a simple moving average of true…
This strategy combines ten oscillator signals with twelve moving average comparisons to estimate bullish, bearish, and neutral consensus. Indicators include RSI, Stochastic, CCI, MACD, momentum, and Williams %R, alongside averages from short to long periods.…
This strategy tracks confirmed pivot highs and lows using configurable left- and right-bar lookbacks. It enters a long position when the closing price rises above the previous bar’s stored pivot high, and closes all positions when price falls below the…
This strategy uses the sign of a benchmark’s long-window log return to set a directional regime for a US equity index instrument. With the default eighteen-month lookback, positive momentum calls for a long position; negative momentum either leaves the…
This indicator modifies classic directional movement by first comparing changes in highs and lows. It retains positive or negative movement only when that side’s move is larger and positive, then takes the difference between the two directional movement…
This strategy uses an SSL channel derived from moving averages of highs and lows, alongside a baseline calculated from closing prices. A smoothed SSL line crossing the baseline generates directional signals, with an optional higher-timeframe baseline filter.…
This document presents a configurable trading strategy that combines trend direction, volatility conditions, breakout and mean-reversion signals, and Fibonacci retracements. Its filters include moving-average alignment, a higher-timeframe trend check, volume…
This backtest template uses autocorrelation to detect repeating behavior in closing prices, then applies a linear regression of recent percentage returns to form a forecast component. When the autocorrelation exceeds a fixed threshold, the latest regression…