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Biblioteca de cunoștințe

Rezumate și idei principale din cărțile, lucrările, articolele și codul citite de agenții noștri AI, redactate de agentul de cercetare Stratmill. Fiecare pagină trimite la sursa originală.

Quant Q&A
20,364 documente
SuperMind
12,226 documente
OKX Learn
8,431 documente
Strategy library
7,910 documente
MQL5 code base
7,090 documente
BigQuant
3,481 documente
Bitget Academy
3,298 documente
MQL5 articles
3,012 documente
TradingView scripts
1,976 documente
ProRealCode
1,507 documente
Deribit Insights
1,232 documente
Machine Learning for Trading
1,124 documente
arXiv papers
1,033 documente
Amberdata research
766 documente
FMZ forum
682 documente
FMZ digest
662 documente
vn.py community
560 documente
QuantInsti blog
511 documente
Galaxy Research
340 documente
QuantStart
246 documente
Stratmill research code
219 documente
Robot Wealth
195 documente
NautilusTrader
191 documente
Hummingbot docs
181 documente
Paradigm research
175 documente
Lumibot
164 documente
Kraken Learn
163 documente
Biblioteca cursurilor cuantitative
157 documente
OctoBot
152 documente
Cryptohopper blog
144 documente
Systematic trading blog (Rob Carver)
132 documente
Qlib
116 documente
TqSdk
86 documente
Quantpedia
86 documente
Hyperliquid docs
79 documente
Freqtrade
68 documente
Hudson & Thames
62 documente
Awesome Systematic Trading
61 documente
backtrader
54 documente
vn.py
50 documente
Binance API docs
45 documente
Prelegeri Quantopian
45 documente
FMZ guides
38 documente
pysystemtrade
34 documente
Freqtrade docs
32 documente
quant-trading
31 documente
FinRL
28 documente
Zipline
22 documente
FMZ live strategies
21 documente
Jesse
17 documente
pyfolio
16 documente
WonderTrader
14 documente
Alphalens
14 documente
backtesting.py
11 documente
Technical Analysis
9 documente
QTPyLib
8 documente
QuantRocket
7 documente
Lumibot strategies
7 documente
Awesome Quant
1 documente

Caută în bibliotecă

3,481 documente

BigQuant

This report studies trend-based allocation across CITIC Securities’ first-level industry indexes. It frames the process as choosing assets, measuring momentum, selecting industries, assigning weights, and managing portfolio tracking. The analysis describes…

AcțiuniUrmărirea tendințeiMomentumConstruirea portofoliului
BigQuant

This brief exchange explains an apparent one-day mismatch between backtest output logs and the trade details table. The stated cause is the difference between a signal and its execution: the log records when a price bar arrives and triggers the signal, while…

Testare istoricăExecuție
BigQuant

The document asks why a historical price-to-earnings series for China’s pharmaceutical industry differs from a series calculated in code. The example selects constituents classified under the 2021 Shenwan industry scheme, joins them to daily stock valuation…

AcțiuniPiețele din ChinaStatistică
BigQuant

The document summarizes a strategy that combines the relative strength index, exponential moving average, volume-weighted average price, and moving average convergence divergence to generate trading signals. It describes this as a “Weapon Candle” approach…

AcțiuniIndicatori tehniciMomentumTestare istorică
BigQuant

The article describes a discretionary review process for short-term stock theme trading. It begins by scanning the ten highest-turnover names, then compares sectors by the number of stocks advancing from a first limit-up day to a second. Next, it checks the…

AcțiuniMomentumStrăpungereMicrostructura pieței
BigQuant

The article argues that widely used price-based stop rules can cluster orders around obvious levels, where sudden moves may trigger many exits. It recommends shifting attention from a fixed loss percentage on each position to a preset total loss budget, with…

Gestionarea risculuiDimensionarea pozițiilorAcțiuni
BigQuant

This short forum exchange reports a TypeError encountered when opening a backtesting module. The response attributes it to a strategy parameter-name list containing an item that is not a string, which prevents the framework from using that item as an…

Testare istorică
BigQuant

This review summarizes research on U.S. actively managed equity mutual funds during the acute COVID-19 market crisis. The study compares net fund returns with broad-market, style-matched, prospectus, and factor-model benchmarks, and examines investor flows…

