Liigu sisu juurde

Teadmiste raamatukogu

Kokkuvõtted ja põhiideed raamatutest, teadustöödest, artiklitest ja koodist, mida meie AI-agendid loevad. Need on koostanud Stratmilli uurimisagent. Igal lehel on link originaalile.

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

Otsi raamatukogust

3,012 dokumenti

MQL5 articles

This article explains Fully Parameterized Quantile Functions (FQF), a distributional reinforcement-learning method for estimating reward distributions in Q-learning. Earlier approaches use fixed reward categories or predetermined quantiles, which require…

MasinõpeStatistikaTagantjärele testimine
MQL5 articles

The article describes the Multi-Agent Self-Adaptive (MASA) framework for dynamic portfolio management. It assigns return generation to a TD3 reinforcement-learning agent, risk adjustment to a separate optimization-based controller, and market analysis to an…

MasinõpeRiskijuhtiminePortfelli koostamineHiina turud
MQL5 articles

This article explains how to build a C# and WPF add-on for launching Expert Advisor optimizations across multiple MetaTrader terminals on one computer. It reviews command-line launch arguments and INI configuration files, which let a terminal start with…

Tehingute täitmineTagantjärele testimine
MQL5 articles

This installment describes an MQL5 workflow for optimizing trading strategy groups and making updated groups available to a running Expert Advisor through a separate EA database. The proposed database avoids recompiling the final EA whenever optimization…

Portfelli koostamineTagantjärele testimineRiskijuhtimine
MQL5 articles

The article explains how to build a MetaTrader 5 Expert Advisor that places a draggable risk dashboard on the chart. Using the platform’s Standard Library controls and CTrade, the panel displays floating profit and offers bulk closures for all filtered…

RiskijuhtimineTehingute täitminePositsiooni suuruse määramine
MQL5 articles

The article describes a live drift monitor for an ONNX trading model running in MetaTrader 5. It compares a frozen reference sample with a rolling live sample for each input feature, using the one-dimensional Wasserstein-1 distance: sort equal-sized samples,…

MasinõpeStatistikaRiskijuhtimineTagantjärele testimine
MQL5 articles

The article proposes a trading signal that compares normalized price slope with an indicator slope over a lookback window, then treats their difference as structural divergence. It combines this measure with a three-horizon attention proxy intended to weight…

ValuutaturgTehnilised indikaatoridMasinõpeTagantjärele testimine
MQL5 articles

The article explores using neural network activation functions to build custom criteria for ranking strategy parameter sets in MetaTrader optimization. It argues that returning zero for an undesirable pass can disrupt genetic search, while unrestricted…

MasinõpeStatistikaTagantjärele testimine
MQL5 articles

This article surveys preparation and selection of input variables for machine learning, with examples aimed at financial data. It recommends handling missing observations, checking near-constant predictors, reducing problematic correlations where…

MasinõpeStatistikaTagantjärele testimine
MQL5 articles

The article explains how Twin Delayed Deep Deterministic Policy Gradient (TD3) modifies DDPG to reduce overestimation of learned Q-values. Its three core changes are training two Critics and using the lower estimate, updating the Actor less often, and…

MasinõpeRiskijuhtiminePositsiooni suuruse määramineTagantjärele testimine
MQL5 articles

This installment explains how to connect Excel, a Python socket server, and MetaTrader 5 as parts of a market-simulation workflow. It recommends running the MetaTrader component as an MQL5 service rather than a chart-bound script, allowing it to operate…

Tehingute täitmineTuru mikrostruktuurStatistika
MQL5 articles

This article presents TimeFound, a Transformer framework for forecasting time series across domains, and discusses how it can inform systematic trading. The model represents data at multiple time scales by splitting histories into patches of different…

MasinõpeStatistikaTehnilised indikaatoridRiskijuhtimine
MQL5 articles

This article explores pairing the Awesome Oscillator (AO), a momentum and trend indicator, with Envelopes, percentage bands around a moving average that can mark stretched prices. It outlines reversal ideas such as a false break beyond a band followed by a…

ValuutaturgTehnilised indikaatoridKeskmise juurde naasmineLäbimurre
MQL5 articles

This tutorial demonstrates a compact market-data learning pipeline using MQL5's ALGLIB data-analysis library. It converts OHLC bars into five numerical features—one-bar return, candle-body ratio, range ratio, and two momentum measures—and labels each…

MasinõpeStatistikaTagantjärele testimineTehnilised indikaatorid
MQL5 articles

This article applies the category-theory idea of a natural transformation to time-series forecasting with differently structured datasets. One dataset contains a moving-average value; another contains the constituent lagged prices. The author treats the…

ValuutaturgMasinõpeStatistikaTagantjärele testimine
MQL5 articles

This article continues an MQL5 implementation of CATCH, a neural approach to anomaly detection in multivariate time series. CATCH transforms series with the Fourier transform, divides the spectrum into frequency patches, and uses complex-valued convolutions…

MasinõpeStatistikaKõrgsageduskauplemine
MQL5 articles

This tutorial shows how to build a basic neural-network trading Expert Advisor by connecting MetaTrader 5 with NeuroPro, a multilayer network tool. It exports EURUSD hourly closing prices to CSV, converts the data to DBF for NeuroPro, trains and tests a…

ValuutaturgMasinõpeTagantjärele testimine
MQL5 articles

This article introduces Deep Deterministic Policy Gradient (DDPG) as a reinforcement-learning approach for trading agents that must choose continuous action values. Instead of expanding a discrete action list for every combination of direction, volume, stop…

MasinõpeRiskijuhtiminePositsiooni suuruse määramineTagantjärele testimine
MQL5 articles

This article examines filters as rules that suppress some of an automated strategy’s signals, dividing them into bandpass filters that select conditions over a range and discrete filters that accept signals according to a pattern. It demonstrates the process…

Tagantjärele testimineTehnilised indikaatoridRiskijuhtimine
MQL5 articles

This article explains how to define custom optimization scores for MetaTrader 5 Expert Advisors through the tester’s OnTester mechanism. It outlines built-in genetic optimization criteria and shows how a custom score can combine outcomes such as profit,…

Tagantjärele testimineStatistikaRiskijuhtimine
MQL5 articles

This guide surveys MetaTrader 4’s built-in indicators and explains their categories, display defaults, and configurable properties. It distinguishes oscillators, trend indicators, Bill Williams indicators, and volume measures, then describes how indicators…

Tehnilised indikaatorid
MQL5 articles

This MQL5 cookbook chapter extends an Expert Advisor so it can retrieve position details that are not available from current position properties alone. By selecting the account's deal history for a position, the program can find the first and most recent…

RiskijuhtiminePositsiooni suuruse määramineTagantjärele testimineTehingute täitmine
MQL5 articles

The article describes a two-wave continuation setup: a main move followed by a correction, with an anticipated resumption in the main trend's direction. It identifies swing points using confirmed fractals and provisional extrema, then applies structural…

ValuutaturgTrendijärgimineTehnilised indikaatoridTagantjärele testimine