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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 brief indicator note defines Leadlag as a comparison between two exponential moving averages of closing prices. It takes closing price data and two period parameters, one for the lead line and one for the lag line. The supplied pseudocode calculates…

Technische indicatorenAandelen
BigQuant

The article investigates why XGBoost training took far longer in some Python process setups than with joblib’s loky backend. Its experiments compare direct execution and several multiprocessing approaches, then identify the OpenMP thread limit as the key…

Machine learningStatistiekBacktesten
BigQuant

This BigQuant backtest handler describes a daily portfolio process driven by a date-filtered prediction ranking. It allocates roughly one holding-period fraction of portfolio value to daily purchases during an initial staging phase; afterward, it can use up…

AandelenMachine learningPortefeuilleconstructieOrderuitvoering
BigQuant

This report studies whether active-buying measures derived from high-frequency trading data can help rank industries for rotation. It constructs buy-share, buy-intensity, net-buy-share, and net-buy-intensity factors using volume and turnover data from the…

Chinese marktenAandelenFactorbeleggenPortefeuilleconstructie
BigQuant

This research note assesses China’s consumer recovery under normalized pandemic controls, using a combination of policy text analysis and indicators of aggregate spending, passenger flows, cinema attendance, and physical store counts. It argues that…

Chinese marktenAandelenGebeurtenisgestuurdStatistiek
BigQuant

This brief note identifies two errors in the conditions used by a stock strategy example. The first concerns a year-over-year net profit growth factor: the intended filter selects positive growth rather than negative growth. The second concerns position…

AandelenFactorbeleggenBacktesten
BigQuant

The article explains why investment teams need to understand how machine-learning models produce decisions, especially when those decisions affect clients, risk controls, or deployment choices. It contrasts inherently interpretable approaches, such as linear…

Machine learningStatistiekRisicobeheer
BigQuant

This 2020 research summary compares valuations and return drivers across large- and small-cap Chinese equity indexes. It reports that small-cap valuations were near historical medians while large-cap indexes, including the SSE 50 and CSI 100, were near…

AandelenChinese marktenFactorbeleggenStatistiek
BigQuant

The document is a user’s question about calculating three-day and five-day moving averages within a custom feature factor on a quantitative trading platform. It asks how to use lagged close-price fields such as the current-day close, how rolling mean…

AandelenTechnische indicatoren
BigQuant

The document defines the Sharpe ratio as a way to assess a portfolio or strategy’s excess return relative to the variability of its returns. It gives the calculation: subtract the risk-free rate from average portfolio return, then divide by the standard…

StatistiekRisicobeheer
BigQuant

This research summary reviews academic momentum-factor development and reports empirical findings for China’s A-share market. It says traditional momentum measures there exhibit reversal, with stronger reversal over shorter formation windows, and that…

AandelenChinese marktenMomentumFactorbeleggen
BigQuant

This report excerpt discusses forecasting equity factor returns as commonly used stock-selection factors fluctuate. It proposes improving and simplifying an earlier conditional-expectation timing model by framing factor timing as a regression-based…

FactorbeleggenAandelenStatistiekPortefeuilleconstructie
BigQuant

This research note studies post-earnings-announcement drift in Chinese A-shares: stocks reporting results above expectations may continue to earn positive abnormal returns, while those below expectations may lag. It estimates expected net profit and revenue…

AandelenChinese marktenGebeurtenisgestuurdFactorbeleggen
BigQuant

This stock-selection proposal combines a daily price-range threshold, afternoon large-order inflows and a closing price between the Bollinger middle band and upper band. The document gives formulas for the range and band conditions, describes a…

AandelenTechnische indicatorenVolatiliteitChinese markten
BigQuant

The document raises a modeling question about predicting whether a future price move is positive using a label that takes only two values. The label compares a later close with an earlier open and assigns one class for an increase and the other for a…

Machine learningStatistiekAandelen
BigQuant

The document reports a discrepancy in a Chinese stock-status data table for one security on a specified historical date. A query against the table returned a status identifying the stock as *ST, while the author says the company was no longer classified that…

AandelenChinese marktenBacktestenStatistiek
BigQuant

The report adapts William O’Neil’s base-pattern and CANSLIM ideas to the Chinese A-share market. It combines price formations such as cup-with-handle and double bottoms with company growth measures, relative price strength, trading activity, and…

Chinese marktenAandelenUitbraakMomentum
BigQuant

The document explains how performance attribution can reveal the sources of a portfolio’s returns, even when portfolios have similar styles and overall results. It outlines three approaches: style analysis, which uses portfolio and benchmark returns to infer…

FactorbeleggenPortefeuilleconstructieRisicobeheer
BigQuant

This article presents a time-series momentum strategy that switches between a short lookback signal and a longer one according to market volatility. The short signal uses one month of returns and the slow signal uses twelve months; each takes a long or short…

MomentumMachine learningVolatiliteitBacktesten
BigQuant

This article outlines a systematic trend-following approach commonly called the Turtle method. It describes choosing liquid markets, using average true range (ATR) as a volatility measure for position sizing, and entering on Donchian channel breakouts. The…

FuturesTrendvolgendUitbraakVolatiliteit
BigQuant

This research summary examines whether institutional trading before earnings announcements contributes to mispricing and post-earnings announcement drift (PEAD). It measures abnormal institutional demand before announcements and relates it to subsequent…

AandelenGebeurtenisgestuurdMarktsentimentStatistiek
BigQuant

The document explains how to build trading agents within a strategy framework. It describes a workflow in which research agents gather market evidence and a dedicated trading agent can submit orders, while deterministic Python can enforce fixed execution and…

Machine learningBacktestenOrderuitvoeringRisicobeheer
BigQuant

This strategy ranks the mainland China A-share universe using company size and a price momentum measure. It removes suspended and specially treated shares, calculates a market-cap rank and the ratio of 20-day to 60-day average closing prices, and adds the…

AandelenChinese marktenFactorbeleggenMomentum
BigQuant

This note describes using a forecast of the time-varying Sharpe ratio as a monthly signal for switching between cash and Chinese equity indices. It outlines two forecasting approaches: a regression model associated with Robert Whitelaw and an ARMA model. The…

AandelenChinese marktenStatistiekBacktesten