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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 report describes a Chinese equity-selection process built from daily price and volume data. Genetic programming generates candidate factors: Rank IC is used to find factors with linear predictive relationships, while mutual information targets nonlinear…

AzioniMercati cinesiApprendimento automaticoInvestimento fattoriale
BigQuant

This practitioner report reviews DeepAlpha, a neural model used to rank stocks from factor inputs, and compares it with other approaches. The author says a simple fully connected network appeared competitive with decision-tree and linear models, and…

Apprendimento automaticoAzioniInvestimento fattorialeBacktest
BigQuant

This overview catalogs machine learning approaches that can be applied to quantitative investing, grouping them into tree models, linear models, unsupervised methods, deep learning, ensembles, and online learning. It links model families to tasks such as…

Apprendimento automaticoInvestimento fattorialeStatisticaBacktest
BigQuant

The document summarizes research on converting stock factors with strong negative-return associations into a long-only selection process. Because short selling is limited in the A-share market, it describes reversing the use of such signals: remove stocks…

Mercati cinesiAzioniInvestimento fattorialeCostruzione del portafoglio
BigQuant

This report describes a monthly stock selection model that uses a random forest, an ensemble of decision trees trained with bagging, to estimate each stock’s probability of rising in the next period. Its workflow covers feature and label preparation,…

Mercati cinesiAzioniApprendimento automaticoInvestimento fattoriale
BigQuant

This research review explains how earnings beta can measure a company’s exposure to systematic risk through the co-movement of its earnings with aggregate market earnings. It compares eleven earnings series built from realized or analyst-forecast earnings,…

AzioniInvestimento fattorialeStatisticaGestione del rischio
BigQuant

This literature summary covers two separate topics. The first describes a framework for studying how mutual fund managers’ personal characteristics relate to performance, decomposing outcomes into overall results, return and risk, and timing and security…

Multi-assetOpzioniCostruzione del portafoglioVolatilità
BigQuant

This research summary describes an adaptation of Robert Whitelaw’s time-varying Sharpe ratio, or Tsharp, for timing the Shanghai Composite. Unlike a conventional Sharpe ratio, the measure estimates returns and variance through regression, making it…

Mercati cinesiAzioniStatisticaBacktest
BigQuant

This opinion article argues that algorithmic trading can harm investors who rely on widely known indicator signals or chase sharp price moves, while creating opportunities through the liquidity and volatility it adds. It describes three potential…

AzioniEsecuzioneGestione del rischioIndicatori tecnici
BigQuant

This study organizes fifty Wind order-flow measures into eight groups, including inflows, outflows, net active buying, and large-order net flows. It assesses their stock-selection value with industry-neutral portfolio sorts, cross-sectional regressions, and…

Mercati cinesiAzioniInvestimento fattorialeMicrostruttura del mercato
BigQuant

This document summarizes an ETF tracking workbook and describes the market landscape it was designed to monitor. It reports that broad-market and sector or theme ETFs formed the largest non-money-market categories, with examples of major index exposures and…

Mercati cinesiAzioniCostruzione del portafoglio
BigQuant

This market-monitoring report reviews Chinese equities during the early 2020 pandemic shock. It combines trading activity, valuation, turnover, sentiment, sector relative performance, fund concentration, and style-factor signals. Its readings describe…

Mercati cinesiAzioniInvestimento fattorialeStatistica
BigQuant

The document reports a platform-specific issue in which an XGBoost classifier’s probability prediction function returns only endpoint values of zero and one. The user expected continuous class probabilities that could be used to rank securities, based on…

Apprendimento automaticoAzioni
BigQuant

This introductory guide explains how machine learning can be applied to quantitative investing through a staged research workflow. Using a fruit-selection analogy, it describes gathering historical data, defining the prediction target, labeling observations,…

Apprendimento automaticoAzioniBacktestStatistica
BigQuant

This discussion distinguishes machine learning for execution optimization from machine learning for directional trading. Execution begins with a known trade and seeks to reduce its cost; alpha generation must identify price direction and capture enough of…

Apprendimento automaticoTrading ad alta frequenzaMicrostruttura del mercatoEsecuzione
BigQuant

This article describes combining two stock selection models designed for different Chinese equity market conditions: a rebound after an index decline, and a mild market pullback after stocks hit their daily price limit. Each model includes market environment…

Mercati cinesiAzioniBacktestMomentum
BigQuant

This Chinese-language support post describes a feature-engineering question: how to count, over a recent window, the days when a five-day moving average exceeds a ten-day average. The proposed first feature assigns a positive or negative value according to…

AzioniIndicatori tecniciApprendimento automatico
BigQuant

This forum post raises a data-timing problem in a trading workflow. In the described backtest, a signal generated on one day is placed the next day, and pre-market processing can apparently retrieve that day’s opening and closing values through historical…

BacktestEsecuzioneStatistica
BigQuant

This article describes 25 reasons retail investors may lose money in equities. It groups them around information and research gaps, overreliance on one strategy, emotional and herd-driven decisions, limited planning and experience, concentrated portfolios,…

AzioniGestione del rischioCostruzione del portafoglioSentiment
BigQuant

This review explains why diversification may help more during declines than during gains, and why average correlations can hide that difference. It recommends estimating an asset pair’s downside relationship by conditioning on the portfolio’s main growth…

Multi-assetCostruzione del portafoglioGestione del rischioStatistica
BigQuant

This review describes a method for identifying crowded markets and distinguishing potential bubble build-up from unwinding. It measures sector or factor clustering from return covariances and principal components, then pairs that measure with relative…

AzioniInvestimento fattorialeMomentumCostruzione del portafoglio
BigQuant

The document raises a question about possible look-ahead bias in a stock-selection workflow. It points to a five-day return calculated from prices shifted forward in time and asks whether using that value as a feature in a test set leaks future information.…

AzioniApprendimento automaticoBacktestStatistica
BigQuant

The document presents a modified MACD indicator built by replacing standard exponential moving averages with a three-stage smoothing expression. It applies that transformation separately to closing prices over 12- and 26-period spans to form DIF, then…

Indicatori tecniciApprendimento automaticoAzioni
BigQuant

This report summary examines a 2018 forecast of CSI 300 constituent changes and the potential trading flows associated with index funds adjusting their holdings. The forecast uses the index's periodic review rules, including measures of past-year trading…

AzioniBasato su eventiEsecuzioneMercati cinesi