Naar inhoud gaan

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
Quantopian-colleges
45 documenten
Binance API docs
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 article introduces discrete-time stochastic control as a method for dynamic asset allocation. Unlike a traditional mean-variance allocation made without an explicit sequence of future decisions, the approach models portfolio choices across multiple…

Multi-assetPortefeuilleconstructieStatistiekChinese markten
BigQuant

This brief support exchange explains why a MACD histogram value can shift substantially when the start date of a stock data list changes. The explanation points to the initialization of the exponential moving average: its first value is not fully smoothed,…

Technische indicatorenStatistiek
BigQuant

This document describes a Chinese stock strategy that combines classification and regression models to forecast intraday returns. It uses XGBoost and an ensemble of machine learning models, drawing on 15 features related to overnight returns, opening auction…

Chinese marktenAandelenMachine learningBacktesten
BigQuant

This intraday system trades the CAC 40 on a 15-minute chart, taking both long and short positions during a defined daytime session. Long entries require the MACD line to cross above its signal line, RSI to remain below an upper threshold, and price to be…

AandelenTechnische indicatorenBacktestenOrderuitvoering
BigQuant

This report summary explores whether macroeconomic indicators can help select individual Chinese stocks, rather than serving only for asset allocation or industry rotation. It proposes estimating each stock’s sensitivity, or MacroBeta, to economic indicators…

Chinese marktenAandelenFactorbeleggenStatistiek
BigQuant

This brief BigQuant platform note explains how to use a factor written as a SQL function and field within a strategy workflow. It distinguishes platform expression factors, described as an operator paired with a field, from SQL factors, described as a…

FactorbeleggenBacktesten
BigQuant

This research review describes a study of whether year-over-year changes in company filings contain information about future stock returns and business performance. It compares filings using four text-similarity measures, sorts stocks by similarity, and…

AandelenMarktsentimentMachine learningFactorbeleggen
BigQuant

The report describes a weekly market-timing model based on a linear-chain conditional random field (CRF). It frames the task as inferring market direction states from observed features, with CRFs able to represent dependencies between observations and…

AandelenChinese marktenMachine learningBacktesten
BigQuant

The document compares two ways to build multifactor equity portfolios. Integration ranks securities using a combined score for all target factors and selects a subset. Mixing first builds separate single-factor portfolios, then allocates among them. The…

AandelenFactorbeleggenPortefeuilleconstructieBacktesten
BigQuant

This overview presents a multi-factor model as a way to explain stock returns through shared risk exposures, factor returns, and stock-specific residual returns. It frames quantitative management as estimating factor behavior and managing portfolio…

AandelenFactorbeleggenStatistiekPortefeuilleconstructie
BigQuant

This article describes modifying OpenFE’s automated feature engineering workflow for futures research. It adds rolling mean, standard deviation, and sum operators across instrument groups, with preset window lengths, and explains how these operators are…

FuturesMachine learningFactorbeleggenStatistiek
BigQuant

This personal account explains how an equity prediction model can appear strong in-sample yet fail when applied to unfamiliar stocks or later periods. The described experiment uses fundamental and technical features, including valuation, profitability,…

AandelenMachine learningStatistiekBacktesten
BigQuant

This example describes a short-horizon stock rotation strategy. It selects shares whose prior-day return was between 2% and 8% and whose turnover was between 3% and 8%, then removes special-treatment shares, halted stocks, and listings younger than the…

AandelenMomentumChinese marktenOrderuitvoering
BigQuant

This report summary describes a method for refining traditional liquidity factors by incorporating intraday trading structure specific to China’s A-share market. The idea is to adapt a broad factor to market-specific trading patterns, with the report…

AandelenFactorbeleggenMarktmicrostructuurStatistiek
BigQuant

The note turns a discretionary stock method into explicit rules: admit a stock to an initial universe when its daily low stays above 99% of the 34-day moving average for ten consecutive days, buy when its profitable-chip proportion exceeds 73%, and sell when…

AandelenTechnische indicatorenFactorbeleggenBacktesten
BigQuant

This Chinese-language example sets up a test of whether stocks that have risen on each of the prior three days are more likely to rise the next day. It defines the condition as three consecutive daily price increases, each exceeding one percent, and labels…

AandelenMomentumStatistiek
BigQuant

This strategy combines model-based stock ranking with trend filters for a selected universe of China A-shares drawn from the CSI 150 and related large-cap core-asset stocks. It aims to rank candidates for potential five-day strength, then apply timing…

Chinese marktenAandelenMachine learningMomentum
BigQuant

This research note examines an equity-selection factor built from differences in stock price behavior across the trading day. It reports that the original APM factor performed well in its in-sample period, weakened out of sample, and suffered a sustained…

AandelenFactorbeleggenStatistiekBacktesten
BigQuant

This article is a catalog of beginner-oriented examples for learning TensorFlow and TFLearn. It lists introductory operations, nearest-neighbor and regression models, neural networks, autoencoders, model saving, visualization, and multi-GPU basics. The…

Machine learning
BigQuant

The document compares a traditional Chinese equity strategy that buys the smallest market-cap stocks with a StockRanker model that ranks stocks using market capitalization as its sole feature. Both are evaluated over 2015–2016, illustrating how a…

AandelenFactorbeleggenMachine learningBacktesten
BigQuant

The article reviews the 2021 revision of China's Shenwan industry classification and its possible uses in quantitative investing. The revision expanded coverage to A-shares, Stock Connect shares, and selected Chinese firms listed overseas, added three…

Chinese marktenAandelenFactorbeleggenPortefeuilleconstructie
BigQuant

The document describes a daily process for building a short-term stock watchlist. It starts by ranking stocks by traded value and keeping the top 50. It then removes stocks that gained less than 5% that day, those whose 30-day moving average is flat or…

AandelenMomentumUitbraakTechnische indicatoren
BigQuant

The document surveys the development of enhanced ETFs in China alongside the expansion of actively managed ETFs in the United States. It presents enhanced ETFs as an effort to seek returns above a benchmark while retaining ETF features such as intraday…

AandelenPortefeuilleconstructieOrderuitvoeringRisicobeheer
BigQuant

This 2020 China equity-sector note combines macroeconomic regime signals, earnings relative to valuation, trend signals, historical regime matching, and public-fund holdings to discuss sector allocation ahead of interim reports. It argues that weaker growth…

Chinese marktenAandelenMomentumFactorbeleggen