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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
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Strategy library
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MQL5 code base
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BigQuant
Dokumentu skaits: 3,481
Bitget Academy
Dokumentu skaits: 3,298
MQL5 articles
Dokumentu skaits: 3,012
TradingView scripts
Dokumentu skaits: 1,976
ProRealCode
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Deribit Insights
Dokumentu skaits: 1,232
Machine Learning for Trading
Dokumentu skaits: 1,124
arXiv papers
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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
Quantopian lekcijas
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Binance API docs
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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
Alphalens
Dokumentu skaits: 14
WonderTrader
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 stock screen selects Chinese A-shares outside the Beijing market with turnover between 3% and 12%, then filters for an opening auction price change above -2% and below 5%. The document gives a formula-style expression and a Python example intended to…

AkcijasĶīnas tirgiCenas impulss
SuperMind

This post proposes an A-share stock screen combining an RSI below 65, a positive product of daily price change and a proxy for very large order net volume, a limit-up event within roughly the past month, and a price-to-earnings ratio below 30. It describes…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This stock-selection approach combines three technical conditions: a daily high-low range above one percent, a newly formed KDJ bullish crossover, and an upward-sloping 30-day moving average. The article proposes using stocks that meet all three conditions…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This algorithmic strategy combines a nine-signal Piotroski-style fundamental score with short-term return reversal. It ranks stocks using the most recently available quarterly statements, classifies firms as strong, middle, or weak on fundamentals, and pairs…

AkcijasAtgriešanās pie vidējās vērtībasFaktoru ieguldīšanaPortfeļa veidošana
SuperMind

This post describes a short-term Chinese stock screen combining daily amplitude, a proxy for main-force control, and a run of at least three consecutive advances. It frames the conditions as a way to find volatile stocks with strong recent price action. The…

Ķīnas tirgiAkcijasCenas impulssCenas izrāviens
SuperMind

This historical stock screen combines a daily price-amplitude condition with a date filter and a morning star candlestick signal. It looks for observations from 2021 where the high-to-low range exceeds 1% under the formula shown, and where the pattern…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This stock selection method combines a technical filter with earnings growth and valuation criteria. It selects Shenzhen main-board stocks whose RSI is below 65, whose parent-company net profit growth is above 20% and no more than 100%, whose…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This proposed screen starts with Chinese stocks whose codes begin with 60 and whose turnover rate is between 3% and 12%, then says to rank qualifying names by individual-stock attention or popularity. The accompanying explanation treats attention as a proxy…

AkcijasĶīnas tirgiTirgus noskaņojumsTehniskie indikatori
SuperMind

This proposed Chinese equity screen selects stocks with daily turnover between 3% and 12%, a reversal or engulfing-style pattern, and a listing history longer than a chosen number of years. The article illustrates the pattern using daily price ranges and a…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese A-share screening proposal combines three conditions: RSI below 65, upward-diverging moving averages on the current day, and at least two limit-up sessions within the preceding 500 days. The article presents the screen as a way to combine…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock-screening idea combines trading activity, recent price movement, and a qualitative early-uptrend condition. It selects shares with turnover between 3% and 12%, a positive ten-day gain below 35%, and a pattern described as the start of a major…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This A-share screening idea looks for stocks associated with the metaverse theme, a circulating share count no greater than 5.5 billion shares, and at least one limit-up day during the prior 25 trading days. The document frames the filters as a way to focus…

AkcijasCenas impulssĶīnas tirgiTehniskie indikatori
SuperMind

This A-share stock screen combines three conditions: daily turnover between 3% and 12%, an opening price within 5% of the ten-day simple moving average of closing prices, and circulating market capitalization between 5 billion and 10 billion yuan. It uses…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

This stock screen ranks candidates by a volume ratio, then filters for positive large-order net volume above 0.05 for at least three consecutive days and a rising 30-day average. The article interprets stronger volume ratios and persistent large-order…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese stock-screening example selects shares in the metaverse industry whose circulating share count is at most 5.5 billion and whose price is at or above its five-day moving average. It presents the rule as a technical filter intended to identify…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

This post proposes screening main-board shares with turnover rates between 3% and 12%, a daily gain above 1%, and an opening price near the 10-day moving average. Its example defines “near” as within 3% of that average. The rationale is to find short-term…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This post describes a short-term equity screen requiring daily price amplitude above 1, evidence of main-force control on the previous day, and a share price below 12. It characterizes the filters as combining technical and fundamental considerations,…

AkcijasTehniskie indikatoriRiska pārvaldībaĶīnas tirgi
SuperMind

This Chinese stock-screening post proposes selecting beverage and alcohol import-export companies with a 14-period RSI below 65 and previous-day turnover value above 60 million yuan. It presents RSI as a gauge of buying and selling conditions, sector…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

This stock selection rule screens for turnover between 3% and 12%, a rising DEA indicator, and a maximum holder concentration value no greater than 20%. The article describes the concentration filter as a way to favor stocks with more dispersed holdings and…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This stock screen combines three conditions: turnover between 3% and 12%, a rising DEA indicator, and a low price threshold. Its accompanying formula describes DEA through moving-average relationships, while the Python example calculates the indicator and…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese-language post describes a short-term A-share screening rule: select stocks in the metaverse sector, require the reported opening-price change at 9:25 to be below six percent, and require a positive institutional-flow indicator. It presents a…

AkcijasĶīnas tirgiTirgus noskaņojumsTehniskie indikatori
SuperMind

This stock-selection idea combines an amplitude filter with a weekly moving-average crossover and a condition described as the start of a strong upward move. The intended approach is to identify stocks near the beginning of a rising trend, then assess them…

AkcijasSekošana tendenceiTehniskie indikatoriCenas impulss
SuperMind

This daily post-close stock screen selects shares whose MACD reading is above zero and whose short-to-long moving-average sequence is rising. It then orders eligible names by a measure of individual-stock heat, intended to represent market attention. The…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This stock-screening concept targets Chinese A-share companies with positive earnings, market capitalization below the stated ceiling, a daily high-low range above the stated threshold, and a nonempty name for an outstanding convertible bond. The document…

Ķīnas tirgiAkcijasTehniskie indikatoriFaktoru ieguldīšana