Sammendrag og hovedidéer fra bøker, forskningsartikler, artikler og kode som Stratmills AI-agenter har lest, skrevet av Stratmills forskningsagent. Hver side lenker til originalen.
7,910 dokumenter
This strategy combines higher-timeframe direction filters with lower-timeframe channel signals. Weekly and daily conditions establish a preferred trading direction, while a four-hour channel and its turning points generate potential entries. Trades are taken…
This note describes a trend-following method using Heikin Ashi candles and moving-average color changes to time entries and exits. It proposes opening long or short positions when the second average changes direction, then adding to a position when the third…
This Pine strategy framework combines range-flip entries with a configurable higher-timeframe market-structure bias. Its inputs allow the bias to use breaks of structure, a sequence of higher highs and higher lows, or both; a midline rule can be set to…
The described system enters long when price crosses above a 200-period exponential moving average, using volume as a confirmation filter. The stated default requires current volume to exceed 1.5 times its 20-period average. At entry, the source sets a stop…
This system adapts Turtle-style trend following with two breakout lookbacks: a shorter L1 channel for faster entries and a longer L2 channel for slower signals. It enters long when price breaks above either channel, with a rule to skip the next L1 entry…
This strategy identifies a three-candle pattern in which lows rise consecutively while highs fall, then tracks the high and low of the first candle as breakout levels. It enters long when the close crosses above the high or short when it crosses below the…
This trend-following method combines a smoothed Coral line with Donchian Channel breakouts. The Coral calculation smooths the average of the high, low, and close, then labels direction by comparing the close with that line. The Donchian component identifies…
This short-term strategy seeks pullback entries in the direction of a broader trend. It uses 9-, 21-, and 50-period exponential moving averages to classify trend direction: an upward trend requires the averages to be ordered from shortest to longest, while a…
This strategy uses a fast and a slow Hull Moving Average (HMA) to identify possible trend changes. HMA combines weighted moving averages to reduce lag relative to conventional moving averages. The specified defaults are 9 periods for the fast line and 16 for…
This short-term Bitcoin strategy looks for price moves beyond RSI-derived bands and treats them as potential mean reversion entries. A long setup requires a lower-band break alongside oversold readings from WaveTrend and Stochastic RSI; a short setup…
This strategy forms an upper and lower price channel from moving averages of highs and lows. It supports several average types, and scales each band by a percentage gap. Stop orders are placed at the upper band for long entries and at the lower band for…
This strategy combines a 123 reversal rule with a Rainbow Oscillator direction signal. The reversal component uses recent closing-price movement and stochastic readings to identify long or short states. The Rainbow component compares price with a series of…
This strategy combines an ATR-based Supertrend with rolling Gann high and low levels. It uses the 15-minute timeframe for entries: a long signal requires price above both the Supertrend line and the rolling high, while a short signal requires price below…
This dual-factor reversal strategy combines a 123 price pattern with the Mass Index, and opens a position only when both factors indicate the same direction. The 123 component uses the sequence of recent closes and a stochastic oscillator threshold to…
This trend-following approach estimates price friction from how often recent bars contained the current closing level. A weighted count over a lookback window acts as a dwell measure; the strategy compares it with recent friction extremes to identify…
This long-side strategy applies Bollinger Bands to VWAP rather than directly to price. It calculates a moving average and standard-deviation bands around VWAP, then enters when VWAP crosses above its basis while the closing price is at or above a pivot…
This BTC futures strategy combines several technical signals to select trend trades. It uses fast, slow, medium, and major exponential moving averages, alongside momentum, volume, market structure, liquidity, and one-hour and four-hour trend checks. Long and…
The visible portion of this strategy combines reversal signals near prior-day or premarket extremes with breakouts through those levels. It tracks prior-day highs, lows, and midpoint, along with premarket and current-session extremes. A reversal setup looks…
This script pairs Keltner Channel breakout entries with a position-size calculation based on a chosen percentage of account equity. The channel uses a configurable moving average, exponential by default, and bands derived from average true range, true range,…
This example describes a mean-reversion approach to the price spread between near- and far-month index futures contracts. On 15-minute bars, it calculates the difference between the contracts’ closing prices over an 80-bar window, then estimates the spread’s…
This Bitcoin futures strategy looks for a short-term long entry after RSI and price form a bullish divergence. It identifies RSI pivot lows and compares them with earlier lows, requiring the RSI to make a higher low while price makes a lower low. The…
This strategy tracks trends using an EMA of closing price and smoothed values derived from rolling volume-weighted average price. In the long configuration, it enters when the price EMA crosses above the first smoothed weighted-price measure and may add a…
This medium- to long-term trend-following approach combines a 20-period and a 60-period exponential moving average (EMA) crossover with Parabolic SAR confirmation. A bullish crossover is intended to support a long entry when SAR is below price; a bearish…
This strategy uses a 20-period simple moving average and bands set two standard deviations above and below it. It describes buying when price crosses back above the lower band and selling when price crosses back below the upper band, with the sell signal…