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Zināšanu bibliotēka

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
Dokumentu skaits: 682
FMZ digest
Dokumentu skaits: 662
vn.py community
Dokumentu skaits: 560
QuantInsti blog
Dokumentu skaits: 511
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
Dokumentu skaits: 45
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

The article outlines an equity screen combining price amplitude above a stated threshold, rising lows as a sign of an improving base, and a ranking by stock or industry attention. It includes example formula logic and Python-like pseudocode, with the latter…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This proposed equity screen selects companies with price amplitude above one percent, market capitalization within 10 billion, positive average net profit, and a current low below the previous session’s low. The article’s example code extends those…

AkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese stock-selection proposal combines three filters: price amplitude above one, a rounded chart pattern, and a nonempty name for outstanding convertible bonds. A referenced indicator formula expresses the amplitude and chart-shape conditions, while…

AkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-selection method screens companies in the metaverse industry using three simultaneous bullish crossovers: MACD above its signal line, the 5-day moving average above the 10-day average, and the 5-day average above the 20-day average. It also…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This code example demonstrates a data workflow for a FinRL stock-trading project. It fetches a single stock’s price history through both yfinance and FinRL’s Yahoo downloader, then downloads a Dow 30 universe over configured training and trading periods. A…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeStatistika
SuperMind

This stock-selection example combines three filters: RSI below 65, revenue in 2021 more than 1.1 times its 2018 level, and an opening price within 6% of the prior close. It proposes selecting the first N qualifying stocks and holding them for one year. The…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus noskaņojums
SuperMind

The proposed Chinese equity screen selects stocks classified in the metaverse industry when the open is near a ten-day moving average and the 2019 dividend ratio exceeds 25%. The post presents a formula-style version and a Python example. It frames…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

The document proposes a Chinese equity screening rule combining three chart conditions: price amplitude above a threshold, a rounded price pattern, and three consecutive declining closes. It interprets the amplitude condition as a way to find active stocks,…

Ķīnas tirgiAkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese equity screen selects companies in the beverage and alcohol import-export industry when turnover falls within a specified band and the opening price is near the ten-day moving average of closing prices. The post describes the approach as…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This note describes a stock screen that combines technical conditions with a basic growth measure. It proposes selecting stocks with at least five aligned moving averages, ranking them by net large-order volume, and retaining those whose revenue in 2021 was…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This note presents a simple Chinese equity screen for companies classified in the metaverse industry. It selects stocks above a stated scale threshold that appeared on the previous day's exchange trading list, using industry membership, a financial size…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecība
SuperMind

This Chinese equity screen selects stocks with daily amplitude above 1, a reversal or engulfing-style price pattern, and circulating market capitalization above 10 billion yuan. The article describes these filters as a mix of technical conditions and a size…

Ķīnas tirgiAkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese equity screening proposal combines a daily amplitude threshold above 1, a top-five rank by the day’s auction amount, and a closing price above its five-day moving average. It interprets large amplitude and strong auction activity as signs of…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This article explains industry rotation in China’s A-share market, describing how economic cycles, policy, fundamentals, and herding can cause leadership to shift across sectors. It outlines a momentum approach that ranks industry indexes by weighted returns…

Ķīnas tirgiAkcijasCenas impulssSekošana tendencei
SuperMind

This stock-selection method screens for companies listed in 2021, with turnover between 3% and 12%, and a price shape described as rounded over the previous 20 days. The article frames turnover and listing year as basic filters, then adds a recent…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock screen combines three conditions: a 14-period RSI below 65, first-level bid volume greater than ask volume, and a dividend ratio above 25% based on 2019 data. The article presents these filters as a way to combine a technical indicator, order-book…

AkcijasTehniskie indikatoriTirgus noskaņojumsRiska pārvaldība
SuperMind

This post describes a Chinese-equity screening rule that combines membership in the metaverse theme with positive net buying attributed to major participants during the opening auction. It further limits candidates to Shenzhen main-board stocks using…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
SuperMind

This article outlines a Chinese stock selection screen using daily price range, market capitalization, profitability, and MACD. The initial rules look for stocks whose high-to-low range exceeds 1%, whose market value is below 10 billion yuan, whose net…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese-language article describes a mainland China stock screen combining technical and fundamental filters. It selects main-board shares with RSI below 65, a daily gain above 1%, market capitalization below 10 billion yuan, and positive net profit.…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screening proposal combines trading activity with a past-event filter. It ranks stocks by volume ratio and selects the top 100, treating a higher ratio as a sign of stronger investor attention or fund activity. It also requires stocks to…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This stock selection rule combines four daily conditions: price range relative to the close, at least two limit-up moves within a rolling 500-day window, current volume above 10,000 lots, and an opening price above the prior close. The document describes…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This post describes a stock screen combining daily price amplitude above 1, positive institutional money flow, and a 10-day return greater than zero but below 35%. Its example indicator logic aggregates positive net institutional flow across five periods,…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This post outlines a Chinese A-share screening rule using three conditions: current trading volume above 10,000 lots, an opening price above the prior close, and a positive 10-day return below 35%. It presents the volume condition as a proxy for stronger…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This stock selection idea combines membership in the metaverse concept group with two technical conditions: the close is above the prior day’s low, and the KDJ indicator has just produced a bullish K-over-D cross while its J value is rising. The document…

AkcijasTehniskie indikatoriCenas impulssPozīcijas apjoma noteikšana