Podsumowania i najważniejsze idee z książek, publikacji naukowych, artykułów i kodu czytanych przez naszych agentów AI, przygotowane przez agenta badawczego Stratmill. Każda strona zawiera link do oryginału.
Liczba dokumentów: 7,910
The document presents a multi-stage strategy that combines directional momentum, RSI conditions, and price levels derived from recent pivots and Fibonacci ratios. Its narrative also describes Bollinger Band levels as confirmation and says position size…
This crypto strategy seeks entries in the direction of a broader trend, using EMA20 as a trend filter and EMA9 and EMA14 to locate pullbacks. It signals a long when the close is above EMA20 but below both faster averages while Stochastic RSI is below its…
This BTC/USDT futures strategy uses 20-period Bollinger Bands with a two-standard-deviation width. It opens a long after price falls sufficiently below the lower band or a short after price rises beyond the upper band, subject to a trade-direction setting.…
This breakout strategy defines a price range from the prior bars' highs and lows, then enters long when the close exceeds the range high or short when it falls below the range low. An optional volume condition requires current volume to exceed its moving…
This document describes a Parabolic SAR signal indicator that classifies direction by whether the SAR value is below or above the closing price. A change from below to above the price produces a sell signal, while a change from above to below produces a buy…
This BTC/USDT futures strategy uses a 14-period RSI to open positions and a 30-period RSI to close them. It enters long when the faster RSI crosses above the oversold threshold and short when it crosses below the overbought threshold. Alongside each initial…
This strategy generates direction changes from a 10-period and 30-period simple moving average crossover. The description says RSI and ATR help assess market conditions, while the source calculates both indicators but does not use them to filter entries. On…
This crypto strategy uses Bollinger Bands on 1-, 3-, 5-, and 15-minute horizons to identify potential reversals. It combines signals from the 3- or 5-minute chart with indications on the shorter and longer horizons, and uses Bitcoin’s 5-minute price relative…
This long-only strategy combines Bollinger Band %B with a 200-day simple moving average filter. It considers an entry when the close is above the long-term average and %B has remained below 0.2 for three consecutive days, treating that condition as a…
This document presents a multi-session strategy built around lower-timeframe volume delta and point of control (POC) analysis. It describes a Pine Script setup with optional London, New York, and Asia session filters, configurable trade sizing, fixed…
This intraday strategy records the high and low of the first candle after a configured session start. A close above that range triggers a long entry, while a close below it triggers a short entry. It allows at most one trade per day. The stop for a long is…
This basic Binance futures grid method records an initial reference price when it starts. It places a short-side order when price is above that anchor and a long-side order when price is below it, using a configurable order value and grid spacing. The…
This strategy uses a fast and slow simple moving average crossover to enter long positions: it buys when the fast average crosses above the slow one. It closes on a bearish crossover unless trailing exits are enabled, in which case a stop follows rising…
This trend-following system combines short- and long-period Hull moving averages (HMAs) for directional entries. A crossover between the shorter averages is filtered by the relative position of longer averages, forming a trend regime. Once in a position, the…
This script describes a session-filtered trading strategy built around the Arnaud Legoux Moving Average (ALMA). It enters long when price is above the baseline and short when below, subject to selected London and New York trading windows. An optional TTM…
This example demonstrates using Python's asyncio and aiohttp to request market data from a futures exchange API. Separate asynchronous functions fetch exchange information, order-book depth, candlesticks, and ticker prices. The main routine schedules…
This strategy uses a 200-period simple moving average as a trend reference. It identifies a cross above or below that average, then seeks a retest within five periods before entering in the breakout direction. Stop-loss and take-profit distances are tied to…
This document describes a selective options-selling approach that combines trend, reversal, volatility, and time filters. It proposes selling calls when the longer-term trend is bearish and price is overbought at the upper Bollinger Band, and selling puts…
This strategy combines a simple moving average as a fair-value reference with recent price ranges labeled as order blocks. It examines the highest high and lowest low over a configurable lookback, then compares the current close with the moving average. The…
This document presents a charting strategy that combines a short 5-period SMA and a longer 20-period SMA with Bollinger Bands, RSI, Ichimoku components, momentum, and rate of change. The crossover of the two SMAs marks potential directional changes. The…
This strategy adapts a squeeze momentum indicator that compares Bollinger Bands with Keltner Channels. It identifies a squeeze when the Bollinger Bands sit inside the Keltner Channels and treats the transition out of that state as a potential entry context.…
This strategy uses a 14-period simple moving average and a 28-period simple moving average to signal directional changes. A cross of the faster average above the slower one prompts a long entry, while a cross below prompts a short entry. The document also…
This strategy uses an ATR-based stop that is smoothed with a recursive moving average to track price trends. The long stop is based on the midpoint price minus smoothed ATR, while the short stop uses the midpoint plus smoothed ATR. Stop levels ratchet with…
This configurable strategy uses RSI extremes to identify possible reversals, short simple moving averages to define entry context and exits, and an optional longer moving average to filter trades by trend. A long setup occurs when RSI is below its lower…