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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
Alphalens
Dokumentu skaits: 14
WonderTrader
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
Dokumentu skaits: 9
QTPyLib
Dokumentu skaits: 8
Lumibot strategies
Dokumentu skaits: 7
QuantRocket
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 79,386

BigQuant

The document discusses how to estimate hedging costs for Chinese equity index futures. It argues that raw futures premiums or discounts need adjustment for time to expiry, convergence, and expected dividends. A dividend model and quadratic equation are…

Nākotnes līgumiĶīnas tirgiRiska pārvaldībaStatistika
MQL5 code base

VolatilityMA is a moving average intended to help identify trade direction. It calculates an average of a chosen price series while adapting the averaging length to changes in normalized price variability. The description says the lookback resets to its…

Tehniskie indikatoriSvārstīgumsStatistika
SuperMind

This stock selection idea combines membership in the metaverse concept group with two technical conditions: the close is above the prior day’s low, and the KDJ indicator has just produced a bullish K-over-D cross while its J value is rising. The document…

AkcijasTehniskie indikatoriCenas impulssPozīcijas apjoma noteikšana
SuperMind

This A-share stock screen combines a technical condition, a fundamental filter, and a short-term activity measure. It selects stocks with RSI below 65, parent-company net profit growth above 20% and at most 100%, and a turnover-based measure between 0.5 and…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
ProRealCode

This indicator converts closing prices into rolling standardized deviations from their recent averages, then smooths the results across three lookback horizons. The supplied periods are 180, 60, and 20 observations. Each series subtracts its lookback average…

Tehniskie indikatoriStatistikaAkcijas
vn.py community

A VeighNa Trader user reports that the platform cannot load its iFind data service module, even though the relevant Python packages are installed and can be imported. The community reply points to the global configuration: the provider name must be entered…

Nākotnes līgumi
BigQuant

This brief troubleshooting exchange addresses a KeyError in a trading strategy. The suggested first step is to inspect the value represented by the variable `s`, since the exception may arise when that value is used to look up a position that is not present…

Rīkojumu izpilde
ProRealCode

The indicator applies Cardwell’s RSI range concept to classify market regimes. It combines price relative to a 50-period simple moving average with RSI(14) membership in a bull band of 40–80 or a bear band of 20–60; otherwise the state is neutral. The…

Tehniskie indikatoriSekošana tendenceiCenas impulssRiska pārvaldība
ProRealCode

This indicator describes a pullback measure built around a short moving average of median price. It subtracts that average from the current median price, then scales the difference by average daily range to normalize the reading for recent price movement.…

Tehniskie indikatoriSekošana tendenceiSvārstīgums
MQL5 code base

The document explains how to measure Expert Advisor runtime in MetaTrader 5 while excluding delays that can distort the tester’s reported duration. It distinguishes total run time, which can include history synchronization and tick preprocessing, from net…

Vēsturisko datu pārbaudeRīkojumu izpildeStatistika
SuperMind

This stock-selection rule screens for Chinese equities with a 14-period RSI below 65, a circulating market value between 50 and 100 billion, and a current low below the previous day's low. The accompanying explanation presents RSI as a gauge of overbought or…

Ķīnas tirgiAkcijasTehniskie indikatoriStatistika
SuperMind

This Chinese stock-selection proposal combines an intraday range filter, afternoon large-order net inflows, exclusion of special-treatment stocks, and selection before 10 a.m. It then describes a five-step buying rule: add once for each 1% price rise, up to…

Ķīnas tirgiAkcijasCenas impulssSvārstīgums
BigQuant

This overview explains how deep learning models can be assembled from input, intermediate, and output layers in a visual strategy-building platform. It surveys layer families including convolution, pooling, recurrent networks, embeddings, noise and dropout,…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
MQL5 code base

This document describes a MetaTrader indicator that displays how much time remains before the current candle closes. Users can adjust its display color, size, and chart corner, and can optionally show server time. The third version adds an audible alert when…

Tehniskie indikatoriRīkojumu izpilde
SuperMind

The document describes a short-term stock selection screen for companies classified in the Chinese metaverse theme. It combines three technical conditions—MACD signal-line crossover, a short moving-average crossover, and an additional MACD-related…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
MQL5 code base

This short description presents Ultra Trend as a standalone indicator for MetaTrader 5 that can operate across supported chart timeframes. It highlights three special timeframe choices: the second higher timeframe, the third higher timeframe, and an…

Tehniskie indikatoriSekošana tendencei
SuperMind

This proposed Chinese A-share screen starts with stocks in the metaverse theme, then selects for an opening gain below 6% and a circulating share count no greater than 5.5 billion. The article’s final version adds a price-to-earnings ratio below 60. It…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
Freqtrade docs

This guide explains how to turn a trading idea into a Freqtrade strategy, from generating a template to defining indicators, entry and exit signals, stop losses, and optional position adjustments. It describes how Freqtrade represents candle data in pandas…

Vēsturisko datu pārbaudeTehniskie indikatoriRīkojumu izpildeRiska pārvaldība
SuperMind

This A-share stock screen combines three conditions: daily price amplitude above 1%, at least one limit-up event in the prior 25 days, and reported institutional buying within the past three months. The article frames the conditions as a mix of volatility,…

AkcijasCenas impulssSvārstīgumsĶīnas tirgi
SuperMind

This document describes a Chinese stock screen that ranks shares by volume ratio, retains those with a 20-day moving average above the 120-day average, and requires at least two limit-up sessions within the prior 500 days. The accompanying explanation treats…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This article explains how market orders and limit orders interact in an electronic market. Limit orders state a desired price and add available liquidity to the limit order book; market orders seek immediate execution against that liquidity and consume it.…

Tirgus mikrostruktūraRīkojumu izpildeAugstas frekvences tirdzniecība
SuperMind

This document outlines a stock-selection screen using three characteristics: position increases above five percent, upward divergence among moving averages, and a dividend ratio above twenty-five percent in 2019. Its explanation associates position increases…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This document describes a Chinese A-share stock screen combining a daily price-range threshold, a newly formed KDJ crossover, and positive large-order net volume over three consecutive days. It presents the conditions as a way to find volatile stocks with…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screen combines three short-term price conditions: amplitude above 1, a positive ten-day gain below 35, and more than two limit-up days within ten days. The document describes amplitude as a measure of price fluctuation, uses the gain…

AkcijasĶīnas tirgiCenas impulssSvārstīgums