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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
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 post outlines a rule-based stock screen for Chinese A-shares. Its initial description selects stocks with an amplitude above one, excludes Beijing-listed shares, and requires at least two limit-up sessions within the prior 500 days. The post then…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This note describes a simple Chinese-equity screen: select stocks whose daily high-low range exceeds 1% of the previous close, whose codes begin with 60, and which are outside the STAR Market. It provides corresponding formula and Python examples, making the…

AkcijasSvārstīgumsTehniskie indikatoriĶīnas tirgi
SuperMind

This stock screen selects companies classified in the metaverse industry with no more than 5.5 billion circulating shares and a dividend payout ratio above 25% for 2019. The accompanying example describes retrieving financial and dividend data, filtering for…

AkcijasĶīnas tirgiFaktoru ieguldīšanaRiska pārvaldība
SuperMind

This stock-selection proposal combines a positive MACD reading with positive net profit and a limit on circulating shares. It presents the screen as a way to identify stocks with upward price momentum, profitable businesses, and a relatively small tradable…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

The document proposes a technical stock screen based on shares with at least five moving averages converging, naming the five-, ten-, twenty-, fifty-, and two-hundred-day averages. It also asks that the stock have a positive return over the previous year.…

AkcijasTehniskie indikatoriSekošana tendenceiRiska pārvaldība
SuperMind

The document describes a Chinese stock screen that first limits candidates to the Metaverse concept, then selects shares whose closing price is above its five-day moving average. It ranks qualifying stocks by turnover rate, treating higher turnover as a…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This stock-selection screen combines three technical conditions: daily amplitude above 1%, at least two limit-up events within a 500-day window, and a rising-trend setup. The trend condition requires the close to be at or above its 20-day moving average,…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock screen combines an RSI reading below 65, three consecutive sessions in which the close is below the open, and a KDJ K-line reading below 20. It is intended to identify shares with recent technical weakness, with the low KDJ value treated as a…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This stock selection idea combines three filters: daily amplitude above 1%, a dividend yield above 25% associated with 2019, and a ranking intended to favor stronger capital flows. The explanation treats amplitude as a way to find more volatile shares, the…

AkcijasTehniskie indikatoriFaktoru ieguldīšanaĶīnas tirgi
SuperMind

This post describes a stock-selection rule that combines membership in the metaverse theme with a prior-day close at or above the 250-day moving average and a condition labeled as a rising arc. It frames the theme membership as exposure to a popular sector,…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post proposes a stock screen combining a relative strength index below 65, seven consecutive sessions in which the close is no higher than the open, and valuation bounds. It targets Shenzhen main-board stocks with price-to-earnings…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This post describes a stock screen using three conditions: a daily high-low range exceeding one percent of the previous close, a trading date in 2021, and a smoothed stochastic-style K value below 20. It supplies formula and Python examples for calculating…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This Chinese-language post proposes a short-term A-share screening rule that combines membership in the metaverse industry, a rounded-base shape, and a bullish morning-star reversal signal. It gives a formula based on the prior and current sessions’ open and…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

The post proposes a Chinese A-share stock screen using three conditions: RSI below 65, seven consecutive sessions in which the close is no higher than the open, and a holder-concentration measure between 20% and 70%. It also provides example code intended to…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese A-share stock screen ranks stocks by volume ratio and selects the top 100, then filters for a positive price-to-earnings ratio and an IPO year of 2021. The post interprets high volume ratio as possible inflow strength and positive P/E as a basic…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This note outlines a stock screen combining MACD above zero, an upward price trend, and a volume ratio between 1.5 and 6. It describes the volume ratio as current volume relative to an average over recent sessions and includes formula and Python examples. A…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This note describes a daily stock screen that selects A-shares in 2021 when the intraday high-low range exceeds 1% and the daily return is between -5% and 2.6%. It gives example implementations using a market formula and Python data processing, although the…

AkcijasSvārstīgumsTehniskie indikatoriĶīnas tirgi
SuperMind

This post describes a Chinese A-share screening rule using three conditions: the day’s increase in buying-position share must exceed five percent, the opening auction price change must be between minus two and five percent, and the ten-day return must be…

AkcijasCenas impulssĶīnas tirgi
SuperMind

This A-share screening example looks for stocks with MACD above zero and an upward-moving-average condition, using a historical period associated with 2021. The article presents MACD as a momentum or trend filter and rising averages as a sign of upward…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This stock screen combines an intraday range threshold with a year filter and a ranking by auction amount, selecting the five highest-ranked stocks. The accompanying explanation treats a larger range as a sign of greater volatility and auction amount as a…

AkcijasSvārstīgumsĶīnas tirgi
SuperMind

The document outlines a Chinese A-share stock screen combining daily price range, relative trading volume, and a measure described as today’s control or large-order share. Its stated selection conditions require a range of at least one percent, relative…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

The document proposes a stock screen combining membership in the metaverse industry, a rounded-base chart pattern, and a favorable company-quality classification. It argues that company characteristics may relate to prospects, management, and profitability,…

AkcijasTehniskie indikatoriRiska pārvaldība