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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
Alphalens
14 documente
WonderTrader
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 introduces environmental, social, and governance investing and outlines six approaches, including exclusions, positive screening, ESG integration, thematic investing, and shareholder engagement. It compares MSCI and Thomson Reuters rating methods…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiPiețele din China
BigQuant

This report overview describes how artificial intelligence may be applied across investment management, including portfolio research, investment decisions, trading, risk control, product development, and client marketing. It highlights information…

Învățare automatăActive din mai multe claseGestionarea risculuiExecuție
BigQuant

This weekly report surveys Chinese equity-selection factors built from intraday trading behavior. Examples include return skewness, downside-volatility share, buying interest and large-order net buying after the open, late-session trading share, average…

AcțiuniPiețele din ChinaTranzacționare de înaltă frecvențăInvestiții bazate pe factori
BigQuant

This document describes an Expert Advisor built around the Adaptive Cyber Cycle indicator. It generates a signal when the indicator crosses its signal line at a bar close. The inputs also allow use of related Adaptive CG Oscillator, CyberCycle, or Adaptive…

ForexIndicatori tehniciTestare istorică
BigQuant

This article explains how to simplify factor research by converting many distinct raw values into a smaller number of bins. Its example is a daily return factor across thousands of stocks, where nearby values may be treated as equivalent for exploratory…

AcțiuniPiețele din ChinaStatisticăInvestiții bazate pe factori
BigQuant

This research summary reviews the 2021 commodity futures market and examines whether exchange increases in trading fees affect commodity prices and CTA strategies. It describes a year of broad price gains followed by sharp reversals amid market…

Contracte futuresMărfuriUrmărirea tendințeiMicrostructura pieței
BigQuant

The article explains how a backtest can look convincing while relying on conditions that may not hold in live markets. It examines three assumptions: orders fill immediately at the signal price, market data forms a continuous sequence, and prices from a…

Testare istoricăExecuțieMicrostructura piețeiGestionarea riscului
BigQuant

The document outlines a financial forum presentation on the use of artificial intelligence in quantitative investing. Its listed examples include a random forest approach to market timing and hedging, a pattern matching method for industry rotation, and a…

Învățare automatăConstruirea portofoliuluiEvaluarea derivatelor
BigQuant

This introductory tutorial explains machine learning concepts before focusing on linear regression. It defines features and labels, distinguishes supervised from unsupervised learning, and outlines classification, regression, clustering, and parameterized…

Învățare automatăStatisticăInvestiții bazate pe factoriTestare istorică
BigQuant

This research summary examines whether analyst earnings forecast errors can help select stocks. It reports that realized forecast errors are strongly negatively associated with subsequent returns: stocks with smaller errors performed better in the described…

AcțiuniInvestiții bazate pe factoriStatistică
BigQuant

This document summarizes a documentary series on the development of money and financial systems. Its topics include the origins and social role of credit and debt, the rise of securities markets and sovereign borrowing, insurance and the welfare state,…

Active din mai multe claseInstrumente cu venit fixAcțiuniGestionarea riscului
BigQuant

This weekly report presents diagnostics for the ten highest-ranked anonymous factors in a Chinese quantitative research competition. It describes average style exposures estimated with daily multivariate regressions and average industry-level Rank ICs, the…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

StockRanker is a tree-based learning-to-rank tool for ordering stocks from supplied features. Its listwise approach optimizes the quality of a stock list’s ranking, and the guide connects the method to the RankNet, LambdaRank, and LambdaMART line of work.…

AcțiuniÎnvățare automatăStatisticăTestare istorică
BigQuant

The document addresses a backtest or trading-log puzzle: a buy order is calculated by rounding available cash down to a whole multiple of 100 shares, yet the recorded final purchase quantity is not a multiple of 100. The explanation given is that the system…

AcțiuniExecuțieTestare istorică
BigQuant

The document explains two differences between backtests and simulated or live trading in a notebook-based platform. In the described live modes, the initialization function runs during each trading period, whereas a backtest runs it once. It also says…

Testare istoricăExecuțieGestionarea riscului
BigQuant

This update log describes changes to a Chinese equity screening expression. The initial filters included a trailing price-to-earnings ceiling and a minimum listing age. The author then replaces a fixed floating-market-capitalization threshold with a…

AcțiuniInvestiții bazate pe factoriTestare istoricăPiețele din China
BigQuant

This literature digest covers two topics. The first evaluates asset-pricing factor models using the maximum squared Sharpe ratio. It describes comparisons among nested models, from CAPM through three-, five-, and six-factor specifications, and non-nested…

Investiții bazate pe factoriConstruirea portofoliuluiGestionarea risculuiAcțiuni
BigQuant

This report summarizes tests of equity factors across industries, covering cash flow, valuation, company size, momentum, liquidity, volatility, beta, and alpha. It compares factor performance using portfolio net value and ranking differences, and discusses…

AcțiuniInvestiții bazate pe factoriStatistică
BigQuant

This review describes a model in which equity factors move through normal conditions, periods of value weakness, and subsequent reversals. The value drawdown may reflect a rally in growth stocks or a collapse in value stocks; reversals then differ according…

Investiții bazate pe factoriAcțiuniMomentumStatistică
BigQuant

The document discusses the rapid growth of China’s quantitative private fund industry since 2019. It attributes that expansion to growing volumes of data, better data processing, and market inefficiencies that may offer more alpha opportunities than mature…

Piețele din ChinaAcțiuniActive din mai multe claseGestionarea riscului
BigQuant

This research summary explains a model in which product-market competition and expected asset returns influence one another. Competition can reduce profit margins, increasing firms’ operating leverage and exposure to systematic shocks. Threats from new…

AcțiuniStatisticăInvestiții bazate pe factoriPiețele din SUA
BigQuant

This Chinese-language research summary describes a top-down framework for institutional fund allocation that connects macro asset views with strategy and product selection. It argues that asset allocation recommendations need to flow through to specific…

Active din mai multe claseInvestiții bazate pe factoriConstruirea portofoliuluiGestionarea riscului
BigQuant

The document introduces the Alligator technical indicator as three moving-average lines calculated from the midpoint of each bar's high and low. It names the lines Lips, Teeth, and Jaw, and describes each as a moving exponential average with a separate fast,…

Indicatori tehniciAcțiuni
BigQuant

This summary of a May 2020 China A-share market-timing report combines sector performance, valuation, market breadth, fund positioning, and an intermediate-term model. It lists the strongest and weakest sectors, notes that valuations fell across several…

Piețele din ChinaAcțiuniIndicatori tehniciStatistică