AcțiuniPiețele din SUAInvestiții bazate pe factoriStatistică
BigQuant

A user reports that a price-ratio buy condition never triggers during a year-long backtest, although the sell condition does. The response attributes the training error to StockRanker receiving only two factors, with a Boolean factor causing the model to…

AcțiuniÎnvățare automatăTestare istorică
BigQuant

The document explains abnormal idiosyncratic volatility (AIV), a price based measure of information risk around earnings announcements. It compares each stock’s residual volatility during the five trading days before earnings announcements with its residual…

AcțiuniVolatilitateInvestiții bazate pe factoriBazat pe evenimente
BigQuant

The document describes pure factor portfolios as a way to test whether a given equity factor has explanatory or investment value while controlling exposure to other factors. A pure portfolio is constructed to have unit exposure to the factor under…

Investiții bazate pe factoriConstruirea portofoliuluiStatisticăAcțiuni
BigQuant

The document introduces the Commodity Selection Index (CSI), specifying high, low, close, and a lookback length as inputs. Its pseudocode builds an average true range measure from intraday range and gaps relative to the previous close. It also estimates…

MărfuriContracte futuresIndicatori tehniciUrmărirea tendinței
BigQuant

This short project note outlines a workflow for preparing data and fitting a predictive model. It divides SQL data construction into a base dataset, a normalized dataset, and a final feature-and-label stage. The note mentions cross-sectional factor ranking…

Învățare automatăStatisticăTestare istorică
BigQuant

This weekly report compares three Huatai fundamental stock-selection portfolios during a market pullback: a high-dividend-yield model, a low price-to-sales model, and a relative price-to-earnings model. It reports absolute returns, benchmark-relative…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiTestare istorică
BigQuant

The article offers four proposed reasons Chinese quantitative funds may find A-shares attractive relative to US equities: a large listed universe and volatile small-cap stocks, lower trading costs, a higher retail share of trading that may create mispricing,…

Piețele din ChinaPiețele din SUAAcțiuniMicrostructura pieței
BigQuant

This excerpt argues that risk control and position sizing deserve priority alongside stock selection and timing. Its proposed framework smooths risk decisions with a moving-average tracking system and calculates a daily score from market or stock…

Gestionarea risculuiDimensionarea pozițiilorUrmărirea tendințeiIndicatori tehnici
BigQuant

This report applies the Fama-French three-factor framework to China’s A-share market, examining monthly evidence from April 2010 through October 2022. It describes the market excess return factor, SMB for company size, and HML for book-to-market, with SMB…

AcțiuniInvestiții bazate pe factoriStatisticăPiețele din China
BigQuant

This monthly allocation report describes a strategic portfolio framework that maps broad asset holdings to underlying macroeconomic risks. It uses principal component analysis to define five factors—economic growth, interest rates, credit, term spread, and…

Active din mai multe claseAcțiuniInstrumente cu venit fixInvestiții bazate pe factori
BigQuant

This Chinese-language strategy note combines two China A-share stock-selection approaches: a small-cap, low-turnover portfolio and a dividend-focused portfolio that excludes the smallest stocks. The first ranks eligible stocks using market capitalization and…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

This report summary describes a growth-stock selection approach for Chinese equities that pairs an earnings-surprise signal with the next-day price gap after an earnings announcement. Rather than comparing reported earnings with a numeric consensus estimate,…

Piețele din ChinaAcțiuniBazat pe evenimenteMomentum
BigQuant

The document explains how to calculate a 14-period Relative Strength Index from closing prices. It separates price changes into gains and losses, averages the first period simply, then smooths later averages by carrying forward the prior value. The ratio of…

AcțiuniIndicatori tehniciMomentumUrmărirea tendinței
BigQuant

This document presents the China Securities Innovative Drug Industry Index as a way to track listed companies whose main businesses involve innovative drug research and development. It describes the index’s exposure to pharmaceutical subsectors, company…

AcțiuniPiețele din ChinaConstruirea portofoliului
BigQuant

This report introduces gcForest, or multi-grained cascade forest, as a tree-based deep learning model proposed as an alternative to deep neural networks. It argues that the method may suit financial data because it is described as more robust to…

Învățare automatăTestare istoricăStatisticăConstruirea portofoliului
BigQuant

This report evaluates risk parity, an asset allocation approach that aims to equalize the risk contributions of assets in a portfolio. It tests the approach using two historical data window designs: rolling windows and expanding recursive windows. For each…

Active din mai multe claseConstruirea portofoliuluiGestionarea risculuiTestare istorică