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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
Quantpedia
86 documente
TqSdk
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
Prelegeri Quantopian
45 documente
Binance API docs
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 document introduces graph representations for modeling relationships among financial assets, arguing that stocks cannot be understood solely as independent observations. Graphs can encode different kinds of links, including sector membership, return…

AcțiuniÎnvățare automatăConstruirea portofoliuluiExecuție
BigQuant

This post proposes screening stocks in the beverage and alcohol import-export industry using an RSI below 65 and a Morning Star candlestick pattern. The RSI is calculated over 14 periods, while the candlestick signal is identified from open, high, low, and…

AcțiuniIndicatori tehniciRevenire la medie
BigQuant

This research overview describes two broad approaches to absolute-return investing: combining equities and bonds, and hedging or taking exposures through derivatives. It lists stock-bond rebalancing, target-volatility, risk-parity, and risk-budgeting…

Active din mai multe claseConstruirea portofoliuluiGestionarea risculuiContracte futures
BigQuant

This report studies cases where Chinese listed companies’ annual earnings forecasts later change, either through a revision announcement or a discrepancy in the formal results. It uses a multinomial Logit model to assess whether company financial data,…

AcțiuniPiețele din ChinaBazat pe evenimenteStatistică
BigQuant

This overview presents QLib as an open-source quantitative research platform that supports data preparation, model training, portfolio construction, risk analysis, backtesting, and execution research. It notes support for supervised learning, market-dynamics…

Învățare automatăTestare istoricăConstruirea portofoliuluiGestionarea riscului
BigQuant

This brief strategy note proposes ranking or selecting stocks by the deviation in price impact associated with five-minute capital flows. Its stated hypothesis is that stocks with smaller price-impact deviations perform better later; it describes these as…

AcțiuniMicrostructura piețeiIndicatori tehnici
BigQuant

The document summarizes the ResNet paper’s approach to training deep convolutional neural networks. Instead of having stacked layers learn a full transformation directly, residual learning lets them learn a change relative to their input. The paper’s…

Învățare automatăStatistică
BigQuant

This July 2018 research summary reviews U.S. equities, gold, and crude oil using earnings, interest rates, investor risk appetite, currency moves, supply conditions, and inventories. For U.S. stocks, it argues that earnings expectations remain supportive and…

Active din mai multe claseAcțiuniMărfuriPiețele din China
BigQuant

This BigQuant forum post presents a SQL query intended to calculate sector-level and market-level returns, compound each series across a rolling window, and derive an information-ratio-like value. The author reports that the underlying daily inputs appear…

AcțiuniStatisticăConstruirea portofoliuluiGestionarea riscului
BigQuant

The document summarizes research on whether seasonal shifts in investor mood help explain recurring cross-sectional patterns in stock returns. It treats January, March, and Fridays as relatively optimistic periods, and September, October, and Mondays as…

AcțiuniSentimentStatisticăInvestiții bazate pe factori
BigQuant

This reference surveys common technical indicators and explains several price, risk, valuation, and execution measures with formulas and numerical illustrations. Topics include simple and exponential moving averages, RSI, beta, Sharpe ratio, price momentum,…

Indicatori tehniciStatisticăGestionarea risculuiMomentum
BigQuant

This article presents a discretionary approach to rotating from an established leading stock or theme into a newer one. It watches for signs of a theme gaining breadth, such as multiple limit-up stocks, rising sector performance, and an increasing count of…

AcțiuniPiețele din ChinaMomentumDimensionarea pozițiilor
BigQuant

This research summary examines newly launched and large mutual funds in China during the first half of 2020, focusing on their managers’ possible portfolio choices as funds completed or continued building positions. It argues that manager-level analysis can…

AcțiuniPiețele din ChinaConstruirea portofoliuluiInvestiții bazate pe factori
BigQuant

This meetup Q&A covers practical choices in quantitative strategy design. It says researchers can choose the forward-return horizon used as the target when calculating information coefficients, and points to model-based and scoring templates. For…

Contracte futuresAcțiuniIndicatori tehniciGestionarea riscului
BigQuant

This document introduces generative adversarial networks (GANs) as a machine learning framework with two neural networks: a generator that creates samples and a discriminator that judges them. Their competing objectives form an adversarial training process.…

Învățare automată
BigQuant

This report summary describes revisions to AlphaNet, a neural network that learns stock-selection factors from price and volume data. AlphaNet-v2 adds six ratio features, replaces pooling and fully connected layers with an LSTM to capture temporal patterns,…

AcțiuniÎnvățare automatăInvestiții bazate pe factoriTestare istorică
BigQuant

This May 2020 market note reviews the reported Sell-in-May calendar pattern in Chinese A-shares and states that defense and military stocks historically performed best from May through September. Given the possibility of a May pullback, its positioning view…

AcțiuniPiețele din China
BigQuant

The transcript surveys four ways quantitative methods enter trading: high frequency strategies, statistical arbitrage, execution algorithms, and quantitative tools used alongside discretionary investing. It describes market making as earning bid–ask spreads,…

Active din mai multe claseTranzacționare de înaltă frecvențăArbitrajExecuție
BigQuant

This research summary addresses how to combine highly correlated stock-selection factors when there are too many inputs to orthogonalize efficiently or when orthogonalization fails to retain their shared information. It describes reducing each factor group…

AcțiuniInvestiții bazate pe factoriStatisticăTestare istorică
BigQuant

The report describes applying Thompson Sampling, an online learning method, to adjust a multi-factor investment model as market leadership changes. It uses China A-share constituents from the CSI 300 and CSI 500, with valuation, profitability, growth,…

Piețele din ChinaAcțiuniInvestiții bazate pe factoriÎnvățare automată
BigQuant

This collection of trading anecdotes describes manual, high-frequency intraday futures scalping based on order-book changes, quick reactions, and repeated attempts to capture small price differences. Practitioners emphasize watching volume and position…

Contracte futuresTranzacționare de înaltă frecvențăExecuțieMicrostructura pieței
BigQuant

This article surveys Microsoft Research’s published work on AI for quantitative investing, especially Chinese equity selection. It explains methods that use graph neural networks to represent relationships among stocks, attention mechanisms to adapt to…

AcțiuniÎnvățare automatăInvestiții bazate pe factoriGestionarea riscului
BigQuant

This overview presents themes MSCI identified for ESG investing over the coming decade. It groups them into climate and equity, the mainstreaming of ESG, and emerging risks and opportunities. Topics include corporate pressure on net-zero supply chains,…

Active din mai multe claseGestionarea riscului
BigQuant

This weekly report reviews market conditions following a sharp equity selloff and describes trend signals across U.S. and Chinese equities, Hong Kong shares, gold, and bonds. Its trend-following system indicated rising trends in U.S. equities and bonds,…

Active din mai multe claseUrmărirea tendințeiConstruirea portofoliuluiGestionarea riscului