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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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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

This post proposes screening Shenzhen main-board stocks for daily price amplitude above one percent, a newly formed KDJ golden cross, and specified price-to-earnings and price-to-book ranges. It describes the crossover as a possible sign of improving…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post outlines a Chinese equity screen that ranks stocks by funding strength, looks for a weekly five-period moving average crossing above a ten-period average, and filters for an opening gain below six percent at 9:25. The proposed rationale is to…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese stock-selection post proposes screening metaverse-related shares for positive institutional movement and a prior-day price pattern described as main-force control. It presents the conditions as a way to focus on a specific industry, follow…

AkcijasĶīnas tirgiTirgus noskaņojumsRiska pārvaldība
SuperMind

This stock-screening proposal looks for shares with an amplitude measure above 1, three technical indicators said to have bullish crosses, and three consecutive declining closes. Its sample Python logic approximates the multiple-cross condition with the 5-,…

AkcijasTehniskie indikatoriCenas impulssVēsturisko datu pārbaude
SuperMind

This Chinese A-share screening proposal combines a technical condition with earnings growth and a concentration filter. It selects stocks with a 14-period RSI below 65, year-over-year net-profit growth above 20% and no more than 100%, and a stated…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This document describes a stock-selection rule that combines a daily high-low range threshold, a recent reversal pattern, and a negative MACD reading from two sessions earlier. It frames range as a volatility filter, the reversal as a possible change in…

AkcijasTehniskie indikatoriSvārstīgumsVēsturisko datu pārbaude
SuperMind

This proposed A-share screen targets metaverse-related stocks with a circulating share count no greater than 5.5 billion and an upward-spreading set of moving averages. The article’s example rules add price, volume, and return conditions: price is…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This stock selection rule screens for companies with market value below 10 billion yuan, positive profit history, turnover between 3% and 12%, and a 14-period RSI below 65. It combines a size filter and profitability condition with activity and…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This post proposes a technical stock screen combining price amplitude above a threshold, progressively rising lows, and a volume ratio between stated bounds. It describes the rising floor as a sign of improving price structure and uses relative volume to…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This community exchange explains how to use data downloaded with Supermind’s data ingestion command. A reply says the downloaded data can be accessed through the platform’s get_price function, without specifying the on-disk file format or a separate…

Vēsturisko datu pārbaude
SuperMind

This Chinese-language post outlines an A-share stock screen combining daily price range, relative trading volume, and recent return. It selects stocks with a daily high–low range of at least one percent, volume between 1.5 and 6 times its five-day average,…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document outlines an equity screen that selects stocks with turnover between 3% and 12%, a rising KDJ K line, and MACD above its zero line. It describes the rising KDJ reading and positive MACD as indicators of upward price momentum, and provides both a…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese equity screen first restricts the universe to metaverse-related companies that are not marked ST and have circulating share capital at or below 5.5 billion shares. It then applies a so-called five-level limit-up method, with selection intended…

Ķīnas tirgiAkcijasCenas impulssCenas izrāviens
SuperMind

This stock-selection idea combines three filters: price amplitude above one percent, appearance on the prior day's notable-trading list with reported buying exceeding selling, and turnover between three and twelve percent. The article presents the filters as…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

The document proposes screening Chinese stocks for amplitude above 1%, an aligned set of three moving averages, and a 2021-to-2018 revenue ratio above 1.1. It presents the moving-average condition as a technical signal and the revenue comparison as a basic…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The document describes a Chinese A-share stock screen that excludes Beijing-listed shares, requires daily high-low amplitude above 1%, and selects stocks with at least one daily gain of 10% or more in the previous 25 trading days. It outlines the rationale…

AkcijasĶīnas tirgiCenas impulssSvārstīgums
SuperMind

The post describes a simple equity-universe filter: identify stocks associated with the metaverse theme, require a circulating market value above 10 billion yuan, and retain codes beginning with 60. It presents these conditions as a way to narrow the…

AkcijasĶīnas tirgiFaktoru ieguldīšana
SuperMind

This stock screen combines three technical conditions: daily price amplitude of at least one percent, turnover above two percent and no greater than nine percent, and a pattern of rising lows. The accompanying explanation interprets the combination as…

AkcijasTehniskie indikatoriSvārstīgumsRiska pārvaldība
SuperMind

This Chinese equity screen looks for companies with market capitalization below 10 billion yuan and nonnegative net profit attributable to parent-company shareholders for 2021. The article presents the size limit as a way to focus on smaller firms that may…

AkcijasFaktoru ieguldīšanaĶīnas tirgi
SuperMind

This Chinese equity screen selects companies associated with the metaverse theme when prior-day actual turnover is between 3% and 28% and both weekly MACD lines, DIFF and DEA, are above zero. The article treats the turnover range as a sign of market…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese equity screening rule combines a 14-period RSI below 65, prior-day auction turnover above 0.26, and a 9:25 price gain below 6%. The article describes RSI as a gauge of overbought or oversold conditions, auction turnover as a measure of trading…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

The document describes a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, positive 10-day gains below 35%, and a rising 30-day moving average. It presents the conditions as a way to combine trading activity with short-term…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

The post describes a Chinese A-share screening rule that combines a daily price-range threshold, at least one limit-up event in the prior 25 trading days, and return on equity above 15% for five consecutive years. It presents the conditions as a way to find…

AkcijasĶīnas tirgiSvārstīgumsCenas impulss