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Stratmill pētniecības aģenta sagatavoti kopsavilkumi un galvenās atziņas par grāmatām, pētījumiem, rakstiem un kodu, ko lasa mūsu MI aģenti. Katrā lapā ir saite uz oriģinālu.

Quant Q&A
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SuperMind
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OKX Learn
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Strategy library
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MQL5 code base
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BigQuant
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Bitget Academy
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MQL5 articles
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TradingView scripts
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ProRealCode
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Deribit Insights
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Machine Learning for Trading
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arXiv papers
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Amberdata research
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FMZ forum
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FMZ digest
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vn.py community
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QuantInsti blog
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Galaxy Research
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QuantStart
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Stratmill research code
Dokumentu skaits: 219
Robot Wealth
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NautilusTrader
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Hummingbot docs
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Paradigm research
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Lumibot
Dokumentu skaits: 164
Kraken Learn
Dokumentu skaits: 163
Kvantitatīvās tirdzniecības kursu bibliotēka
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OctoBot
Dokumentu skaits: 152
Cryptohopper blog
Dokumentu skaits: 144
Systematic trading blog (Rob Carver)
Dokumentu skaits: 132
Qlib
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TqSdk
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Quantpedia
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Hyperliquid docs
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Freqtrade
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Hudson & Thames
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Awesome Systematic Trading
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backtrader
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vn.py
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Binance API docs
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Quantopian lekcijas
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FMZ guides
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pysystemtrade
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Freqtrade docs
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quant-trading
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FinRL
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Zipline
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FMZ live strategies
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Jesse
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pyfolio
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WonderTrader
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Alphalens
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backtesting.py
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Technical Analysis
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QTPyLib
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QuantRocket
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Lumibot strategies
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Awesome Quant
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Meklēt bibliotēkā

Dokumentu skaits: 7,910

Strategy library

The described method uses the prior day's high, low, and close to derive a pivot reference, then considers long trades when price reaches support and short trades when it reaches resistance. ATR sets volatility-scaled stop-loss and take-profit distances,…

KriptoaktīviNākotnes līgumiTehniskie indikatoriRiska pārvaldība
Strategy library

This strategy uses a higher timeframe to establish direction from a break of structure (BOS), then searches a lower timeframe for a fair value gap (FVG) as a potential entry area. The described long setup combines an upward structure break with an upward gap…

KriptoaktīviNākotnes līgumiCenas izrāviensTehniskie indikatori
Strategy library

This intraday trend-following strategy derives three moving-average series by applying selected Fourier sinusoidal components to price, then smoothing them with a configurable moving-average type. It enters long when the fast series is above the middle…

Sekošana tendenceiTehniskie indikatoriPozīcijas apjoma noteikšanaRiska pārvaldība
Strategy library

This strategy combines a 20-period and 200-period EMA crossover with an RVI direction check and a third, external buy or sell signal. A long entry requires all three conditions to align; short entries reverse them. ATR is used to set stop-loss and…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This example pairs a long-entry trigger from a WaveTrend crossover with layered exit management. It describes four percentage-based profit targets that can close portions of a position, alongside potential target levels drawn from 100- and 200-period…

KriptoaktīviNākotnes līgumiTehniskie indikatoriRiska pārvaldība
Strategy library

This long-only strategy compares price with three Bollinger Band envelopes calculated over 20, 120, and 240 periods, each using a simple moving average and bands two standard deviations away. It enters a long position when the close is below all three lower…

KriptoaktīviSekošana tendenceiCenas izrāviensTehniskie indikatori
Strategy library

This strategy uses a fast and a slow exponential moving average to identify possible trend changes. A fast EMA crossing above the slow EMA triggers a long entry when RSI is below its overbought threshold; a cross below prompts a short entry when RSI is above…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This strategy uses a fast and a slow exponential moving average to identify possible trend changes. A bullish crossover generates a long entry signal, while a bearish crossover closes longs and can open shorts. RSI acts as a filter: the long entry requires…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This example demonstrates a lightweight account event stream: it requests a Binance user data listen key, opens a WebSocket connection for that stream, and renews the key every 30 minutes. It filters incoming account events for trade execution reports and…

