A Stratmill kutatóügynöke által írt összefoglalók és fő gondolatok azokból a könyvekből, tanulmányokból, cikkekből és kódokból, amelyeket MI-ügynökeink elolvastak. Minden oldal az eredeti műre mutat.
Dokumentumok száma: 7,910
This Python example demonstrates an iceberg-style execution workflow for a futures contract using a trading API’s target-position task. The user specifies a target trade amount, a minimum and maximum order size, a buy or sell direction, and an execution…
This strategy combines two simple moving averages (SMAs) with the relative strength index (RSI). The short SMA is compared with the long SMA to define direction: the strategy enters long when the short average is above the long average and RSI is below 30,…
This strategy uses an exponential moving average (EMA) as a reference for price bounces. A bullish setup occurs when the prior candle’s low stayed above the EMA, the current candle’s low dips below it, and the current close finishes above it. A bearish setup…
This strategy turns a Hull moving average indicator into a directional trading system. It compares the current Hull value with a value from two bars earlier: a higher reading triggers a long entry and a lower reading triggers a short entry. The script offers…
This strategy starts with either RSI or MFI as a measure of directional strength, then adjusts the bullish and bearish readings using a Dow-inspired factor: the correlation between price and volume over a configurable lookback. It derives adjusted bull,…
This simple daily trend-following method compares the latest daily close with a configurable moving average. When the close is at or above the average and the strategy is not holding the asset, it buys using 95% of the account balance. When the close falls…
This trend-following system combines a 200-period exponential moving average with an ATR-based Chandelier Exit, Price Volume Trend (PVT), and a momentum oscillator. A long entry requires price above the EMA, a Chandelier buy signal, and confirmation from…
This trend-following approach combines 8- and 21-period exponential moving averages with sequences of higher lows or lower highs. The accompanying description presents those price patterns as confirmation for reversals, with stop-loss and take-profit levels…
This crypto strategy combines a linear-regression approximation to KAMA with TEMA, MACD, RSI, and volume conditions. Long entries require the regression line to cross above TEMA, positive MACD alignment, RSI above its oversold threshold, elevated volume, and…
This futures strategy opens a long position when a 15-minute bar crosses above the upper Bollinger Band, using a 30-bar window and a 2.2 standard-deviation setting. If price later falls at least 4% below the last entry, it adds another long position, with…
This strategy combines Bollinger Bands with a volume threshold to identify breakouts. It calculates a moving average and standard deviation of closing prices over a configurable lookback, then signals a long entry when price closes above the upper band while…
This document describes a trend-following system that uses 5-period and 15-period exponential moving average crossovers to open long or short positions. It places a stop loss 1.5% from entry and a take-profit target 3% from entry, giving a stated 1:2…
This document describes a multi-symbol perpetual-futures strategy whose trading logic is delegated to external services. Its main loop polls for stop commands, applies strategy interactions and symbol selection, checks entry signals, processes reduction…
This controller coordinates multiple configured grids for one trading pair. Each grid has a price range, limit price, side, enable flag, and share of total quote capital. The controller checks the mid-price and creates a grid executor when price is within…
This strategy uses 8-, 13-, and 21-period exponential moving averages relative to a 55-period EMA to identify directional trends. The described approach goes long when all three shorter averages cross above the 55-period average, goes short when they cross…
This short-term strategy combines 10-, 21-, and 50-period moving averages with a 200-period CCI to signal long and short trades. It enters long when the 10-period average is above both longer averages and CCI is positive; the inverse conditions signal a…
This long-only trend-following system compares a 20-period exponential moving average with a 50-period EMA. It enters long when the faster average crosses above the slower one and exits when it crosses below. Optional percentage-based stop-loss and…
This trend-following system uses a fast and slow double exponential moving average (DEMA) to generate directional signals: a cross above prompts a long entry, while a cross below prompts a short signal. A third, configurable DEMA can filter crossovers by…
This strategy uses RSI, a volume-weighted money-flow measure, CCI, and Stoch RSI to identify strong price conditions. Its stated concept is to combine indicator readings around the neutral level of 50, using agreement among measures to confirm a possible…
This futures strategy combines a reversal signal with the Three-Ten oscillator and trades only when both signals agree. The reversal component looks for two consecutive closes moving in the same direction, with a stochastic condition around the 50 level. The…
The strategy computes RSI, applies a stochastic calculation to that RSI, then smooths the K and D lines with simple moving averages. A long entry occurs when K crosses above the oversold threshold, set to 20 by default. The exit order combines a trailing…
This strategy scores long and short setups using four conditions: price relative to a 200-period EMA, volume relative to its moving average, RSI thresholds, and the current candle's direction. When a score reaches a configurable minimum, it places a stop…
This strategy combines a rolling price channel, deviation bands around the channel midpoint, and a two-period RSI to identify potential reversals. Its channel logic retains a bullish or bearish trend state after price moves beyond a band, while bar direction…
This indicator requests prior-period open, high, low, and close data from a selected higher timeframe, converts the values to Heikin-Ashi candles, and smooths each candle component with a selectable moving-average variant. The options include EMA, DEMA,…