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 studies stacking as a way to combine predictions from an ensemble of extreme learning machine classifiers. The base models produce outputs on separate training and evaluation samples; those outputs become features for a second-level combiner.…

MasinõpeStatistikaTagantjärele testimineFutuurid
MQL5 articles

This article explains how MetaTrader 5 exposes exchange order book data and how to build a reusable MQL5 class to simplify access. It describes subscribing to book-change events for selected symbols, retrieving second-level quotes, and organizing price…

FutuuridTuru mikrostruktuurTehingute täitmineKõrgsageduskauplemine
MQL5 articles

This tutorial outlines how to connect an MQL5 Expert Advisor to a Telegram bot so the terminal can send trading notifications. It describes creating a bot, retrieving its API token, obtaining a chat identifier from an update, and allowing Telegram's API…

Tehingute täitmineValuutaturgTehnilised indikaatorid
MQL5 articles

In this championship interview, Andrey Voitenko describes an Expert Advisor that trades breaks from a horizontal price channel. It calculates channel boundaries from highs and lows over five minute bars, then places pending orders at the boundaries after…

ValuutaturgLäbimurreVolatiilsusTehingute täitmine
MQL5 articles

This article explains Supported Policy Optimization (SPOT), an offline reinforcement learning method intended to reduce unreliable value estimates when a learned policy chooses actions that are poorly represented in its fixed training data. SPOT estimates…

MasinõpeStatistikaRiskijuhtimineTagantjärele testimine
MQL5 articles

The article tests how often markets qualify as trending versus flat by comparing five classification methods: ADX above a threshold, a Bollinger based trend indicator, Percentage of Trend, an RSI filter, and a ZigZag trend detector. It describes an MQL5 tool…

Tehnilised indikaatoridStatistikaTrendijärgimineMitme varaklassiga
MQL5 articles

The article presents a workflow for preparing labeled market time series and training an N-HiTS forecasting model with PyTorch Lightning and PyTorch Forecasting. It retrieves M15 price data through MetaTrader 5, converts it to a dataframe, and adds time and…

MasinõpeStatistikaFutuurid
MQL5 articles

The article explains how Renko charts represent price movement with fixed-size bricks while omitting regular time spacing. It outlines construction from a selected timeframe and box size, typically using closing prices: a new brick appears after price…

Tehnilised indikaatoridValuutaturgTrendijärgimine
MQL5 articles

The article explains ridge regression as a way to estimate linear model coefficients when predictors are correlated. It frames regularization as a bias–variance tradeoff: accepting some bias can reduce variance and overfitting. It also contrasts ridge with…

MasinõpeStatistikaValuutaturg
MQL5 articles

The article applies Gaussian Naïve Bayes to classify whether a bar closes above or below its open, using Bulls Power, Bears Power, RSI, tick volume, and Money Flow Index as features. It explains preparing a labeled matrix, splitting observations into…

MasinõpeStatistikaValuutaturgTehnilised indikaatorid
MQL5 articles

The article turns topological features of a rolling price window into chart and Expert Advisor buffers. It defines persistence entropy separately for H0 connected-component bars and H1 loop bars: entropy is low when persistence is concentrated in a few…

Tehnilised indikaatoridStatistikaMasinõpe
MQL5 articles

This installment in a logging-library series describes changes intended to make file logging more flexible and efficient. It moves formatting responsibility from a single shared formatter to each handler, allowing destinations such as a console and a file to…

Tehingute täitmineRiskijuhtimine
MQL5 articles

The article explains when MQL5 class objects are constructed and destroyed, covering global variables, local variables, and dynamically allocated objects. Global objects initialize in declaration order and are destroyed in reverse; local objects are created…

Riskijuhtimine
MQL5 articles

This article describes an infrastructure layer that lets an Expert Advisor request logical instrument names while resolving broker-specific symbol variants at runtime. Its components include a persistent mapping store, a resolver, an in-memory cache, and a…

Tehingute täitmineMitme varaklassigaStatistika
MQL5 articles

The article proposes a way to test whether price repeatedly reacts at retracement ratios between or beyond standard Fibonacci levels. It describes collecting historical OHLCV data, treating each bar’s high-low range as a candidate swing, filtering out ranges…

ValuutaturgTehnilised indikaatoridStatistikaTagantjärele testimine
MQL5 articles

This article shows how to build a MetaTrader 5 indicator that displays several timeframe charts inside a chart subwindow. Buttons let users add chart objects for selected timeframes and toggle chart properties, including settings that are unavailable through…

Mitme varaklassigaTehnilised indikaatorid
MQL5 articles

The article compares ten rule-based approaches to trading range-bound markets. Their common structure is to use an indicator channel to mark a presumed sideways range, enter when price reaches an outer boundary, and aim to exit near the opposite boundary. A…

Tehnilised indikaatoridKeskmise juurde naasmineTagantjärele testimineRiskijuhtimine
MQL5 articles

The article outlines an MQL5 mean-reversion strategy that calculates rolling price statistics, including mean, variance, skewness, kurtosis, and the Jarque-Bera statistic. It looks for price moves beyond confidence intervals, using skewness thresholds and a…

Keskmise juurde naasmineStatistikaRiskijuhtimineTagantjärele testimine
MQL5 articles

The article turns rough-volatility theory into a rolling local Hurst estimate for an XAUUSD intraday trading system. It blocks short-horizon returns into realized-variance observations, takes their logarithms, and estimates roughness from the slope of log…

VolatiilsusMasinõpeTagantjärele testimineToorained
MQL5 articles

The article considers which data sources might help a multilayer perceptron forecast the next quarter’s direction for the SPDR XLV healthcare ETF. Candidate inputs include historical OHLC changes, volatility, volume, insurance claims, pharmaceutical sales,…

AktsiadMasinõpeStatistikaUSA turud
MQL5 articles

The article explains genetic algorithms as gradient-free methods for optimizing parametric models, including neural trading models that are not differentiable or are difficult to train with gradient descent. It describes evolving a population of agents…

MasinõpeTagantjärele testimineStatistika
MQL5 articles

This article explains how a Virtual Order Manager (VOM) can preserve order-centric behavior in MetaTrader 5, where multiple trades on one symbol may be combined into a single position. It targets setups where several Expert Advisors, or a complex EA, need to…

Tehingute täitmineTuru mikrostruktuurVõrgukauplemineRiskijuhtimine
MQL5 articles

This article describes Biogeography-Based Optimization (BBO), a population-based method in which each candidate solution is modeled as a habitat and its quality as habitat suitability. Better solutions have higher emigration rates and can share selected…

MasinõpeStatistikaTagantjärele testimine
MQL5 articles

This article presents reusable MQL5 checks intended to catch invalid trading requests before they reach the broker. It covers validating and normalizing lot sizes against symbol minimums, maximums, and volume steps; checking stop-loss and take-profit…

Tehingute täitmineRiskijuhtiminePositsiooni suuruse määramine