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Kennisbibliotheek

Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.

Quant Q&A
20,364 documenten
SuperMind
12,226 documenten
OKX Learn
8,431 documenten
Strategy library
7,910 documenten
MQL5 code base
7,090 documenten
BigQuant
3,481 documenten
Bitget Academy
3,298 documenten
MQL5 articles
3,012 documenten
TradingView scripts
1,976 documenten
ProRealCode
1,507 documenten
Deribit Insights
1,232 documenten
Machine Learning for Trading
1,124 documenten
arXiv papers
1,033 documenten
Amberdata research
766 documenten
FMZ forum
682 documenten
FMZ digest
662 documenten
vn.py community
560 documenten
QuantInsti blog
511 documenten
Galaxy Research
340 documenten
QuantStart
246 documenten
Stratmill research code
219 documenten
Robot Wealth
195 documenten
NautilusTrader
191 documenten
Hummingbot docs
181 documenten
Paradigm research
175 documenten
Lumibot
164 documenten
Kraken Learn
163 documenten
Bibliotheek quantcursussen
157 documenten
OctoBot
152 documenten
Cryptohopper blog
144 documenten
Systematic trading blog (Rob Carver)
132 documenten
Qlib
116 documenten
TqSdk
86 documenten
Quantpedia
86 documenten
Hyperliquid docs
79 documenten
Freqtrade
68 documenten
Hudson & Thames
62 documenten
Awesome Systematic Trading
61 documenten
backtrader
54 documenten
vn.py
50 documenten
Binance API docs
45 documenten
Quantopian-colleges
45 documenten
FMZ guides
38 documenten
pysystemtrade
34 documenten
Freqtrade docs
32 documenten
quant-trading
31 documenten
FinRL
28 documenten
Zipline
22 documenten
FMZ live strategies
21 documenten
Jesse
17 documenten
pyfolio
16 documenten
Alphalens
14 documenten
WonderTrader
14 documenten
backtesting.py
11 documenten
Technical Analysis
9 documenten
QTPyLib
8 documenten
QuantRocket
7 documenten
Lumibot strategies
7 documenten
Awesome Quant
1 documenten

Doorzoek de bibliotheek

3,481 documenten

BigQuant

This summary of a Chinese A-share research report explains small-cap and value premiums through stocks’ differing sensitivities to cash-flow expectations and discount rates. It frames equity returns with a two-beta model that separates those influences,…

AandelenChinese marktenFactorbeleggenPortefeuilleconstructie
BigQuant

This article describes a strategy that changes exposure to equity factors according to a four-state business-cycle classification: recovery, expansion, slowdown, and contraction. It combines the US Leading Economic Indicator with a Global Risk Appetite Cycle…

AandelenFactorbeleggenMomentumPortefeuilleconstructie
BigQuant

This study examines Bitcoin risk using high-frequency returns and realized variance, with particular attention to jumps and their role in forecasting. It finds that conventional jump measures can be biased by frequent, extended price moves. Threshold-based…

CryptoVolatiliteitRisicobeheerStatistiek
BigQuant

This document summarizes an article on applying quantitative methods to environmental, social, and governance investing. It argues that quantitative portfolio tools can translate investor preferences into portfolio construction and extend sustainability…

AandelenPortefeuilleconstructieFactorbeleggenStatistiek
BigQuant

This 2020 research summary assesses when reported global COVID-19 cases might peak and whether China could face another major outbreak. It argues that expanded testing could first reveal a turning point in daily reported cases as backlogs clear, while…

StatistiekChinese marktenGebeurtenisgestuurd
BigQuant

This document outlines a daily MACD strategy applied to five named Chinese stocks. It describes buying when the MACD fast line crosses above the slow line and selling when the slow line crosses above the fast line. The listed securities span consumer goods,…

