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Sammenfatninger og hovedpointer fra de bøger, artikler, forskningsartikler og den kode, som vores AI-agenter læser, skrevet af Stratmills researchagent. Hver side linker til originalen.

Quant Q&A
20,364 dokumenter
SuperMind
12,226 dokumenter
OKX Learn
8,431 dokumenter
Strategy library
7,910 dokumenter
MQL5 code base
7,090 dokumenter
BigQuant
3,481 dokumenter
Bitget Academy
3,298 dokumenter
MQL5 articles
3,012 dokumenter
TradingView scripts
1,976 dokumenter
ProRealCode
1,507 dokumenter
Deribit Insights
1,232 dokumenter
Machine Learning for Trading
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arXiv papers
1,033 dokumenter
Amberdata research
766 dokumenter
FMZ forum
682 dokumenter
FMZ digest
662 dokumenter
vn.py community
560 dokumenter
QuantInsti blog
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Galaxy Research
340 dokumenter
QuantStart
246 dokumenter
Stratmill research code
219 dokumenter
Robot Wealth
195 dokumenter
NautilusTrader
191 dokumenter
Hummingbot docs
181 dokumenter
Paradigm research
175 dokumenter
Lumibot
164 dokumenter
Kraken Learn
163 dokumenter
Bibliotek med kvantkurser
157 dokumenter
OctoBot
152 dokumenter
Cryptohopper blog
144 dokumenter
Systematic trading blog (Rob Carver)
132 dokumenter
Qlib
116 dokumenter
TqSdk
86 dokumenter
Quantpedia
86 dokumenter
Hyperliquid docs
79 dokumenter
Freqtrade
68 dokumenter
Hudson & Thames
62 dokumenter
Awesome Systematic Trading
61 dokumenter
backtrader
54 dokumenter
vn.py
50 dokumenter
Binance API docs
45 dokumenter
Quantopian-forelæsninger
45 dokumenter
FMZ guides
38 dokumenter
pysystemtrade
34 dokumenter
Freqtrade docs
32 dokumenter
quant-trading
31 dokumenter
FinRL
28 dokumenter
Zipline
22 dokumenter
FMZ live strategies
21 dokumenter
Jesse
17 dokumenter
pyfolio
16 dokumenter
WonderTrader
14 dokumenter
Alphalens
14 dokumenter
backtesting.py
11 dokumenter
Technical Analysis
9 dokumenter
QTPyLib
8 dokumenter
QuantRocket
7 dokumenter
Lumibot strategies
7 dokumenter
Awesome Quant
1 dokumenter

Søg i biblioteket

3,481 dokumenter

BigQuant

The document outlines the role of an integrated quantitative trading platform. It describes a workflow that brings market data analysis, strategy development, historical backtesting, risk assessment, and automated execution together. It also notes that…

BacktestingOrdreudførelseRisikostyringFlere aktivklasser
BigQuant

The document outlines a broad framework for evaluating equity factors. It combines periodic cross-sectional robust linear regression to estimate factor returns, information coefficients (IC) to measure the relationship between factor exposures and subsequent…

AktierFaktorinvesteringStatistikBacktesting
BigQuant

This stock-selection strategy ranks shares using large-order net inflow and relative price performance. Its stated purchase screen looks at the prior 30 trading days, selecting stocks whose net inflow share from very large orders is among the top 5% of the…

AktierMomentumStatistikBacktesting
BigQuant

This research note describes a method for detecting support and resistance lines in Chinese A-share price series. It adapts a local high and low point approach with quantile regression, defining line slopes for continuation patterns such as triangles,…

AktierKinesiske markederTekniske indikatorerKursgennembrud
BigQuant

This tutorial explains how to request foreign exchange futures market data through an HTTP endpoint and a WebSocket connection. It uses the micro British pound continuous contract as an example, showing how request parameters identify the bar interval,…

FuturesValutahandelMarkedsmikrostrukturOrdreudførelse
BigQuant

The article summarizes research on whether diversified business groups take longer than single industry firms to have earnings news reflected in share prices. It argues that interpreting segment results is harder when a company spans businesses with…

AktierMomentumStatistikFaktorinvestering
BigQuant

A user reports that BigQuant’s trade simulation showed a purchase at the market open and a sale at the close on the same day, despite having no carried position and expecting the position to be zero. The response explains that this can be normal because the…

