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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
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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
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Kvantitatīvās tirdzniecības kursu bibliotēka
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OctoBot
Dokumentu skaits: 152
Cryptohopper blog
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Systematic trading blog (Rob Carver)
Dokumentu skaits: 132
Qlib
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Quantpedia
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TqSdk
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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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Quantopian lekcijas
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Binance API docs
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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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Alphalens
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WonderTrader
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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

This trend-following method builds a modified price-volume trend measure by accumulating volume-scaled percentage changes in price. It divides volume by 50,000, multiplies that value by the relative change in the typical price, and adds the result to the…

Nākotnes līgumiKriptoaktīviSekošana tendenceiTehniskie indikatori
Strategy library

This strategy combines a 200-period simple moving average for broad trend direction with volume, RSI, and MACD conditions for entries. A long setup requires price above the moving average, RSI above 50, a bullish MACD crossover, and volume greater than 1.2…

Nākotnes līgumiKriptoaktīviSekošana tendenceiCenas impulss
Strategy library

The strategy defines Open Market Exposure (OME) as the current close relative to the prior bar's open, accumulates that measure within each day, and uses threshold levels to manage a long position. It enters when cumulative OME is above a positive threshold…

Nākotnes līgumiTehniskie indikatoriRiska pārvaldībaVēsturisko datu pārbaude
Strategy library

This trend-following strategy compares a conventional EMA with an adaptive zero-lag EMA. The adaptive period can be estimated with cosine or I-Q instantaneous-frequency methods, or an average of both. A crossover of the adaptive line above the conventional…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This example demonstrates how an algorithm can submit a covered call through an option strategy helper and check the resulting position group. It selects a call contract near the underlying price, preferring later expirations among the sorted candidates,…

OpcijasAkcijasRīkojumu izpilde
Strategy library

This five-minute long-only strategy combines MACD, a short-period RSI, and Bollinger Bands. It enters when MACD is above zero and its signal line, the upper Bollinger Band is rising, and RSI exceeds 70. It exits when RSI rises above 80. The author describes…

Cenas impulssTehniskie indikatoriRiska pārvaldība
Strategy library

This stock-oriented strategy combines RSI with a short moving average to seek long entries near potential price reversals. It uses a 14-period RSI and a 9-period simple moving average in the published parameters. A long entry is triggered when RSI is below…

Atgriešanās pie vidējās vērtībasTehniskie indikatoriRiska pārvaldībaNākotnes līgumi
Strategy library

This strategy uses a K-nearest-neighbors model to turn seven technical features into a directional prediction: price momentum, RSI, volume ratio, volatility, trend strength, MACD, and Bollinger Band position. The features are Z-score standardized so their…

Nākotnes līgumiMašīnmācīšanāsTehniskie indikatoriStatistika
Strategy library

This strategy applies Bollinger-style bands to an oscillator rather than directly to price. It calculates RSI or Money Flow Index from price and volume, forms bands around the selected indicator, and looks for readings beyond the lower or upper band…

Nākotnes līgumiKriptoaktīviAtgriešanās pie vidējās vērtībasTehniskie indikatori
Strategy library

The strategy calculates a simple moving average and places several offset levels above and below it. Limit orders at the lower levels can build a long position, while orders at upper levels can build a short position. The number of levels, their percentage…

Nākotnes līgumiKriptoaktīviSekošana tendenceiTehniskie indikatori
Strategy library

This strategy combines Bollinger Bands with a moving average alignment filter to seek entries during an established upward trend. It calculates seven averages spanning short to long lookbacks and scores their ordering to estimate trend direction. A long…

Nākotnes līgumiKriptoaktīviSekošana tendenceiTehniskie indikatori
Strategy library

This strategy uses pivot highs and lows to construct rising support and falling resistance lines, then trades price crossings of those lines. A close crossing above resistance triggers a long signal, while a crossing below support triggers a short signal.…

Nākotnes līgumiKriptoaktīviCenas izrāviensSekošana tendencei
Strategy library

This script pairs MACD crossovers with RSI thresholds to time long and short entries in a strategy presented for choppy crypto markets. A bullish MACD crossover is accepted when RSI is below its configured threshold; a bearish crossover is accepted when RSI…

KriptoaktīviTehniskie indikatoriCenas impulssRiska pārvaldība
Strategy library

This proposed system combines five signal families: MACD crossovers, Stochastic RSI thresholds, RSI-based overbought and oversold conditions, Supertrend direction changes, and moving-average crossovers. It assigns configurable weights to their signals and…

Tehniskie indikatoriSekošana tendenceiAtgriešanās pie vidējās vērtībasRiska pārvaldība
Strategy library

This example calculates an AR price-momentum measure from the prior 14 daily bars. It sums the differences between each bar's high and open, divides by the sum of the differences between open and low, and multiplies by 100. If the denominator is zero, it…

Nākotnes līgumiIzejvielasCenas impulssTehniskie indikatori
Strategy library

This indicator fits a linear regression to a selected price series over a configurable lookback, which defaults to 100 bars. It estimates dispersion around the fitted line from the squared residuals, then places upper and lower bands at a chosen multiple of…

Tehniskie indikatoriStatistikaKriptoaktīviVēsturisko datu pārbaude
Strategy library

This strategy sets long and short price thresholds around the previous day’s close using the Average True Range (ATR). A move beyond the close by 0.8 ATR triggers an entry, with the description specifying ten lots. It defines stop and profit levels using ATR…

Nākotnes līgumiKriptoaktīviSekošana tendenceiSvārstīgums
Strategy library

This trend-following system uses 21-, 50-, and 100-period simple moving averages. On the stated primary five-minute timeframe, a long signal occurs when the fast average crosses above the middle average while both are above the 100-period filter. A short or…

Sekošana tendenceiTehniskie indikatoriRiska pārvaldībaVēsturisko datu pārbaude
Strategy library

The available source describes a multi-timeframe MACD signal score built from changes in the MACD line and histogram, with extra weight for signal-line crossovers. The current-timeframe score is blended with a higher-timeframe score, whose interval is…

Sekošana tendenceiCenas impulssTehniskie indikatoriSvārstīgums
Strategy library

This strategy combines a 200-period exponential moving average trend filter, RSI thresholds, and bullish or bearish candlestick patterns. Long entries require price above the average, RSI below its upper threshold, and either an engulfing candle or pin bar;…

Nākotnes līgumiSekošana tendenceiCenas impulssTehniskie indikatori
Strategy library

The strategy treats five ordered exponential moving averages as a trend channel. It looks for a pullback into that channel while RSI remains above a bullish threshold or below a bearish threshold, then enters when price crosses back through the fastest EMA.…

Nākotnes līgumiSekošana tendenceiCenas impulssTehniskie indikatori
Strategy library

This strategy combines Ichimoku signals with moving average and weekly RSI filters. It proposes long entries when the Tenkan line is above the Kijun line and price is above the cloud; short entries use the reverse conditions. Optional trend filters compare…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This basic trend-following method compares a fast simple moving average with a slower one. It enters long when the fast average crosses above the slow average and enters short when it crosses below. The average periods are adjustable; the source lists…

Sekošana tendenceiTehniskie indikatoriNākotnes līgumiKriptoaktīvi
Strategy library

This trend-following approach combines fast and slow exponential moving averages (EMAs) with RSI and MACD confirmation. It signals a long entry when the fast EMA crosses above the slow EMA, RSI is above 50, and the MACD line is above its signal line. The…

KriptoaktīviNākotnes līgumiSekošana tendenceiCenas impulss