AandelenTechnische indicatorenMomentumChinese markten
BigQuant

This 2019 outlook reviews China’s financial product and asset management markets amid regulatory change. It argues that rapid market expansion had already slowed before the new asset management rules, with aggregate assets contracting in 2018. The report…

Multi-assetVastrentende waardenAandelenChinese markten
BigQuant

This report studies whether the stability of intraday trading patterns can help rank Chinese stocks. It calculates seven measures from five-minute returns and volume, including volatility, skewness, kurtosis, and a volume concentration index. To account for…

AandelenStatistiekFactorbeleggenChinese markten
BigQuant

This forum post presents a Chinese A-share strategy built from the Pearson correlation between each stock’s one-minute closing prices and trading volumes over a day. It sums the daily correlation factor over a rolling five-day window, then ranks stocks by…

AandelenStatistiekMarktmicrostructuurBacktesten
BigQuant

This article reviews an empirical study of whether skilled active equity fund managers perform differently when investor sentiment and noise trading are elevated. Using US domestic active equity mutual funds from 2002 to 2014, the study estimates rolling…

AandelenFactorbeleggenMarktsentimentStatistiek
BigQuant

This report explains why common equity factors may need adjustment for banks. Large cash and financial asset balances complicate comparisons of liquidity, while provisions and reserve practices can distort earnings multiples. Some operating measures used for…

AandelenChinese marktenFactorbeleggenBacktesten
BigQuant

The article explains why feature selection can reduce irrelevant or redundant inputs while preserving a model’s predictive ability. It illustrates the idea with a water park ticket-sales example, using weather, ice cream consumption, coffee consumption, and…

Machine learningStatistiek
BigQuant

This support discussion concerns a simulated trading strategy that reportedly generated no signals after submission. The response says the shared strategy link could not be accessed and asks for a link created through the development environment’s sharing…

BacktestenOrderuitvoering
BigQuant

The document explains why conventional random or K-fold cross-validation can mislead when tuning models on time-series data. Because observations are ordered and related, a random split may train on later periods and validate on earlier ones, allowing future…

Machine learningStatistiekBacktestenChinese markten
BigQuant

This document outlines the Directional Movement Index (DMI) calculation from high, low, and close prices using a configurable lag. It first derives a smoothed true-range measure from the current bar's range and gaps relative to the previous close. Upward and…

Technische indicatorenTrendvolgend
BigQuant

This research note proposes a stock-selection factor based on the trend in quarterly gross profitability. It estimates the trend as the time coefficient in a linear regression, using either sequential-quarter or year-over-year observations. The study…

AandelenChinese marktenFactorbeleggenStatistiek
BigQuant

This BigQuant workflow illustrates a daily Chinese equity ranking process. It prepares stock features from price and prefactor data, including lagged returns and volume ranking, then creates a supervised label from a clipped forward return. Training data is…

AandelenMachine learningFactorbeleggenPortefeuilleconstructie
BigQuant

The article explores using an LSTM neural network to forecast five-day returns on the CSI 300 and use the forecast as a market timing signal for a separate stock-ranking strategy. It describes feeding the model 30 days of standardized open, high, low, close,…

AandelenMachine learningRisicobeheerBacktesten
BigQuant

This Chinese-language summary introduces a research paper on factor timing, which combines ideas from market timing and factor investing. It frames the theoretical argument around the stochastic discount factor (SDF), assuming a conditional factor model can…

FactorbeleggenPortefeuilleconstructieStatistiek
BigQuant

The article proposes a buy-side strength factor from minute-level order-book data. It combines price and displayed quantity at each of the first five bid levels, does the same for the first five ask levels, and forms a ratio of the bid-side total to the…

AandelenMarktmicrostructuurHoogfrequente handelFactorbeleggen
BigQuant

The article explains how a long short-term memory network can use sequential market data for short-horizon stock selection. It outlines LSTM’s forget, input, and output gates, then describes a model with an LSTM layer, dropout, and a dense layer. The model…

AandelenMachine learningFactorbeleggenBacktesten