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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
Dokumentu skaits: 20,364
SuperMind
Dokumentu skaits: 12,226
OKX Learn
Dokumentu skaits: 8,431
Strategy library
Dokumentu skaits: 7,910
MQL5 code base
Dokumentu skaits: 7,090
BigQuant
Dokumentu skaits: 3,481
Bitget Academy
Dokumentu skaits: 3,298
MQL5 articles
Dokumentu skaits: 3,012
TradingView scripts
Dokumentu skaits: 1,976
ProRealCode
Dokumentu skaits: 1,507
Deribit Insights
Dokumentu skaits: 1,232
Machine Learning for Trading
Dokumentu skaits: 1,124
arXiv papers
Dokumentu skaits: 1,033
Amberdata research
Dokumentu skaits: 766
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
Dokumentu skaits: 340
QuantStart
Dokumentu skaits: 246
Stratmill research code
Dokumentu skaits: 219
Robot Wealth
Dokumentu skaits: 195
NautilusTrader
Dokumentu skaits: 191
Hummingbot docs
Dokumentu skaits: 181
Paradigm research
Dokumentu skaits: 175
Lumibot
Dokumentu skaits: 164
Kraken Learn
Dokumentu skaits: 163
Kvantitatīvās tirdzniecības kursu bibliotēka
Dokumentu skaits: 157
OctoBot
Dokumentu skaits: 152
Cryptohopper blog
Dokumentu skaits: 144
Systematic trading blog (Rob Carver)
Dokumentu skaits: 132
Qlib
Dokumentu skaits: 116
TqSdk
Dokumentu skaits: 86
Quantpedia
Dokumentu skaits: 86
Hyperliquid docs
Dokumentu skaits: 79
Freqtrade
Dokumentu skaits: 68
Hudson & Thames
Dokumentu skaits: 62
Awesome Systematic Trading
Dokumentu skaits: 61
backtrader
Dokumentu skaits: 54
vn.py
Dokumentu skaits: 50
Binance API docs
Dokumentu skaits: 45
Quantopian lekcijas
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FMZ guides
Dokumentu skaits: 38
pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
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quant-trading
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FinRL
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Zipline
Dokumentu skaits: 22
FMZ live strategies
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Jesse
Dokumentu skaits: 17
pyfolio
Dokumentu skaits: 16
WonderTrader
Dokumentu skaits: 14
Alphalens
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
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QTPyLib
Dokumentu skaits: 8
Lumibot strategies
Dokumentu skaits: 7
QuantRocket
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 79,386

SuperMind

This document presents a stock selection rule for Chinese companies classified in the metaverse theme. It screens for previous-day actual turnover between 3% and 28% and requires the daily MACD difference line to be above its signal line. The text explains…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
MQL5 code base

This document explains a chart indicator that builds Fibonacci levels from successive swings identified by the ZigZag indicator. Keyboard controls move through swings, while users can show, hide, drag, or extend a Fibonacci drawing and edit its levels.…

Tehniskie indikatoriSvārstīgumsValūtu tirgus
SuperMind

This document describes a Chinese A-share stock screen combining turnover, market capitalization, profitability, and order-flow measures. It selects stocks with turnover between 3% and 12%, market value below 10 billion yuan, positive average earnings per…

AkcijasĶīnas tirgiTirgus mikrostruktūraStatistika
SuperMind

This stock screen combines three filters: at least five moving averages are described as converging, price-to-earnings and price-to-book ratios fall within specified ranges, and the 20-day moving average is above the 120-day average. The first condition is…

AkcijasTehniskie indikatoriSekošana tendenceiFaktoru ieguldīšana
MQL5 code base

This short description presents a modified display of the Parabolic Stop and Reverse indicator in a separate chart window. Its additional function checks whether the charted instrument has an open position and issues an alert when the SAR signal moves…

Tehniskie indikatoriRiska pārvaldībaRīkojumu izpilde
SuperMind

This Chinese-language article outlines an A-share stock screen combining market capitalization, turnover, a KDJ bullish crossover, and a prior-day opening call-auction price near the daily limit-down level. The final stated criteria require market value…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This stock-selection approach screens companies in the metaverse sector for a bullish MACD crossover and a rising KDJ K value. The post also gives an example implementation that adds a market-cap range, though its code uses a KDJ-based RSI threshold and does…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
ProRealCode