OrdreudførelseBacktesting
BigQuant

This brief question-and-answer explains how to assess whether returns across factor-sorted groups are ordered. A factor analysis sorts stocks in a chosen universe by factor value and divides them into groups; the lowest-ranked factor values form the bottom…

FaktorinvesteringAktierStatistik
BigQuant

This BigQuant example builds a mainland Chinese stock portfolio by screening for eligible main-board shares and excluding suspended, ST, and recently listed names. It requires positive trailing earnings and dividend yield, caps float market capitalization,…

AktierKinesiske markederFaktorinvesteringPorteføljekonstruktion
BigQuant

This discussion compares high-frequency price and volume strategies with lower-frequency fundamental quant investing in China’s equity market. It argues that high-frequency approaches depend heavily on hardware and execution capabilities, while fundamental…

Kinesiske markederAktierHøjfrekvenshandelFaktorinvestering
BigQuant

This support exchange addresses errors encountered while following a BigQuant tutorial. It identifies two script issues: a data source table name cannot contain spaces, and the daily Chinese stock bar table exposes fields such as close, open, high, and low…

AktierStatistik
BigQuant

The report analyzes cross-sectional price momentum in Chinese equities and organizes possible improvements along two dimensions: whether a change refines the measurement or the formation process, and whether it uses price or return information. Examples…

AktierKinesiske markederMomentumFaktorinvestering
BigQuant

This report surveys asset-allocation approaches grouped by their inputs: mean-variance models, risk-allocation models, and subjective methods. It expresses several optimization-based risk models, including mean-variance, risk parity, and maximum…

Flere aktivklasserPorteføljekonstruktionRisikostyringBacktesting
BigQuant

This example selects stocks from the Chinese equity market using dividend yield, share price, and circulating market capitalization. It first keeps the highest-dividend-yield quarter of the market and stocks priced below 10 yuan, then excludes certain…

Kinesiske markederAktierFaktorinvesteringPorteføljekonstruktion
BigQuant

The document introduces quantitative investing as using computer technology to analyze investment data, make trading decisions, and execute trades. It outlines two practical advantages: computers can process large amounts of information quickly, and…

Flere aktivklasserStatistikRisikostyring
BigQuant

This research summary compares three sources for studying foreign ownership of China A-shares: QFII/RQFII disclosures, Stock Connect holdings, and Refinitiv Ownership data. QFII reports arrive at lower frequency and can be substantially delayed. Stock…

AktierKinesiske markederFaktorinvesteringStatistik
BigQuant

The document shows a workflow for calculating daily industry-level average price-to-earnings ratios for Chinese stocks. It queries industry membership and valuation data, groups constituents by date and industry, filters valuation records to each group,…

AktierKinesiske markederStatistikOrdreudførelse
BigQuant

The document summarizes a study of stock price movement prediction in China’s A-share market. It describes combining five data types: historical trading data, technical indicators, company announcements, news, and Baidu search activity. The researchers…

AktierKinesiske markederMaskinlæringTekniske indikatorer
BigQuant

The report presents a Chinese equity timing approach that combines a prior model based on limit-move breadth with a price-volume confirmation model. Its premise is that the two systems capture different long-entry periods: the combined model aims to retain…

AktierKinesiske markederMomentumBacktesting
BigQuant

The document describes research that turns intraday stock volume data into factors for stock selection. It presents seven conventional volume distribution factors and six specialized ones. The methods include measuring minute volume through bucket entropy…

AktierFaktorinvesteringHøjfrekvenshandelStatistik
BigQuant

This overview introduces several machine learning approaches used in stock strategies: deep neural networks, convolutional networks, LSTMs, gradient-boosted trees, and a ranking model built around GBDT. It briefly describes what each model can learn or…

MaskinlæringAktierRisikostyringBacktesting
BigQuant

This indicator takes the derivative of the difference between an arithmetic moving average and a geometric moving average. Both averages are calculated from OHLC4 prices, the mean of the open, high, low, and close for each bar. The description identifies…

Tekniske indikatorer
BigQuant

This Chinese-language report reviews the development of China’s quantitative fund industry across three periods: before 2010, 2010–2015, and 2016 onward. It outlines a strategy landscape spanning market-neutral equity, index enhancement, quantitative stock…

Kinesiske markederFlere aktivklasserTrendfølgningArbitrage
BigQuant

This review summarizes research on how company news coverage relates to investment efficiency in US firms. The study measures inefficient investment as the difference between actual investment and an expected level based on sales growth, separating…

AktierAmerikanske markederBegivenhedsdrevetMarkedssentiment