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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 introductory article presents ten practical points about machine learning for non-specialists. It emphasizes that machine learning finds patterns in data, so data quality, accurate labels, representative samples, and careful transformations often matter…

Machine learningStatistiekRisicobeheer
BigQuant

The article explains how a long-only smart beta portfolio can combine equity factors to seek steadier returns than relying on one factor. It highlights value, low beta, profitability, investment, momentum, and size, arguing that their different return…

AandelenFactorbeleggenPortefeuilleconstructieMomentum
BigQuant

This report evaluates whether changes in listed companies’ employee compensation can help distinguish future stock returns. It compares growth in compensation payable, which represents amounts owed, with growth in compensation already paid, and also…

AandelenFactorbeleggenChinese markten
BigQuant

The post asks how to define groups for a learning-to-rank model in a stock selection setting. In ranking algorithms, each group contains observations that should be ranked against one another; the author proposes grouping stock samples by trading date so…

AandelenMachine learningStatistiek
BigQuant

This convertible-bond research note describes a relative-value approach based on the embedded option. It first compares implied volatility with the underlying stock’s historical volatility: relatively low implied volatility is treated as evidence that the…

VolatiliteitPrijsbepaling van derivatenBacktestenVastrentende waarden
BigQuant

FactorVAE is described as a probabilistic dynamic factor model that applies a variational autoencoder to noisy market data to forecast cross-sectional stock returns. In training, an encoder-decoder uses future returns to identify posterior factors that…

AandelenMachine learningFactorbeleggenStatistiek
BigQuant

This introductory article explains Matplotlib’s role in Python data visualization and outlines the Figure and Axes objects, along with its state-based pyplot and object-oriented interfaces. It notes that the library supports chart types such as lines,…

AandelenStatistiek
BigQuant

The report develops stock selection factors from abnormal operating cash flow as proxies for real earnings management. Its premise is that firms can alter real business activity to make reported performance look stronger, potentially harming future…

Chinese marktenAandelenFactorbeleggenBacktesten
BigQuant

This research summary discusses how asset prices can reflect economic expectations before official data is released. It proposes comparing year-over-year changes in a basket of asset prices with economic indicators, and comparing asset-price changes with…

Multi-assetStatistiekMomentum
BigQuant

This trading exercise translates a discretionary method into explicit stock-selection rules. A candidate must close above its five-day moving average for three consecutive days and remain within ten percent above its lowest price over the previous twenty…

AandelenTechnische indicatorenMomentumRisicobeheer
BigQuant

The report develops stock-selection factors from one-minute Chinese equity data, adding transaction counts to price and volume inputs. It examines average trade value and the direction of large-trade activity, then evaluates these signals both alone and…

AandelenChinese marktenFactorbeleggenHoogfrequente handel
BigQuant

This platform guide distinguishes raw financial statement records from processed point-in-time (PIT) data and explains why the distinction matters in quantitative investing. Raw records are organized by instrument, report date, publication date, and change…

AandelenChinese marktenBacktestenStatistiek
BigQuant

This brief Chinese-language forum exchange concerns whether a user can retrieve feature importance from a random forest in a visual quantitative-strategy platform. The reply identifies the random forest module and suggests creating a visual strategy template…

Machine learningFactorbeleggen
BigQuant

This monthly review compares equity factors using information coefficients (IC) and long-short returns. It reports that growth and turnover factors were relatively consistent over the preceding three months, while profitability and reversal results varied;…

AandelenFactorbeleggenStatistiekBacktesten
BigQuant

This research summary studies whether lagged returns from related industries can help predict industry returns for sector rotation. It motivates the question by noting that such predictability would not be expected in an ideal frictionless market, while real…

AandelenChinese marktenMachine learningStatistiek
BigQuant

This research summary examines low-volatility investing in overseas markets and mainland Chinese equities. It presents the low-volatility anomaly as a source of long-run risk-adjusted performance, with a behavioral explanation: speculative demand and…

AandelenChinese marktenFactorbeleggenVolatiliteit
BigQuant

This report summary describes a Barra-style risk model for Hong Kong stocks, built to study factor returns and portfolio exposures. Its data foundation combines security details, prices, trading activity, Hang Seng industry classifications, valuation…

AandelenFactorbeleggenStatistiekChinese markten
BigQuant

The article outlines common aims of algorithmic execution: splitting a parent order to follow market volume, reducing market impact, and concealing trading intent. It also presents automation as a way to improve order-entry efficiency and reduce manual…

OrderuitvoeringMarktmicrostructuurHoogfrequente handelMachine learning
BigQuant

This note proposes screening Chinese equities associated with the metaverse theme, requiring a positive institutional-flow measure and a weekly crossover involving a 30-week reference. The intended rationale is to combine thematic exposure, evidence of…

AandelenChinese marktenTrendvolgendTechnische indicatoren
BigQuant

This overview explains Chinese depositary receipts (CDRs) as securities traded domestically that represent rights in foreign shares through a depositary institution. It summarizes the historical pilot eligibility criteria described in the document, says…

AandelenChinese marktenMarktmicrostructuurRisicobeheer
BigQuant

This forum post describes a reproducibility question in a quantitative modeling workflow. The author sets a learning-rate parameter to the same value in the model and in a hyperparameter-search module, and configures the search grid to contain only that…

Machine learningStatistiekBacktesten
BigQuant

The document explains sliced inverse regression (SIR) as a supervised dimension-reduction method for financial prediction. Unlike principal component analysis, which summarizes variation in predictors without using the target, SIR uses the forecast variable…

AandelenStatistiekFactorbeleggenPortefeuilleconstructie
BigQuant

This overview surveys models used to relate asset values or expected returns to risk and other inputs. It describes CAPM as linking expected return to the risk-free rate and market exposure, then introduces multifactor models such as Fama–French, which add…

Multi-assetFactorbeleggenPrijsbepaling van derivatenVastrentende waarden