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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
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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
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 stock screen combines three filters: daily amplitude above a threshold, a shrinking negative MACD histogram on a 15-minute interval, and positive indicators associated with beverage and alcohol imports and exports. The stated rationale is to seek…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This document proposes screening A-shares for turnover between 3% and 12%, total market value below 10 billion yuan, no reported losses, and free-float market value above 1 billion yuan. It frames the combination as a way to narrow the universe by trading…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
SuperMind

This document describes a stock-selection rule for A-shares using three conditions: price amplitude above 1%, a 2021 date filter, and best bid volume greater than best ask volume. It presents the rule as a way to identify more volatile stocks with potential…

AkcijasSvārstīgumsTirgus mikrostruktūraTehniskie indikatori
SuperMind

This article describes a daily pre-market stock screen for Chinese equities. It selects stocks whose MACD value is above zero, whose trailing price-to-earnings ratio is positive, and whose observation falls in 2021. The article interprets positive MACD as an…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This post proposes an equity screen combining daily range above a threshold, rising lows, and price above its five-day moving average. Its expanded version adds a longer-term trend check using the 20-day and 250-day averages, valuation limits, market-cap…

AkcijasTehniskie indikatoriCenas impulssSekošana tendencei
SuperMind

This post describes a short-term stock screen combining three prior-day conditions: price amplitude above 1%, appearance on the market’s named trading list, and turnover above 8%. The rationale is to find shares with notable movement and active trading,…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This introductory article explains the basic objects and notation of linear algebra used in machine learning and deep learning. It defines scalars, vectors, matrices, and higher-order tensors, with examples such as feature vectors, neural-network weights,…

MašīnmācīšanāsStatistikaPortfeļa veidošana
SuperMind

This document describes a short-term stock screen using three conditions: daily amplitude above a threshold, a high daily control measure, and a positive product between price change and net flow from very large orders. Its refined version also restricts…

AkcijasCenas impulssTehniskie indikatoriRīkojumu izpilde
SuperMind

This note describes a screen for A-shares whose codes begin with 60, whose turnover is between 3% and 12%, and whose top 20% of shareholders collectively hold less than 70% of shares. It presents these conditions as filters for liquidity and ownership…

AkcijasĶīnas tirgiStatistikaRiska pārvaldība
SuperMind

This note describes a stock screen for A-shares whose codes begin with 60, whose turnover is between 3% and 12%, and whose price-to-earnings ratio is positive. The code example obtains a current trading date and filters listed stocks using those criteria.…

AkcijasĶīnas tirgiFaktoru ieguldīšanaRiska pārvaldība
SuperMind

This proposed equity screen selects stocks with amplitude above 1, an RSI below 65, and prior-day turnover above 60 million. It combines a price-range measure with a momentum oscillator and a liquidity threshold, aiming to find stocks with activity while…

AkcijasTehniskie indikatoriCenas impulssSvārstīgums
SuperMind

This proposed equity screen combines membership in the metaverse sector, a rounded price pattern, and a circulating share count capped at 5.5 billion. The article frames the float limit as a way to focus on relatively smaller stocks and suggests…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

This stock-selection screen combines price amplitude above 1, a dividend-related payout ratio above 25% for 2019, and a rising-bottom condition. The explanation treats larger amplitude as a sign of greater trading opportunity, the dividend filter as a way to…

AkcijasTehniskie indikatoriSvārstīgumsRiska pārvaldība
SuperMind

This Chinese equity screening rule ranks stocks by capital strength and requires more than two limit-up days in the past ten days. It also requires a nonempty name for an outstanding convertible bond. The article explains these conditions as signs of…

AkcijasCenas impulssĶīnas tirgiTehniskie indikatori
SuperMind

This research summary reviews six studies on industry rotation and index enhancement in China. Its multi-factor framework considers expected and historical fundamentals, price and volume information, market leadership, and system-risk concentration. It…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaCenas impulss
SuperMind

The document proposes a Chinese equity screen requiring MACD to be above zero, the DEA signal line to be rising, and the ten-day return to be positive but below 35%. It presents the indicators as a way to identify favorable short-term trend conditions while…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This document is a structured metadata record about Lumiwealth and its Lumibot project. It identifies the organization as the project owner, describes Lumibot as a Python framework for building, backtesting, and deploying trading bots, and lists supported…

SuperMind

The document describes a Chinese equity screening rule combining three filters: turnover between 3% and 12%, a positive ten-day return below 35%, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and at most 100%.…

AkcijasCenas impulssFaktoru ieguldīšanaĶīnas tirgi
SuperMind

This article outlines an equity screen combining membership in the Metaverse theme, positive net buying by large participants during the auction, and a moving-average trend condition. Its formula expresses the trend condition as the 30-day average above the…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This note describes a stock screening rule that combines a positive MACD reading, a company or concept filter, and a stochastic K value below 20. The intended logic is to select shares with an upward trend signal while looking for an oversold condition that…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This note presents a short-term Chinese equity screen based on daily price range greater than 1, volume above 10,000 lots, an opening price above the previous close, and a reported increase in positions of at least 5%. It frames range, volume, and the…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This note proposes screening Chinese equities for turnover between 3% and 12%, a K reading below 20, and first-level bid volume greater than first-level ask volume. Its indicator examples also include additional filters for price, market capitalization, and…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This note describes a short-term screen for Chinese equities associated with the metaverse theme. It combines a user-defined arc-shaped price pattern with current volume above 10,000 lots and an opening price above the previous session’s high. The article…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss