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Zināšanu bibliotēka

Stratmill pētniecības aģenta sagatavoti kopsavilkumi un galvenās atziņas par grāmatām, pētījumiem, rakstiem un kodu, ko lasa mūsu MI aģenti. Katrā lapā ir saite uz oriģinālu.

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

Meklēt bibliotēkā

Dokumentu skaits: 511

QuantInsti blog

The document describes a stock-screening process that looks for shares rising beyond a chosen percentage threshold during intraday trading, with the aim of identifying candidates for short positions. A first stage compares the current price with the prior…

AkcijasAtgriešanās pie vidējās vērtībasTehniskie indikatoriRiska pārvaldība
QuantInsti blog

This article uses a series of trading examples to show how implementation choices can make backtests look stronger or weaker than a live strategy. It highlights omitted transaction costs and slippage, incorrect treatment of reinvestment and whole-unit…

Vēsturisko datu pārbaudeRiska pārvaldībaMašīnmācīšanāsRīkojumu izpilde
QuantInsti blog

The document introduces XGBoost as a gradient boosting method that combines decision trees sequentially, with each new tree aimed at correcting earlier prediction errors. Its objective balances predictive loss against a regularization term that discourages…

MašīnmācīšanāsAkcijasTehniskie indikatoriVēsturisko datu pārbaude
QuantInsti blog

The article explains dark pools as private securities trading venues, often used by institutions seeking to execute large orders with less exposure of their intentions. It describes execution linked to the National Best Bid and Offer, outlines independent,…

AkcijasRīkojumu izpildeTirgus mikrostruktūraAugstas frekvences tirdzniecība
QuantInsti blog

The article outlines the mathematical, statistical, and programming foundations associated with quantitative finance, then describes common quant work: trading strategy development, portfolio optimization, risk management, and asset pricing. It recommends…

MašīnmācīšanāsTehniskie indikatoriRiska pārvaldībaPortfeļa veidošana
QuantInsti blog

The article classifies market events as black swans (unexpected), grey swans (possible but unlikely), or white swans (expected), then considers how they may affect stocks, bonds, and derivatives. It suggests that strategies should reflect how much warning…

Uz notikumiem balstīta tirdzniecībaRiska pārvaldībaSvārstīgumsVairāku aktīvu tirdzniecība
QuantInsti blog

Survivorship bias arises when analysis includes only assets or funds that remain observable, omitting those that failed, delisted, or closed. The document explains the issue with the military aircraft example: examining only planes that returned can…

Vēsturisko datu pārbaudeAkcijasPortfeļa veidošanaStatistika
QuantInsti blog

The document introduces K-nearest neighbors (KNN), a supervised learning method that classifies or estimates a new observation using nearby examples selected by a distance metric. For classification, neighboring labels determine the predicted class by…

MašīnmācīšanāsAkcijasVēsturisko datu pārbaudeStatistika
QuantInsti blog

Market impact is an implicit trading cost measured by the difference between the pre-trade reference price and the execution price. The document separates temporary impact, which reflects the concession needed to find counterparties, from permanent impact,…

Rīkojumu izpildeTirgus mikrostruktūraMašīnmācīšanāsRiska pārvaldība
QuantInsti blog

This beginner overview explains algorithmic trading as rules that use market inputs such as price, time, and volume to generate orders. It outlines a basic architecture with a market-data handler, a strategy module, and an order router, describing how data…

Rīkojumu izpildeVēsturisko datu pārbaudeAugstas frekvences tirdzniecībaStatistika
QuantInsti blog

This personal account describes an algorithmic trader’s move from strategies written in Rust without machine learning to Python-based work that combines machine learning with trading-system development. The central lesson is that predictive-model metrics…

MašīnmācīšanāsVēsturisko datu pārbaudeStatistika
QuantInsti blog

The article explains K-means clustering as an unsupervised method for grouping stocks with similar feature values, then applies it to candidate selection for statistical arbitrage. It contrasts clustering with manually choosing pairs by sector or industry,…

AkcijasPāru tirdzniecībaMašīnmācīšanāsStatistika
QuantInsti blog

This project backtests equal-weight stock portfolios selected using alpha, prior-year returns, volatility, beta, and return divided by volatility. It varies portfolio size, stock universe, and annual, semiannual, or quarterly rebalancing, while describing…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
QuantInsti blog

This guide explains VADER, a rule-based text sentiment tool that assigns word-level valence and combines it into a normalized compound score. It describes how the lexicon incorporates words, slang, and emoticons, and how sentence-level heuristics account for…

Tirgus noskaņojumsAkcijasTehniskie indikatoriVēsturisko datu pārbaude
QuantInsti blog

This beginner tutorial explains how Python variables are created by assignment, updated, and assigned together. It outlines naming rules and readability conventions, then introduces integers, floating-point numbers, strings, and booleans. Examples use values…

Statistika
QuantInsti blog

This project outlines a market-neutral long-short portfolio framework that selects assets with cross-sectional momentum and compares equal weighting, inverse-volatility weighting, Hierarchical Risk Parity (HRP), and Hierarchical Equal Risk Contribution…

Vairāku aktīvu tirdzniecībaCenas impulssPortfeļa veidošanaMašīnmācīšanās
QuantInsti blog

The article explains how standard GARCH models capture volatility clustering while treating positive and negative return shocks symmetrically. GJR-GARCH adds a term activated by negative shocks, allowing downside moves to have an additional effect on…

AkcijasSvārstīgumsStatistikaRiska pārvaldība
QuantInsti blog

The article describes directional change (DC), a threshold-based way to represent price movement through confirmed turning points rather than fixed-time observations. It defines upward and downward runs, their overshoots, and three derived measures: total…

Valūtu tirgusTehniskie indikatoriMašīnmācīšanāsSvārstīgums
QuantInsti blog

The article introduces hidden Markov models as a way to infer unobserved states from observed data. It explains the Markov property, transition probabilities, and time-homogeneous chains, then relates hidden-state estimation to the Kalman filter’s prediction…

StatistikaMašīnmācīšanāsSvārstīgums
QuantInsti blog

This article describes market sentiment as the collective outlook of participants and explains how text sentiment analysis attempts to classify opinions as positive, negative, or neutral. It outlines a workflow of collecting news, social media, or financial…

Tirgus noskaņojumsMašīnmācīšanāsStatistikaRiska pārvaldība
QuantInsti blog

This beginner guide explains that cryptocurrency wallets manage the keys used to access and transact with crypto assets. It distinguishes a public address, which can be shared to receive funds, from a private key, which must remain protected. The article…

KriptoaktīviRiska pārvaldībaTūlītējo darījumu tirgi
QuantInsti blog

This interview traces a trader’s progression from executing commodity orders to coding trading systems and researching algorithmic strategies. The subject describes developing trend detection and momentum systems with position sizing, then building a…

IzejvielasSekošana tendenceiCenas impulssOpcijas
QuantInsti blog

The document introduces portfolio management when the portfolio’s components are trading strategies as well as assets. It contrasts equal weighting as a starting point with Markowitz efficient-frontier allocation, which balances return against a risk…

Portfeļa veidošanaRiska pārvaldībaVēsturisko datu pārbaudePozīcijas apjoma noteikšana
QuantInsti blog

In this interview, trader Nikolas Pareschi recounts his move from discretionary trading to algorithmic research and describes how he developed ideas through finance papers and statistical testing. He emphasizes that many indicators and methods fail…

Valūtu tirgusVairāku aktīvu tirdzniecībaCenas impulssAtgriešanās pie vidējās vērtības