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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
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
Dokumentu skaits: 682
FMZ digest
Dokumentu skaits: 662
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
Dokumentu skaits: 32
quant-trading
Dokumentu skaits: 31
FinRL
Dokumentu skaits: 28
Zipline
Dokumentu skaits: 22
FMZ live strategies
Dokumentu skaits: 21
Jesse
Dokumentu skaits: 17
pyfolio
Dokumentu skaits: 16
WonderTrader
Dokumentu skaits: 14
Alphalens
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
Dokumentu skaits: 9
QTPyLib
Dokumentu skaits: 8
QuantRocket
Dokumentu skaits: 7
Lumibot strategies
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 12,226

SuperMind

This document describes a Chinese equity screen for 2021. It selects stocks with turnover rates between 3% and 12% and three consecutive declining sessions. The stated rationale is to combine a liquidity or activity filter with recent price weakness, which…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This proposed stock screen selects shares using price amplitude, positive institutional fund flows, and a recent sequence of three limit-up sessions. The article presents the filters as a way to combine short-term price behavior with institutional activity…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This stock-selection proposal combines three filters: a price amplitude threshold, a high dividend ratio for 2019, and at least two limit-up events within a 500-day lookback. The article frames amplitude as a measure of trading activity, the dividend…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-selection approach screens for shares with turnover between 3% and 12% that have declined for seven consecutive days. It also uses a recent two-day high as the stated buy-price reference. The document gives example formula and Python…

AkcijasAtgriešanās pie vidējās vērtībasTehniskie indikatoriĶīnas tirgi
SuperMind

The proposed Chinese equity screen combines an RSI reading below 65 with a qualitative filter for favorable company type and a dividend payout ratio above 25% for 2019. The article describes the payout ratio as a measure of company returns and quality, then…

AkcijasTehniskie indikatoriFaktoru ieguldīšanaRiska pārvaldība
SuperMind

This Chinese stock screen combines a 14-period RSI below 65 with first-level bid volume greater than ask volume and a condition involving five moving averages: 5, 10, 20, 30, and 60 days. The supplied formula requires those averages to be in descending…

AkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This document presents a short-term screen for Chinese main-board stocks. It selects non-ST shares with turnover between 3% and 12%, a daily gain greater than 1%, and no limit-up close on the previous day. The accompanying Python example also checks that the…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This document describes a Chinese A-share screening idea that combines technical conditions with a historical dividend filter. It seeks stocks with RSI below 65, weekly MACD above its zero line, and a dividend ratio above 25% for 2019. The accompanying…

Ķīnas tirgiAkcijasTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This proposed A-share screen focuses on stocks classified in the metaverse theme. It selects names whose price is above the five-day moving average and whose close exceeds both the upper and middle Bollinger Bands, using a 20-period band calculation with a…

AkcijasĶīnas tirgiCenas izrāviensCenas impulss
SuperMind

This proposed A-share stock screen combines a 14-period RSI below 65, an external-to-internal trading volume ratio of at least 1.3, and a positive daily return. The stated intent is to identify stocks with room to rise, using a momentum filter alongside a…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This stock-selection proposal screens companies classified in the metaverse industry for three bullish crossovers: MACD over its signal line, a five-day moving average over a ten-day average, and the five-day average over a twenty-day average. It also…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document outlines a stock selection rule that combines a technical indicator, a fundamental growth measure, and a snapshot of order book pressure. It screens for stocks with RSI below a stated ceiling, parent attributable net profit growth within a…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This document describes a short term stock selection screen for mainland Chinese equities. It selects main board stocks whose turnover falls within a stated range, whose current daily gain exceeds a threshold, and whose prior sessions showed three…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This Chinese-language article proposes screening mainland Chinese stocks with RSI below 65, seven consecutive declining sessions, and a weekly close crossing above the 30-week moving average. It also discusses adding fundamental filters and gives an…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document presents a Chinese equity screen combining daily price range, the presence of an outstanding convertible bond, and positive institutional trading activity. It explains the intended roles of these filters: selecting volatile stocks, using…

AkcijasĶīnas tirgiSvārstīgumsTirgus noskaņojums
SuperMind

This Chinese-language post describes a daily mainland China stock screen. It filters main-board shares to a turnover range of 3% to 12% and a circulating market value between 5 billion and 10 billion yuan, then ranks candidates using the product of daily…

AkcijasĶīnas tirgiCenas impulssStatistika
SuperMind

The document outlines an equity selection rule that filters for turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and a 20-day simple moving average above the 120-day average. The moving-average condition serves as…

AkcijasTehniskie indikatoriSekošana tendenceiĶīnas tirgi
SuperMind

This document describes a daily premarket stock screen combining MACD above zero, positive trailing P/E, and a rounded candlestick condition. It interprets positive MACD as an upward trend signal, positive P/E as a normal valuation reading, and the candle…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This screening approach selects stocks classified in the metaverse industry when the KDJ indicator has just formed a bullish crossover and the reported daily position increase exceeds 5%. The document gives platform formula guidance and a Python example that…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This stock-selection rule filters for turnover between 3% and 12%, an outside-volume to inside-volume ratio above 1.3, and a maximum daily decline between 4% and 5%. The article presents the combination as a way to find liquid stocks with buying pressure…

AkcijasTirgus mikrostruktūraTehniskie indikatori
SuperMind

This Chinese stock-selection note describes a three-condition screen: ten-day price gain above zero but below 35, MACD below zero two days earlier, and amplitude above 1. It frames the conditions as combining recent performance, a technical indicator, and…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The document proposes a stock screen that combines technical weakness with a fundamental growth condition. It selects stocks with RSI below 65, seven consecutive sessions in which the close is below the open, and year-over-year growth in net profit…

Ķīnas tirgiAkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This document presents a stock-selection screen for Chinese A-shares. It combines RSI below 65, an external-to-internal trading volume ratio above 1.3, and a close above the previous session’s low. The sample screening logic also restricts floating market…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus noskaņojums
SuperMind

This Chinese equity screening note selects stocks with a daily amplitude above a threshold, a prior-day “main force control” condition, and a positive daily MACD. It frames these criteria as combining volatility, inferred trading control, and improving…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss