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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
WonderTrader
Dokumentu skaits: 14
Alphalens
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 stock-screening example combines a 14-period RSI below 65, three consecutive bearish candles, and a circulating share count no greater than 5.5 billion. The document presents the rules as a way to identify stocks showing short-term weakness…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese stock-screening example ranks shares by capital strength and initially selects stocks with more than two limit-up sessions in the previous ten days and a gain below six percent at 9:25. The accompanying explanation treats stronger capital inflow…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This note proposes a short-term Chinese equity screen with three conditions: amplitude above 1, the current high equal to the highest high over two days, and the opening price near the ten-day moving average. It gives formula and Python examples, including a…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This forum post raises a factor-research reproducibility problem: a user reports that returns from reproducing four factors differ substantially from the platform’s published results. The suggested comparison holds the factor and backtest period constant,…

AkcijasFaktoru ieguldīšanaVēsturisko datu pārbaudeStatistika
SuperMind

This note describes a Chinese equity screening rule that combines price movement, trading activity, opening behavior, and recent limit-up frequency. It selects stocks with amplitude above 1, current volume above 10,000 lots, a higher open, and more than two…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese equity screen looks for stocks with turnover between 3% and 12%, a negative product of the daily price change and net super-large-order quantity, and a pattern described as three consecutive declining sessions. It uses turnover and large-order…

AkcijasTehniskie indikatoriTirgus mikrostruktūraĶīnas tirgi
SuperMind

This Chinese stock-selection idea filters for companies in the metaverse theme whose net major-investor buying during the opening auction is positive and whose KDJ indicator has just formed a bullish crossover. The three conditions combine thematic exposure,…

AkcijasTehniskie indikatoriTirgus mikrostruktūraTirgus noskaņojums
SuperMind

This Chinese equity screen selects main-board stocks with a 14-period RSI below 65, a daily gain greater than 1%, and an increase-in-position share above 5%. The note interprets the position increase as a possible sign of near-term capital inflow and pairs…

AkcijasTehniskie indikatoriCenas impulssTirgus noskaņojums
SuperMind

This note describes a Chinese equity screen combining a positive MACD reading with a favorable company classification and a circulating market value between 5 billion and 10 billion yuan. It frames the approach as a blend of technical momentum and company or…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This post presents a Chinese stock-selection screen that combines a daily price-range threshold, a pattern described as a morning star, and ranking by auction activity, selecting the top five names. It frames the inputs as measures of price movement,…

AkcijasTehniskie indikatoriCenas izrāviensCenas impulss
SuperMind

This post outlines a technical screen for Chinese stocks in the metaverse theme. It requires the stock’s price to be above its five-day moving average and applies a rule intended to identify an arc-shaped price pattern. The document describes these…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post describes a daily, after-close screen for Chinese equities. It selects stocks whose MACD line is above zero, ranks candidates by individual-stock popularity, and restricts turnover to between 2% and 9%. It explains the indicators as rough proxies…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The post proposes an A-share stock screen centered on a reported increase in holdings above 5% and a relationship between price change and net large-order flow. It also refers to 2021 performance, then adds market capitalization above 10 billion and a…

AkcijasĶīnas tirgiTirgus mikrostruktūraRiska pārvaldība
SuperMind

This A-share screening idea looks for stocks classified in the metaverse sector that appeared on the previous day’s trading activity leaderboard and whose intraday low is 4% to 5% below the previous day’s high. The article frames the screen as a way to find…

AkcijasAtgriešanās pie vidējās vērtībasĶīnas tirgiVēsturisko datu pārbaude
SuperMind

This Chinese-language post describes a stock-selection screen focused on the metaverse concept. It requires the 30-day moving average to be rising and filters stocks using a measure combining the prior turnover rate with the ratio of today’s auction volume…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This proposed stock screen looks for companies with daily high-low range above 1%, market capitalization below 10 billion, and no losses. The initial description refers to 2021 data; the refined version adds positive net income in each of the latest four…

AkcijasTehniskie indikatoriRiska pārvaldībaPozīcijas apjoma noteikšana
SuperMind

This stock-selection approach filters for companies in the beverage and alcohol import-export industry, a 14-period RSI below 65, and return on equity above 15% for five consecutive years. It combines a price-based indicator with an industry classification…

AkcijasTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This post outlines a stock selection rule that combines MACD above zero, a favorable company classification, and previous-day actual turnover between three and twenty-eight percent. It interprets the MACD condition as a positive technical signal and the…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This post proposes a Chinese equity screen combining recent price-limit events, trading activity, and an increase in position holdings. Its stated initial conditions are more than two limit-up days within ten days, prior-day turnover above sixty million, and…

AkcijasCenas impulssCenas izrāviensTehniskie indikatori
SuperMind

This proposed screen targets stocks associated with the metaverse theme and combines an arc-shaped price pattern with a rising K value from the KDJ oscillator. The explanation treats a rising K value as a sign of improving bullish momentum. The formula and…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese-equity screening rule selects companies with turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, total market value below 10 billion yuan, and positive reported profits. Turnover is used as a…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
SuperMind

This note describes a stock screen combining daily amplitude above a stated threshold, a positive weekly MACD signal, and first-level buy volume greater than sell volume. It presents the buy-versus-sell volume condition as a way to gauge near-term trading…

AkcijasTehniskie indikatoriCenas impulssTirgus mikrostruktūra
SuperMind

The document presents a Chinese A-share screening rule that selects stocks with a daily high-low range exceeding one percent, at least one limit-up session in the prior 25 trading days, and a high ranking on a large-order net-volume measure. The combined…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This overview explains mean reversion as a tendency for a time series to move back toward a typical level, contrasting it with a random walk and relating the idea to the Ornstein–Uhlenbeck process. It describes the Augmented Dickey-Fuller test as a unit-root…

Atgriešanās pie vidējās vērtībasStatistikaTehniskie indikatori