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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
WonderTrader
14 documenten
Alphalens
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 Chinese-language post describes a stock-selection screen that ranks shares by a measure called capital strength, interpreted in the post as trading volume, and applies a condition on float concentration plus a limit on the price gain observed at 9:25.…

Chinese marktenAandelenMomentumTechnische indicatoren
BigQuant

This short homework response defines quantitative investing as using scientific methods to seek profitable predictions. It identifies systematic analysis and statistical reasoning as strengths, then cautions that simulated results can create a false sense of…

StatistiekBacktestenMachine learning
BigQuant

The article presents five principles for trading: build decisions around one coherent set of rules, practice execution until it becomes habitual, judge performance over many trades, wait when conditions are noisy, and accept that strategies can fail. It…

RisicobeheerStatistiekOrderuitvoeringChinese markten
BigQuant

This retrospective examines US exchange traded products and China’s ETF market during 2020, covering fund flows, product launches, fees, providers, regulation, and investor preferences. In the United States, bond ETF inflows were strong amid Federal Reserve…

Multi-assetAandelenVastrentende waardenChinese markten
BigQuant

This short note highlights that feature importance can differ across predictive models, naming StockRanker and XGBoost as examples. It also points to changing the number of leaf nodes and the learning rate as model-tuning choices. These observations can help…

Machine learningAandelenStatistiekBacktesten
BigQuant

This report describes a high-frequency futures CTA approach that uses the relationship between traded prices and adjusted intraday open interest. It argues that open interest can provide information beyond trading volume, and derives directional signals from…

FuturesHoogfrequente handelTechnische indicatorenBacktesten
BigQuant

The document addresses a timing problem when using weekly indicators in a daily trading strategy. A weekly calculation may be absent or incomplete during the current week if the data pipeline only forms values after the week closes. Its example asks how to…

AandelenTechnische indicatorenStatistiekBacktesten
BigQuant

This essay groups chart-centered approaches such as candlestick analysis, Dow Theory, Elliott waves, Wyckoff methods, and Gann techniques under a broad category of pattern-based trading theories. It proposes examining whether any of their components have…

Technische indicatorenStatistiekRisicobeheerAandelen
BigQuant

A platform user reports that a backtest transaction record can misstate realized profit and loss when a stock position passes through an ex-rights corporate action. The example compares transactions in Chinese equities before and after such an adjustment and…

AandelenBacktestenStatistiek
BigQuant

The post outlines an intended Chinese equity strategy that buys stocks when their price-to-earnings ratio ranks near the low end of its rolling history and sells when it reaches the high end, while restricting the universe to companies above a large…

AandelenChinese marktenTerugkeer naar het gemiddeldeBacktesten
BigQuant

This article explains a GBDT-plus-logistic-regression method for classifying stock direction. Gradient-boosted decision trees capture nonlinear feature relationships; each tree maps observations to leaf nodes, which are encoded as indicator variables.…

Machine learningAandelenStatistiekBacktesten
BigQuant

This Chinese-language community post outlines a stock screening rule combining three technical conditions: daily amplitude above one percent, a newly formed KDJ golden cross, and three consecutive sessions in which the close is below the open. It frames high…

AandelenTechnische indicatorenMomentumChinese markten
BigQuant

A user reports that a template stock strategy fails during model training after replacing its full A-share universe with a manually chosen set of only a few stocks. The response recommends expanding the sample pool, explaining that the template is designed…

AandelenMachine learningChinese markten
BigQuant

This report introduces machine learning as data-driven learning and outlines its three broad forms: supervised, unsupervised, and reinforcement learning. It describes how computing advances, larger datasets, and accessible software libraries have helped make…

Machine learningStatistiekChinese marktenBacktesten
BigQuant

This report reviews the weekly returns and directional changes of 16 equity factors. For the week covered, a three-month price momentum or reversal measure led with a reported return of 1.45%, while the 24-day Relative Strength Index returned 0.43%. All…

AandelenFactorbeleggenMomentumTechnische indicatoren
BigQuant

This research summary investigates the A-share small-cap premium, comparing its strength across market-cap segments, industries, and global markets. It reports a pronounced size effect across the broader A-share market and within CSI 500 constituents, but a…

AandelenChinese marktenFactorbeleggenStatistiek
BigQuant

This research summary examines whether internet search attention can help anticipate rotations between Chinese large-cap and small-cap equity indices. It treats search-index changes related to the two market styles as a proxy for investor sentiment,…

AandelenChinese marktenMarktsentimentPortefeuilleconstructie
BigQuant

This brief overview introduces genetic programming as an evolutionary approach to generating quantitative investment factors. It describes starting with basic data inputs and mathematical operators, then iteratively evolving candidate expressions through…

Machine learningFactorbeleggenStatistiekAandelen
BigQuant

The article discusses translating plain-language trading rules into Python strategies for the QMT platform. Its example is a moving-average crossover on a named Chinese equity, with an all-in position rule and adjusted price data. The author reports that an…

Machine learningAandelenTrendvolgendBacktesten
BigQuant

This article advocates using the 20-day moving average as a simple guide to intermediate stock trends. It defines the line as the average closing price over the preceding 20 trading sessions, roughly a month of trading. The proposed reading combines the…

AandelenTechnische indicatorenTrendvolgend
BigQuant

The document outlines an end-to-end portfolio construction framework that embeds a differentiable convex optimization layer within a neural network. Raw asset data passes through the network for feature extraction and combination, then an optimization layer…

Machine learningPortefeuilleconstructieBacktestenStatistiek
BigQuant

The document answers a data-preparation question: how to retain the time of day from a timestamp column while omitting its calendar date. It describes applying a datetime formatting operation to each value in a pandas column, creating a separate time field,…

FuturesStatistiekChinese markten
BigQuant

This short forum exchange addresses how to use a custom benchmark for a strategy such as pair trading, where a portfolio of two stocks may be a more relevant comparison than a broad market index. The suggested approach is to construct an index from the two…

AandelenPairstradingPortefeuilleconstructie