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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 presents a market-timing experiment that applies a Gaussian hidden Markov model to daily CSI 300 data. Its feature set combines the one-day log return, five-day log return, and log high-low range. The model is configured with six latent states…

Kinesiske markederAksjerMaskinlæringStatistikk
BigQuant

The document describes turning intraday order-book and trade data into monthly equity-selection factors. It introduces volume order imbalance (VOI), order imbalance ratio (OIR), and market price bias (MPB). MPB classifies trades by whether buyers or sellers…

AksjerFaktorinvesteringHøyfrekvenshandelMarkedsmikrostruktur
BigQuant

This introductory note defines quantitative investing as using numerical methods, models, and algorithms to make investment decisions, including automated execution. It lists potential advantages: rules can reduce emotion-driven choices, computers can…

StatistikkMaskinlæringHistorisk testing
BigQuant

The document demonstrates a simple cross-sectional factor evaluation for Chinese stocks. It queries daily records for 20-day average turnover and a five-day forward close-to-close return, then groups observations by date and calculates the Spearman rank…

AksjerKinesiske markederFaktorinvesteringStatistikk
BigQuant

The document proposes an equity factor combining turnover with changes in shareholder counts. It first scales shareholder change by the total shareholder count, aiming to reduce the influence of differences in company size. It then applies a signed…

Kinesiske markederAksjerFaktorinvesteringMomentum
BigQuant

This review examines target-risk funds, which aim to maintain a relatively stable portfolio risk level through fixed style categories such as aggressive, moderate, and conservative. It describes their role in US retirement accounts, their fund-of-funds fee…

Flere aktivaklasserPorteføljekonstruksjonRisikostyringStatistikk
BigQuant

This platform troubleshooting note explains that a shared code sample may run without producing backtest data because it is incomplete. The reported sample lacks a data source and a backtest module, and contains only some backtest component methods. It also…

Historisk testingAksjerKinesiske markeder
BigQuant

The report introduces unsupervised learning, focusing on dimensionality reduction and clustering for financial analysis. It describes factor analysis and principal component analysis as ways to compress many stock or bond characteristics into a smaller set…

MaskinlæringStatistikkFaktorinvesteringPorteføljekonstruksjon
BigQuant

This Chinese-language research digest introduces two overseas studies in quantitative stock selection and timing. The first examines factor timing empirically, asking whether investors can adjust factor exposure over time, and discusses the challenges and…

AksjerFaktorinvesteringStatistikkHistorisk testing
BigQuant

This document summarizes a machine learning timing strategy that uses a long short-term memory network to model stock market time series. It presents the model as a way to learn dependencies across observations and adapt to sharp changes in a trend. The…

MaskinlæringAksjerKinesiske markederHistorisk testing
BigQuant

This research summary outlines a progression from single-factor IC and IR analysis toward attribution in machine-learning models and causal analysis. It says IC and IR are foundational for traditional multifactor research but do not capture interactions…

MaskinlæringStatistikkFaktorinvestering
BigQuant

The document describes monthly stock-selection factors built from news sentiment. Summing a stock’s monthly article sentiment scores combines the direction of coverage with its volume, while averaging scores captures sentiment without the same direct…

AksjerMarkedssentimentFaktorinvesteringHistorisk testing
BigQuant

This report examines how corporate tax figures relate to business performance and how tax accounting differs from tax cash flows. It distinguishes tax payable, income tax expense, taxes and surcharges, deferred tax assets or liabilities, and cash taxes paid.…

AksjerFaktorinvesteringKinesiske markederHistorisk testing
BigQuant

This report applies dynamic drawdown control to an enhanced equity strategy based on GARP, combining valuation and growth ideas. It describes using relative price strength (RPS) to adapt the drawdown-control signal to the market’s relative strength, with the…

AksjerKinesiske markederRisikostyringFaktorinvestering
BigQuant

This report outlines a strategic and tactical framework for multi-asset allocation. Strategic allocation favors assets with relative strength over a medium-term horizon, while tactical timing adjusts asset weights according to changing conditions. The…

Flere aktivaklasserFaktorinvesteringPorteføljekonstruksjonRisikostyring
BigQuant

The document explains Elliott Wave theory as a framework for interpreting market trends through a repeating five-wave impulse followed by a three-wave correction. It describes nested wave degrees, three structural rules for impulse waves, and common forms…

Tekniske indikatorerTrendfølgende handelAksjerKinesiske markeder
BigQuant

This forum post describes a daily stock rotation setup: invest the available cash in one stock, sell it the next day, and repeat. The author reports that orders filled close to fully invested earlier in the backtest but did not use all available capital near…

AksjerHistorisk testingPosisjonsstørrelse
BigQuant

The article explains how orders travel from a broker through trading infrastructure into an exchange order book, where matching determines whether and at what price they execute. It describes price priority and time priority, then presents a price-selection…

MarkedsmikrostrukturOrdreutførelseAksjer
BigQuant

The document links prospect theory and mental accounting to the disposition effect: investors may treat gains and losses differently, which can slow how prices incorporate new information. It proposes that post announcement price drift lasts longer when the…

AksjerHendelsesdrevet handelMomentumStatistikk
BigQuant

The document summarizes research on whether hedge funds that perform well continue to do so, depending on overall market conditions. It describes two performance measures based on returns across hedge fund industries: RET_DOWN for weaker markets and RET_UP…

Flere aktivaklasserStatistikkRisikostyring
BigQuant

This Chinese-language forum post asks how BigQuant applies transaction costs to convertible bond strategies. It shows a per-order commission configuration with equal buy and sell rates and a minimum charge, then reports that a sell order still appears to…

Historisk testingRisikostyringKinesiske markeder
BigQuant

This Chinese-language Q&A covers practical questions about equity factors, model templates, backtest assessment, and trading tools. It names market capitalization, turnover, momentum, quality, valuation, growth, and profitability as commonly used factors,…

AksjerFaktorinvesteringHistorisk testingRisikostyring
BigQuant

The document describes an A-share stock screen combining three conditions: a 14-period RSI below 65, free-float market capitalization between 5 and 10 billion yuan, and a MACD value from two sessions earlier below zero. It presents RSI and MACD as technical…

AksjerTekniske indikatorerKinesiske markeder
BigQuant

This Chinese research summary explores using data-mining models to time factor exposure and rotate among equity factors. It describes random forests conditioned on external market variables to assess when factors may be effective, alongside approaches that…

AksjerFaktorinvesteringMaskinlæringStatistikk