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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
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 forum exchange describes a fix for a BigQuant data query that failed with a missing date key while combining two data sources. The suggested query explicitly selects the date and instrument fields along with technical factor fields. It also filters…

AandelenTechnische indicatorenBacktesten
BigQuant

This research summary forecasts constituent changes for China’s CSI 300 and CSI 500 indices ahead of their scheduled December 2018 reviews. It explains that the indices are reviewed in June and December, and that changes can create trading opportunities when…

AandelenChinese marktenGebeurtenisgestuurdPortefeuilleconstructie
BigQuant

This brief platform discussion explains how users can call MACD in BigQuant 3.0 after an older expression format stopped working. It gives two supported expression forms: a windowed MACD function and a shorthand helper. Both calculate MACD from closing…

Technische indicatorenAandelen
BigQuant

A user reports a discrepancy between a trade’s recorded execution price and the stock’s historical prices on the same date after adjustment for corporate actions. The example contrasts a reported buy price with lower adjusted open and close values. The…

AandelenBacktestenStatistiek
BigQuant

This excerpt summarizes a Chinese weekly research note on machine learning and commodity trading advisor strategies. It reports recent results for a neural network strategy on the CSI 500, a commodity futures strategy, and a commodity strategy combining…

Machine learningFuturesAandelenGrondstoffen
BigQuant

This document explains how to remove ChiNext stocks from both the training and test portions of a visual AI stock-selection strategy on BigQuant. It instructs users to insert a shared “filter market” module before the missing-data handling module in each…

AandelenMachine learningChinese marktenBacktesten
BigQuant

The report describes a multifactor stock-selection process that first evaluates and selects robust factors, then combines them into a composite score. It builds separate models for six stock universes and compares direct selection with portfolios that select…

AandelenChinese marktenFactorbeleggenPortefeuilleconstructie
BigQuant

The document explains how portfolio attribution compares a portfolio with its benchmark and decomposes excess return into drivers. It distinguishes return-based approaches, including Treynor-Mazuy, Henriksson-Merton, and related factor extensions, from…

RisicobeheerPortefeuilleconstructieFactorbeleggenAandelen
BigQuant

This historical overview traces the independent development of the Capital Asset Pricing Model by Jack Treynor, William Sharpe, John Lintner, and Jan Mossin. It connects their different starting points to portfolio selection and corporate finance, and…

AandelenMulti-assetFactorbeleggenPortefeuilleconstructie
BigQuant

The study describes a machine-learning approach for classifying the optimal rebalance frequency of a two-asset portfolio strategy. It uses minute-level prices for 50 Binance crypto assets from 2022 and 2023, forms asset pairs, and groups them by correlation.…

CryptoPairstradingMachine learningBacktesten
BigQuant

This opinion piece argues that retail traders should be cautious about relying on remembered successes and discretionary short-term trading habits as markets become more influenced by institutions and quantitative models. Its central practical message is to…

AandelenChinese marktenRisicobeheerStatistiek
BigQuant

This brief strategy outline proposes a weekly rotation among three of the smallest stocks that meet fundamental quality and growth screens. The listed criteria include sustained net-profit growth over three consecutive years and gross margins above 20%; it…

Chinese marktenAandelenFactorbeleggenPortefeuilleconstructie
BigQuant

This document introduces the Campisi model as a framework for explaining the performance of pure bond funds. It describes decomposing a fund’s total return and excess return into four sources: income, government-bond effects, spread effects, and security…

Vastrentende waardenPortefeuilleconstructieStatistiek
BigQuant

This article describes using recurrent neural networks to predict the direction of the next price change from high-frequency order-book data. The study uses data from Nasdaq stocks and keeps observations where prices change, reducing the input sequence. It…

AandelenHoogfrequente handelMachine learningMarktmicrostructuur
BigQuant

This discussion raises a timing problem in backtests that use premarket processing. In the example, a signal is generated on one day and orders are submitted the next day; the author notes that historical data queried before trading may already include that…

BacktestenOrderuitvoeringStatistiek
BigQuant

This discussion describes a backtest problem caused by missing historical prices in a rolling maximum calculation. The author expected the portfolio to hold ten stocks, but in earlier periods it sometimes held only one or two. The suspected cause was that a…

AandelenBacktestenStatistiekPortefeuilleconstructie
BigQuant

This research examines whether industry rotation can enhance a CSI 500 benchmark portfolio. It compares two allocation approaches based on industry views: a moderate deviation from benchmark industry weights, and a concentrated approach that removes bearish…

Chinese marktenAandelenFactorbeleggenPortefeuilleconstructie
BigQuant

This report evaluates a China ChiNext equity index that selects stocks using profitability, accounting strength, investment discipline, default risk, and low volatility. It argues that the index offers a more fundamental and lower-volatility alternative to…

AandelenFactorbeleggenVolatiliteitChinese markten
BigQuant

This study compares two ways to build multifactor equity portfolios. Integration ranks securities by a combined score and selects those with strong exposure across the target factors. Mixing first builds separate single-factor portfolios, then allocates…

AandelenFactorbeleggenPortefeuilleconstructieBacktesten
BigQuant

This analysis examines whether limits on how far bond yields can fall weaken bonds’ return contribution and diversification value. It models a global bond portfolio, a global 60/40 stock-bond portfolio, and a leveraged risk-balanced portfolio, using equal…

Vastrentende waardenPortefeuilleconstructieRisicobeheer
BigQuant

The document identifies the fitness-function setting used by a genetic programming module and lists its available objectives. These include information coefficient to information coefficient ratio, mutual information, long-only Sharpe, volatility and return…

Machine learningStatistiekFactorbeleggen
BigQuant

This document summarizes research on how investment fund flows relate to fund performance and asset growth. It reports that international studies generally find a positive association between performance and inflows, with a nonlinear relationship to…

StatistiekPortefeuilleconstructieChinese markten
BigQuant

This forum post asks how to understand two approaches to adapting factors to market style. For a W-style split, the author proposes dividing a factor using a reference variable such as trading amount and treating the difference between the resulting groups…

FactorbeleggenStatistiekAandelen