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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

The document outlines a way to run multiple parameterized tasks in BigQuant, a low-code platform where a visual workflow is represented as a graph of modules. A parallel mapping function can dispatch different inputs to a function, and the same pattern can…

MaskinlæringHistorisk testing
BigQuant

The document describes deploying the small Kronos pretrained model on a quantitative research platform to forecast five-minute candlestick data for stocks. Kronos represents OHLCV sequences as hierarchical discrete tokens using a specialized tokenizer, then…

MaskinlæringAksjerHistorisk testingKinesiske markeder
BigQuant

This research summary compares Naive Bayes, linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) as supervised methods for multi-factor stock selection. The described process extracts and preprocesses features and labels, retrains…

AksjerMaskinlæringFaktorinvesteringHistorisk testing
BigQuant

The document proposes separating sector allocation from industry selection because broad sector shifts are linked more closely to economic conditions, while industry performance depends on factors such as earnings, valuation, and capital flows. It argues…

Kinesiske markederAksjerFaktorinvesteringPorteføljekonstruksjon
BigQuant

This paper-reading digest summarizes several computer vision methods: InstanceFCN for generating object instance masks from position-sensitive score maps; a two-stream residual network that combines full-resolution detail with pooled features for…

MaskinlæringStatistikk
BigQuant

This article explains Bollinger Bands as a moving average surrounded by upper and lower bands set a chosen number of standard deviations away. It walks through a small closing-price example and gives a second illustrative calculation using a 20-period…

Tekniske indikatorerVolatilitetTilbakevending mot gjennomsnittetTrendfølgende handel
BigQuant

The document summarizes research using public Northbound investor holdings and trading-flow data to build 12 factors for Chinese equities. It reports testing those factors from December 2016 through December 2019 across Northbound-held stocks, the CSI 800,…

AksjerKinesiske markederFaktorinvesteringStatistikk
BigQuant

This research summary argues that bond fund rankings based on a single historical performance measure can be distorted by differences in market style, objectives, holdings, manager skill, fund size, and risk controls. Its proposed approach narrows the…

RentepapirerStatistikkFaktorinvesteringPorteføljekonstruksjon
BigQuant

This proposed Chinese equity screen combines three conditions: price amplitude above a stated threshold, a shortening negative MACD histogram on a 15-minute chart, and evidence interpreted as institutional buying. The rationale is that elevated amplitude…

Kinesiske markederAksjerTekniske indikatorerMomentum
BigQuant

This note argues that quantitative strategy results depend on the combination of input factors and predictive models. It says that different factors can produce substantially different backtests when paired with the same model, and that a given factor can…

FaktorinvesteringMaskinlæringHistorisk testing
BigQuant

This study examines whether U.S. equity mutual fund managers adjust market exposure when broad stock mispricing changes. It builds a market mispricing measure from a financing-based long-short factor, then orthogonalizes it against macroeconomic variables. A…

AksjerFaktorinvesteringStatistikkHistorisk testing
BigQuant

This factor study examines whether the share of a stock’s trading volume occurring in the opening call auction contains information useful for equity selection. It builds an opening call-auction volume proportion factor from relative volume and moving…

AksjerHøyfrekvenshandelMarkedsmikrostrukturFaktorinvestering
BigQuant

This research summary describes a model for estimating whether a company will meet or exceed analyst expectations in its next reporting period. Its premise is that earnings delivery has persistence: stocks that beat expectations in one period are more likely…

AksjerMaskinlæringStatistikkFaktorinvestering
BigQuant

The report applies a modified Grinold-style decomposition to attribute equity index returns to dividend yield, nominal earnings growth, and changes in the price-to-earnings multiple. It compares major Chinese broad-market indexes and selected industry…

AksjerKinesiske markederAmerikanske markederFaktorinvestering
BigQuant

This overview explains Dow Theory through three trend scales: primary movements that define the broad market direction, secondary moves that correct the primary trend, and shorter daily fluctuations. It also summarizes six principles later writers attributed…

Trendfølgende handelTekniske indikatorerMarkedsmikrostruktur
BigQuant

This brief Chinese-language post describes a stock-selection submission that adds price-to-sales and dividend-yield filters, then increases the weight assigned to dividend yield. The author says the results improved, but provides no performance figures, test…

AksjerFaktorinvesteringPorteføljekonstruksjon
BigQuant

The document outlines a China equity industry-rotation strategy using the Shenwan Level 1 industry classification. It ranks industries with a composite momentum measure formed from recent 5-day, 20-day, and 60-day returns, weighted 0.4, 0.3, and 0.3. Each…

Kinesiske markederAksjerMomentumFaktorinvestering
BigQuant

The document raises a measurement question about Rank IC, a rank-based measure of association between model predictions and subsequent returns. The author reports that Rank IC computed on a custom training set differs substantially from the value produced by…

StatistikkMaskinlæringHistorisk testing
BigQuant

This research report explains how equity risk factors and factor models can help identify portfolio risks, estimate return covariances, and analyze portfolio performance. It distinguishes risk factors from alpha factors and discusses factor returns,…

Kinesiske markederAksjerRisikostyringPorteføljekonstruksjon
BigQuant

This report outlines a framework for researching quantitative commodity signals in iron ore. It groups inputs into fundamental factors covering supply, demand, and inventories, plus a separate sentiment category. Because fundamental data updates less…

RåvarerFaktorinvesteringMarkedssentimentMomentum
BigQuant

This research summary examines generalized linear models as ways to combine stock factor exposures into forecasts of future returns. Its workflow includes extracting features and labels, preprocessing features, forming training sets, and retraining on a…

Kinesiske markederAksjerMaskinlæringFaktorinvestering
BigQuant

This discussion explores representing Chinese stocks that hit the daily price limit as members of a shared hot theme, then counting limit-up names within each theme. The example is state-owned enterprise reform, where stocks from different industry sectors…

AksjerKinesiske markederMomentumFaktorinvestering
BigQuant

This summary of a 2018 A-share report reviews quantitative fund products, equity factor styles, and institutional responses to a difficult market structure. It says index-enhanced fund assets rose by 55.31 billion while hedged and actively managed…

AksjerKinesiske markederFaktorinvesteringTilbakevending mot gjennomsnittet
BigQuant

This brief indicator note introduces the Consecutive Break (CB) measure and names a close-price input with upward and downward length parameters. Its pseudocode defines an upward count as the number of consecutive bars in which the close exceeds the previous…

AksjerTekniske indikatorerMomentum