Teadmiste raamatukogu

This strategy combines Hammer and Shooting Star candlestick patterns with an Average True Range filter. It defines each pattern using the relative lengths of candle bodies and wicks, and requires the candle’s total range to exceed an ATR-based threshold. A…

This Freqtrade example shows how to use Parabolic SAR (PSAR) values to set a custom stop loss. The indicator is calculated for each candle, and the callback retrieves the latest analyzed value when a trade is active. It then converts the difference between…

This intraday long strategy seeks bull flags in small-cap stocks during the morning session. It first detects a bullish impulse bar whose range exceeds an ATR-based threshold and whose volume is elevated relative to its moving average. It then tracks a…

This strategy adapts a squeeze-momentum indicator to trade volatility breakouts. It identifies a squeeze when Bollinger Bands fall inside Keltner Channels, then waits for the squeeze to release and uses the direction of a linear-regression momentum measure…

This document describes a single-pair implementation of a long-only dollar-cost-averaging strategy driven by three RSI signals. The base order starts when a 14-period RSI on a 15-minute chart crosses above 30. Additional safety orders require a rebound…

This strategy uses the Ichimoku cloud to identify medium- to long-term directional moves. Its entry rule compares the close with the cloud boundaries, calculated from Senkou Span A and B: a close crossing above the upper boundary signals a long, while a…

This SOLUSDT perpetual strategy is a long-only averaging framework. Its entry filter is a 14-period RSI below 28 on a four-hour timeframe. After a base order, it places up to five additional orders at fixed price declines from the base entry: 2%, 5%, 9.5%,…

This trend-following strategy watches price crossings of four simple moving averages: 21, 50, 100, and 200 periods. A close crossing above any one of them triggers a long entry, while a cross below any one triggers a short. The source also calculates stop…

The strategy uses ATR-based SuperTrend direction changes to generate long and short signals, then filters entries by the price’s position relative to a long-term average. The accompanying explanation describes a DEMA filter, requiring price above the average…

This strategy looks to buy short-term weakness while the market remains above a long-term moving average. It enters long when the close is above the 200-day simple moving average but below the 10-day average, with RSI(3) below 30. The stated rules set a stop…

This strategy combines RSI, MACD histogram direction, above-average volume, and a 50-period simple moving average to form long and short entry conditions. Long signals require RSI above the oversold threshold, positive MACD histogram, elevated volume, and…

This cryptocurrency futures strategy identifies turning points in two exponential moving averages. A bullish setup occurs when both averages form a local trough across recent bars; a bearish setup occurs when both form a local peak. The system enters long or…

This two-sided strategy tracks the latest close associated with an up move and the latest close associated with a down move. It measures the current close’s percentage change from each reference level, then compares those changes with configurable thresholds…

This strategy uses five-minute bars on bank and other indices to enter when price moves beyond a recent high-low range. It compares the selected price series with the prior bar’s highest and lowest levels over a configurable lookback, then requires an…

The excerpt is for a multi-session strategy organized around intrabar volume delta and point-of-control levels. Its settings include lower-timeframe data, a configurable delta-profile lookback, POC cluster zones, optional London, New York, and Asia session…

This long-only trend system layers a long-term EMA filter with Williams Alligator and Fractals to establish trend direction, then uses an Awesome Oscillator saucer pattern to time entries. It can add positions as further signals appear, allocating a portion…

This trend-following strategy lets the user select a price input and moving-average calculation, then compares the resulting average with a percentage-based adaptive stop line. The source generates long and short entries when the average crosses that line in…

This BTC futures strategy combines a rate-of-change measure with three simple moving averages. It enters long when price is below a reference average, the lookback price range exceeds a lower ROC threshold, and the fast average is rising while the slow one…

This strategy combines a reversal signal based on closing-price patterns and the Stochastic oscillator with a direction signal from the Chande Forecast Oscillator. The reversal component looks for a two-bar change in closing-price direction alongside a…

This example describes two triangular arbitrage directions across BTC/USDT, LTC/USDT, and LTC/BTC markets. It compares prices from the three tickers and estimates whether converting through the triangle could yield a positive return after applying a stated…

This strategy uses the Detrended Price Oscillator (DPO) and an EMA of the DPO to generate long entries and exits. It calculates a 24-period simple moving average, reads a displaced value of that average, and subtracts it from the close to form the…

This tutorial implements a SuperTrend strategy for a BTC futures contract. It calculates ATR-based upper and lower bands around the midpoint of each bar, then carries forward adjusted bands to define the active trend line. A change in which side of the line…

This strategy opens a long or short position in a chosen calendar month and closes it in another chosen month, aiming to capture recurring seasonal price behavior. The example enters in October and exits in January. It permits only one open position at a…

This framework combines trend, momentum, volume, volatility, and candle-pattern inputs to classify the market into ten named states. It describes indicators including EMA, MACD, RSI, ATR, and volume averages, then assigns different weights to signals…