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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 market note summarizes a difficult week for major Chinese equity indexes and sectors, then reports changes in factor behavior. It says quality and analyst sentiment factors strengthened relative to the prior week, while value, reversal, and alternative…

Chinese marktenAandelenFactorbeleggenMomentum
BigQuant

This Chinese language literature digest summarizes research on return predictability and portfolio covariance estimation. One study examines stock prices and dividends in the Netherlands, the United Kingdom, and the United States over nearly four centuries.…

AandelenFactorbeleggenStatistiekPortefeuilleconstructie
BigQuant

This research summary examines how broad equity factors behaved across Chinese A-share industries from July 2009 through November 2018. It links differences in factor effectiveness to industry characteristics: small-cap effects were stronger in industries…

AandelenChinese marktenFactorbeleggenPortefeuilleconstructie
BigQuant

This tutorial introduces two strategy-building approaches on BigQuant: an AI-driven workflow that trains a model from selected factors and filters, and a user-coded approach with explicit selection rules. It focuses on the latter, outlining how to clone a…

AandelenChinese marktenBacktestenFactorbeleggen
BigQuant

This BigQuant example assembles a China A-share workflow from stock selection through backtesting. It selects eligible main board, STAR Market, and ChiNext stocks associated with the CSI 1000, then calculates current and lagged volume relative to a five-day…

AandelenChinese marktenTechnische indicatorenBacktesten
BigQuant

This meetup note explains factor exposure as an asset’s sensitivity to factor returns. It sketches a way to estimate that sensitivity: form a low-versus-high valuation long-short portfolio, treat its return series as the factor return, and regress an asset’s…

AandelenFactorbeleggenStatistiekPortefeuilleconstructie
BigQuant

This legacy platform example shows how to model a stock purchase at a specified price relative to the day’s open. A custom slippage model sets buy orders at 98% of the opening price, while sell orders use the current close. A daily order check compares the…

AandelenOrderuitvoeringBacktestenMarktmicrostructuur
BigQuant

This discussion examines how to exclude Chinese convertible bonds after an issuer announces early redemption. The author found that the platform’s redemption-terms table showed one row each for two example bonds, including contractual trigger conditions,…

Vastrentende waardenChinese marktenGebeurtenisgestuurdBacktesten
BigQuant

This article discusses practical choices when tuning a short-term stock-selection strategy: starting capital, number of holdings, capital allocated per holding, holding period, and factor selection. Its author argues that the number of names and per-name…

AandelenFactorbeleggenPositiegrootteBacktesten
BigQuant

The document examines whether rolling Fama-French five-factor (FF5) alphas can guide U.S. sector rotation. It compares FF5 with the three-factor model (FF3), using monthly returns for ten U.S. industry portfolios from 1964 to 2014. The rotation signal is…

FactorbeleggenAandelenPortefeuilleconstructieBacktesten
BigQuant

This Chinese-language assignment turns a discretionary trading idea into a simple rule for constituents of the CSI 300: buy when the five-day moving average crosses above the ten-day average and MACD is positive, and sell otherwise. It also sketches a…

Chinese marktenAandelenTechnische indicatorenMomentum
BigQuant

This research summary tests whether negative sentiment in posts on Xueqiu, a Chinese investing forum, can help time major Chinese equity indexes. It describes using machine learning to classify post sentiment and building a weekly negative-sentiment ratio…

MarktsentimentMachine learningAandelenChinese markten
BigQuant

The article summarizes research on how speculative stocks perform around earnings announcements. It measures speculative characteristics using proxies such as maximum daily return, idiosyncratic volatility, price, expected skewness, and jackpot probability,…

AandelenGebeurtenisgestuurdMarktsentimentFactorbeleggen
BigQuant

This brief support exchange asks how the numbers displayed after decision branches in a visual stockRanker model are calculated. The response points the reader toward material on tree models and information entropy, implying that the displayed values relate…

Machine learningStatistiek
BigQuant

The article introduces quantitative trading as the use of mathematical models, statistical analysis, historical and real-time market data, and algorithms to guide or automate decisions. It describes stock screening and rule-based execution as common…

AandelenMachine learningFactorbeleggenBacktesten
BigQuant

This brief support exchange addresses a user’s report that a hyperparameter module raises a key error even though the key appears in the visual chart and can be found in code-mode parameters. The response attributes the issue to an error in the…

Machine learningBacktestenStatistiek
BigQuant

This forum post describes an attempted 12–1 momentum strategy on S&P 500 constituents and reports two backtest problems: target-percent orders repeatedly encounter null prices, and a visual workflow produces no instruments or trades. The strategy ranks…

AandelenAmerikaanse marktenMomentumBacktesten
BigQuant

This brief describes a deep neural network approach intended for quantitative stock selection. Its stated implementation goals are to run on systems with limited memory, use GPU acceleration when available, and adapt the number of input features. It also…

AandelenMachine learningBacktesten
BigQuant

The article explains five behavioral traps that it associates with retail trading losses: confirmation bias, reacting to noisy opening-auction signals, trying to recover losses through riskier trades, loss aversion that delays selling, and greed that delays…

RisicobeheerMarktsentimentAandelenChinese markten
BigQuant

This meetup Q&A surveys several quantitative trading topics: using Level 2 order-book data, reproducing a legacy strategy, allocating idle capital to a gold ETF, factor decomposition, building CNN strategies, and portfolio optimization. Most answers point…

PortefeuilleconstructieRisicobeheerMachine learningMarktmicrostructuur
BigQuant

This forum post records an attempt to create an A-share factor from securities appearing on the trading ranking list, using a transaction category and several broker department codes. The submitted expression tests whether the category matches a specified…

AandelenChinese marktenFactorbeleggenStatistiek
BigQuant

The article presents a scenario analysis of how sustained high crude prices could affect energy-importing and energy-exporting economies. It argues that higher energy costs may shift income toward resource exporters, raise manufacturing expenses in importing…

GrondstoffenVolatiliteitMulti-asset
BigQuant

The document introduces the task of developing a complete strategy from daily factors extracted with a high-frequency expression engine. It identifies strategy development as the topic of a meetup presentation and points readers to a related recording, but…

FactorbeleggenMachine learningBacktesten
BigQuant

This report examines listed companies’ interest-bearing debt as a quantitative stock-selection and risk-screening measure. It defines the debt measure around short-term and long-term borrowings and bonds, and observes that debt ratios tend to reflect…

AandelenRisicobeheerFactorbeleggenBacktesten