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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 article explains a four-part decomposition of market beta based on whether market and individual stock returns are positive or negative together. The components distinguish joint losses, joint gains, and the two mixed-sign cases. Using realized…

AcțiuniStatisticăGestionarea risculuiConstruirea portofoliului
BigQuant

This summary of a 2018 brokerage study examines whether capital-flow measures can help anticipate shifts among equity investment styles. It argues that raw fund-flow observations may add little beyond price and volume because those variables move together,…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiStatistică
BigQuant

This article warns retail equity traders that fast algorithms may exploit order-flow speed differences, bursts of retail enthusiasm, and clustered stop levels. It illustrates possible behaviors: entering ahead of slower orders, buying into a sentiment-driven…

AcțiuniPiețele din ChinaMicrostructura piețeiExecuție
BigQuant

This study examines whether futures-curve shape can rank commodity markets. It explains backwardation, where deferred contracts are cheaper than nearer ones, and contango, where they are more expensive. The article connects these patterns to supply, demand,…

MărfuriContracte futuresCarryInvestiții bazate pe factori
BigQuant

This platform support thread discusses how to preserve a model after rolling training and whether the final saved artifact represents the intended result. The replies characterize rolling training as a research-stage feature rather than a direct route to…

Învățare automatăTestare istorică
BigQuant

The post contains a proposed monthly China A-share industry-rotation backtest. It ranks second-level industries by where current price-to-earnings ratios sit within their own rolling 60-session ranges, then selects six industries with the lowest relative…

Piețele din ChinaAcțiuniInvestiții bazate pe factoriTestare istorică
BigQuant

The article describes turning rolling OHLC windows into sparse, binary candlestick images for a convolutional neural network. Each sample uses 32 time steps, normalized and mapped onto a 128-by-128 grid; three columns represent each candle’s open, high-low…

AcțiuniÎnvățare automatăTestare istoricăIndicatori tehnici
BigQuant

The article presents a speculative outlook for China’s A-share market in 2026. It anticipates a gradual upward market with a spring positioning period, a stronger phase from May through September, and a sharp interim pullback that it interprets as a possible…

Piețele din ChinaAcțiuniConstruirea portofoliuluiGestionarea riscului
BigQuant

This research digest summarizes two distinct topics. For multi-factor index construction, it contrasts a top-down approach, which combines single-factor indexes using assigned proportions, with a bottom-up approach, which optimizes holdings to increase…

Investiții bazate pe factoriConstruirea portofoliuluiAcțiuniMicrostructura pieței
BigQuant

This forum post describes an exploratory factor-construction exercise in the Chinese A-share market. The author says a small modification to a factor combination produced strong short-side results, then describes a revised version that removed the short…

Piețele din ChinaAcțiuniInvestiții bazate pe factoriStatistică
BigQuant

The document outlines three ways to explain portfolio results: style analysis using return regressions, benchmark-relative return decomposition, and multi-factor attribution. It describes the data each approach needs, including portfolio and benchmark…

Investiții bazate pe factoriConstruirea portofoliuluiGestionarea risculuiStatistică
BigQuant

This opinion article argues that quantitative trading has different effects across market structures. It contrasts a US market it characterizes as institutionally dominated with China’s A-share market, which it portrays as retail-heavy and more driven by…

Piețele din ChinaAcțiuniMicrostructura piețeiSentiment
BigQuant

This review summarizes research on whether skilled active U.S. equity fund managers add more value when prices are noisier. It measures skill mainly through portfolio selectivity, proxied by one minus a fund’s return-model R-squared, and also uses a…

AcțiuniSentimentStatisticăGestionarea riscului
BigQuant

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

AcțiuniPiețele din ChinaÎnvățare automatăInvestiții bazate pe factori
BigQuant

The document summarizes a study of four MSCI smart beta equity indexes—value weighted, equal weighted, momentum, and minimum volatility—against a market-cap-weighted benchmark. Using monthly returns over 1999–2014, the study applies principal component…

AcțiuniInvestiții bazate pe factoriStatisticăConstruirea portofoliului
BigQuant

The document explains a cost-concentration measure for the estimated purchase costs of a selected share of investors’ holdings. It defines the measure as the difference between the upper and lower bounds of that cost interval divided by their sum. A narrower…

AcțiuniStatisticăInvestiții bazate pe factori
BigQuant

This article outlines an event-driven strategy for Chinese equities, using quarterly reports as the trigger. It treats a published year-over-year increase of more than 30% in attributable net income as a positive event, buys qualifying stocks when reported,…

Piețele din ChinaAcțiuniBazat pe evenimenteTestare istorică
BigQuant

This essay focuses on how fear can affect trading decisions, including hesitation after losses, reluctance to buy near highs, and difficulty acting during market weakness. Its central idea is that traders need not eliminate fear to act consistently; they can…

AcțiuniExecuțieGestionarea risculuiStatistică
BigQuant

The report reviews the development of Smart Beta index funds in China and compares single-factor strategies in A-shares with counterparts in the US. It describes a Chinese market where offerings are relatively early-stage, commonly single-factor, and held…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiPiețele din China
BigQuant

This report summary describes a Chinese equity ETF rotation approach built from industry indices with matching exchange-traded funds. It selects 14 industries from the broader industry classification and rotates exposure among their ETFs. The strategy is…

AcțiuniPiețele din ChinaUrmărirea tendințeiContracte futures
BigQuant

This strategy ranks stocks across mainland China’s A-share market using a small-cap factor and a five-period momentum measure. It combines the market-cap rank with momentum into a composite score, selects the top 50 names, and assigns equal weights. The…

Piețele din ChinaAcțiuniMomentumInvestiții bazate pe factori
BigQuant

The article argues that quantitative trading is an execution method, not a source of returns by itself. A trading system can automate orders and support consistent discipline, but it cannot make a weak or faulty strategy profitable. It also questions the…

ExecuțieGestionarea risculuiTestare istoricăAcțiuni
BigQuant

The document reviews tactical and dynamic asset allocation, then focuses on predicting short-term movements in Chinese equity indices. It compares logistic regression, artificial neural networks, and support vector machines across different inputs and…

AcțiuniPiețele din ChinaÎnvățare automatăUrmărirea tendinței