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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
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 stock selection approach combines three technical filters: daily price amplitude above one percent, a reversal or engulfing-style candle condition, and a weekly MACD histogram at or above zero. The post presents the combination as a way to seek active…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

The document presents a Chinese-equity screening rule that combines a minimum daily amplitude, a circulating-market-cap threshold, and a morning star candlestick signal. It describes the pattern as a possible bullish reversal after a decline and provides…

AkcijasĶīnas tirgiTehniskie indikatoriVēsturisko datu pārbaude
SuperMind

This stock-selection idea combines three daily-chart conditions: a price range above a stated threshold, at least two limit-up events during the prior 500 days, and an opening price near the ten-day moving average. The article frames range and limit-up…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This proposed Chinese equities screen selects stocks with turnover between 3% and 12%, an opening price within 5% of the 10-day moving average, and a recent seven-day low condition. The post presents the combination as a way to find active stocks amid a…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This post proposes screening Chinese equities using three conditions: buying-pressure share above a threshold, prior-day turnover value above a threshold, and a high dividend ratio in a specified historical year. It frames buying pressure as a sign of…

AkcijasĶīnas tirgiFaktoru ieguldīšanaVēsturisko datu pārbaude
SuperMind

This introductory guide lays out five areas for developing quantitative trading capability: mathematics and statistics, programming, financial knowledge, strategy research, and practical testing. It highlights time-series and cross-sectional econometrics,…

StatistikaMašīnmācīšanāsVēsturisko datu pārbaudeRiska pārvaldība
SuperMind

This post presents a short-term stock screen combining price amplitude, a morning-star pattern, exclusion of specially treated stocks, a market-wide limit-up count capped at five, and selection before 10 a.m. It includes a platform formula and Python example…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This note describes a rule-based screen for Chinese A-share stocks in the metaverse sector. It selects stocks whose quoted 9:25 price change is below 6% and whose 30-day moving average is rising. The post includes indicator expressions and sample Python…

AkcijasĶīnas tirgiTehniskie indikatoriSekošana tendencei
SuperMind

The document describes a stock screen that looks for shares with an amplitude above 1, an upward-spreading moving-average condition, and high auction trading value. It ranks qualifying stocks by auction value and selects the top five, aiming to combine price…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

The document outlines a daily Chinese stock screen taken at 14:00. It retains stocks with MACD above its zero line, positive afternoon large-order net inflow and positive popularity, then sorts candidates by popularity from highest to lowest. It gives the…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document proposes a Chinese stock selection rule combining current turnover rate, the ratio of external to internal trading volume, and a prior-day opening-auction price condition. It then ranks qualifying stocks by current auction turnover and selects…

AkcijasĶīnas tirgiTirgus mikrostruktūraTehniskie indikatori
SuperMind

This post proposes screening Chinese stocks by metaverse industry membership, a custom “arc” pattern, and dates within 2021. It describes using industry data and a date filter, then adding technical and fundamental measures for a broader assessment. The…

AkcijasTehniskie indikatoriVēsturisko datu pārbaudeRiska pārvaldība
SuperMind

This stock-screening concept combines price amplitude above one percent, RSI below 65, and a shortening negative MACD histogram on a 15-minute chart. The text interprets shrinking negative bars as potentially weakening selling pressure and a possible rebound…

AkcijasTehniskie indikatoriCenas impulssStatistika
SuperMind

The document presents a Chinese equity screen combining a turnover ratio from 3% to 12%, appearance on the prior day’s 龙虎榜 (a public ranking of notable trading activity), and a dividend ratio above 25% for 2019. It interprets turnover as a liquidity measure,…

AkcijasĶīnas tirgiFaktoru ieguldīšanaRiska pārvaldība
SuperMind

This stock selection rule targets companies in the metaverse sector that recorded a limit-up event within the prior 25 days and show positive large-order net inflow in the afternoon. The document frames the combination as a way to find stocks with recent…

AkcijasĶīnas tirgiCenas impulssTirgus mikrostruktūra
SuperMind

This Chinese stock-screening proposal selects equities with turnover between 3% and 12%, an appearance on the previous day’s trading leaderboard, and at least one daily gain of 10% or more during the preceding 25 sessions. It gives equivalent descriptions in…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This note describes an A-share stock-selection rule combining turnover between 3% and 12%, three consecutive declining sessions, and a close above the prior day's low. The intended pattern is a short-term pullback followed by a close recovering above a…

AkcijasTehniskie indikatoriĶīnas tirgiRiska pārvaldība
SuperMind

This note outlines an A-share stock screen based on a daily price range above 1%, excluding Beijing-listed shares, requiring a specified reversal or engulfing pattern, and capping circulating market value at 10 billion yuan. It provides formula and Python…

AkcijasTehniskie indikatoriĶīnas tirgiRiska pārvaldība
SuperMind

This note describes a short-term A-share stock screen combining turnover, the opening price relative to the 10-day moving average, and the day's low relative to the previous day's low. It selects stocks with turnover between 3% and 12%, an open within 5% of…

AkcijasTehniskie indikatoriĶīnas tirgiRiska pārvaldība
SuperMind

This Chinese stock-screening proposal combines three technical conditions: daily high-low amplitude above 1%, a newly formed KDJ crossover, and weekly MACD above its zero axis. The explanation treats a larger daily range as evidence of volatility, the…

AkcijasTehniskie indikatoriCenas impulssSekošana tendencei
SuperMind

This Chinese equity screen selects stocks with turnover between 3% and 12%, membership in the robotics concept, and float market capitalization below 10 billion yuan, while excluding the STAR Market. The post frames the constraints as a way to narrow the…

AkcijasĶīnas tirgiRiska pārvaldībaTehniskie indikatori
SuperMind

This proposal screens Chinese stocks using three conditions: daily high-low amplitude above 1%, a reversal or “wrap-up” pattern, and a 2019 dividend ratio above 25%. Its indicator reference defines the amplitude threshold as a one-percent range and describes…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This Chinese A-share screening proposal combines a recent price-limit event with industry filters. Its stated rule looks for stocks in the metaverse sector that had a limit-up within the prior 25 days and are classified under a beverage and alcohol…

AkcijasCenas impulssĶīnas tirgiTehniskie indikatori
SuperMind

The post outlines a Chinese stock screening idea combining a large price amplitude, a three-session limit-up sequence on the prior day, a market capitalization ceiling, and positive earnings. It proposes tightening the amplitude threshold and checking…

Ķīnas tirgiAkcijasCenas izrāviensTehniskie indikatori