Pāriet uz saturu

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

The proposed Chinese equity screen selects main-board stocks associated with beverage and alcohol imports and exports. Its stated criteria include an RSI below 65 and a daily price rise greater than 1%. The accompanying discussion frames the industry filter…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This stock selection approach combines three signals: more than two limit-up sessions within ten days, a closing price above the previous day's low, and a reported daily position increase above 5%. The post interprets these as signs of buying interest and…

AkcijasCenas impulssCenas izrāviensRiska pārvaldība
SuperMind

This Chinese stock screen combines a positive MACD reading with a volume ratio between 1.5 and 6 and positive net profit. The rationale is to find shares with upward price momentum, stronger than usual trading activity, and a basic profitability signal. The…

AkcijasCenas impulssTehniskie indikatoriRiska pārvaldība
SuperMind

This post outlines a Chinese equity screen that combines metaverse-sector membership, an arc-shaped price pattern, and a prior-day close above the 250-day moving average. The long moving-average condition is intended to favor stocks already in an established…

AkcijasTehniskie indikatoriSekošana tendencei
SuperMind

This Chinese stock-selection proposal combines three technical conditions: daily price amplitude above 1%, at least two limit-up events within 500 days, and a reported external-to-internal volume ratio above 1.3. The document interprets the first two…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This document introduces factor research as a quantitative way to study characteristics that may help explain asset returns and risk. It names market capitalization, quality, momentum, low volatility, and yield as examples, and describes using statistical or…

Faktoru ieguldīšanaStatistikaPortfeļa veidošanaRiska pārvaldība
SuperMind

This Chinese A-share stock screen combines a positive MACD reading with a stock-heat ranking and a prior-day actual-turnover range of 3% to 28%. It proposes selecting after the daily close. The accompanying explanation treats MACD as a short-term trend…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This post proposes screening Chinese stocks for a daily price move of at least one percent, a nonempty name for an outstanding convertible bond, and exclusion from a specified market segment. It presents the range condition as a way to identify active stocks…

AkcijasĶīnas tirgiTehniskie indikatoriStatistika
SuperMind

This post describes a Chinese equity screen combining three conditions: reported position increases above a threshold, the prior close above a long-term moving average, and a limited opening gain at 9:25. It also offers an alternative using turnover and a…

AkcijasĶīnas tirgiTehniskie indikatoriVēsturisko datu pārbaude
SuperMind

This stock screen combines four filters: price amplitude above a stated threshold, market capitalization below a stated ceiling, positive net profit, and exclusion of the STAR Market. The accompanying discussion presents the amplitude filter as a way to find…

AkcijasĶīnas tirgiSvārstīgumsFaktoru ieguldīšana
SuperMind

This short-term stock screen combines three conditions: prior-day price amplitude above 1%, a prior-day appearance on China’s Dragon-Tiger list with reported buying greater than selling, and a current high that is the highest over the recent two-day window.…

AkcijasĶīnas tirgiCenas izrāviensSvārstīgums
SuperMind

This daily stock screen selects securities before the market opens using three conditions: MACD above zero, a positive price-to-earnings ratio, and more than one year since listing. The document presents MACD as a way to identify an upward trend, treats…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock screening approach combines a Metaverse concept classification with an upward-sloping 30-day moving average and fundamental filters. It first selects companies associated with the theme, then looks for a rising average and firms below the stated…

AkcijasTehniskie indikatoriSekošana tendenceiFaktoru ieguldīšana
SuperMind

This equity selection proposal combines RSI below 65, a circulating market value between 5 billion and 10 billion yuan, and simultaneous bullish crossovers in three technical indicators, with MACD, KDJ, and DMI offered as examples. It interprets the RSI…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This proposed equity screen looks for stocks with turnover between 3% and 12%, three consecutive declining sessions, and a high product of price change and very large order net volume. The article frames the setup as a possible rebound candidate: the…

AkcijasAtgriešanās pie vidējās vērtībasTirgus mikrostruktūraTehniskie indikatori
SuperMind

This stock-selection rule filters for shares with daily high-low amplitude above 1%, a ten-day return above zero but below 35%, and positive PE. The stated rationale is to find stocks with some recent upward movement without selecting the largest short-term…

AkcijasCenas impulssSvārstīgumsTehniskie indikatori
SuperMind

The post outlines a daily A-share selection process that keeps stocks with MACD above its zero line, a price condition relative to the five-day moving average, and positive investor attention or “heat,” then ranks candidates by heat. It gives the standard…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The post describes a simple Chinese A-share stock screen requiring daily high-low movement above 1%, a nonempty outstanding-convertible-bond name, and a share price around 18.5 yuan. Its final restatement widens the price condition to 18–19 yuan, while the…

AkcijasĶīnas tirgiTehniskie indikatoriStatistika
SuperMind

This theme-based stock screen looks for shares with turnover between 3% and 12%, a robot-related classification, floating market value below 10 billion, and a metaverse-related classification. The article supplies an example formula and Python outline. The…

AkcijasĶīnas tirgi
SuperMind

The proposed stock filter combines RSI below 65, best bid volume greater than best ask volume, and exclusion of STAR Market listings. The article interprets RSI as a way to identify relatively low-priced shares and the bid-ask size comparison as a sign of…

AkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This short-term stock screen selects shares with RSI below 65, a daily gain above 1%, and eligibility outside the STAR Market segment. It adds a 15-minute MACD histogram condition: the histogram is negative and becoming less negative, which the document…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This stock screen combines three conditions: daily high-low amplitude above 1%, closing price below 20, and displayed best bid volume greater than best ask volume. The document gives matching formula and Python examples, framing amplitude as a measure of…

AkcijasTehniskie indikatoriTirgus mikrostruktūra