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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
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Amberdata research
Dokumentu skaits: 766
FMZ forum
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FMZ digest
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vn.py community
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QuantInsti blog
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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
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Quantopian lekcijas
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FMZ guides
Dokumentu skaits: 38
pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
Dokumentu skaits: 32
quant-trading
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FinRL
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Zipline
Dokumentu skaits: 22
FMZ live strategies
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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: 79,386

BigQuant

The document explains turnover as the number of shares traded during a period divided by the average number of shares available to trade, expressed as a percentage. It illustrates the calculation with a quarterly example in which traded volume is twice the…

AkcijasStatistikaRīkojumu izpildeTirgus mikrostruktūra
ProRealCode

The Waddah Attar Explosion indicator combines the change in MACD with Bollinger Band width to represent directional momentum and volatility expansion. The MACD change is multiplied by a sensitivity coefficient and split into positive and negative histograms.…

Valūtu tirgusTehniskie indikatoriCenas impulssSvārstīgums
BigQuant

The document describes a China A-share index enhancement approach that adds industry rotation to a CSI 300 stock-selection portfolio. Its motivation is that the benchmark has uneven industry weights, making active industry exposure a meaningful part of…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This research summary extends a framework for selecting functional equity funds for fund-of-funds portfolios. It distinguishes sectors where active stock selection may add value from those better served by sector ETFs. For consumer and growth exposures, it…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldība
MQL5 code base

This page describes a higher-timeframe variant of the UltraAbsolutelyNoLagLwma indicator. It adds a timeframe input so the user can select the chart period from which the indicator operates; the provided default is a four-hour period. This lets a trader view…

Tehniskie indikatoriNākotnes līgumi
SuperMind

This page introduces a lesson on using correlation coefficients to identify stock candidates for pairs trading and then building a strategy to trade them. It frames correlation as a screening tool for finding potentially suitable arbitrage pairs, followed by…

AkcijasPāru tirdzniecībaArbitrāžaStatistika
SuperMind

This post presents a Chinese equity screen for main-board stocks. It selects shares with turnover between 3% and 12%, year-over-year growth in net profit attributable to parent-company shareholders above 20% and up to 100%, and a daily price gain above 1%.…

AkcijasCenas impulssFaktoru ieguldīšanaĶīnas tirgi
SuperMind

This Chinese-language post describes an equity screen using three conditions: price amplitude above 1%, a ten-day gain greater than zero but below 35%, and a positive institutional-flow measure. It explains these filters as seeking stocks with some recent…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
FMZ forum

The document outlines three broad stages in the development of commodity trading adviser strategies. It attributes early CTA success in the 1960s and 1970s to persistent commodity trends associated with economic growth, inflation, and oil-market shocks.…

Nākotnes līgumiIzejvielasSekošana tendenceiAtgriešanās pie vidējās vērtības
FMZ forum

This brief trading-platform example shows how to use an IO function to submit a BitMEX post-only limit order, submit several such orders together through the bulk endpoint, and cancel all orders for a specified symbol. The examples use XBTUSD and set an…

KriptoaktīviRīkojumu izpildeTirgus mikrostruktūra
SuperMind

This note proposes a short-term stock screen based on daily amplitude above 1, a condition described as main-force control on the prior day, and a 9:25 a.m. gain below 6%. It interprets the range as a sign of active price movement, the control measure as an…

AkcijasSvārstīgumsTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese-language strategy note describes a stock screen combining RSI below 65, the product of price change and large-order net inflow, and bullish crossovers in three indicators, with MACD, KDJ, and DMA as examples. Its sample implementation also…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This document presents a Chinese equity screening rule that selects stocks with daily turnover between 3% and 12%, parent-company net profit growth between greater than 20% and up to 100%, and tradable shares capped at 5.5 billion. It describes the…

AkcijasFaktoru ieguldīšanaĶīnas tirgiStatistika
ProRealCode

ASCTrend is a chart indicator that uses Williams Percent Range to generate buy and sell arrows. Its RISK setting controls the indicator period and shifts the thresholds used to identify signals. A signal is produced when the indicator moves from an…

Tehniskie indikatoriNākotnes līgumiValūtu tirgus
Zipline

This documentation explains how Zipline organizes risk and performance measurements for algorithm simulations. A metrics set defines which values a backtest tracks, and its metrics can report at different frequencies. The default set includes examples such…

Vēsturisko datu pārbaudeRiska pārvaldībaStatistika
Amberdata research

The document describes two risks institutions may encounter in decentralized finance: scam tokens, especially liquidity-draining rug pulls, and crypto assets connected to illicit activity. It argues that blockchain data can support token due diligence by…

KriptoaktīviDeFiBlokķēdes datiRiska pārvaldība
SuperMind

This Chinese stock-screening note combines daily price movement, a morning-star style candlestick condition, and a ranking based on large-order net volume. Its example code also checks recent moving averages and requires the latest large-order net amount to…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus mikrostruktūra
MQL5 code base

This indicator note explains a short-term trading idea based on alternating periods of small and large price ranges. Range is treated as the distance traveled over a chosen interval, and a narrow range is described as a possible warning that a wider move may…

Tehniskie indikatoriSvārstīgumsCenas impulssRiska pārvaldība
SuperMind

This stock-selection method filters for shares with turnover between 3% and 12%, a rising K value in the KDJ indicator, and a 2019 dividend measure above a stated threshold. The note presents the combination as a way to pair trading activity and improving…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-screening note combines three filters: membership in the metaverse theme, positive net buying by major participants during the opening auction, and a three-session limit-up streak ending the previous day. It presents the screen as a way to…

Ķīnas tirgiAkcijasCenas impulssCenas izrāviens
MQL5 code base

V1N1 LONNY is described as a multi-symbol intraday Expert Advisor that trades breakouts during the London session. It treats the pre-London Asian range as a no-trade zone, placing buy stops above the range high and sell stops below its low. Entries use the…

Valūtu tirgusCenas izrāviensTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese-market stock screen combines a metaverse industry filter with Shenzhen main-board eligibility, valuation bounds, and a recent KDJ bullish crossover. It selects stocks with price-to-earnings ratios from 0 to 29.01 and price-to-book ratios from 0…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
MQL5 code base

Adaptive Volatility Analysis (AVA) is an indicator intended to measure whether market volatility is increasing or easing. It compares a short-period exponential moving average of ATR with a longer-period exponential moving average, producing a relative…

SvārstīgumsTehniskie indikatoriStatistika