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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
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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
Quantpedia
Dokumentu skaits: 86
TqSdk
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 Chinese equity screen combines three short-term filters: price amplitude above 1, a ranking based on large-order net activity, and a 9:25 a.m. gain below 6%. The stated rationale is to identify active, volatile shares whose early move is comparatively…

AkcijasĶīnas tirgiSvārstīgumsTehniskie indikatori
SuperMind

This Chinese equity screening note combines a price-amplitude threshold with a named candlestick pattern and an exchange-market exclusion. It calls for amplitude above 1, a “Morning Star” pattern associated with Kute Intelligent, and exclusion of…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This note describes a Chinese equity screen combining turnover with a stock-code filter and a recent price condition. It selects stocks whose codes begin with 60 and whose turnover is between 3% and 12%, then ranks candidates by the highest closing price…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This A-share screen selects stocks with a daily range above one percent, a day's low between four and five percent below the previous close, and a rising DEA line. The article presents range and decline as short-term price conditions and DEA movement as a…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This A-share selection rule combines a daily high-low range above one percent, a nonempty unsettled convertible-bond name, and a newly formed upward KDJ crossover. The provided formula further requires the K value to meet or exceed D after being at or below…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This note presents an A-share stock screen that ranks names by capital strength, keeps the five with the largest auction value for the day, and requires the 30-day moving average to be rising. It interprets fund flow and auction activity as signs of…

AkcijasĶīnas tirgiSekošana tendenceiCenas impulss
SuperMind

The document proposes screening Chinese metaverse-related stocks for a positive daily close-to-close return while the session low falls between 4% and 5% below the previous close. This combines a positive closing result with a substantial intraday decline,…

Ķīnas tirgiAkcijasAtgriešanās pie vidējās vērtībasTehniskie indikatori
SuperMind

This post describes a Chinese equity screening rule combining daily price range, a historical dividend measure, and a fixed share price. Its stated logic selects stocks whose high-to-low amplitude exceeds a threshold, whose 2019 dividend ratio is above a…

AkcijasĶīnas tirgiSvārstīgumsFaktoru ieguldīšana
SuperMind

This stock screen combines a price-range filter, a five-day moving-average condition, and a metaverse-related classification. It selects shares whose high-to-low range, measured against the previous close, exceeds a threshold; whose closing price is above…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock screen combines a turnover range of 3% to 12%, a K value below 20, and year-over-year net profit growth above 20% and no more than 100%. The article frames the turnover condition as a liquidity filter, the K threshold as a technical selection…

AkcijasTehniskie indikatoriFaktoru ieguldīšanaĶīnas tirgi
SuperMind

This Chinese stock-screening example combines a technical threshold with price movement, large-order net volume, and a popularity ranking. It proposes selecting shares with RSI below 65, using the product of percentage change and large-order net volume as a…

AkcijasTehniskie indikatoriTirgus noskaņojums
SuperMind

This stock-selection rule combines three short-term conditions: daily amplitude above 1%, an opening price within about 5% of the 10-day moving average, and buying-side volume more than 1.3 times selling-side volume. The accompanying explanation interprets…

AkcijasTehniskie indikatoriTirgus noskaņojums
SuperMind

This document outlines a Chinese stock selection rule using turnover of 3% to 12%, circulating market capitalization from 1 to 55 billion yuan, and a control activity indicator above 21. The page gives the criteria in prose and in formula-like and Python…

Ķīnas tirgiAkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

The document describes a Chinese equity screen that selects beverage manufacturing stocks with daily turnover between 3% and 12% and a reversal or engulfing-style pattern. Its rationale is that turnover may indicate trading activity while the pattern may…

Ķīnas tirgiAkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This post proposes screening Chinese stocks by daily price amplitude, a measure described as current-day shareholder control, and prior-day major-investor net buying. It presents the combination as a way to capture market sentiment and capital flows. The…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus noskaņojums
SuperMind

This post describes a Chinese equity screening idea that combines three criteria: a dividend payout ratio above 25% in 2019, strong capital activity ranked from high to low, and evidence of major-investor control on the prior day. It suggests turnover and…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTirgus noskaņojums
SuperMind

This ProRealTime indicator estimates average forward price movement conditional on the current reading of RSI, Stochastic, Williams %R, or ADX. It divides indicator readings into 20 five-point ranges, then separates observations according to whether the…

Tehniskie indikatoriStatistikaVēsturisko datu pārbaude
SuperMind

This Chinese equity screening rule combines a turnover filter with a recent price pattern and listing-year condition. It selects stocks with turnover between 3% and 12%, listed in 2021, whose closing prices have fallen for three consecutive days. The post…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This Chinese-market stock screen combines three historical activity filters: daily amplitude above 1%, turnover between 2% and 9%, and at least two limit-up events within a 500-day lookback. The document frames amplitude as a volatility measure, turnover as…

Ķīnas tirgiAkcijasSvārstīgumsTehniskie indikatori
SuperMind

This stock screen targets companies classified in the metaverse sector whose opening price is near the 10-day moving average and whose prior-day turnover exceeds 8%. It combines a sector filter with a short-term price condition and a measure of recent…

Ķīnas tirgiAkcijasTehniskie indikatori
SuperMind

This stock selection method combines three conditions: turnover between 3% and 12%, an opening price near the ten-day moving average, and positive institutional activity. Its example implementation also requires the close to exceed the previous close, making…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese stock-selection note proposes screening for shares with an amplitude above one, ranking among the top five by the day’s auction amount, current volume above ten thousand lots, and a positive opening gap. The accompanying explanation treats a…

Ķīnas tirgiAkcijasTehniskie indikatoriRīkojumu izpilde
SuperMind

This Chinese-language post proposes a stock screen combining three conditions: daily price range above 1%, a positive ten-day return below 35%, and a measure labeled today’s position increase above 5%. It interprets the range as a sign of active price…

AkcijasCenas impulssTehniskie indikatoriStatistika
SuperMind

This Chinese A-share screening idea filters for stocks classified in the metaverse industry, limits circulating shares to at most 5.5 billion, and selects the five with the highest amount traded in the current day’s opening auction. The article provides a…

AkcijasĶīnas tirgiRīkojumu izpildeTirgus mikrostruktūra