Pāriet uz saturu

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

This introductory article explains object-oriented programming in Python and contrasts it with procedural and functional styles. It presents classes as templates and objects as individual instances, using cars and stocks as examples. It also introduces…

Vēsturisko datu pārbaude
QuantInsti blog

This project develops a market-neutral mean-reversion strategy for pairs drawn from 25 large-cap NSE stocks across several sectors. It estimates hedge ratios with ordinary least squares, tests spread residuals for stationarity using a lag-zero ADF procedure,…

AkcijasPāru tirdzniecībaAtgriešanās pie vidējās vērtībasStatistika
QuantInsti blog

This project tests whether a Random Forest classifier using six technical indicators can generate useful long-only signals for ten South African Top40 stocks. The indicators cover trend, oscillation, volatility, and volume. The study trains separate models…

AkcijasTehniskie indikatoriMašīnmācīšanāsVēsturisko datu pārbaude
QuantInsti blog

A bear trap is a brief selloff that appears to signal a reversal but is followed by recovery and continuation of an existing uptrend. The article describes how bearish traders may mistake a pullback or liquidation-driven move for a lasting breakdown, then…

Valūtu tirgusSekošana tendenceiRiska pārvaldībaTehniskie indikatori
QuantInsti blog

The article recounts a portfolio project that selects 22 stocks from 11 sectors of the S&P 500. It assigns weights using each asset’s standard deviation and rebalances quarterly: riskier stocks receive less exposure, while less volatile stocks receive more.…

AkcijasPortfeļa veidošanaRiska pārvaldībaPozīcijas apjoma noteikšana
QuantInsti blog

This profile describes a student project that builds a diversified portfolio from 22 S&P 500 stocks across 11 sectors. The allocation is rebalanced quarterly using each stock’s standard deviation: higher-volatility stocks receive smaller weights, while…

AkcijasPortfeļa veidošanaRiska pārvaldībaPozīcijas apjoma noteikšana
QuantInsti blog

The article compares trading with professional gambling to draw lessons about preparation and decision-making. It advises traders to understand the instruments they trade, how they are priced, relevant charts and indicators, and their own strategy before…

Riska pārvaldībaVēsturisko datu pārbaudeTehniskie indikatoriStatistika
QuantInsti blog

The document introduces a Bayesian time-varying parameter vector autoregression with stochastic volatility (TVP-VAR-SV). Unlike a standard VAR with fixed coefficients and constant error variance, this model allows lag relationships, contemporaneous…

StatistikaSvārstīgumsVēsturisko datu pārbaude
QuantInsti blog

The document explains harmonic trading as a method that combines geometric price swings with Fibonacci ratios to identify potential reversal zones. It describes the Gartley, Butterfly, Bat, and Crab patterns, outlining the retracement and extension…

Valūtu tirgusTehniskie indikatoriRiska pārvaldība
QuantInsti blog

The document presents statistical arbitrage as a family of systematic strategies that seek to trade relative mispricing, often using mean reversion in historically related instruments. It describes pairs trading as one approach: identify assets whose prices…

StatistikaAtgriešanās pie vidējās vērtībasPāru tirdzniecībaArbitrāža
QuantInsti blog

The article introduces quantitative and algorithmic trading as the combination of programming with market knowledge, statistics, finance, mathematics, and other disciplines. It traces a broad shift from physical trading to screen-based exchanges and…

Augstas frekvences tirdzniecībaStatistikaTirgus mikrostruktūraRīkojumu izpilde
QuantInsti blog

The document explains how crypto arbitrage seeks to capture price or lending-rate differences across exchanges. It describes why gaps can arise, including capital controls, uneven liquidity and reaction speeds, volatility, and differences in transaction…

KriptoaktīviArbitrāžaRīkojumu izpildeTirgus mikrostruktūra
QuantInsti blog

The article presents stationarity as a key condition for many time-series models: a stationary series has stable statistical properties, while trends, seasonality, or changing variance can make a series non-stationary. It distinguishes strict, first-order,…

StatistikaAkcijasTehniskie indikatori
QuantInsti blog

The article explains stationarity as stability in a time series’ statistical behavior over time, distinguishing strict, first-order, weak, trend, and difference stationarity. It describes why the assumption matters: many forecasting procedures rely on past…

StatistikaAkcijasVēsturisko datu pārbaude
QuantInsti blog

The article surveys data sources that can supplement price and volume analysis. It covers company ratios and financial statements, macroeconomic indicators, earnings dates, financial news, tweets, and sentiment scores. It names services and Python libraries…

Tirgus noskaņojumsAkcijasStatistika
QuantInsti blog

The article explains direct market access (DMA) as a broker-provided route for submitting orders to exchange order books, with checks such as margin review before execution. It contrasts this with retail arrangements where a broker may intermediate orders or…

Rīkojumu izpildeTirgus mikrostruktūraValūtu tirgusAugstas frekvences tirdzniecība
QuantInsti blog

The article introduces mixture models as a possible framework for forecasting asset returns when their statistical behavior changes over time. It notes that returns can exhibit changing means and volatility, nonlinear patterns, volatility clustering,…

StatistikaMašīnmācīšanāsSvārstīgumsVēsturisko datu pārbaude
QuantInsti blog

The document explains walk-forward optimization (WFO) as a rolling backtest procedure intended to address weaknesses in a single static optimization and validation split. In each cycle, strategy parameters are fitted using a historical in-sample window, then…

Vēsturisko datu pārbaudeStatistikaMašīnmācīšanāsRiska pārvaldība
QuantInsti blog

The document outlines a basic workflow for algorithmic Bitcoin trading: generate entry and exit signals from a strategy, allocate capital according to risk rules, then send orders to an exchange through its API. It describes Bitcoin as a decentralized…

KriptoaktīviArbitrāžaTirgus veidošanaTehniskie indikatori
QuantInsti blog

The document introduces swing trading as holding positions for days to weeks to capture price moves between local highs and lows. It contrasts this horizon with day trading, describes swings as occurring within broader price trends, and favors…

AkcijasSekošana tendenceiTehniskie indikatoriRiska pārvaldība
QuantInsti blog

This lecture description introduces advanced options portfolio management through the use of first-, second-, and third-order Greeks. It notes that risk can be managed by examining how portfolio exposures respond to underlying factors, including how…

OpcijasRiska pārvaldībaSvārstīgumsAtvasināto instrumentu cenu noteikšana
QuantInsti blog

This FAQ addresses practical questions about algorithmic trading, including latency, frequency categories, competition with manual traders, market efficiency, coding chart patterns, automation, and retail access. It frames latency as the time required for…

Rīkojumu izpildeTirgus mikrostruktūraAugstas frekvences tirdzniecībaTehniskie indikatori
QuantInsti blog

This tutorial explains how an ARIMA model represents a univariate time series through autoregressive terms, differencing, and lagged forecast errors. Its proposed workflow tests price-series stationarity with sequential Augmented Dickey-Fuller tests, uses…

AkcijasStatistikaVēsturisko datu pārbaudeSvārstīgums
QuantInsti blog

This analysis uses daily Nifty 50 futures data from exchange files to examine price, trading volume, open interest, rollover percentages, and foreign and domestic institutional activity during the first quarter of 2020. It explains how to interpret price…

Nākotnes līgumiAkcijasCenas impulssTehniskie indikatori