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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 document introduces a quantitative way to assess an individual stock before deciding whether to buy it and how much capital to allocate. Rather than forecasting which stocks will be attractive, the proposed diagnostic approach looks backward at how the…

AcțiuniStatisticăDimensionarea pozițiilorPiețele din China
BigQuant

This Chinese equity strategy screens for stocks whose opening price is above the previous close and whose five-day closing-price average is above its ten-day average. It ranks qualifying candidates by price-to-earnings ratio in ascending order and selects…

AcțiuniPiețele din ChinaIndicatori tehniciMomentum
BigQuant

This research note summarizes evidence that changes in the wording and structure of company filings can contain information about future operating performance and equity returns. The underlying study compares the text of SEC annual and quarterly reports with…

AcțiuniPiețele din SUASentimentStatistică
BigQuant

This report summary examines how market and style conditions may affect equity market-neutral strategies. Such strategies select stocks using fundamental or price-and-volume signals, then hedge broad market exposure with index futures or short selling. Their…

AcțiuniInvestiții bazate pe factoriConstruirea portofoliuluiGestionarea riscului
BigQuant

The article explains why a factor’s strong historical returns may come from an unintended exposure to market capitalization or liquidity. It uses large-order sell value as an example: because the measure is an absolute amount, it tends to be larger for…

Investiții bazate pe factoriAcțiuniTestare istoricăStatistică
BigQuant

This research summary describes an equity selection process built from daily price and volume data. Genetic programming searches for candidate factors, using RankIC to favor linear relationships or mutual information to seek nonlinear ones. To focus on…

AcțiuniÎnvățare automatăInvestiții bazate pe factoriTestare istorică
BigQuant

This exchange explains how to handle a stock that remains in a backtest portfolio after it leaves the benchmark universe. The example concerns a strategy restricted to CSI 300 constituents: a stock bought while it belonged to the index may still be held…

AcțiuniTestare istoricăPiețele din ChinaConstruirea portofoliului
BigQuant

This brief explanation addresses why applying a one-period lag to closing prices can return a missing value. If the available data begins on the current day, the prior day’s close is outside the dataset, so there is no value for the lag operation to…

Statistică
BigQuant

This forum excerpt concerns constructing training labels for a Chinese stock dataset and asks why label extraction produces an empty training set. The displayed expression derives a future return from a later close divided by a later open, assigns a…

Piețele din ChinaAcțiuniÎnvățare automatăStatistică
BigQuant

This article examines how the length of an AI model’s training window can affect an equity strategy. It compares manually rolled long windows spanning several years with shorter windows ranging from a month to a few years, and recommends evaluating each…

Învățare automatăTestare istoricăAcțiuniInvestiții bazate pe factori
BigQuant

This brief Chinese market report summarizes A-share sector performance, index and sector valuations, market breadth, fund positioning, and an intermediate-term LLT model. It reports the strongest and weakest sectors, notes declining valuations across several…

AcțiuniPiețele din ChinaIndicatori tehniciUrmărirea tendinței
BigQuant

This research summary examines whether market conditions and macro variables can predict the next month’s long-short reversal-factor returns in Chinese equities. It identifies market funding sensitivity, turnover, volatility, and bid-ask spread as…

AcțiuniPiețele din ChinaRevenire la medieInvestiții bazate pe factori
BigQuant

This BigQuant forum post describes a factor-research problem: detect a recent stock event, then later compare price with a level from the event day. The example defines an event using volume more than twice the prior value and a return above a stated…

AcțiuniStatisticăIndicatori tehnici
BigQuant

This brief BigQuant support exchange addresses a simulation error reported as having no data remaining after missing rows are dropped. The user had already tried extending the feature-extraction lookback by several different periods, without resolving the…

Testare istoricăÎnvățare automatăStatistică
BigQuant

The post asks why a daily stock-ranking strategy sells positions in backtests but appears only to buy them in simulation. Its code includes a trailing stop based on a percentage below the highest observed price since purchase, then manages capital and ranks…

AcțiuniÎnvățare automatăGestionarea risculuiDimensionarea pozițiilor
BigQuant

This brief BigQuant support exchange explains an error raised when a time-series minimum function receives a window argument that is not an integer. The example first derives a value from the position of the highest high within a fixed lookback, then passes…

StatisticăÎnvățare automată
BigQuant

The document explains a data-processing approach for high-frequency factors that are first aggregated from intraday observations to daily values and then smoothed over multiple days. Instead of loading the full intraday history needed for the rolling window…

Tranzacționare de înaltă frecvențăIndicatori tehniciStatistică
BigQuant

This note describes a single-security, multi-day approach to constructing intraday volume factors. For each trading day, the proposed measures calculate the share of full-day volume transacted within selected intervals. The intervals cover early trading,…

Tranzacționare de înaltă frecvențăMicrostructura piețeiStatistică
BigQuant

This short exchange addresses how to sell stock shares according to the age of each entry. The example strategy opens separate lots in the same stock on consecutive days, then intends to close each lot after a specified holding period. That requires tracking…

AcțiuniExecuțieDimensionarea pozițiilorGestionarea riscului
BigQuant

This note describes a reproduction of a Guosen Securities quantitative research report on daily momentum factors that combine individual stock and industry returns. Its central idea is to use the relationship between a stock’s performance and its industry’s…

AcțiuniMomentumInvestiții bazate pe factoriTestare istorică
BigQuant

This April 2020 market note combines a long-term trend assessment, short-term liquidity view, sector preferences, and tracking of A-share fund flows. It says a market breadth model had turned bearish and describes weakening turnover and a declining stock of…

Piețele din ChinaAcțiuniStatisticăGestionarea riscului
BigQuant

The report proposes combining company-level stock selection with industry allocation for Chinese equities. Its coupling model uses each stock’s historical beta to its industry as a dynamic weight: more industry-sensitive stocks receive more influence from…

Piețele din ChinaAcțiuniInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

This summary of a Changjiang Securities study explains a stock-selection factor based on the balance between active and passive buying. Active buying occurs when an investor’s order trades against displayed sell orders; passive buying places a limit order…

AcțiuniSentimentInvestiții bazate pe factoriStatistică
BigQuant

This research summary argues that factor signals weaken over time, so holding a monthly portfolio unchanged can leave later-period capital exposed to less informative signals. It proposes measuring a factor’s decay speed through the half-life of its…

Investiții bazate pe factoriTestare istoricăConstruirea portofoliuluiExecuție