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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
QuantRocket
Dokumentu skaits: 7
Lumibot strategies
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 79,386

BigQuant

This study considers whether a company’s decision to capitalize research and development spending conveys information about future project profitability. Because accounting rules allow judgment in deciding whether development costs should be capitalized, the…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaFaktoru ieguldīšana
BigQuant

This study turns unusual intraday stock behavior into a measurable event signal. It describes days when a stock repeatedly moves against the direction of the broader index, then uses correlation to screen for these cases. The resulting event samples are…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaStatistika
BigQuant

This study examines whether managers of equity-focused and mixed equity funds can anticipate shifts between market styles defined by company size, and whether any apparent skill persists. It identifies funds that ranked near the top around past style…

AkcijasĶīnas tirgiStatistikaFaktoru ieguldīšana
SuperMind

The post outlines a rules-based stock screen using three filters: price amplitude above 1, circulating market capitalization above 10 billion yuan, and a volume-ratio range above 1.5 but below 6. It presents the combination as a way to select stocks with…

AkcijasTehniskie indikatoriĶīnas tirgiStatistika
Amberdata research

The newsletter assesses a sharp rise in Bitcoin volatility alongside macroeconomic catalysts and crypto market positioning. It uses options implied volatility and term-structure richness as indicators of stress, noting that a high backwardation reading has…

KriptoaktīviOpcijasSvārstīgumsNākotnes līgumi
vn.py community

This release overview describes VeighNa 4.0 and its new vnpy.alpha module for developing machine-learning, multi-factor strategies. The module is organized around feature datasets, model training, strategy research, workflow management, and example…

MašīnmācīšanāsFaktoru ieguldīšanaAkcijasVēsturisko datu pārbaude
BigQuant

The document presents a SQL approach to estimating annualized variance for Chinese stocks. It first calculates daily close-to-close returns for each instrument, then applies a rolling 20-observation standard deviation, squares that value, and multiplies by…

AkcijasStatistikaSvārstīgums
BigQuant

The article describes a framework that links macroeconomic and style factors with traditional asset-class allocation. It proceeds from selecting factors and estimating asset exposures to building factor-mimicking portfolios, forecasting their returns,…

Vairāku aktīvu tirdzniecībaFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
SuperMind

This stock screen selects shares with a daily range above a stated threshold, at least two limit-up moves during the preceding 500 days, and a current low below the previous day’s low. The article interprets the range and historical limit-up conditions as…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
MQL5 code base

The PDFma indicator is described as a weighted average or digital filter whose coefficients are derived from a probability density function. It offers floating levels, quantile levels, or no levels, with the last option enabling a slope-based mode. Color…

Tehniskie indikatoriStatistika
MQL5 code base

This Expert Advisor runs separate long and short systems using signals from the ColorMaRsi-Trigger indicator. Each side has its own magic number, position sizing settings, and switches for enabling entries and exits, allowing its parameters to be configured…

Valūtu tirgusTehniskie indikatoriPozīcijas apjoma noteikšanaVēsturisko datu pārbaude
MQL5 code base

The document describes a multi-timeframe version of the ChannelsFIBO_v2 indicator. Its distinguishing setting is a source-data timeframe parameter: the indicator can display the situation associated with a chosen chart period even when the user’s active…

Tehniskie indikatoriVairāku aktīvu tirdzniecība
SuperMind

The document presents a Chinese-market equity screen for stocks classified in the metaverse industry. It requires a bullish MACD crossover, a 5-day moving average crossing above both the 10-day and 20-day averages, and at least one daily gain of 10% or more…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
MQL5 code base

The document outlines an extended Wilder double-smoothed exponential moving average that adapts its responsiveness using a volatility ratio. According to the description, the adaptation is intended to make the indicator react more quickly to market changes…

Tehniskie indikatoriSvārstīgumsSekošana tendencei
SuperMind

The document describes a Chinese-market stock screen combining three conditions: rank stocks by volume ratio and retain the top 100, require the opening price to be near the 10-day moving average, and require the close to be above the 30-day average. It…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This note describes a Chinese stock screen requiring an RSI below 65, greater displayed buy-side than sell-side volume at the best quote, and an issuance year of 2021. It presents RSI as a price-momentum measure and the order-book comparison as a gauge of…

AkcijasTehniskie indikatoriTirgus mikrostruktūraĶīnas tirgi
SuperMind

This note proposes a Chinese stock screen using three conditions: daily amplitude above 1%, a weekly five-period moving average crossing above the ten-period average, and free-float shares no greater than 5.5 billion. It frames amplitude as a measure of…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This note describes a Chinese A-share screen that selects stocks with turnover between 3% and 12%, excludes Beijing-listed shares, and requires MACD to have been below zero two days earlier. It presents the filters as a way to combine trading activity with a…

AkcijasTehniskie indikatoriĶīnas tirgi
MQL5 code base

This MetaTrader 5 Expert Advisor trades reversals in the direction of the FatlMacd indicator. It forms a signal at bar close when the indicator changes direction. Running the advisor requires the compiled FatlMacd indicator file in the platform's Indicators…

Valūtu tirgusTehniskie indikatoriVēsturisko datu pārbaude
vn.py community

A forum user asks how to check whether enough funds are available before starting a spread-arbitrage order algorithm. The stated motivation is to avoid opening only one leg of a paired trade when the account cannot support both sides. A reply points to…

ArbitrāžaPāru tirdzniecībaRiska pārvaldība
MQL5 code base

The document describes an indicator that plots relative strength or correlation across eight currencies and gold. Users choose one of several technical measures as the basis for the calculation: moving average, MACD, stochastic oscillator, RSI, CCI, Relative…

Valūtu tirgusIzejvielasTehniskie indikatori
MQL5 code base

This document explains an MT5 indicator for placing an alert at a chosen price directly on a chart. A trader selects an alert type and time zone, then clicks the chart to set the price threshold. The alert can appear in a window, arrive as a mobile push…

Tehniskie indikatoriRīkojumu izpilde
MQL5 code base

This Expert Advisor variant adds a configurable weekly trading window to an EA based on a Spearman rank correlation histogram. Inputs set whether interval-based trading is enabled and define the start and end by weekday, hour, minute, and second. The example…

Tehniskie indikatoriStatistikaVēsturisko datu pārbaudeRiska pārvaldība
MQL5 code base

LaguerreVolume applies a Laguerre filter to smooth volume data. The document identifies the indicator’s creators as Emerald King and t_david and notes that it was first implemented in MQL4 and published in 2007. The description offers no equations, parameter…

Tehniskie indikatoriStatistika