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Kennisbibliotheek

Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.

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

Doorzoek de bibliotheek

34 documenten

pysystemtrade

This Python module defines four types of trading forecasts from price or carry series. Its breakout rule locates the rolling high-low range, measures the current price relative to the range midpoint, scales that reading, and smooths it with an exponentially…

UitbraakCarryTerugkeer naar het gemiddeldeTechnische indicatoren
pysystemtrade

This risk stage calculates portfolio risk for several position representations. It can pass optimized portfolio weights directly to the portfolio stage, or estimate risk from original positions after buffering and rounding. For the latter path, it gathers…

PortefeuilleconstructieRisicobeheerPositiegrootte
pysystemtrade

This document explains how a futures trading system uses several instrument sets: the full catalog, instruments sampled for price data, instruments with adjusted prices, and the smaller sets used in simulation or production backtests. It describes…

FuturesBacktestenPortefeuilleconstructieOrderuitvoering
pysystemtrade

This code models order and trade state for a scalping system. When flat with no open orders, it places buy and sell limit orders around the current price, with their distance based on a volatility-like measure R and a configurable multiplier. After one order…

OrderuitvoeringRisicobeheerPositiegrootteBacktesten
pysystemtrade

This documentation explains the production workflow for pysystemtrade, from obtaining market prices and generating desired positions to sending orders and reconciling accounting information. It covers the production system’s components and data flow, broker…

OrderuitvoeringMarktmicrostructuurFuturesValutahandel
pysystemtrade

This code implements a portfolio stage that recalculates instrument positions across dates. For each date, it builds an optimization objective from target contract positions, a covariance estimate, contract values, transaction costs, previous positions,…

PortefeuilleconstructiePositiegrootteOrderuitvoeringRisicobeheer
pysystemtrade

This position-sizing stage converts a combined trading forecast into a subsystem position. It scales the forecast by an average position size derived from the account’s daily cash volatility target and the instrument’s volatility, then normalizes by the…

PositiegrootteVolatiliteitRisicobeheer
pysystemtrade

This document describes a raw-data stage in a futures trading system that prepares reusable price and carry calculations for later forecasting. It retrieves daily, natural-frequency, and hourly prices; computes absolute daily and hourly price changes; and…

FuturesVolatiliteitCarryStatistiek
pysystemtrade

The code builds a portfolio of instruments through a greedy selection process. It first scores each eligible instrument individually, then repeatedly adds the candidate that gives the highest estimated portfolio Sharpe ratio. Correlations enter through a…

PortefeuilleconstructieRisicobeheerPositiegrootteOrderuitvoering
pysystemtrade

This system stage combines already scaled and capped forecasts from multiple trading rules for an instrument. It aligns rule weights with available forecasts, adjusts weights when forecasts are missing, carries weights forward across dates, smooths them with…

PortefeuilleconstructieRisicobeheer