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.
9,797 documents
This strategy looks for pullbacks within an established futures trend. It defines direction by whether the close is above or below a 100-period EMA, then signals a long when RSI is at or below a configurable threshold and a short when RSI is at or above its…
This proposed strategy combines a stochastic reversal rule with a signal-to-noise measure to seek confirmation around possible turning points. Its description says the reversal component considers recent price movement alongside fast and slow stochastic…
This strategy combines a stochastic-based reversal signal with a signal-to-noise measure and trades only when both components agree. The description uses fast and slow stochastic values and recent price changes to identify a reversal, with a threshold…
This indicator adapts Ichimoku components into a separate oscillator-style display. It applies a T3 smoothing process to closing prices over the conversion, base, and second lagging-span periods, then uses displaced values to form a cloud midpoint and cloud…
This document describes an Ergotic CSI oscillator inspired by William Blau’s work on momentum, direction, and divergence. It combines an adaptive directional index with true range and price to calculate a CSI value, then smooths that value with a simple…
This document outlines a trend-following system that combines a fast and slow EMA relationship with RSI thresholds and divergence checks. Long signals require the fast EMA to be above the slow EMA, RSI to exceed the stated upper threshold, and no bearish…
The document describes a Pine strategy that sizes purchases as a fixed daily cash amount divided by the closing price, then enters only when the close crosses above one of several EMAs. It sets a trade-count cap and plots the EMA ribbon. The published…
This strategy measures the range between the highest high and lowest low over a lookback period, then compares that Donchian channel width with its simple moving average. When width exceeds its average, the example takes a short position; when width falls…
This document describes a trailing-stop framework for long or short positions. A trade begins when its entry condition is met, with an initial stop set from the entry price. As price moves favorably by more than one percent relative to the most recently…
This strategy combines a gamma-weighted average price (GWAP) with a short-term momentum condition to generate Bitcoin futures entries. It weights recent closing prices more heavily through an exponential decay factor, then compares the current close with…
This document describes a JavaScript library for managing commodity futures positions through a CTP exchange interface. Its functions aggregate positions by contract and direction, submit or close orders, cancel pending orders, and report account balance…
This example builds a futures trend strategy from a linearly weighted moving average and its rate of change. A rate above a positive threshold sets a long position, while a rate below the negative threshold sets a short position. In the neutral band, the…
The strategy combines 9-period and 15-period exponential moving averages with full-body candle patterns to signal directional trades. It enters long when a bullish candle closes above both averages, and short when a bearish candle closes below both. A candle…
This strategy calculates the True Strength Index by double-smoothing price changes and their absolute values with exponential averages. It then smooths the TSI into a signal line, entering long when TSI crosses above that line and closing the position when…
This trend-following method compares a fast and a slow moving average, entering long when the fast line crosses above the slow one and short when it crosses below. Users can select among nine smoothing methods, including simple, exponential, weighted,…
This described strategy combines moving average direction, candlestick patterns, price levels, and volume expansion to signal trades. Its long condition requires the fast average above the slow average, a bullish engulfing pattern, a close above a fixed…
This strategy sets long entry and exit levels by shifting a selected price source by percentages. It uses the prior bar’s close as the reference in its overview: a lower shifted level acts as a limit buy, while an upper level acts as a limit exit. The source…
This trend-following system combines price position relative to VWAP and a short EMA with direction from SuperTrend. It adds several confirmation filters: RSI, Bollinger Band midpoint, Parabolic SAR, MACD, ADX, and Stochastic RSI. Trades are considered only…
This strategy measures the percentage distance between price and a configurable moving average, usually an EMA. It seeks entries when price has moved sufficiently far from the average and closes positions as the gap narrows toward a chosen threshold. The…
This short-term strategy uses a fast and slow exponential moving average to form a MACD line, then compares it with a smoothed signal line. A bullish crossover opens a long position; a bearish crossover closes it. An optional rule also closes the long when…
This strategy attempts to estimate favorable hours for long and short trades from cumulative hourly rate-of-change data. It calculates a weighted average hour using ROC values for the buy estimate and inverse ROC values for the sell estimate, then compares…
This strategy transforms RSI values into a Stochastic RSI oscillator, smooths that series with Ehlers’ SuperSmoother filter, and compares it with a short moving average. The source uses RSI calculated from log-transformed prices, then generates long signals…
This long-only trend-following setup combines a moving-average filter, a candlestick pattern, a momentum threshold, and volatility-based exits. It requires the 100-period EMA to be above the 200-period EMA, then enters when a bullish engulfing condition…
This strategy uses RSI on a higher timeframe to set directional bias, then looks for entries on a lower timeframe. It identifies swing highs and lows in the higher-timeframe RSI over a lookback window. A new swing low paired with the higher-timeframe open…