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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: 79,386

SuperMind

The article surveys the development of quantitative trading through stories about Jules Regnault, Edward Thorp, and James Simons. It describes using historical price data and mathematical models to identify market patterns, Thorp’s probability-based…

StatistikaMašīnmācīšanāsVairāku aktīvu tirdzniecībaRiska pārvaldība
SuperMind

This Chinese stock-screening proposal selects high-amplitude shares that had three consecutive limit-up sessions, then checks whether the latest close lies between the middle and upper Bollinger Bands. The post presents the sequence as a way to find active…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas izrāviens
MQL5 code base

This indicator guide explains how logarithmic transformations can express price behavior in relative rather than absolute terms. It distinguishes a log price, calculated as the natural logarithm of the close, from log returns, calculated as the difference…

Tehniskie indikatoriStatistikaSvārstīgumsCenas impulss
SuperMind

This stock-screening idea combines three conditions: at least five moving averages converge, company scale exceeds two hundred million in the source’s stated units, and the dividend payout ratio for 2019 is above 25 percent. The post interprets converging…

Ķīnas tirgiAkcijasTehniskie indikatoriFaktoru ieguldīšana
BigQuant

This older Chinese-equity strategy looks for stocks that rally to the daily limit, pull back, and later break to a new high. It defines a pullback as any post-limit-up close below the earlier limit-up price. After the pullback, a new high triggers a purchase…

Ķīnas tirgiAkcijasCenas izrāviensCenas impulss
SuperMind

This screening approach focuses on stocks classified in the metaverse sector, with actual turnover on the prior day between 3% and 28%, and a rising KDJ K value. The article interprets sector membership as exposure to a potentially growing theme, turnover as…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

The proposed stock screen selects equities with turnover between 3% and 12%, first-level bid volume greater than first-level ask volume, and a K-line value below 20. The article characterizes these as technical conditions and suggests the combined filters…

AkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This stock-selection rule combines three conditions: price amplitude above 1, evidence of main-fund control on the prior day, and shortening MACD histogram bars on a 15-minute chart. The document presents these as signs of activity, capital interest, and…

AkcijasTehniskie indikatoriCenas impulss
MQL5 code base

This Expert Advisor combines entry signals from the DeMarker oscillator with a position-sizing rule that increases the lot after a losing trade. It exposes the oscillator period, take-profit distance, stop-loss distance, initial lot size, a trade identifier,…

Tehniskie indikatoriPozīcijas apjoma noteikšanaRiska pārvaldībaVēsturisko datu pārbaude
SuperMind

This document describes a Chinese equity screen that combines three conditions: daily amplitude above 1%, weekly MACD above the zero axis, and positive net buying attributed to major investors during the opening auction. It frames the range and MACD measures…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This document proposes a weekly Chinese equity screen focused on metaverse-related stocks. It selects shares that recorded a limit-up within the prior 25 days and had large-order net volume above 0.05 for at least three consecutive days. The stated approach…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This document describes a Chinese equity screening rule that combines a turnover range of 3% to 12%, a stochastic K value below 20, and a rising MACD signal line (DEA). It presents the conditions as a buy signal and gives example implementations using a…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This document presents an A-share stock screen that combines a turnover range of 3% to 12%, a newly formed KDJ golden cross, and a volume ratio between 1.5 and 6. It describes turnover and the crossover as participation and trend signals, while the volume…

AkcijasTehniskie indikatoriCenas impulssTirgus mikrostruktūra
MQL5 code base

This brief page describes an MQL5 indicator for Chaikin smoothed volatility that allows the user to select the chart timeframe through an input parameter. The default shown is a four-hour period. The page is primarily an indicator listing and setup note: it…

SvārstīgumsTehniskie indikatori
SuperMind

This A-share selection rule filters for stocks in the beverage and alcohol import-export industry, with turnover between 3% and 12% and at least one limit-up event during the prior 25 days. The post explains the turnover range as a way to seek moderate…

AkcijasĶīnas tirgiCenas impulssTirgus noskaņojums
SuperMind

This A-share screening idea selects stocks with a MACD line above zero, high relative investor attention, trading volume above a stated threshold, and an opening price above the previous close. The screen is run after the daily close. Its rationale is to…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
ProRealCode

This stock strategy builds a daily signal from two nested exponential moving averages: a longer average of closing prices and a shorter average of that result. Their percentage difference serves as a proxy for comparing daily and weekly RSI behavior around…

AkcijasTehniskie indikatoriSvārstīgumsRiska pārvaldība
SuperMind

This post describes a Chinese A-share stock screen based on three conditions: price amplitude above one percent, a nonempty name for an outstanding convertible bond, and at least one daily gain of ten percent or more during the previous 25 trading days. It…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
BigQuant

This Chinese-language conference excerpt introduces how artificial intelligence is being adopted by global asset managers. It frames technology as one response to falling margins per unit of managed assets, alongside efforts to grow assets under management.…

MašīnmācīšanāsFaktoru ieguldīšanaPortfeļa veidošanaTirgus noskaņojums
Amberdata research

The newsletter links weaker U.S. payroll data and expectations for Federal Reserve rate cuts with diverging moves in gold and crypto. It interprets low VIX readings, short VIX futures positioning, and differences between September and October VIX futures as…

KriptoaktīviOpcijasSvārstīgumsAtvasināto instrumentu cenu noteikšana
SuperMind

This document proposes screening Chinese stocks with codes beginning in 60 for turnover between 3% and 12% that appeared on the prior day’s market watchlist, known as the Dragon and Tiger List. Turnover is treated as a liquidity filter, while the watchlist…

AkcijasĶīnas tirgiTirgus mikrostruktūraTirgus noskaņojums