Pāriet uz saturu

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
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 Chinese stock-screening note describes a rule that combines daily price amplitude, a bounded turnover rate, and a ranking based on large-order net flow. Its rationale is to find shares with meaningful price movement and trading activity while using net…

AkcijasĶīnas tirgiSvārstīgumsTirgus mikrostruktūra
SuperMind

This document describes a Chinese equity screening rule combining daily amplitude above a threshold, a positive weekly MACD histogram, and exclusion of stocks that hit their daily price limit on the previous day. It presents versions of the rule for a…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This document outlines a daily stock screen for Chinese A-shares. It selects stocks whose MACD is above zero, ranks qualifying names by market attention from highest to lowest, and requires positive net buying by major participants during the opening…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document outlines an A-share stock screen combining a 3%–12% turnover range, a market capitalization below 10 billion yuan, a profitability filter, and a signal described as main-fund control on the previous day. It also provides a sample indicator…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-selection idea filters for RSI below 65 and a circulating market value between 5 billion and 10 billion yuan, then ranks qualifying stocks by that day’s auction amount and selects the top five. The article frames RSI as a short-term overbought or…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This document describes a screen for Shenzhen main-board stocks combining daily price movement, opening price relative to the 10-day moving average, and valuation limits. It seeks stocks with amplitude above 1%, an open within 5% of the moving average,…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

The document proposes a Chinese-equity selection screen combining prior-session price amplitude, a maximum free-float share count, and a price-position condition called “reverse covering.” Its examples operationalize that last condition as a close at or…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

The proposed Chinese equity screen selects stocks with turnover between 3% and 12%, a newly formed KDJ bullish crossover, and at least one limit-up move during the preceding month. The article frames these conditions as a combination of trading activity, a…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document describes a China A-share screening idea focused on main-board stocks in the metaverse sector. It selects candidates whose volume ratio is above 1.5 and below 6, and whose daily price gain exceeds 1%. The stated rationale is to find stocks with…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This post proposes screening Chinese metaverse-sector equities with circulating market capitalization above 10 billion yuan after their prior-day 9:15 opening-match price reached the limit-down level. The rationale is an expectation that stocks hit by an…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaAtgriešanās pie vidējās vērtības
SuperMind

This Chinese-language post describes an equity screen combining price amplitude above 1, a 2019 dividend ratio above 25%, market capitalization below 10 billion yuan, and positive profits. It frames the criteria as a way to find smaller companies with…

AkcijasĶīnas tirgiSvārstīgumsFaktoru ieguldīšana
SuperMind

This analysis describes the CSI Dividend Index and the Bosera CSI Dividend ETF that tracks it. The index selects 100 Shanghai and Shenzhen A-shares with high average after-tax cash dividend yields over the previous two years, then weights constituents by…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
SuperMind

This stock-selection method combines price range, recent large gains, and a trading-activity proxy. It looks for stocks with amplitude above 1, at least one daily gain of 10% or more during the past 25 trading days, and an external-to-internal trading volume…

AkcijasĶīnas tirgiCenas impulssSvārstīgums
SuperMind

This short-term A-share screen combines metaverse sector membership with an early-session price condition and a fundamental filter. It selects stocks whose 9:25 gain is below 6% and whose year-over-year growth in net profit attributable to parent-company…

AkcijasĶīnas tirgiCenas impulssRiska pārvaldība
SuperMind

This document presents a Chinese A-share screening rule that selects stocks with turnover between 3% and 12%, excludes Beijing-listed shares, and requires the institutional-flow indicator to be positive. It provides a corresponding platform formula and a…

AkcijasĶīnas tirgiTirgus mikrostruktūraRiska pārvaldība
SuperMind

This document describes a short-term A-share stock screen combining membership in the Metaverse theme with an opening-price condition and a measure based on price change and large-order trading activity. The stated rules require the previous close relative…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This stock-screening idea combines three filters: companies without losses, a market capitalization below a stated ceiling, and a newly formed KDJ golden cross. It also ranks candidates by a measure of capital strength derived from turnover and trading…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This document proposes screening stocks for amplitude above 1, MACD above its zero line, and first-level bid volume greater than first-level ask volume. It frames amplitude and MACD as technical strength filters and the order-book comparison as a way to…

AkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This document describes a Chinese equity screen for stocks listed in 2021, with turnover between 3% and 12% and tradable share capital no greater than 5.5 billion shares. It gives a platform formula and a Python example that retrieves listed stocks, applies…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This document describes an equity screen combining price amplitude above 1, a daily control indicator above 21, and a positive daily MACD. It presents these conditions as a way to identify stocks with technical support and provides sample implementations for…

AkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-selection idea screens Chinese A shares for turnover between 3% and 12%, a newly formed KDJ golden cross, and a K value below 20. The turnover band is intended to select stocks with some trading activity, while the low K value is treated as an…

Ķīnas tirgiAkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This screen targets Chinese stocks in the metaverse category whose closing price is above the five-day moving average and whose large-order net activity exceeds 0.05 for three consecutive days. The article interprets the price condition as short-term…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori