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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
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 document proposes screening Chinese stocks for daily turnover between 3% and 12%, three consecutive declining sessions, and a bullish morning star candlestick pattern on the current day. It presents the combination as a way to use trading activity and…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This document describes a Chinese equity screen for stocks in the metaverse industry. It combines three bullish technical crossovers—MACD crossing its signal line, a 5-period moving average crossing above the 10-period average, and the 5-period average…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post proposes an equity screen using four conditions: daily amplitude above a threshold, a prior-day opening auction match at the limit-down price, a product of absolute price change and large-order net volume, and current volume above…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus noskaņojums
SuperMind

The document describes a simple Chinese equity screen combining daily price range, a closing price condition, and a large-order net-flow ranking. It presents the rules both as a conceptual selection recipe and as examples of indicator logic, then says to…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This Chinese stock-screening proposal combines relative trading activity, historical limit-up frequency, and the opening gain measured at 9:25. Its initial rules select stocks ranked among the top 500 by volume ratio, with at least two limit-up sessions in…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This A-share selection method combines amplitude above 1, a weekly five-period moving average crossing above the ten-period average, and a ranking based on large-order net volume. The article presents these as complementary signals: price movement, an…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This A-share screen combines MACD above zero, an upward-moving average condition, and turnover between 2% and 9%. The article interprets positive MACD and rising averages as signs of upward direction, while the turnover band is intended to avoid both very…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This short-term A-share screening method looks for stocks with amplitude above 1, a circulating share count no greater than 5.5 billion, and a volume ratio between 1.5 and 6. The article frames these filters as a way to find stocks with meaningful price…

AkcijasĶīnas tirgiSvārstīgumsTehniskie indikatori
SuperMind

This A-share screen combines daily amplitude above 1 with a positive weekly MACD reading and a listing history longer than one year. The article then adds valuation and profitability constraints: price-to-earnings below 20, price-to-book below 3, and return…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post describes a Chinese equity screening idea that combines membership in the metaverse concept with positive net buying by large participants during the opening auction and a prior-day measure of main-fund control. Its stated interpretation requires…

AkcijasĶīnas tirgiTirgus noskaņojumsFaktoru ieguldīšana
SuperMind

The post describes a simple random stock-selection process: buy ten stocks, hold them for five days, sell the two weakest performers, then randomly choose two replacements and repeat. It frames the strategy as a challenge to expert stock picking and notes…

AkcijasPortfeļa veidošanaVēsturisko datu pārbaude
SuperMind

The document explains impermanent loss for decentralized exchange liquidity providers. AMMs maintain pool balances through pricing formulas; when an asset’s market price moves relative to its pool partner, arbitrage trades restore alignment and change the…

KriptoaktīviDeFiTirgus veidošanaRiska pārvaldība
SuperMind

This stock screen combines three criteria: rank equities by capital strength, require yesterday’s turnover rate to exceed 8%, and select companies whose 2019 dividend payout ratio exceeded 25%. The accompanying explanation treats capital strength as an…

AkcijasĶīnas tirgiFaktoru ieguldīšana
SuperMind

This post describes a stock screen combining two signals: an increase in holdings above 5% and moving averages that diverge upward. It interprets the holdings measure as possible recent buying interest and the moving-average pattern as an upward trend. The…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This short-term A-share screening idea combines three filters: a prior-session price range above a stated threshold, appearance on the previous day’s trading activity list, and a high ranking in large-order net flow. The post interprets the combination as a…

AkcijasĶīnas tirgiCenas impulssTirgus mikrostruktūra
SuperMind

This note describes an A-share screen that combines a metaverse industry filter, a stated free-float threshold, and a three-candle pattern described as a morning star. It presents the pattern as a possible reversal setup after a pullback, and suggests adding…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This proposed Chinese stock screen selects companies classified in the metaverse theme, with prior-day actual turnover between 3% and 28%, and a listing or issuance date in 2021. The post treats the industry classification as a growth-oriented universe…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This proposed stock screen combines three filters: turnover between 3% and 12%, a newly formed KDJ bullish cross, and a positive institutional net-purchase measure. The post frames turnover as a liquidity and activity filter, the KDJ signal as a trend or…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This proposed Chinese equity screen focuses on stocks classified in the metaverse theme. It combines a price condition involving the five-day moving average with a directional filter: the product of the stock’s daily return and a measure of net large-order…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document proposes a stock screen combining intraday amplitude above 1, excluding ST-designated stocks, selection before 10 a.m., a named five-step limit-up method, and floating shares no greater than 5.5 billion. It describes float as a measure related…

AkcijasCenas izrāviensTehniskie indikatoriRiska pārvaldība
SuperMind

The document describes a short-term stock screen combining a 14-period RSI below 65, three consecutive declining sessions, and a daily price change between -5% and 2.6%. It frames the conditions as a way to find weak stocks that may be positioned for a…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaude
SuperMind

This Chinese equity screening strategy selects stocks with turnover between 3% and 12%, three consecutive declining sessions, and return on equity above 15% for five consecutive years. The article presents the ROE filter as a way to favor firms with…

AkcijasFaktoru ieguldīšanaTehniskie indikatoriRiska pārvaldība
SuperMind

This document describes a Chinese equity screening rule combining daily amplitude above a threshold, higher successive lows, and upward separation among short, medium, and longer moving averages. Its indicator example compares five-, ten-, and twenty-period…

AkcijasTehniskie indikatoriSekošana tendenceiRiska pārvaldība