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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
Quantpedia
86 dokumenter
TqSdk
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
Quantopian-forelesninger
45 dokumenter
Binance API docs
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 framework for testing stock-selection factors. It evaluates each trading day’s stock factor values against returns over subsequent holding periods, aiming to show how predictive information changes as the holding period grows. Daily…

AksjerFaktorinvesteringStatistikkHistorisk testing
BigQuant

The post asks how to adapt a portfolio-selling routine so that, when the equity allocation exceeds 60% of total portfolio value, the excess exposure is sold from the lowest-ranked holdings. The supplied routine builds a set of currently held securities,…

AksjerPorteføljekonstruksjonPosisjonsstørrelseOrdreutførelse
BigQuant

The post reports an observation from more than six months of intraday modeling in Chinese equities using five-minute bars. At each time point, the author independently tuned parameters with tree-structured Parzen estimation. The reported optimization…

AksjerKinesiske markederMaskinlæringStatistikk
BigQuant

This research summary examines where mutual fund excess returns may come from, separating security-selection skill from timing skill. Timing is framed as adjusting a fund's market beta, with stronger exposure during rising markets and reduced exposure during…

AksjerFaktorinvesteringStatistikkPorteføljekonstruksjon
BigQuant

The document introduces quantitative investing as an approach that uses numerical models to build an investment process, contrasting it with methods that rely more on qualitative judgment. It describes how quantitative methods can combine computing with…

Flere aktivaklasserAksjerStatistikkPorteføljekonstruksjon
BigQuant

This short assignment response defines quantitative investing as turning recurring patterns observed through statistical analysis of financial markets into structured methods for future trading. It mentions stocks, futures, and digital assets, and describes…

Flere aktivaklasserStatistikkMaskinlæringRisikostyring
BigQuant

The note explains how a Chinese stock daily bar series relates to adjusted and unadjusted prices. It identifies the cited index daily data as back-adjusted and shows that dividing the close by its adjustment factor can recover an unadjusted price. The…

AksjerKinesiske markeder
BigQuant

This guide explains how to carry training data for a StockRanker model from BigQuant’s 1.0 environment into version 3.0. In the older environment, it exports the training dataset with date, instrument, label, and the selected feature columns. The file is…

MaskinlæringAksjer
BigQuant

This weekly market report organizes several indicators of Chinese equity liquidity by sector: ETF subscriptions and redemptions, northbound investor flows, estimated allocations from pending and newly raised equity funds, company buybacks, and…

AksjerKinesiske markederStatistikkMarkedssentiment
BigQuant

The document examines how trend following could address the equity risk concentration in conventional target-date funds. Their glide paths reduce stock allocations as retirement approaches, yet the portfolio may remain dominated by equity risk, leaving…

Trendfølgende handelFlere aktivaklasserRisikostyringPorteføljekonstruksjon
BigQuant

This BigQuant support exchange explains a possible source of confusion in backtests: the platform’s `hold_days` setting defines a build-up period during which the strategy can buy, and does not itself require each purchased stock to remain in the portfolio…

Historisk testingPorteføljekonstruksjonOrdreutførelse
BigQuant

The document explains a two-stage model that uses gradient-boosted decision trees to create features for logistic regression. The trees split and combine the original inputs; each sample is then represented by a binary vector marking the leaf it reaches in…

MaskinlæringStatistikkHistorisk testing
BigQuant

This tutorial demonstrates extracting minute-level stock data for a selected date range with a distributed query platform, then calculating features through SQL-style operators. The examples cover a five-period moving average of closing prices, a…

AksjerTekniske indikatorerStatistikkMaskinlæring
BigQuant

The document presents an individual-investor approach inspired by Peter Lynch: use familiar products and services to generate company ideas, then assess business quality, growth, debt, and valuation. Its suggested checks include sustained profit growth,…

AksjerPosisjonsstørrelsePorteføljekonstruksjonRisikostyring
BigQuant

This research summary examines why stocks can earn excess returns before earnings announcements. It proposes that investors and analysts resolve some uncertainty ahead of the report, supporting price gains before the announcement itself. The study measures…

AksjerOpsjonerHendelsesdrevet handelVolatilitet
BigQuant

The document reports a single-factor study of operating-efficiency and growth measures. For six operating factors, it says the analysis used grouped portfolio net values, long-short group returns, information coefficients, and Fama–MacBeth methods. Four…

AksjerFaktorinvesteringStatistikkHistorisk testing
BigQuant

The study summary examines whether active stock selection that increases a mutual fund portfolio’s technological similarity predicts subsequent performance. Company patent distributions are compared using cosine similarity, and a fund’s active technological…

AksjerFaktorinvesteringStatistikkPorteføljekonstruksjon
BigQuant

This Chinese-language forum post raises practical questions about what factor weights from a labeling or training process represent. It distinguishes possible interpretations, including neural-network parameters, regression coefficients, and tree-based…

FaktorinvesteringMaskinlæringStatistikk
BigQuant

This summary of an equity research report explains portfolio optimization as a framework for managing risk exposures, holdings, weights, turnover, and market impact while incorporating investor views. It argues that simple portfolio construction may perform…

AksjerPorteføljekonstruksjonRisikostyringStatistikk
BigQuant

This brief report summarizes a quantitative market-timing view of Chinese A-shares as of early April 2020. It describes the market as being in a bottoming phase with limited downside, and lists sector strength, index and industry valuations, stock-market…

AksjerKinesiske markederTekniske indikatorerStatistikk
BigQuant

The document presents Wyckoff analysis as a way to interpret market supply and demand through price and volume. It describes three guiding principles: compare demand with supply, treat trading ranges as potential causes of later moves, and assess whether…

AksjerKinesiske markederTekniske indikatorerKursbrudd
BigQuant

The article argues that quantitative trading depends on market understanding as well as technical implementation. It contrasts trend-following and mean-reversion approaches as examples of strategies grounded in different views of market behavior, and…

FaktorinvesteringTrendfølgende handelTilbakevending mot gjennomsnittetRisikostyring
BigQuant

The article describes a supervised learning approach that classifies whether a stock’s closing price will be higher or lower after a chosen horizon. It smooths historical prices with exponential weighting, then uses six technical indicators—including RSI,…

AksjerMaskinlæringTekniske indikatorerHistorisk testing