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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
Quantpedia
Dokumentu skaits: 86
TqSdk
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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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
Alphalens
Dokumentu skaits: 14
WonderTrader
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 outlines a session on managing option portfolios that span multiple instruments. Its stated focus is on Delta and Gamma, including how market characteristics affect their behavior, and on making several higher-order Greeks easier to understand:…

OpcijasAtvasināto instrumentu cenu noteikšanaSvārstīgums
QuantInsti blog

This interview follows Derek’s path from futures trading and professional card games into quantitative trading and the creation of Golden Compass with collaborator Maxime. Their partnership developed through continued remote research, a shared derivatives…

Nākotnes līgumiOpcijasTirgus mikrostruktūra
QuantInsti blog

This first-person account describes experiments with a volatility-triggered scalping strategy and a moving-average momentum strategy. The initial scalping rule used Average True Range to set a trading threshold and compared recent price action, but its…

Vēsturisko datu pārbaudeCenas impulssSekošana tendenceiPortfeļa veidošana
QuantInsti blog

The article introduces logistic regression as a supervised learning method for estimating the probability of a categorical outcome. For trading, it presents a binary classification setup: predict whether a stock will rise or fall using historical inputs such…

MašīnmācīšanāsStatistikaTehniskie indikatoriAkcijas
QuantInsti blog

The document explains leverage as the use of borrowed capital to increase investment exposure, with the aim of earning more than the financing cost. Hedge funds may use it to hold long and short positions larger than their capital base. The article frames…

Riska pārvaldībaPozīcijas apjoma noteikšanaAkcijas
QuantInsti blog

The article compares programming languages used in algorithmic trading and frames language choice as dependent on the task. It characterizes Python as a readable, open-source option for research, strategy development, and backtesting, with libraries that…

Vēsturisko datu pārbaudeRīkojumu izpildeAugstas frekvences tirdzniecībaStatistika
QuantInsti blog

The guide explains how to estimate return variance for a single asset, covariance between asset returns, and total variance for a portfolio. It begins with historical returns, using their average as an expected-return estimate and variance or standard…

Portfeļa veidošanaRiska pārvaldībaStatistikaAkcijas
QuantInsti blog

The article surveys five skills it presents as useful for modern trading: quantitative analysis, Python, backtesting, machine learning, and risk management. It links quantitative research to statistical testing of market data and technical signals, and…

Vēsturisko datu pārbaudeMašīnmācīšanāsRiska pārvaldībaStatistika
QuantInsti blog

The project builds a long-only daily strategy across nine SPDR sector ETFs using short- and long-term exponential moving average crossovers. It reallocates capital quarterly based on each ETF’s relative quarterly return, aiming to direct more capital toward…

AkcijasSekošana tendenceiVēsturisko datu pārbaudePortfeļa veidošana
QuantInsti blog

The document defines the Arms Index, or TRIN, as the ratio of advancing stocks to declining stocks divided by advancing volume to declining volume. It interprets readings below 1 as generally bullish and readings above 1 as generally bearish, while unusually…

AkcijasTehniskie indikatoriTirgus noskaņojumsAtgriešanās pie vidējās vērtības
QuantInsti blog

The document explains the role of a securities master: a shared system for collecting, storing, cleaning, validating, and distributing instrument, pricing, fundamental, and transaction data. It describes a range of instruments and downstream uses including…

StatistikaRiska pārvaldībaRīkojumu izpildeTirgus mikrostruktūra
QuantInsti blog

The document introduces price action trading as analysis of raw price movements and chart patterns, with limited reliance on indicators. It surveys support and resistance, trend following, candlestick setups, breakouts, range trading, and analysis across…

Tehniskie indikatoriCenas izrāviensSekošana tendenceiRiska pārvaldība
QuantInsti blog

This article explains how exchange-traded funds pool securities into units traded on exchanges, then surveys market, sector, dividend, style, commodity, currency, and bond ETFs. It describes their potential uses, including broad diversification, targeted…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaRiska pārvaldība
QuantInsti blog

This article contrasts algorithmic trading, where coded rules generate and execute orders, with discretionary trading, where a person interprets market information and decides when to trade. It illustrates rule-based execution with a moving-average example…

Rīkojumu izpildeStatistikaRiska pārvaldība
QuantInsti blog

This guide collects free educational materials for learning machine learning and applying it to trading. It groups courses, books, blogs, research papers, and videos, ranging from introductory machine learning and Python tools to interpretable models, neural…

MašīnmācīšanāsVēsturisko datu pārbaudeStatistika
QuantInsti blog

This project outlines a process for predicting trade exits with machine learning. It samples market data into dollar bars, estimates volatility from each bar’s high and low using Parkinson’s method, and generates initial buy or sell signals from a…

MašīnmācīšanāsVēsturisko datu pārbaudeTehniskie indikatoriRiska pārvaldība
QuantInsti blog

The article introduces blockchain as a distributed ledger for recording transactions across networked computers. It explains how blocks hold records and the previous block’s hash, linking the history so that changes become detectable. Copies of the ledger…

KriptoaktīviDeFiTirgus mikrostruktūra
QuantInsti blog

This interview describes how options trader Vishnu Bharath moved from an engineering and telecommunications background into quantitative trading by combining market familiarity with programming skills. His initial interest in markets came through discussions…

OpcijasVēsturisko datu pārbaude
QuantInsti blog

This article introduces technical indicators as mathematical transformations of price, volume, or related market data, and distinguishes technical analysis from fundamental valuation. It groups indicators into trend, momentum, volume, and volatility…

Tehniskie indikatoriCenas impulssSekošana tendenceiVēsturisko datu pārbaude
QuantInsti blog

This overview summarizes a SEBI discussion paper on algorithmic trading and co-location in Indian markets. It reports that algorithms generate a large share of exchange orders and a substantial portion of trades, and reviews research findings that…

Augstas frekvences tirdzniecībaTirgus mikrostruktūraRīkojumu izpilde
QuantInsti blog

This project outlines an intraday strategy for trading the spread between a security’s spot price and its futures price. It classifies futures trading above spot as contango and below spot as backwardation, then calculates the spread from one-minute prices.…

ArbitrāžaNākotnes līgumiTūlītējo darījumu tirgiTehniskie indikatori
QuantInsti blog

This article presents a basic text sentiment workflow for financial commentary using R. It applies a bag-of-words approach: prepare positive and negative term lists, clean an earnings-call transcript, tokenize it into words and n-grams, and compare the…

Tirgus noskaņojumsMašīnmācīšanāsAkcijasStatistika
QuantInsti blog

This guide lays out a sequence for building an algorithmic strategy: define the trading idea and market, specify instrument filters, check the logic visually, backtest, tune parameters, forward test in simulation, and deploy. Its running example is a daily…

Vēsturisko datu pārbaudeAtgriešanās pie vidējās vērtībasTehniskie indikatoriAkcijas
QuantInsti blog

This project describes a dispersion strategy using Bank Nifty options and options on its constituent bank stocks. It compares implied volatility across the index and its components, using implied correlation as a signal: high correlation points toward…

OpcijasSvārstīgumsAtgriešanās pie vidējās vērtībasRiska pārvaldība