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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 market commentary considers whether foreign investor outflows and a rise in shares becoming tradable would materially affect Chinese equities. It distinguishes short-term trading flows from longer-term institutional allocations, including new mutual…

Piețele din ChinaAcțiuniSentimentBazat pe evenimente
BigQuant

This meetup summary covers several practical quant trading questions. It suggests examining order book behavior with Level 2 data when developing capital-flow signals, and describes using a Plotly heatmap to inspect correlations among factors. It also points…

Microstructura piețeiInvestiții bazate pe factoriStatisticăGestionarea riscului
BigQuant

This review describes machine-learning approaches to predicting stock returns from accounting data and company characteristics. It compares linear methods, including ordinary least squares, LASSO, and ridge regression, with nonlinear models such as random…

AcțiuniPiețele din ChinaÎnvățare automatăInvestiții bazate pe factori
BigQuant

This submission reflects on a quantitative strategy test whose results changed substantially when the author replaced its default factors or broadened the stock universe to include main-board and ChiNext shares. The observation highlights two practical…

Investiții bazate pe factoriÎnvățare automatăTestare istoricăPiețele din China
BigQuant

The article reviews research on whether individual commitment within US equity mutual fund management teams affects performance. It classifies managers as committed when they work only for one fund, and noncommitted when they also manage other funds. The…

AcțiuniInvestiții bazate pe factoriStatisticăConstruirea portofoliului
BigQuant

The report studies whether intraday return distributions contain stock selection information beyond conventional daily factors. Using one-minute stock prices, it constructs factors from intraday return variance, skewness, and kurtosis, then examines…

AcțiuniInvestiții bazate pe factoriTranzacționare de înaltă frecvențăStatistică
BigQuant

This guide describes a workflow for training an end-to-end stock model locally on compressed minute and multi-minute bar data, then submitting its weights and training code for cloud prediction. It explains that local files store prices and amounts as scaled…

AcțiuniÎnvățare automatăTestare istoricăExecuție
BigQuant

This note tests an A-share stock screen inspired by a “Beautiful 50” concept. It selects companies using three annual-report criteria: net profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below…

AcțiuniInvestiții bazate pe factoriTestare istoricăPiețele din China
BigQuant

This article argues that a high percentage of winning trades does not guarantee profits. It emphasizes the relationship between win rate and the relative size of gains and losses, using examples to illustrate how a strategy with fewer winning trades may…

Gestionarea risculuiDimensionarea pozițiilorSentimentAcțiuni
BigQuant

This overview introduces artificial intelligence and machine learning as tools for analyzing financial data and supporting investment decisions or trading operations. It groups methods by task: supervised learning for prediction and classification,…

Învățare automatăStatisticăGestionarea risculuiConstruirea portofoliului
BigQuant

This note addresses a mismatch in factor analysis: a prediction set has been restricted by strategy conditions, so only a small number of stocks receive scores, while the analysis module still expects broad market coverage. The suggested response is to skip…

AcțiuniInvestiții bazate pe factoriTestare istorică
BigQuant

This community post describes a discrepancy between a CNN-based stock strategy's backtest and simulated-trading signals. With a rolling window of five, both reportedly signal the same stock on January 4. With a window of ten, the simulation notification…

AcțiuniÎnvățare automatăTestare istoricăExecuție
BigQuant

The article argues that unusually high trading volume after a stock advance is an ambiguous event rather than an automatic sell signal. Every trade has both a buyer and a seller, so volume alone cannot reveal whether existing holders are distributing shares…

AcțiuniIndicatori tehniciMomentum
BigQuant

This educational overview introduces common inputs for quantitative stock selection, beginning with simple and exponential moving averages, RSI, Bollinger Bands, MACD, moving-average crossovers, VWAP, and historical volatility. It describes their usual…

AcțiuniIndicatori tehniciÎnvățare automatăStatistică
BigQuant

This research summary revisits the capital asset pricing model by splitting daily stock returns into open-to-close intraday returns and close-to-open overnight returns. It reports that, in the US sample, beta is negatively related to intraday returns but…

AcțiuniStatisticăInvestiții bazate pe factoriPiețele din SUA
BigQuant

The document outlines a Chinese stock screening and trading strategy that targets shares which closed at the daily limit-up on each of the previous two days. Candidates must trade above their five-day moving average, have a price-to-earnings ratio of roughly…

AcțiuniPiețele din ChinaMomentumStrăpungere
BigQuant

This article describes a modification to random forest models that lets an investor express factor preferences directly in the tree-building process. Selected factors are forced to drive splits near the top of each decision tree, increasing their influence.…

Învățare automatăInvestiții bazate pe factoriAcțiuniPiețele din China
BigQuant

The strategy selects Chinese stocks on the day they lose ST designation, buys qualifying names at the open, and holds them for three days. It describes closing trades at the end of the holding period and applying the rule to every stock that meets the event…

AcțiuniBazat pe evenimentePiețele din China
BigQuant

This research explores whether online search interest can serve as a timely measure of investor sentiment and help identify shifts between large-cap and small-cap Chinese equities. It treats search activity related to each style as a sentiment proxy,…

AcțiuniSentimentPiețele din ChinaTestare istorică
BigQuant

This exchange asks whether MACD components and a short-window swing-volatility feature used in model training and prediction contain future information. The response says these factors are calculated from historical data, implying that the indicators…

Indicatori tehniciÎnvățare automatăTestare istoricăStatistică
BigQuant

This research note proposes an equity factor based on how each stock’s intraday volume pattern differs from the market’s. It starts from the common U-shaped market volume profile and argues that a stock with unusually concentrated or uneven trading may have…

AcțiuniInvestiții bazate pe factoriStatisticăMicrostructura pieței
BigQuant

The document introduces stationarity and cointegration as the basis for pairs trading. It describes a stationary series as having a stable mean and variance, and presents a pair as cointegrated when the difference between their prices is stationary. Under…

Contracte futuresTranzacționarea perechilorRevenire la medieStatistică
BigQuant

This brief support note answers when a newly purchased position’s cost information appears in BigQuant. It distinguishes three operating modes: backtests and simulated trading update the value after the market close on the trade date, while live trading…

Testare istoricăAcțiuni