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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

SuperMind

This stock selection rule screens for companies with market value below 10 billion yuan, positive profit history, turnover between 3% and 12%, and a 14-period RSI below 65. It combines a size filter and profitability condition with activity and…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
FMZ forum

This overview compares execution strategies that split orders over time or respond to market conditions. TWAP distributes an order evenly across intervals, making it simple to use when intraday volume is hard to estimate, though large slices can still move…

Rīkojumu izpildeTirgus mikrostruktūraRiska pārvaldība
SuperMind

This post proposes a technical stock screen combining price amplitude above a threshold, progressively rising lows, and a volume ratio between stated bounds. It describes the rising floor as a sign of improving price structure and uses relative volume to…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
Hummingbot docs

These release notes describe changes to Hummingbot’s client, Gateway, and related tools. Client updates include a headless command-line interface, new spot exchange connectors, connector fixes, and improvements to liquidity provision executors. The LP…

KriptoaktīviRīkojumu izpildeTirgus mikrostruktūraRiska pārvaldība
MQL5 code base

This indicator description presents a Keltner Channel whose center line can use a chosen price input and smoothing method. The upper and lower channel boundaries are based on the Average True Range (ATR), with a configurable multiplier controlling the…

Tehniskie indikatoriSvārstīgums
SuperMind

This community exchange explains how to use data downloaded with Supermind’s data ingestion command. A reply says the downloaded data can be accessed through the platform’s get_price function, without specifying the on-disk file format or a separate…

Vēsturisko datu pārbaude
ProRealCode

This post adapts the DeMarker oscillator into an on-chart display of possible reversal points. The indicator compares averaged upward high changes with averaged downward low changes and scales the result to a range from zero to one hundred. In the chart…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasNākotnes līgumi
SuperMind

This Chinese-language post outlines an A-share stock screen combining daily price range, relative trading volume, and recent return. It selects stocks with a daily high–low range of at least one percent, volume between 1.5 and 6 times its five-day average,…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
MQL5 code base

This document describes an Expert Advisor built around the CCFp, or Complex Common Frames percent, cluster indicator. It identifies the indicator as the basis for the automated system and lists controls for trade volume, stop loss, take profit, trailing…

Valūtu tirgusTehniskie indikatoriRīkojumu izpildeRiska pārvaldība
MQL5 code base

This note describes a histogram version of an adaptive moving average based on Perry Kaufman’s KAMA and an update by Vitali Apirine. The update accounts for where the close sits within the high–low range when adapting the average. The indicator combines the…

Tehniskie indikatoriSekošana tendenceiVēsturisko datu pārbaude
SuperMind

The document outlines an equity screen that selects stocks with turnover between 3% and 12%, a rising KDJ K line, and MACD above its zero line. It describes the rising KDJ reading and positive MACD as indicators of upward price momentum, and provides both a…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
MQL5 code base

The document describes a price-chart moving average using JSmooth smoothing, an approach attributed to Mark Jurik. It identifies two user inputs: the lookback period and the price series used in the calculation. The formula updates a sequence of intermediate…

Tehniskie indikatori
FMZ forum

The document explains grid trading as repeated buying during declines and selling during advances, with portfolio rebalancing used to harvest price fluctuations. Its central example, attributed to Shannon’s Demon, splits capital equally between shares and…

Režģa tirdzniecībaPozīcijas apjoma noteikšanaStatistikaRiska pārvaldība
SuperMind

This Chinese equity screen first restricts the universe to metaverse-related companies that are not marked ST and have circulating share capital at or below 5.5 billion shares. It then applies a so-called five-level limit-up method, with selection intended…

Ķīnas tirgiAkcijasCenas impulssCenas izrāviens
SuperMind

This stock-selection idea combines three filters: price amplitude above one percent, appearance on the prior day's notable-trading list with reported buying exceeding selling, and turnover between three and twelve percent. The article presents the filters as…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus mikrostruktūra
BigQuant

This article describes a market-level risk control for an equity strategy. It calculates the five-day cumulative return of the Shanghai Composite Index and uses that reading as a benchmark risk signal. If the index return falls below negative four percent,…

Ķīnas tirgiAkcijasRiska pārvaldība
Freqtrade

GodStra is a Freqtrade long strategy that builds a broad set of technical indicators and evaluates configurable entry and exit rules. Each rule compares a selected indicator with another indicator or a numeric threshold; supported operators include…

Tehniskie indikatoriVēsturisko datu pārbaudeRiska pārvaldība
Amberdata research

This podcast recap explains how real-world assets can be represented on blockchains, with examples including real estate, commodities, stablecoins, and Treasury-backed products. It presents tokenization as a way to broaden access, improve transferability,…

KriptoaktīviDeFiBlokķēdes datiFiksēta ienākuma instrumenti
SuperMind

The document proposes screening Chinese stocks for amplitude above 1%, an aligned set of three moving averages, and a 2021-to-2018 revenue ratio above 1.1. It presents the moving-average condition as a technical signal and the revenue comparison as a basic…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The document describes a Chinese A-share stock screen that excludes Beijing-listed shares, requires daily high-low amplitude above 1%, and selects stocks with at least one daily gain of 10% or more in the previous 25 trading days. It outlines the rationale…

AkcijasĶīnas tirgiCenas impulssSvārstīgums
SuperMind

The post describes a simple equity-universe filter: identify stocks associated with the metaverse theme, require a circulating market value above 10 billion yuan, and retain codes beginning with 60. It presents these conditions as a way to narrow the…

AkcijasĶīnas tirgiFaktoru ieguldīšana
SuperMind

This stock screen combines three technical conditions: daily price amplitude of at least one percent, turnover above two percent and no greater than nine percent, and a pattern of rising lows. The accompanying explanation interprets the combination as…

AkcijasTehniskie indikatoriSvārstīgumsRiska pārvaldība
BigQuant

The post asks how to add an industry-strength ranking to a short-term stock momentum selection process. The proposed workflow first selects five stocks using a momentum strategy, then ranks them by the speed of gains in their primary or secondary industry,…

AkcijasCenas impulssFaktoru ieguldīšana
Amberdata research

The commentary considers how trade war headlines and scheduled US economic releases could affect crypto prices and options volatility. Its base case is that Bitcoin remains in a broad consolidation range, with a possible test of the lower boundary and a…

KriptoaktīviOpcijasSvārstīgumsUz notikumiem balstīta tirdzniecība