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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 an early-stage study of market microstructure signals in the IF equity index futures contract. It proposes examining the difference between midpoint and trade-price log returns, quoted depth, large trades, and signed volume. The…

Contracte futuresMicrostructura piețeiStatisticăTranzacționare de înaltă frecvență
BigQuant

This document reviews an empirical comparison of machine learning approaches for forecasting monthly returns in China’s A-share market. The described process trains models on prior data, uses a validation period for tuning, and tests predictions out of…

Piețele din ChinaAcțiuniÎnvățare automatăInvestiții bazate pe factori
BigQuant

This research summary reviews tests of eight proprietary price-volume factors in Chinese equities, comparing monthly, weekly, and biweekly rebalancing. The factors include active buying and selling, smart money, ideal amplitude, APM, ideal reversal, large-…

AcțiuniPiețele din ChinaMomentumIndicatori tehnici
BigQuant

The document outlines the Chaikin oscillator, a technical indicator built from price and volume data. It first weights volume by the relationship between the close and open relative to the day's high-low range, cumulatively sums that measure, and then takes…

Indicatori tehniciStatisticăAcțiuni
BigQuant

This tutorial describes a Python workflow for comparing two subfunds with the China Securities 1000 Index using weekly net asset values. It calculates rolling correlations over a 20-day window and plots how those relationships change, then compares period…

Piețele din ChinaStatisticăGestionarea risculuiConstruirea portofoliului
BigQuant

This example describes a daily, long-only futures strategy using a 10-period average crossing a 30-period average to generate entry and exit signals. A 120-period moving average acts as a trend filter: the strategy opens a position after an upward crossover…

Contracte futuresUrmărirea tendințeiIndicatori tehniciTestare istorică
BigQuant

The document outlines a workflow for building equity strategies that adapt their stock-selection logic to market conditions. It proposes measuring market sentiment with signals such as the number of limit-up stocks and average returns, then adding industry…

AcțiuniInvestiții bazate pe factoriStatisticăTestare istorică
BigQuant

This post is a satirical warning about trusting impressive quantitative strategy claims and backtest curves. It points readers toward shared deep-learning strategy code, but supplies no description of the model, training data, signals, or validation process.…

Testare istoricăGestionarea risculuiDimensionarea pozițiilor
BigQuant

This Chinese market-timing report reviews sector strength, valuation, breadth, moving-average structure, and equity-fund positioning around July 2020. Its summary highlights stronger recent breadth: the share of stocks reaching 60-day highs and the balance…

AcțiuniPiețele din ChinaMomentumIndicatori tehnici
BigQuant

The article presents a robust version of equal risk contribution (risk parity) portfolio construction. It treats the estimated covariance matrix as uncertain and builds a bounded uncertainty set around the estimate. The optimization then accounts for…

Construirea portofoliuluiGestionarea risculuiStatisticăTestare istorică
BigQuant

This research note describes an enhancement strategy for China’s CSI 1000 small-cap equity index. It combines factors representing valuation, growth, trading behavior, capital flows, and network relationships within index constituents. After neutralizing for…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiTestare istorică
BigQuant

This research summary describes how to build and compare active and passive portfolios of Chinese healthcare-themed funds. For active funds, it argues that screening should use actual underlying holdings, since a fund's label may not reflect a concentrated…

AcțiuniPiețele din ChinaConstruirea portofoliuluiTestare istorică
BigQuant

The document discusses whether stochastic-process mathematics, including Brownian motion, still matters as machine learning becomes more common in quantitative finance. It presents several practitioner views: stochastic calculus has a stronger role in…

Învățare automatăStatisticăEvaluarea derivatelorExecuție
BigQuant

This 2018 research summary forecasts changes to the FTSE China A50, an index of large Chinese mainland stocks selected with free-float and liquidity considerations. It describes quarterly reviews in March, June, September, and December, and identifies index…

AcțiuniPiețele din ChinaBazat pe evenimenteConstruirea portofoliului
BigQuant

This commentary examines sharp style swings in China’s A-share market, using recent surges and reversals in the nonferrous metals sector as its main example. It argues that a rapid rise concentrated in a small number of stocks can pull liquidity from other…

Piețele din ChinaAcțiuniMicrostructura piețeiSentiment
BigQuant

This overview distinguishes language generation from financial prediction, arguing that strong text generation does not by itself solve markets’ low signal-to-noise ratios, changing patterns, and limited data. It explains GPT’s development and instruction…

Învățare automatăStatisticăTestare istoricăEvaluarea derivatelor
BigQuant

The document outlines a daily trend-following strategy for commodity futures based on Bollinger bands. It enters long when price breaks above the upper band and short when price breaks below the lower band, then exits when price crosses back through the…

Contracte futuresMărfuriUrmărirea tendințeiStrăpungere
BigQuant

This weekly review compares style-factor performance across Chinese equity universes and summarizes quantitative public-fund returns against broader stock and equity-oriented funds. It reports that price and trading activity related factors—including…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriRevenire la medie
BigQuant

The article describes a method for estimating consensus net profit from analyst forecasts and using that estimate to build equity selection signals. It weights forecasts by report recency and by each analyst’s prior adjusted forecast error, giving greater…

AcțiuniInvestiții bazate pe factoriStatisticăTestare istorică
BigQuant

This opinion article argues that retail traders face a structural disadvantage in short-term equity trading because quantitative firms can use fast systems and direct market connectivity. It attributes the gap to execution speed and claims that automated…

AcțiuniExecuțieMicrostructura piețeiGestionarea riscului
BigQuant

The article describes REDD-COPS, a dynamic allocation method designed to constrain rolling portfolio drawdown while pursuing long-term growth. It replaces a lifetime peak-to-trough reference with a rolling economic maximum, then adjusts exposure to risky…

Active din mai multe claseConstruirea portofoliuluiGestionarea risculuiVolatilitate
BigQuant

This short forum exchange addresses how to adapt a BigQuant strategy to rebalance on a five-day schedule. The reply recommends defining the holding-period setting in the backtest module’s initialization function, then using the K-line processing function to…

AcțiuniTestare istoricăConstruirea portofoliului
BigQuant

This article explains why high-frequency trading firms invest heavily in reducing the time it takes to receive market information and send orders. It describes an earnings-news episode in which an automated firm traded before financial news terminals…

Tranzacționare de înaltă frecvențăExecuțieMicrostructura pieței
BigQuant

The document introduces an MQL4 library that ports regular-expression functionality from the .NET Framework. It outlines the library’s components for patterns, matches, capture groups, options, and Unicode character categories. It also lists options such as…

Execuție