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Kunnskapsbibliotek

Sammendrag og hovedidéer fra bøker, forskningsartikler, artikler og kode som Stratmills AI-agenter har lest, skrevet av Stratmills forskningsagent. Hver side lenker 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
1,124 dokumenter
arXiv papers
1,033 dokumenter
Amberdata research
766 dokumenter
FMZ forum
682 dokumenter
FMZ digest
662 dokumenter
vn.py community
560 dokumenter
QuantInsti blog
511 dokumenter
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 for kvantkurs
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-forelesninger
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
Alphalens
14 dokumenter
WonderTrader
14 dokumenter
backtesting.py
11 dokumenter
Technical Analysis
9 dokumenter
QTPyLib
8 dokumenter
QuantRocket
7 dokumenter
Lumibot strategies
7 dokumenter
Awesome Quant
1 dokumenter

Søk i biblioteket

3,481 dokumenter

BigQuant

This post proposes a stock-selection screen using daily price amplitude, a rounded price shape, MACD above its zero line, and volume above its recent average. The stated rationale is that amplitude and the rounded pattern identify active stocks, while…

AksjerKinesiske markederTekniske indikatorerMomentum
BigQuant

The article presents four warning signs that a rising equity market may be approaching a peak: an index making new highs while volume contracts, momentum indicators failing to confirm price highs, heavy volume accompanying a falling or sharply rejected…

AksjerKinesiske markederTekniske indikatorerMomentum
BigQuant

The article compares three consumer activity measures for publicly traded companies: estimated in-store visits, traffic to company and related websites, and interest in brands measured through search and social activity. It forms growth proxies by comparing…

AksjerFaktorinvesteringMarkedssentimentHistorisk testing
BigQuant

The document outlines six assumptions used to simplify asset pricing theory, especially the Capital Asset Pricing Model: competitive and efficient markets, no taxes or transaction costs, risk-averse investors, shared expectations, normally distributed…

StatistikkRisikostyringPorteføljekonstruksjonFaktorinvestering
BigQuant

The research note describes factor-mimicking portfolios (FMPs) as an alternative representation of alpha factors, with conversion between the two under a given stock covariance structure. It argues that linearly combining alpha signals corresponds to…

AksjerFaktorinvesteringPorteføljekonstruksjonStatistikk
BigQuant

This short note introduces data preprocessing as a step that can help machine-learning and deep-learning estimators work with raw feature vectors. It points readers to scikit-learn’s preprocessing module, which provides transformation classes and functions…

MaskinlæringStatistikk
BigQuant

This research summary examines whether Chinese listed companies’ earnings previews can add information to conventional equity factor models. Because previews arrive before earnings announcements and periodic financial reports, the report treats them as an…

AksjerFaktorinvesteringHendelsesdrevet handelStatistikk
BigQuant

This short BigQuant support exchange answers how to obtain an algorithm’s daily returns from backtest performance data. Its method reads the raw performance table, takes the cumulative algorithm period return, converts it to a growth index by adding one, and…

Historisk testingStatistikk
BigQuant

This research summary examines two responses to a prolonged value-factor drawdown: changing how the factor is constructed and forecasting when its returns may be stronger. It compares conventional cross-sectional valuation with time-series measures of a…

AksjerFaktorinvesteringStatistikkKinesiske markeder
BigQuant

This assignment asks learners to build a trading strategy using the standard deviation of turnover rate as a stock selection factor. It also specifies two exit rules: liquidate positions when the broad market falls by 4% consecutively, and close an…

Kinesiske markederAksjerFaktorinvesteringRisikostyring
BigQuant

The article contrasts discretionary stock trading with quantitative approaches that analyze large datasets for statistical relationships. It describes using price and volume alongside less conventional inputs, such as online search activity and social media,…

AksjerMaskinlæringMarkedssentimentOrdreutførelse
BigQuant

The document presents a discretionary chart-reading idea for stocks that rally sharply and then drift lower on shrinking volume and narrow price ranges. It interprets this pattern as possible position cleaning by a large market participant, arguing that slow…

AksjerTekniske indikatorerKinesiske markeder
BigQuant

This research applies macroeconomic momentum signals to active bond trading, aiming to forecast government bond yield direction as well as changes in term and credit spreads. It contrasts active strategies focused on capital gains with passive approaches…

RentepapirerMomentumStatistikkHistorisk testing
BigQuant

The document introduces microstructure segmentation: using high-frequency price and volume data to divide trading into intervals with different trading characteristics. It argues that activity levels can correspond to different price-trend behavior and…

HøyfrekvenshandelMarkedsmikrostrukturFaktorinvesteringStatistikk
BigQuant

This 2020 investment analysis discusses the ChiNext index and Bosera's ETF tracking it. It argues that refinancing policy changes and the stock registration system could improve financing access for technology and growth companies. The index is described as…

AksjerKinesiske markederPorteføljekonstruksjon
BigQuant

This research summary introduces APM, a stock-selection factor built from differences between morning and afternoon price behavior in Chinese A-shares. Its premise is that informed traders are more active in the morning, making morning price moves a stronger…

AksjerFaktorinvesteringKinesiske markederHistorisk testing
BigQuant

This short forum exchange raises a practical concern about transparency in visual quantitative research tools. A user asks for fuller descriptions of how drag-and-drop modules calculate outputs, especially whether feature-generation steps first group data by…

StatistikkMaskinlæringHistorisk testing
BigQuant

This research note describes a daily equity alpha approach that uses supervised neural networks to generate many candidate factors from designed factor units. It then transforms the original inputs into weak, mutually orthogonal factors and weights them…

AksjerMaskinlæringFaktorinvesteringStatistikk
BigQuant

This study adapts SinGAN, a multiscale generative adversarial network trained on one sample, to generate financial return sequences. Its pyramid trains progressively across scales: coarse layers represent broad, low-frequency structure, while finer layers…

MaskinlæringStatistikkHistorisk testingAksjer
BigQuant

This report reviews equity factor performance, emphasizing a February 2018 snapshot and trends over a longer historical period. It compares factor information coefficients, which measure association with subsequent returns, and market neutral long-short…

AksjerFaktorinvesteringMomentumTekniske indikatorer
BigQuant

This summary describes a single-stock strategy for Changchun High-Tech, a Chinese pharmaceutical company. It argues that steady fundamentals and stable analyst expectations for earnings growth create a valuation reference point. Using a price-to-earnings…

AksjerKinesiske markederRisikostyringPosisjonsstørrelse
BigQuant

The document summarizes research that derives two liquidity factors from high-frequency order-book data, one associated with buy orders and one with sell orders. The factors are then aggregated to monthly frequency for use in stock selection. It reports that…

AksjerMarkedsmikrostrukturFaktorinvesteringHistorisk testing
BigQuant

This edited seminar transcript surveys a Chinese quantitative research program on deep learning, then focuses on AlphaNet, a neural approach to stock factor discovery. It frames a multi-factor process as factor generation, factor combination, and portfolio…

AksjerKinesiske markederMaskinlæringFaktorinvestering