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Libreria delle conoscenze

Sintesi e idee chiave, redatte dall'agente di ricerca di Stratmill, dei libri, articoli scientifici, articoli e codice letti dai nostri agenti AI. Ogni pagina rimanda all'originale.

Quant Q&A
20,364 documenti
SuperMind
12,226 documenti
OKX Learn
8,431 documenti
Strategy library
7,910 documenti
MQL5 code base
7,090 documenti
BigQuant
3,481 documenti
Bitget Academy
3,298 documenti
MQL5 articles
3,012 documenti
TradingView scripts
1,976 documenti
ProRealCode
1,507 documenti
Deribit Insights
1,232 documenti
Machine Learning for Trading
1,124 documenti
arXiv papers
1,033 documenti
Amberdata research
766 documenti
FMZ forum
682 documenti
FMZ digest
662 documenti
vn.py community
560 documenti
QuantInsti blog
511 documenti
Galaxy Research
340 documenti
QuantStart
246 documenti
Stratmill research code
219 documenti
Robot Wealth
195 documenti
NautilusTrader
191 documenti
Hummingbot docs
181 documenti
Paradigm research
175 documenti
Lumibot
164 documenti
Kraken Learn
163 documenti
Libreria di corsi quantitativi
157 documenti
OctoBot
152 documenti
Cryptohopper blog
144 documenti
Systematic trading blog (Rob Carver)
132 documenti
Qlib
116 documenti
TqSdk
86 documenti
Quantpedia
86 documenti
Hyperliquid docs
79 documenti
Freqtrade
68 documenti
Hudson & Thames
62 documenti
Awesome Systematic Trading
61 documenti
backtrader
54 documenti
vn.py
50 documenti
Binance API docs
45 documenti
Lezioni Quantopian
45 documenti
FMZ guides
38 documenti
pysystemtrade
34 documenti
Freqtrade docs
32 documenti
quant-trading
31 documenti
FinRL
28 documenti
Zipline
22 documenti
FMZ live strategies
21 documenti
Jesse
17 documenti
pyfolio
16 documenti
Alphalens
14 documenti
WonderTrader
14 documenti
backtesting.py
11 documenti
Technical Analysis
9 documenti
QTPyLib
8 documenti
QuantRocket
7 documenti
Lumibot strategies
7 documenti
Awesome Quant
1 documenti

Cerca nella libreria

3,481 documenti

BigQuant

This research summary describes a bull-bear indicator built from changes in equity-market volatility and turnover. It classifies conditions according to whether each measure is rising or falling. Rising volatility with falling turnover is presented as a…

AzioniMercati cinesiVolatilitàIndicatori tecnici
BigQuant

The article surveys execution algorithms by their main objective: reducing market impact, controlling total trading costs, or adapting execution to favorable market conditions. It describes TWAP as time-based order slicing, VWAP as matching execution to…

EsecuzioneMicrostruttura del mercatoGestione del rischio
BigQuant

This study summary examines an improvement to a one-sided volatility-difference timing model. It reports that bullish signal accuracy rises with trading amount, while bearish signal win rates show no similar relationship. The proposed change uses relative…

Mercati cinesiAzioniIndicatori tecniciBacktest
BigQuant

This research summary argues that low valuation alone can select weak businesses, so investors should assess company quality before deciding whether its price is reasonable. It evaluates A-share companies using indicators related to profitability, growth,…

Mercati cinesiAzioniInvestimento fattorialeCostruzione del portafoglio
BigQuant

This research summary compares five classifiers for predicting stock returns from historical equity factors: multinomial logistic regression, linear support vector machines, random forests, XGBoost, and deep neural networks. It distinguishes the linear…

AzioniInvestimento fattorialeApprendimento automaticoStatistica
BigQuant

The document reports a mismatch between a portfolio strategy’s expected rebalance schedule and its simulated trading activity. The author says the backtest rebalances every five days or after a take-profit trigger, while the simulation records trades on many…

BacktestEsecuzioneCostruzione del portafoglioMercati cinesi
BigQuant

The document summarizes an analysis of Chinese A-share investor research visits, using public company announcements to identify when institutions visit firms. These events are usually targeted visits involving five or fewer institutions, and announcements…

