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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

511 documente

QuantInsti blog

The document introduces general and finance-tuned language models, then describes using natural language processing to turn financial text into sentiment measures. It outlines a workflow for collecting and preprocessing Federal Open Market Committee…

SentimentÎnvățare automatăPiețele din SUABazat pe evenimente
QuantInsti blog

The article introduces algorithmic trading as using coded rules to generate and execute orders, then compares it with manual trading. It highlights speed, simultaneous monitoring of markets, reduced reliance on emotional judgment, and the ability to backtest…

ExecuțieTestare istoricăGestionarea risculuiTranzacționare de înaltă frecvență
QuantInsti blog

This project describes two classifiers intended to predict whether Bank Nifty and its leading constituents would open higher or lower on the following trading day. The stock models use daily OHLCV history and technical indicators for five constituents; the…

Învățare automatăAcțiuniIndicatori tehniciTestare istorică
QuantInsti blog

The article explains data engineering as the work of collecting, preparing, organizing, and maintaining data so analysts and trading models can use it reliably. It describes engineers as building data infrastructure and pipelines, removing problems such as…

Învățare automatăTestare istoricăGestionarea risculuiStatistică
QuantInsti blog

The article considers how increasingly capable artificial intelligence could change trading and financial markets. It distinguishes current rule-based automated trading from systems that learn and adapt, then speculates that AI could assess technical,…

Învățare automatăAcțiuniMicrostructura piețeiGestionarea riscului
QuantInsti blog

This webinar description explains how high-frequency prices can extend portfolio risk analysis beyond the low-frequency data commonly used in portfolio metrics. The proposed approach uses intraday observations to estimate risk and support portfolio…

AcțiuniStatisticăGestionarea risculuiConstruirea portofoliului
QuantInsti blog

This event overview outlines a two-day NSE workshop on algorithmic trading, with material spanning strategy research, trading technology, regulation, and portfolio management. Topics include execution methods such as time- and volume-weighted orders,…

ExecuțieMicrostructura piețeiTranzacționare de înaltă frecvențăGestionarea riscului
QuantInsti blog

This interview describes David U. Ordiz’s progression from discretionary Bund futures trading to systematic research and portfolio management. His approach focuses on intraday algorithms seeking short-term trend or counter-trend moves across index futures,…

Contracte futuresVolatilitateGestionarea risculuiTestare istorică
QuantInsti blog

The article introduces multithreading as a way to handle several stock data downloads concurrently. Since network requests spend time waiting for external responses, separate threads can work on different tickers while other requests are pending. It outlines…

AcțiuniExecuțieTestare istorică
QuantInsti blog

The article explains Linear Discriminant Analysis (LDA) as a supervised method for classifying observations and estimating the probability of belonging to a class. It contrasts LDA with logistic regression and describes LDA’s use of Bayes’ theorem, class…

Învățare automatăGestionarea risculuiTranzacționarea perechilorConstruirea portofoliului
QuantInsti blog

This article introduces FIX as a standardized messaging protocol used to connect participants and systems across electronic trading workflows. It describes how a shared format can reduce integration effort, simplify communication with multiple brokers, and…

ExecuțieMicrostructura piețeiTranzacționare de înaltă frecvență
QuantInsti blog

This article uses simple betting examples to explain expected value as the probability-weighted average of gains and losses. It shows how a favorable payoff structure can produce positive expectation even when a win is uncertain, while a symmetric…

StatisticăGestionarea risculuiConstruirea portofoliuluiOpțiuni
QuantInsti blog

This document explains ADDM, a method for detecting changes in a trading model’s prediction errors and adapting the model when market conditions shift. Its detector uses a Self-Exciting Threshold Autoregressive (SETAR) model to divide error behavior into…

Învățare automatăStatisticăTestare istorică
QuantInsti blog

This interview with trader Priyanka S. includes practical advice for developing and testing equity signals. She cautions that familiar technical indicators such as moving average crossovers may contain little information about future prices, and encourages…

AcțiuniIndicatori tehniciTestare istoricăInvestiții bazate pe factori
QuantInsti blog

The article explains how a time-series generative adversarial network can produce synthetic financial observations when historical data is limited. It describes the generator and discriminator conceptually, then focuses on the conditional probabilistic…

Învățare automatăTestare istoricăAcțiuniStatistică
QuantInsti blog

This project tests a simple ETF pairs strategy in oil, technology, and financial sectors: USO with XLE, XLK with IYW, and XLF with PSCF. It estimates a hedge ratio by regression, evaluates spread stationarity with an Augmented Dickey-Fuller test, then enters…

AcțiuniTranzacționarea perechilorRevenire la medieArbitraj
QuantInsti blog

The document explains how to stitch successive futures contracts into a longer time series for analysis when each individual contract has limited history. Simply joining contract prices can create artificial jumps because adjacent expiries may trade at…

Contracte futuresMărfuriTestare istoricăStatistică
QuantInsti blog

The article introduces spread trading as a hedged position that buys and sells related contracts, such as options on the same security with different strikes or expiries, or futures with different delivery months, commodities, or locations. It recommends…

OpțiuniContracte futuresMărfuriGestionarea riscului
QuantInsti blog

The article demonstrates simple and multiple linear regression on historical returns for Coca-Cola, PepsiCo, the S&P 500 ETF, and the US Dollar Index. It first uses pairwise correlations, then fits a single-predictor model for Coca-Cola returns using the S&P…

AcțiuniStatisticăÎnvățare automatăTestare istorică
QuantInsti blog

The article introduces the Kalman filter as a recursive method for estimating a changing, partly unobserved state by combining model predictions with noisy measurements and their uncertainty. It explains concepts including normal distributions, variance,…

StatisticăTranzacționarea perechilorVolatilitateConstruirea portofoliului
QuantInsti blog

The article explains divergence as a mismatch between an asset’s price swings and an indicator or oscillator’s swings. It distinguishes regular bullish and bearish divergence, which may warn of a trend reversal, from hidden bullish and bearish divergence,…

Indicatori tehniciUrmărirea tendințeiRevenire la medieGestionarea riscului
QuantInsti blog

This overview explains high-frequency trading as automated order placement that depends on rapid market data, fast decision systems, and low-latency execution. It describes co-location, tick-by-tick feeds, and market making, where firms quote both sides and…

Tranzacționare de înaltă frecvențăMarket makingMicrostructura piețeiVolatilitate
QuantInsti blog

This guide describes a walk-forward workflow for forecasting stock prices with XGBoost. It motivates repeated model updates as a response to concept drift and changing data distributions. Historical price data are cleaned, adjusted prices are used, and…

Învățare automatăAcțiuniTestare istoricăIndicatori tehnici
QuantInsti blog

This project tests a market-neutral pairs strategy on Brazilian equities, grouping stocks by sector and screening pairs with the Johansen cointegration test. It keeps pairs with a consistently signed spread and a half-life no longer than 60 days. Entry and…

AcțiuniTranzacționarea perechilorRevenire la medieStatistică