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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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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
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Kraken Learn
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Kvantitatīvās tirdzniecības kursu bibliotēka
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OctoBot
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Cryptohopper blog
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Systematic trading blog (Rob Carver)
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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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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 machine-learning example predicts whether each crypto futures asset’s next closing price will rise or not, then uses those binary predictions as portfolio weights. It builds candidate features from futures data, including a weighted moving-average trend…

KriptoaktīviNākotnes līgumiMašīnmācīšanāsStatistika
Strategy library

This approach combines a price reversal rule based on recent closes and the stochastic oscillator with a Triple Exponential Moving Average (TEMA) direction filter. The reversal component produces a bullish or bearish state from a two-step change in closing…

KriptoaktīviNākotnes līgumiTehniskie indikatoriSekošana tendencei
Strategy library

This strategy looks for disagreement between price pivots and RSI pivots. A regular bullish divergence pairs a lower price low with a higher RSI low, while a regular bearish divergence pairs a higher price high with a lower RSI high. The described entry…

KriptoaktīviNākotnes līgumiTehniskie indikatoriAtgriešanās pie vidējās vērtības
Strategy library

This strategy combines a fast and slow EMA crossover with a higher-timeframe EMA filter. It describes long entries when the fast EMA crosses above the slow EMA while above the reference EMA, or crosses above the reference EMA itself; short signals use the…

Nākotnes līgumiKriptoaktīviSekošana tendenceiTehniskie indikatori
Strategy library

The described method seeks aligned directional signals from a bundle of indicators: a fast/slow moving-average crossover, MACD, RSI, stochastic, and price relative to VWAP. A long signal requires bullish readings across those measures, while a short signal…

Tehniskie indikatoriCenas impulssRiska pārvaldībaVēsturisko datu pārbaude
Strategy library

This strategy combines several technical measures on 15-minute price data to produce long and short signals. A 10-period and 30-period simple moving average crossover sets direction; MACD, RSI relative to 50, price relative to a volume-weighted average, and…

Tehniskie indikatoriCenas impulssRiska pārvaldībaVēsturisko datu pārbaude
Strategy library

The document describes a short-term crossover strategy using an 8-period EMA and a 34-period EMA for directional signals, with a 200-period simple moving average as a trend filter. It specifies ATR-based exits using a 14-period ATR: a stop at 1.5 times ATR…

Nākotnes līgumiCenas impulssSekošana tendenceiTehniskie indikatori
Strategy library

This script defines momentum as the difference between the current close and the close 12 bars earlier, then measures whether that momentum itself is rising or falling. It places a stop entry one minimum tick above the bar’s high when both measures are…

Cenas impulssTehniskie indikatoriRiska pārvaldība
Strategy library

This tutorial template uses a Ridge Classifier to predict whether a stock's next closing price will be higher or lower than its current close. Its main example loads Amazon data from the Nasdaq-100 universe, uses log closing prices as features, and reserves…

MašīnmācīšanāsAkcijasStatistikaVēsturisko datu pārbaude
Strategy library

This strategy pairs Bollinger Bands with a reversal candle pattern. It looks for a candle whose body is less than half the preceding candle's body, with the two candles changing direction, after the preceding close has moved outside a band. A smaller bullish…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasNākotnes līgumiKriptoaktīvi
Strategy library

This trend strategy combines MACD crossovers with a set of 14 bands. Each band is built from a price linear regression line plus or minus a multiple of price standard deviation over a different lookback. The overview describes selecting the most distant…

Tehniskie indikatoriSekošana tendenceiCenas izrāviensSvārstīgums
Strategy library

This indicator combines Bollinger Bands with a smoothed Stochastic RSI to flag potential reversals. A bullish signal follows a close below the lower band when the next close returns above it and both Stochastic RSI lines are below the lower threshold. A…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasNākotnes līgumiKriptoaktīvi
Strategy library

PresentTrend is a trend-following method that builds a trailing level from average true range and a custom indicator using either RSI or MFI. The indicator’s value is compared with its value two bars earlier to generate long and short signals; a direction…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriSvārstīgums
Strategy library

This document describes an execution utility for opening, closing, or reversing positions in two perpetual futures contracts. When opening, it calculates each leg's quantity from a shared per-asset value and the current ticker price, with a contract-value…

Nākotnes līgumiPerpetuālie nākotnes līgumiArbitrāžaRīkojumu izpilde
Strategy library

This cryptocurrency strategy uses a 50-period EMA and a 100-period SMA to set direction: an upward crossover opens a long position, while a downward crossover opens a short. RSI provides exit conditions, closing longs above the stated overbought level and…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This BTC perpetual futures strategy combines an EMA crossover with RSI and ADX filters. It enters long when price crosses above the EMA while RSI is above 50 and ADX exceeds a threshold; short entries use the inverse crossover and RSI condition. ATR sets…

Nākotnes līgumiSekošana tendenceiTehniskie indikatoriRiska pārvaldība
Strategy library

This scalping strategy uses higher-timeframe trend filters to constrain entries on a lower timeframe. It compares the current price with exponential moving averages calculated on hourly, four-hour, and daily intervals; longs require price above all three…

Nākotnes līgumiKriptoaktīviTehniskie indikatoriCenas impulss
Strategy library

This strategy combines three exponential moving averages with Supertrend direction. It uses the 5-, 10-, and 20-period averages to identify bullish or bearish alignment: the faster averages must sit on the corresponding side of the 20-period average, with…

Tehniskie indikatoriSekošana tendenceiNākotnes līgumiVēsturisko datu pārbaude
Strategy library

This strategy combines MACD conditions with a 200-period simple moving average to filter directional trades. The described long setup requires positive MACD momentum and histogram readings, the fast average above the slow average, and price above the…

Tehniskie indikatoriSekošana tendenceiCenas impulssNākotnes līgumi
Strategy library

This strategy places a sequence of buy and sell levels across a price range. The range can be set manually or estimated from recent closing prices using highs and lows, or an average with a deviation. Grid spacing follows from the range and the selected…

Režģa tirdzniecībaAtgriešanās pie vidējās vērtībasNākotnes līgumiPozīcijas apjoma noteikšana
Strategy library

This BTC/USDT futures strategy uses the TTM Squeeze framework to identify periods when Bollinger Bands contract inside Keltner Channels. It enters a long position after three consecutive squeeze bars and exits when price crosses below a 21-period simple…

KriptoaktīviNākotnes līgumiCenas izrāviensSvārstīgums
Strategy library

The strategy derives speed, acceleration, jerk, and jounce from a Hull Moving Average. It opens long positions when acceleration, jerk, and jounce are all positive, and shorts when all three are negative. Positions may close on a signal in the opposite…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This one-hour Bitcoin strategy takes short positions when Stochastic RSI forms a reversal signal: K was recently overbought, crosses back below the threshold, and sits below D. It also requires price below a higher-timeframe EMA, a low reading from its VIX…

KriptoaktīviTehniskie indikatoriRiska pārvaldībaSekošana tendencei
Strategy library

This source describes a bar-based moving-average strategy that compares closing prices with a simple moving average and checks the latest price’s distance from that average. An upward-cross signal is intended to open long positions when both the bar close…

AkcijasTehniskie indikatoriPozīcijas apjoma noteikšanaRīkojumu izpilde