KriptoaktīviRīkojumu izpildeTirgus mikrostruktūra
Strategy library

WJ Strategy B builds a composite score from three kinds of weakness: price below the lower Bollinger Band, price below progressively longer moving averages, and low RSI readings. When the score reaches at least 3, the strategy starts monitoring rather than…

Atgriešanās pie vidējās vērtībasTehniskie indikatoriPozīcijas apjoma noteikšanaRiska pārvaldība
Strategy library

This strategy combines short-term signals with a higher-timeframe trend filter. It uses a custom order-block calculation based on the recent high-low range, SMA crossovers for short-term direction, and 1-hour EMA 50 and EMA 200 values to define the broader…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This strategy buys when a 14-period relative strength index (RSI), calculated on 30-minute data, falls below 30. It is described as a multi-timeframe setup for trading on a 1-hour chart. After entry, the script records a take-profit price set at a default 3%…

Nākotnes līgumiAtgriešanās pie vidējās vērtībasTehniskie indikatoriRiska pārvaldība
Strategy library

This short-term strategy signals long trades when price crosses above a simple moving average (SMA) and short trades when it crosses below. Its default SMA length is 20, and it closes positions when the bar’s high or low reaches a fixed point target relative…

Nākotnes līgumiCenas impulssTehniskie indikatoriRiska pārvaldība
Strategy library

This strategy uses the 200-period exponential moving average (EMA) as a directional filter: long entries are allowed above it and short entries below it. The source also uses crossovers between 14- and 28-period simple moving averages (SMAs) to trigger…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriSvārstīgums
Strategy library

This example uses a RidgeClassifier to predict whether each crypto futures asset’s next closing price will rise or fall. For features, it takes the logarithms of recent closing prices from three other futures contracts, then fits a separate classifier for…

KriptoaktīviNākotnes līgumiMašīnmācīšanāsVēsturisko datu pārbaude
Strategy library

This strategy description proposes combining short and long EMAs for direction with RSI, MACD, Bollinger Bands, volume, and ADX as additional filters. It also describes a stop distance based on ATR. The stated concept is to seek trades using several kinds of…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This document introduces a Bitcoin strategy intended for 1-hour charts. It describes a multi-timeframe engulfing setup with stop-loss flips, pyramiding, and tuned indicators. The visible settings include equity-based trade sizing, a drawdown halt, a capped…

KriptoaktīviTehniskie indikatoriRiska pārvaldībaPozīcijas apjoma noteikšana
Strategy library

This example demonstrates how to combine incoming futures quote data into larger time-based bars for use in an algorithm. It subscribes to an S&P 500 E-mini futures chain, filters contracts by expiry, and creates a five-minute quote-bar consolidator for each…

Nākotnes līgumiTirgus mikrostruktūraRīkojumu izpilde
Strategy library

This swing-trading framework combines SuperTrend for direction, ADX for trend strength, and a volume-based liquidity delta for buying and selling pressure. Optional Parabolic SAR adds another directional check. The described logic produces a signal only when…

Vairāku aktīvu tirdzniecībaSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This trend-following method calculates price momentum as the percentage change over a lookback period, then normalizes recent momentum values to a zero-to-one range. It compares the normalized reading with a midpoint threshold and checks price relative to a…

Nākotnes līgumiSekošana tendenceiCenas impulssTehniskie indikatori
Strategy library

This strategy combines a long-term EMA alignment filter with pullback entries and volatility-based exits. It identifies an uptrend when the 20-, 50-, 100-, and 200-period EMAs are ordered from shortest to longest, then enters long when price is between the…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This document describes a trend strategy using a 10-period fast EMA and a 20-period slow EMA. The fast average above the slow one marks bullish direction and below it marks bearish direction; the source enters long or short according to that state. It also…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This short-term strategy combines a 21-period and 65-period EMA pair, RSI, and ATR. The description presents the EMA cross as a broad trend filter and RSI above or below 50 as a directional check. Its source triggers entries when price moves beyond an…

Nākotnes līgumiKriptoaktīviAugstas frekvences tirdzniecībaTehniskie indikatori
Strategy library

This strategy uses a short and a long exponential moving average to indicate direction. With the stated defaults of 20 and 50 periods, a cross above the longer average signals a long entry, while a cross below signals a short entry. Its code tracks position…

KriptoaktīviNākotnes līgumiSekošana tendenceiCenas impulss