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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
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FMZ forum
682 documenti
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vn.py community
560 documenti
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QuantStart
246 documenti
Stratmill research code
219 documenti
Robot Wealth
195 documenti
NautilusTrader
191 documenti
Hummingbot docs
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175 documenti
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164 documenti
Kraken Learn
163 documenti
Libreria di corsi quantitativi
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152 documenti
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Qlib
116 documenti
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86 documenti
Quantpedia
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79 documenti
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68 documenti
Hudson & Thames
62 documenti
Awesome Systematic Trading
61 documenti
backtrader
54 documenti
vn.py
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Binance API docs
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Lezioni Quantopian
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FMZ guides
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quant-trading
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FinRL
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Zipline
22 documenti
FMZ live strategies
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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

8 documenti

QTPyLib

The document explains three QTPyLib utilities for working with Interactive Brokers futures. A tuple-generation helper builds a valid contract specification from a symbol, expiry, and optional exchange. Another helper selects the most active contract using…

FuturesDimensionamento delle posizioniGestione del rischio
QTPyLib

This tutorial explains how to bring market data from external providers or existing CSV files into QTPyLib for strategy backtesting. It outlines supported download routes for daily and intraday bars from Yahoo Finance, Google, and Interactive Brokers, with…

BacktestFuturesEsecuzione
QTPyLib

This guide explains how to bring market data from an outside provider into QTPyLib for backtesting. The workflow module’s preparation step converts a data frame into the library’s expected format and can write the result as a CSV file. The example uses…

BacktestEsecuzione
QTPyLib

This reference page catalogs technical indicators and data utilities available in QTPyLib for use with bar data. The built-in list covers volatility and range measures, moving averages, channels, momentum oscillators, returns, volume-related measures, price…

Indicatori tecniciEsecuzioneStatisticaVolatilità
QTPyLib

The document explains how QTPyLib’s Blotter connects to Interactive Brokers through TWS or IB Gateway, receives market data, and distributes updates to algorithms through ZeroMQ. It can also store tick and minute data in MySQL for later research and…

BacktestEsecuzioneMicrostruttura del mercato
QTPyLib

This documentation explains the structure of QTPyLib trading algorithms. It describes optional callbacks for startup, quotes, ticks, bars, order-book updates, and fills, and shows how strategies can use these events to inspect instrument history and…

Indicatori tecniciAzioniFuturesEsecuzione
QTPyLib

This QTPyLib example illustrates a simple event-driven futures strategy for the S&P E-mini. It counts incoming ticks and acts on every tenth tick. When flat and without a pending order, it randomly chooses a side and submits a one-contract limit order around…

FuturesEsecuzioneGestione del rischioTrading ad alta frequenza
QTPyLib

This guide describes QTPyLib, an event-driven framework for building algorithmic strategies with historical testing, paper trading, and live execution through a broker connection. Its architecture separates market data collection, broker operations, strategy…

Indicatori tecniciBacktestEsecuzioneMicrostruttura del mercato