AzioniBasato su eventiStatisticaMercati cinesi
BigQuant

This note diagnoses a backtest error in BigQuant position-condition functions. Both the opening and closing condition functions attempt to filter a DataFrame using a column named “fantanbili.” The author points out that the prediction output supplied by an…

BacktestStatistica
BigQuant

The document outlines a systematic stock-selection model built from valuation, profitability, growth, operating-efficiency, and technical factors. It describes a scoring approach: choose candidate factors, test their predictive usefulness, remove redundant…

AzioniInvestimento fattorialeStatisticaBacktest
BigQuant

This summary examines whether frequent constituent changes weaken returns for a portfolio tracking the CSI 300. It reports a Wilcoxon test finding short-term price effects around index adjustments: additions tended to rise and removals to fall, with the…

AzioniMercati cinesiCostruzione del portafoglioBacktest
BigQuant

The article explains “price desensitization”: a cyclical company’s shares stop advancing, or weaken, while the underlying commodity price continues to rise. Its proposed rationale is that equity prices anticipate earnings and may have priced in future gains…

AzioniMaterie primeMomentumGestione del rischio
BigQuant

This Chinese-language manual explains a portfolio optimizer for constructing benchmark-aware equity portfolios. It describes initializing the optimizer with a dated stock universe and benchmark, refreshing factor data for each trading date, and then…

AzioniCostruzione del portafoglioInvestimento fattorialeGestione del rischio
BigQuant

This research digest summarizes two studies on equity signals. The first trains a deep neural network on five years of fundamental data to forecast future fundamentals. The summary reports that, relative to a simple forecast assuming current data persist,…

AzioniApprendimento automaticoInvestimento fattorialeSentiment
BigQuant

This document summarizes a framework for deciding whether and how to combine single-factor smart beta strategies with multifactor portfolios. It represents each candidate strategy as exposures to a small set of investable elementary smart betas—initially…

Investimento fattorialeCostruzione del portafoglioGestione del rischioAzioni
BigQuant

This introductory guide surveys algorithmic trading, from the history and terminology of financial markets to the roles of quants, traders, and market makers. It describes common benefits of automation, such as speed and scalability, alongside constraints…

BacktestGestione del rischioMomentumRitorno alla media
BigQuant

This strategy seeks to outperform the CSI 1000 while controlling industry, style, and individual-stock exposures. It proposes combining value, growth, size, quality, volatility or liquidity, and alternative signals. Factors are cleaned for outliers,…

Mercati cinesiAzioniInvestimento fattorialeCostruzione del portafoglio
BigQuant

The document summarizes a study of a composite fundamental factor based on the Piotroski framework and its stock-selection value in the Chinese A-share market. It reports that stocks in the highest factor decile outperformed those in the lowest by an average…

AzioniMercati cinesiInvestimento fattorialeStatistica
BigQuant

A user asks how to express a specific six-session price pattern in a platform’s daily factor-expression syntax. The condition is that the latest close exceeds each of the previous five closes, while the close from five sessions earlier also exceeds the…

AzioniIndicatori tecniciInvestimento fattoriale
BigQuant

This example equity strategy selects stocks using valuation and trading activity. At each 30-trading-day interval, it buys at the open shares with positive price-to-book ratios below 1.5, price-to-earnings ratios below 15, and volume between 1.5 and 2.5…

AzioniMercati cinesiIndicatori tecniciBacktest
BigQuant

The document presents asset allocation as a combination of choosing assets and timing the market, with portfolio risk and expected return as the objectives. It explains that a hidden Markov model infers unobservable market states from observable data, then…

Apprendimento automaticoStatisticaCostruzione del portafoglioMercati cinesi
BigQuant

This study describes a revised deep Q-network approach for timing individual Chinese stocks. The earlier version used daily OHLCV data and several common factors as its state. The revision instead takes a configurable window of recent closing prices and…

AzioniApprendimento automaticoBacktestDimensionamento delle posizioni
BigQuant

This forum discussion asks how a visual stock-selection strategy combines multiple factors when no explicit weights are visible, and how the same logic might be represented in SQL. The example lists dividend yield, price-to-book, return on equity, and profit…

AzioniInvestimento fattorialeCostruzione del portafoglio
BigQuant

The document explains why a stock filter set to the CSI 500 can return fewer securities than the index membership count. In the cited example, the filter is applied to a particular date, and some constituents were suspended, leaving their five-day return…

AzioniMercati cinesiStatistica