The document describes a short-selling rule set for equities and indices. It opens a short position when the close is below the 200-day moving average and closes have risen for four consecutive days. The position is exited when the close falls below the…

AkcijasSekošana tendenceiTehniskie indikatoriVēsturisko datu pārbaude
Amberdata research

This webinar overview describes a panel discussion about the development of digital asset markets and institutional participation. Its topics include market structure, regulation, trading technologies, institutional entry, and practical approaches to trading…

KriptoaktīviTirgus mikrostruktūraRīkojumu izpilde
MQL5 code base

This brief description introduces a Parabolic Moving Average indicator that displays standard deviation bands. It identifies three user-adjustable inputs: the moving-average period, the price series used for the calculation, and the band deviation. Together,…

Tehniskie indikatoriSvārstīgums
SuperMind

This proposed A-share screen selects stocks with turnover from 3% to 12%, an opening price within roughly 5% of the ten-day moving average, a latest close at or above that average, and at least one limit-up event in the preceding month. The article frames…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-selection proposal filters for turnover between 3% and 12%, a rising DEA signal, and at least one daily gain of 10% or more during the previous 25 trading sessions. The article presents these conditions as a combination of trading…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This proposed Chinese equity screen combines three conditions: at least five moving averages clustered near the closing price, floating market capitalization above 200 million, and more than two limit-up sessions within ten trading days. The article…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock screen combines daily price amplitude and a controlling-shareholder measure with valuation limits for Shenzhen main-board shares. It selects stocks with amplitude above 1, a stated control measure above 21, price-to-earnings ratios from 0 to…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-selection rule screens for main-board shares with turnover between 3% and 12%, a daily gain above 1%, and a reversal-style candle condition. The stated pattern requires the current open to exceed the prior close while the current close falls below…

AkcijasTehniskie indikatoriCenas izrāviensĶīnas tirgi
Qlib

This documentation explains formulaic alpha factors: signals represented as mathematical expressions that can be computed from market data. It uses MACD as an example, defining the signal from the difference between short- and long-period exponential moving…

AkcijasTehniskie indikatoriCenas impulssMašīnmācīšanās
Awesome Systematic Trading

This strategy ranks U.S. stocks by return on assets (ROA) separately within larger- and smaller-capitalization groups. ROA is defined using quarterly income before extraordinary items divided by assets from the prior quarter. Within each size group, it buys…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaASV tirgi
MQL5 code base

This expert advisor concept uses candle size as a trade filter: when a candle exceeds a configurable pip threshold, it opens a buy trade. If that trade loses, the next trade uses a larger lot, with the scaling factor controlled by the user. The author frames…

Valūtu tirgusRiska pārvaldībaVēsturisko datu pārbaude
TqSdk

This example demonstrates an iceberg-style execution workflow for a futures contract. The trader chooses a symbol, a total volume, minimum and maximum order sizes, and a buy or sell direction. A target-position task manages orders toward the desired net…

Nākotnes līgumiRīkojumu izpildeTirgus mikrostruktūra
MQL5 code base

This brief document describes a higher-timeframe version of the HVR indicator. A user selects the indicator’s chart period through an input setting, allowing the HVR display to use a timeframe different from the chart where it is viewed. The description says…

Tehniskie indikatori
MQL5 code base

This document describes an expert advisor built around crossovers between two moving averages, with a third moving average used as a filter. It exposes settings for each average’s period, shift, method, and display color, and describes plotting the averages…

Tehniskie indikatoriSekošana tendenceiPozīcijas apjoma noteikšanaRiska pārvaldība
Kraken Learn

This overview introduces rules-based crypto trading and distinguishes discretionary decision-making from systematic strategies that use indicators, algorithms, or automation. It explains dollar-cost averaging as recurring purchases at fixed intervals, then…

KriptoaktīviTehniskie indikatoriVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

This brief response addresses preprocessing for deep-learning models applied to stock data, including Boolean values and infinite observations. Its direct recommendation for infinities is to remove them. For broader feature preparation, it lists outlier…

MašīnmācīšanāsAkcijasStatistika
SuperMind

The post describes a Chinese equity screening rule combining a 14-period RSI below 65, a specified range for tradable market capitalization, and a share price below 12. When at least five stocks meet the filters, the example selection function sorts…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi