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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
Binance API docs
Dokumentu skaits: 45
Quantopian lekcijas
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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 China A-share screening idea starts with stocks in the metaverse theme, then requires the indicated 9:25 price change to be below 6% and positive large-order net inflow in the afternoon. The article describes the theme filter as a way to define the…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaTirgus mikrostruktūra
SuperMind

This proposed China A-share screen combines three conditions: daily amplitude above 1%, positive prior-day main-fund flow, and turnover between 3% and 12%. The post frames the amplitude and turnover filters as ways to focus on active, liquid stocks, while…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

The document presents a Chinese equities screening idea combining a robot-industry concept, a circulating market value below 10 billion yuan, a turnover band of 3% to 12%, and exclusion of stocks associated with northbound capital. It suggests sorting…

AkcijasĶīnas tirgiFaktoru ieguldīšana
SuperMind

This Chinese-language post describes an equity screening idea that combines three conditions: RSI below 65, KDJ’s K line below 20, and a positive product of daily price change and net volume attributed to very large orders. The author presents RSI as a…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasRiska pārvaldība
SuperMind

This stock-selection approach combines a market-capitalization ceiling, positive profitability, recent limit-up activity, and a price-range condition. The stated idea is to find relatively small companies showing strong recent price action while excluding…

AkcijasCenas impulssCenas izrāviensRiska pārvaldība
SuperMind

This stock screen combines three consecutive declining sessions with a daily price range above one percent and a stated turnover-rate band of two to nine percent. The document presents the conditions as a way to find shares with short-term downward momentum…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This stock-screening method combines positive MACD readings with an upward arrangement of short-term moving averages. The document describes MACD as a way to identify positive price momentum and compares five-day and ten-day averages as a simple trend…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This document describes an A-share stock selection screen combining daily price amplitude, a history of limit-up moves, and MACD above zero. It gives indicator conditions and a Python example using historical stock data. The intended idea is to focus on…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This daily stock-selection method combines price activity, past limit-up events, and valuation filters. It screens Shenzhen Main Board stocks for amplitude above 1, at least two limit-ups during the prior 500 days, a price-to-earnings ratio between 0 and…

AkcijasĶīnas tirgiCenas izrāviensTehniskie indikatori
SuperMind

This short-term stock screen selects shares with amplitude above 1, ranks them by the day’s auction amount, keeps the top five, and requires positive net buying attributed to major participants. The article’s rationale is that large price movement and active…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This note proposes a short-term A-share screen based on daily price range, relative volume, and a ranking for net large-order flow. The written rule calls for amplitude above one, relative volume between 1.5 and 6, and a high large-order net-volume ranking.…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This note describes an A-share stock screen combining MACD above zero, upward divergence among moving averages, and prior-day trading value above a stated threshold. It presents these conditions as signs of an upward market state, a rising trend, and…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

The article proposes screening Chinese stocks using three technical conditions: daily high-low amplitude above 1%, at least two limit-up events over a 500-day window, and a 14-period RSI below 65. It supplies indicator formulas and a Python-style example…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This article describes a Chinese stock screen combining turnover of 3% to 12%, a 2021 listing year, and a reversal pattern identified by the Chinese term “fanbao.” It provides sample indicator and Python-style snippets, including a three-session average…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This stock-screening idea targets main-board Chinese equities associated with robotics. It combines turnover between 3% and 12%, a circulating market value below 10 billion yuan, and a rising 30-day moving average relative to the 60-day average. The article…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This opinion article argues that quantitative trading is a tool used by larger market participants rather than the primary force setting a stock's longer-term direction. It describes how large orders might trigger automated buying or stop-driven selling,…

AkcijasTirgus mikrostruktūraTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-selection recipe screens Chinese equities before each trading day for three conditions: MACD above zero, a positive price-to-earnings ratio, and a positive recent return. The return calculation compares the prior close with the close from an…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This article presents a stock-selection screen for Chinese equities whose codes begin with 60. It further requires turnover to fall within a stated 3% to 12% band and MACD to be above zero. The post provides example query and Python-based references for…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-screening example combines three filters for an investment watchlist: daily high-low amplitude above 1%, at least one limit-up session in the previous 25 trading days, and a return rank in the top fifth of stocks from 2021 onward. It…

AkcijasĶīnas tirgiCenas impulssSvārstīgums
SuperMind

This post describes a Chinese stock screen combining a minimum intraday price range, a named morning-star candlestick condition, and a prior-day turnover-related filter bounded between 3% and 28%. It presents the combination as a way to find stocks with…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-screening post describes selecting shares with a daily range greater than 1, circulating market value above 10 billion yuan, and a low K value from a stochastic-style indicator. The accompanying explanation frames the low reading as a…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This Chinese stock-screening post proposes filtering shares by daily price range, whether the previous session was a limit-up day, and relative trading volume. Its written description specifies a range greater than 1 and a volume ratio between 1.5 and 6,…

AkcijasTehniskie indikatoriSvārstīgumsĶīnas tirgi
SuperMind

This Chinese stock-screening post describes selecting shares with turnover between 3% and 12%, a 2021 listing year, and a KDJ bullish crossover on the current day. It presents the crossover as a signal that a stock may be entering an upward phase, while…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This document outlines a Chinese stock selection rule based on three conditions: the 30-day average is rising, yesterday’s price is above the 250-day average, and today’s position increase ratio exceeds 5%. The post interprets these as short- and long-term…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss