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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
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

The document proposes a Chinese stock-screening rule combining three conditions: today’s increase in shareholding proportion exceeds a threshold, large-order net inflow is positive during the afternoon, and the 30-day moving average is rising. The stated…

AkcijasCenas impulssTehniskie indikatoriStatistika
SuperMind

The document describes a short-term equity screen for main-board stocks. It selects shares with turnover between 3% and 12%, a K indicator below 20, and a daily gain above 1%. The post also gives a reference expression and a sample Python workflow that…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This note presents a Chinese-equity screening approach that ranks stocks by relative volume and selects prices between the middle and upper Bollinger Bands, while also considering an early-session gain threshold. Its initial description uses a gain below 6%,…

Ķīnas tirgiAkcijasTehniskie indikatoriSvārstīgums
SuperMind

This stock selection method focuses on companies classified in the metaverse industry. It filters for a volume ratio between 1.5 and 6 and then keeps stocks in the top 10% by large-order net flow. The intended idea is to find shares experiencing elevated…

AkcijasĶīnas tirgiTirgus mikrostruktūraCenas impulss
SuperMind

This proposed stock screen combines a technical condition with a dividend measure. It calls for RSI below 65, a positive product of percentage price change and a large-order net-flow measure, and a 2019 dividend ratio above 25%. The article describes the…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This A-share screening rule combines daily turnover between 3% and 12%, market capitalization below 10 billion yuan, a profitability condition based on return on equity, and price amplitude above 1. It is intended to focus on smaller companies that are…

AkcijasFaktoru ieguldīšanaRiska pārvaldībaĶīnas tirgi
SuperMind

This A-share stock screen selects shares with a 14-period RSI below 65, a circulating market capitalization between 5 billion and 10 billion yuan, and no limit-up close on the previous day. The stated rationale is to use RSI as a short-term weakness filter,…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This A-share stock screen combines a 14-period RSI below 65 with three consecutive sessions in which the close is below the open, plus a stated control-ratio threshold. The article frames the conditions as a way to find technically weak stocks that may…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This article introduces a proposed relationship between the intensity of market capital flows and investors’ choice of equity style. It suggests that when flows are subdued, style investors tend to retain their existing direction, while unusually strong…

AkcijasFaktoru ieguldīšanaStatistika
SuperMind

This A-share stock screen selects companies classified in the metaverse sector, limits the previous session’s morning opening gain to under six percent, and requires the prior closing price to sit above its 250-day moving average. The article frames the…

Ķīnas tirgiAkcijasTehniskie indikatoriSekošana tendencei
SuperMind

This Chinese-equity screening proposal combines a reported increase in investor positions above 5%, a daily return constrained to a narrow band, and an opening gain below 6%. The post’s description gives the daily-return limits as below 2.6% and above -5%,…

AkcijasCenas impulssTehniskie indikatoriRiska pārvaldība
SuperMind

This proposed stock screen combines three conditions: daily amplitude greater than 1, a shrinking negative MACD histogram on a 15-minute chart, and price near the ten-day moving average. The rationale is to find volatile stocks where downside momentum may be…

AkcijasTehniskie indikatoriSvārstīgumsCenas impulss
SuperMind

This stock-screening approach selects equities with MACD above zero, a positive return over ten days capped at 35%, and a qualifying enterprise characteristic. The article frames positive MACD as evidence of an upward trend, the return band as a way to limit…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This proposed Chinese A-share screen combines three conditions: MACD above zero, trailing price-to-earnings ratio above zero, and substantial large or extra-large order volume during the opening auction. It is intended to run after the auction ends each…

AkcijasTehniskie indikatoriCenas impulssRīkojumu izpilde
SuperMind

This stock screen combines four proposed conditions: a metaverse industry classification, a rounded or arc-like price pattern, association with a robotics concept, and circulating market value below a stated threshold. The article explains that the small-cap…

AkcijasĶīnas tirgiTehniskie indikatoriStatistika
SuperMind

This Chinese stock-selection example combines a turnover-rate band with an order-flow ratio and a rising KDJ stochastic value. The stated screen looks for turnover between 3% and 12%, outside volume more than 1.3 times inside volume, and a positive…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post describes a stock screen that selects shares with turnover between 3% and 12%, an initial listing year of 2021, and a candle formation labeled a Kute Intelligence Morning Star. The pattern is framed as a possible reversal after a…

AkcijasTehniskie indikatoriĶīnas tirgiVēsturisko datu pārbaude
SuperMind

This A-share screening proposal looks for stocks with MACD above the zero line, a share price below 12 yuan, and revenue growth exceeding 10% over the prior three years. It combines a technical momentum condition and a low nominal price with a fundamental…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This A-share stock screen combines an amplitude threshold above 1, a prior-day 9:15 matched price at the limit-down level, and a rounded-bottom condition. The article offers CCI below -100 as a possible numerical proxy for the rounded shape, then gives…

AkcijasSvārstīgumsAtgriešanās pie vidējās vērtībasTehniskie indikatori
SuperMind

This A-share screening proposal combines an RSI reading below 65, an outer-to-inner trading volume ratio above 1.3, and three consecutive declining closes. The article describes the conditions as a way to find stocks with weak recent price action that might…

AkcijasAtgriešanās pie vidējās vērtībasTehniskie indikatoriĶīnas tirgi