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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

The note proposes adding a 20-period average true range (ATR) volatility factor to a trading strategy, with the aim of improving its Sharpe ratio. It describes a regime-dependent relationship: higher ATR is associated with stronger returns in bull markets,…

VolatilitateGestionarea risculuiTestare istorică
BigQuant

This A-share stock selection strategy buys the ten smallest companies by market capitalization each day and rebalances daily. Its universe is drawn from the CSI 1000 and excludes ST and delisted stocks. Additional filters require a positive trailing…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriIndicatori tehnici
BigQuant

This BigQuant community post reports that applying a lagged value in a query that joins stock prefactors directly to an index-component table can produce zero-filled results. The example calculates a two-period stock return using a lagged close price, then…

Piețele din ChinaAcțiuniStatistică
BigQuant

This short forum answer addresses how to aggregate price-to-earnings data across stocks in an industry. It suggests using a grouped sum operation keyed by an industry classification and applying it to trailing-twelve-month P/E values in a stock-factor…

AcțiuniPiețele din ChinaStatistică
BigQuant

This article proposes interpreting value, momentum, quality, and low-volatility returns through a recurring factor cycle inferred from factor performance itself. It describes normal periods, episodes when value suffers a major drawdown due to growth stocks…

AcțiuniInvestiții bazate pe factoriMomentumRevenire la medie
BigQuant

This Chinese-language summary reviews a quantitative research team’s 2017 results across four areas: multi-asset allocation, index enhancement, factor timing, and commodity trading adviser strategies. It reports that an equity-and-bond active risk-parity…

Piețele din ChinaActive din mai multe claseInvestiții bazate pe factoriUrmărirea tendinței
BigQuant

The document describes preparing supervised-learning labels from Chinese daily stock bars. It calculates a forward price ratio using lead values, clips observations to the cross-sectional 1st and 99th percentile boundaries, and assigns the result as the…

AcțiuniPiețele din ChinaÎnvățare automatăStatistică
BigQuant

This report frames next-day direction in China’s Wind All A-share index as a binary classification task. It trains a decision-tree-based AdaBoost model on 51 daily features drawn from several markets and asset classes, including repo rates, credit spreads,…

Piețele din ChinaAcțiuniÎnvățare automatăTestare istorică
BigQuant

This event page outlines a presentation on moving from discovering individual factors to designing their portfolio weights. It identifies linear and nonlinear combinations and ICIR-based weighting as methods, with attention to their underlying rationale and…

Investiții bazate pe factoriConstruirea portofoliuluiTestare istorică
BigQuant

This shared open-source example builds a daily classifier for Chinese stocks using price and volume data, technical indicators, and three supervised models: a random forest, logistic regression, and a linear support vector classifier. Features include…

Piețele din ChinaAcțiuniÎnvățare automatăIndicatori tehnici
BigQuant

This summary compares two research reports on protecting portfolios during market stress: one published before a major volatility episode and another written afterward. It frames their comparison around how investors assess defensive strategies before a…

Gestionarea risculuiOpțiuniMomentumInvestiții bazate pe factori
BigQuant

The report describes applying OpenFE, an enumerate-and-filter framework, to discover interpretable fundamental factors from Chinese companies’ balance sheets, income statements, and cash-flow statements. It first removes fields with substantial missing data,…

AcțiuniInvestiții bazate pe factoriÎnvățare automatăStatistică
BigQuant

This research summary describes a monthly sector-rotation framework for Chinese equities. It groups 29 CITIC first-level industries into financial, cyclical, consumer, and growth sectors, builds market-cap-weighted sector indices, and proposes selecting…

AcțiuniPiețele din ChinaConstruirea portofoliuluiStatistică
BigQuant

This research summary describes a multi-factor approach to selecting Chinese convertible bonds. It treats each bond’s value as a combination of straight-bond value and embedded option value, and examines how bond returns relate to the underlying stock. The…

Instrumente cu venit fixOpțiuniInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

This study proposes a market mechanism for trading data products by separating data ownership from the right to use the data. Ownership is divided into tradable units to support liquidity, while use rights remain indivisible and go to an end user. The…

Microstructura piețeiÎnvățare automatăStatisticăExecuție
BigQuant

This overview defines factors as common drivers of security returns and distinguishes systematic factor exposure from asset-specific risk. It traces the move from the market-only CAPM to multi-factor explanations such as the Fama–French market, size, and…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiStatistică
BigQuant

The article argues that Rust can suit quantitative trading infrastructure where large data workloads, dense computation, concurrency, and low latency matter. It attributes this fit to Rust’s performance, memory and thread safety guarantees, and lack of…

ExecuțieTranzacționare de înaltă frecvențăAcțiuniContracte futures
BigQuant

The document defines the Mass indicator using the high-low range. It first applies an exponential moving average to that range, then smooths the result with a second exponential moving average of the same length. The ratio of the first smoothed range to the…

Indicatori tehniciVolatilitateStatistică
BigQuant

This forum post compares backtest results for a 20-day and 110-day moving-average strategy on Vanke A shares across two platforms. The strategy buys when the shorter average exceeds the longer one and exits when it falls below, using full portfolio…

AcțiuniPiețele din ChinaUrmărirea tendințeiIndicatori tehnici
BigQuant

This research summary describes an A-share market-impact model intended to narrow the gap between simulated strategy returns and realized portfolio returns. It argues that applying one fixed slippage rate cannot reflect how impact varies across stocks,…

AcțiuniExecuțieMicrostructura piețeiConstruirea portofoliului
BigQuant

This forum post presents a DAI query for filtering Chinese A-share records and asks how to save a large result table as an XLS spreadsheet for separate analysis. Its SQL selects dates, instruments, and derived indicators for price-limit events, including…

AcțiuniPiețele din ChinaIndicatori tehniciStatistică
BigQuant

This Chinese research summary examines the turn-of-month calendar effect, described as stronger returns in the first half of a month than in the second. It reports that a simple strategy of buying during the first half and shorting during the second…

Piețele din ChinaAcțiuni
BigQuant

This research summary examines whether inventory cycle phases can help time broad sectors and the Shanghai Composite. It describes four phases—active restocking, passive restocking, active destocking, and passive destocking—and compares qualitative phase…

Piețele din ChinaAcțiuniInvestiții bazate pe factoriTestare istorică
BigQuant

The document raises a data-timing question about China’s Dragon-Tiger List, a report of stocks with notable trading activity. It names fields for returns one, two, and five days after a stock appears on the list, and says the five-day return is unavailable…

Piețele din ChinaAcțiuniTestare istoricăGestionarea riscului