Spring til indhold

Videnbibliotek

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
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 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
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

Søg i biblioteket

3,481 dokumenter

BigQuant

The document presents price resiliency (RES), a covariance-based measure intended to capture both the price impact of liquidity shocks and how long those shocks persist. It compares returns in the first half-hour of trading with returns over the rest of the…

AktierStatistikMarkedsmikrostrukturFaktorinvestering
BigQuant

This brief project note reports a modification to an existing quantitative strategy: market capitalization was added to the scoring process and return on equity was removed. The author says the backtest improved after the change, but provides no performance…

AktierFaktorinvesteringPorteføljekonstruktionBacktesting
BigQuant

The document explains how to choose between regression and classification when building machine-learning models for stock research. A regression task predicts a continuous quantity, illustrated by forecasting a stock’s five-day return. It introduces fitting…

MaskinlæringAktierStatistikKinesiske markeder
BigQuant

The report introduces a Barra-style multi-factor risk and return attribution model for Chinese equities. Its central idea is to explain the returns and risks of many stocks through a smaller set of style factors, making portfolio exposures easier to analyze.…

AktierKinesiske markederFaktorinvesteringRisikostyring
BigQuant

This short BigQuant discussion asks whether factor analysis of a custom stock universe requires manually importing a data table. The response says custom feature data can instead be passed into the factor-analysis module, enabling analysis for a user-defined…

AktierFaktorinvesteringStatistikKinesiske markeder
BigQuant

This BigQuant example attempts to close a stock position after its price falls more than 10% below cost, then exclude that instrument from target holdings until a cooldown expires. It tracks expiration dates in a pool, removes expired entries each day,…

AktierRisikostyringBacktesting
BigQuant

This guide explains how BigTrader turns simulated strategy signals into live orders through a desktop trading terminal. Users connect an account and access credential, load a simulation task, review the resulting plans, adjust order sizes and times, then…

OrdreudførelsePositionsstørrelseAktierKinesiske markeder
BigQuant

The document summarizes a report that uses a random forest model to identify rising and falling market patterns from macroeconomic indicators and market data. It describes two applications: timing exposure to the CSI 300 index and rotating among industry…

MaskinlæringAktierKinesiske markederTrendfølgning
BigQuant

This explanation defines an asset’s exposure to a factor as its sensitivity to that factor’s returns. It illustrates the idea with a value factor: filter a broad A-share universe, sort stocks by price-to-earnings ratio, and form a long-short portfolio from…

AktierFaktorinvesteringStatistikPorteføljekonstruktion
BigQuant

This BigQuant help exchange explains how to select a fixed number of records after ranking a stock universe. The question concerns approximating a CSI 1000 universe when a direct index-membership filter is unavailable and usable daily constituent data is…

AktierKinesiske markederPorteføljekonstruktion
BigQuant

The report compares ordinary K-fold cross-validation with time-series cross-validation for tuning machine-learning models on sequential data. Random folds can place later observations in training while earlier ones are used for validation, creating leakage…

MaskinlæringStatistikBacktestingKinesiske markeder
BigQuant

This short support discussion explains why HFTrade applies a volume limit during high-frequency backtests and why that setting can prevent an order from filling completely. The discussion says volume caps may be poorly suited to minute and tick data, where…

HøjfrekvenshandelBacktestingOrdreudførelseMarkedsmikrostruktur
BigQuant

This research summary outlines a strategic allocation model that maps Chinese equities and bonds to underlying macroeconomic risks. It uses principal component analysis to define five factors: economic growth, interest rates, credit, term spread, and…

Flere aktivklasserAktierRentepapirerFaktorinvestering
BigQuant

The document summarizes research on the disposition effect among actively managed U.S. equity mutual funds: managers may sell winning stocks too readily while holding losing stocks. It describes a measurement based on quarterly changes in reported holdings…

AktierStatistikFaktorinvestering
BigQuant

The document distinguishes temporary factor decay from permanent factor failure. It attributes much of the decline in a signal’s excess returns to competition: as more capital uses a factor, its alpha can shrink, while changing market styles may later…

FaktorinvesteringHøjfrekvenshandelOrdreudførelse
BigQuant

This essay presents a set of survival rules for trading Chinese equities during overheated bull markets, using the 2007 and 2015 market peaks as cautionary examples. It describes a recurring pattern of shakeouts, rapid speculative advances, and liquidity…

Kinesiske markederAktierRisikostyringPositionsstørrelse
BigQuant

This brief presents a market review for Chinese A-shares during March 23–27, 2020, alongside a report title stating that the strategic long stance remained unchanged. It lists the strongest and weakest industry groups for the week and tracks several breadth…

AktierKinesiske markederTekniske indikatorerPorteføljekonstruktion
BigQuant

This Chinese equity research note proposes unexpected profitability as a source of stock-selection alpha. It measures operating profitability with return on net operating assets (RNOA), which separates operating activity from financing and is presented as…

AktierFaktorinvesteringStatistikKinesiske markeder
BigQuant

This article presents a critical account of quantitative trading’s possible effects on Chinese equity markets. It argues that rapid order placement and cancellation can make displayed depth incomplete, that some funds combine stock baskets with short index…

AktierKinesiske markederHøjfrekvenshandelMarkedsmikrostruktur
BigQuant

This document outlines a recurring BigQuant program for people developing quantitative trading skills. It has three stages: an online selection round in which participants submit factor models built from a provided template; training for selected entrants;…

FaktorinvesteringBacktestingMaskinlæringHøjfrekvenshandel
BigQuant

This project note describes iterative construction and evaluation of equity factors using amount, turnover, price, market capitalization, and price-to-book data. Candidate expressions combine standardized ratios and rolling statistics, including volatility,…

AktierFaktorinvesteringBacktestingMaskinlæring
BigQuant

This post outlines a Chinese equity screening rule combining turnover, a rising DEA condition, and a cap on tradable share count. It selects stocks with turnover between 3% and 12%, a rising signal derived from moving-average differences, and a circulating…

AktierTekniske indikatorerKinesiske markederRisikostyring
BigQuant

This article describes a reproduction of residual network experiments on CIFAR-10, focusing on two changes from an earlier run: image augmentation and shortcut design. It pads training images by four pixels on each edge and randomly crops them back to the…

MaskinlæringBacktestingStatistik
BigQuant

This document outlines a simple Chinese A-share strategy that ranks stocks by return on equity and selects the ten highest-scoring candidates. It describes filtering out special-treatment stocks, suspended shares, recently listed companies, and Beijing Stock…

AktierFaktorinvesteringPorteføljekonstruktionBacktesting