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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

A brief forum exchange addresses a user whose stock strategy appears not to run. The response suggests two checks: use English names for features, and print the daily buy and sell candidate lists to see whether any stocks meet the strategy’s conditions. The…

AandelenOrderuitvoering
BigQuant

This research summary proposes combining price-to-book ratio (PB) with return on equity (ROE) to find companies with stronger fundamentals and lower valuations in China’s A-share market. It treats ROE and other operating measures as indicators of value…

Chinese marktenAandelenFactorbeleggenPortefeuilleconstructie
BigQuant

This market-monitoring report summarizes Chinese trading conditions for July 13, 2022. It reviews broad index and sector performance, then gauges equity sentiment using limit-up and limit-down counts, next-day returns for stocks that had hit either limit,…

AandelenFuturesMarktsentimentMarktmicrostructuur
BigQuant

This student submission translates a Chinese “dragon returning” trading approach into a factor-based stock strategy. It first identifies strong sectors with sector momentum, then selects leading stocks within them using stock momentum and price-volume…

Chinese marktenAandelenMomentumTerugkeer naar het gemiddelde
BigQuant

The document summarizes a study of dividend-focused Smart Beta strategies in Chinese equities. It argues that dividend factors show a consistent ranking pattern across the CSI 300, CSI 500, and broader market universe, with higher-dividend portfolios…

AandelenFactorbeleggenChinese marktenBacktesten
BigQuant

The document surveys a Chinese securities research team’s work on applying artificial intelligence to quantitative investing. It organizes that research around model evaluation, factor discovery, overfitting controls, synthetic data, and methods intended to…

Machine learningFactorbeleggenAandelenPortefeuilleconstructie
BigQuant

This document summarizes a securities research report on constructing factors from high-frequency data, with a focus on combining intraday and day-level information. It frames the choice of calculation method around whether price and volume signals retain…

AandelenHoogfrequente handelFactorbeleggenMomentum
BigQuant

This Chinese-language post discusses connecting BigQuant research with Guojin Securities’ QMT platform for automated live trading. Its concrete example is a stock strategy that first processes daily data to select a watchlist, then monitors those names and…

Chinese marktenAandelenUitbraakHoogfrequente handel
BigQuant

This equity research note examines suppliers of radio-frequency components for active phased-array radar amid anticipated military equipment upgrades in China. It explains that active arrays connect a separate transmit/receive module to each radiating…

Chinese marktenAandelen
BigQuant

This report tests the ratio of research and development spending to revenue as an equity-selection factor across industries. Single-factor tests find some effectiveness in technology-oriented sectors, including pharmaceuticals, electronics, communications,…

Chinese marktenAandelenFactorbeleggenPortefeuilleconstructie
BigQuant

The note answers whether factors shown in BigQuant’s factor dashboard can be referenced directly. It says they cannot be called directly from the dashboard; users need to open a factor’s detail page and extract its expression. When available, the displayed…

Factorbeleggen
BigQuant

The document gives a brief historical overview of quantitative investing. It describes how advances in computing made it practical to store and process large amounts of historical data, supporting the use of statistical and mathematical models in investment…

StatistiekMachine learningBacktesten
BigQuant

A BigQuant user raises a timing problem involving premarket data processing in backtests. In the example, a signal generated on one day leads to an order for the next day; premarket history in the backtest appears to expose that day’s open and close. Such…

BacktestenOrderuitvoeringMarktmicrostructuurAandelen
BigQuant

This educational article introduces support vector machines (SVMs) as classification models, with examples framed around separating two classes using features. It explains the maximum-margin objective: choose a decision boundary that stays as far as possible…

Machine learningStatistiek
BigQuant

This report challenges mean-variance optimization assumptions that returns are normally distributed, volatility captures risk symmetrically, and portfolios should maximize return per unit of risk. It instead frames investor concerns as preserving principal…

Multi-assetPortefeuilleconstructieRisicobeheerStatistiek
BigQuant

This article explains a Dual Thrust trend-following method and its application to a basket of nickel, rebar, and coking coal futures. It defines a range from historical highs, lows, and closes, then sets upper and lower breakout thresholds around the current…

FuturesGrondstoffenTrendvolgendUitbraak
BigQuant

The article evaluates whether a stock’s overnight return, measured from the prior close to the next open, can proxy for firm-level investor sentiment. The rationale is that retail investors may place orders outside regular market hours, concentrating demand…

AandelenMarktsentimentTerugkeer naar het gemiddeldeStatistiek
BigQuant

This reference describes several candidate fitness objectives for genetic programming that produces equity factors. It defines IC information ratio as the mean information coefficient divided by its standard deviation, with the information coefficient…

AandelenFactorbeleggenMachine learningStatistiek
BigQuant

This research roundup summarizes three studies. The first examines whether unexpected US monetary policy announcements affected hedge fund alpha after the financial crisis, using event studies, structural-break tests, and Markov-switching models. It reports…

Multi-assetPortefeuilleconstructieGebeurtenisgestuurdMarktsentiment
BigQuant

This report examines shortcomings in the Henriksson–Merton (HM) and Treynor–Mazuy (TM) models for assessing fund managers’ market and style timing. TM represents beta adjustment as a gradual quadratic pattern, while HM assumes a two-state exposure shift;…

StatistiekFactorbeleggenPortefeuilleconstructie
BigQuant

This report overview defines smart beta as a systematic, rules based way to obtain exposure to selected investment factors. It compares the United States and China through their ETF markets, describing differences in product scale, factor coverage, and index…

FactorbeleggenAandelenChinese marktenAmerikaanse markten
BigQuant

The document outlines the five factors used to explain differences in stock returns: market excess return, company size, book-to-market value, profitability, and investment. It describes each as a comparison between groups of stocks, such as small versus…

AandelenFactorbeleggenStatistiekPortefeuilleconstructie
BigQuant

This BigQuant example builds a daily Chinese-stock portfolio by ranking eligible shares on 30-day turnover variability relative to their industry group. It filters out risk-warning stocks and applies price and listing-age conditions, then selects five names…

AandelenChinese marktenFactorbeleggenPortefeuilleconstructie
BigQuant

This market note reviews a modest rebound in Chinese equities and discusses the forces behind it. It attributes the recovery partly to expectations of improved second-quarter corporate earnings and reduced global risk aversion. It also cautions that…

AandelenChinese marktenPortefeuilleconstructieRisicobeheer