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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 document describes a cross-sectional equity reversal factor that separates recent returns according to trading activity. For each stock, it looks back over 20 sessions, calculates average transaction value per trade each day, ranks the sessions by that…

AcțiuniRevenire la medieInvestiții bazate pe factoriMicrostructura pieței
BigQuant

The report examines Chinese analyst earnings forecasts, ratings, and target prices as inputs to equity selection. It compares six ways to combine analyst estimates and finds that weighting forecasts by analysts’ past accuracy performs better than several…

AcțiuniInvestiții bazate pe factoriStatisticăPiețele din China
BigQuant

The document reports a pandas error raised when a factor-analysis workflow formats the minimum date with strftime. The shown failing expression takes the minimum of a date column and immediately formats it; pandas raises the error when that value is NaT, its…

StatisticăAcțiuni
BigQuant

The article introduces XGBoost as a boosting ensemble and contrasts its sequential fitting of weak learners with the parallel training used in bagging. It explains residual-based improvement, complexity penalties, sample and feature subsampling, and…

Învățare automatăInvestiții bazate pe factoriAcțiuniTestare istorică
BigQuant

This summary of a Changjiang Securities study examines whether the weak side of equity style factors can help improve an index-enhancement portfolio. It reports historical measurements from 2007 through 2019, identifying negative excess returns for…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

This report summary outlines a method for inferring informed trading from minute-level data. It first applies a “smartness” measure to identify trades attributed to smart money, then aggregates their relative execution prices into sentiment factor Q. Higher…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriSentiment
BigQuant

This short assignment response describes quantitative investing as using data to check market observations and identify patterns. It frames the goal as building strategies that can be backtested and evaluated for stability over time, then using software to…

StatisticăTestare istoricăExecuție
BigQuant

The example constructs price-based stock factors from recent daily observations. For each half-month sampling date, it retrieves a recent window of daily high, open, low, close, and average price data for the stock universe. It calculates three mean…

AcțiuniInvestiții bazate pe factoriIndicatori tehniciPiețele din China
BigQuant

This research note proposes that stock price changes reflect market forces, firm-specific short-term information, longer-term fundamentals, and noise. It uses daily minute data and cross-lag regressions of returns on changes in trading volume to estimate…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriStatistică
BigQuant

This brief report summary reviews changes in Chinese public mutual fund holdings during the fourth quarter of 2017. It says fund exposure rose in several sectors, led by food and beverage and home appliances, with increases also reported for electrical…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

The document explains a portfolio approach built around StockRanker, a model that ranks stocks using historical data. Each day, the strategy buys the highest-ranked candidates and sells or replaces holdings that fall toward the bottom of the ranking. The…

AcțiuniÎnvățare automatăConstruirea portofoliuluiDimensionarea pozițiilor
BigQuant

The post outlines a low-frequency model for timing Chinese A-share exposure and selecting trading targets. It describes using daily Wind data and a large set of predetermined spreadsheet formulas to generate bullish or bearish signals and identify an…

AcțiuniIndicatori tehniciTestare istoricăPiețele din China
BigQuant

This brief BigQuant support exchange addresses a question about a backtest whose logs and apparent trade signals stop before the requested end date. The user says the run was set through the 23rd, exchange data stopped at the 17th, and the output log stopped…

Testare istoricăGestionarea risculuiStatistică
BigQuant

This forum post raises a practical backtesting question: whether strategy data indexed by the current date can be used to trade at that same day’s open without introducing lookahead bias. The example ranks stocks using market capitalization, tradable market…

Testare istoricăExecuțieAcțiuniGestionarea riscului
BigQuant

This dated Chinese equity market report combines market activity, sentiment, sector flows, concentration measures, and style-factor performance. It describes subdued overall valuations, rising consumer-sector turnover, a recovery in TMT activity, and strong…

AcțiuniPiețele din ChinaInvestiții bazate pe factoriMomentum
BigQuant

This review examines whether controlling for quality changes the apparent size premium in equity markets and whether small-cap exposure can strengthen other factors. It compares size-factor returns with quality and related factor exposures using time-series…

AcțiuniInvestiții bazate pe factoriStatisticăPiețele din SUA
BigQuant

The article reviews empirical research comparing commodity futures momentum based on total returns with momentum based on residual, or idiosyncratic, returns after accounting for selected systematic factors. The study forms ranked portfolios across…

MărfuriContracte futuresMomentumInvestiții bazate pe factori
BigQuant

This short exchange explains how to assign groups when training a learning-to-rank model on stock observations. The questioner expects each trading date to form a group, so the model ranks stocks against other stocks observed on that date, and asks where…

AcțiuniÎnvățare automatăStatistică
BigQuant

This brief assignment reflects on translating discretionary investment ideas into a quantitative process. The author cites assessing future demand for a company’s product, with examples involving a stablecoin business in the context of US Treasury pressures…

AcțiuniTestare istoricăGestionarea risculuiInvestiții bazate pe factori
BigQuant

This Chinese-language research digest summarizes two separate studies. The first considers adding trend-following strategies to target-date funds in defined-contribution retirement plans. It argues that these funds may concentrate too much risk in equities…

Urmărirea tendințeiConstruirea portofoliuluiAcțiuniStatistică
BigQuant

This Chinese-language tutorial describes implementing a stock-ranking strategy in BigTrader by passing StockRanker predictions directly to the trading engine and coding the trade logic there. It allocates purchases among the top-ranked stocks using weights…

AcțiuniÎnvățare automatăDimensionarea pozițiilorConstruirea portofoliului
BigQuant

This study mines short-horizon price and volume factors for Chinese equities, then examines how transaction costs and rebalance frequency affect portfolio results. It uses genetic programming to generate candidate daily factors from conventional price and…

Piețele din ChinaAcțiuniInvestiții bazate pe factoriConstruirea portofoliului
BigQuant

This BigQuant note explains how to change a strategy template’s initialization settings from a declining weight schedule to equal weights. The existing example assigns larger allocations to earlier stocks using weights proportional to the inverse logarithm…

AcțiuniConstruirea portofoliuluiDimensionarea pozițiilor