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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
Quantpedia
Dokumentu skaits: 86
TqSdk
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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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 post presents a stock screen using three conditions: daily price range above 1%, positive price-to-earnings ratio, and a ten-day return above zero but below 35%. The intended rationale is to find profitable companies showing recent gains and active…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This post describes a Chinese A-share screening rule: select stocks in the metaverse theme with a positive institutional-flow signal and prior-session auction turnover above 0.26. It gives indicator references and a Python example intended to implement the…

AkcijasĶīnas tirgiTirgus mikrostruktūraTirgus noskaņojums
SuperMind

This proposed stock screen combines a daily turnover rate between 3% and 12%, a positive product of daily price change and large-order net flow, and a 2019 dividend ratio above 25%. The article frames turnover as a measure of market activity and the…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This stock screen selects companies assigned to the metaverse industry using two size conditions: circulating shares at or below 5.5 billion and a stated size threshold of at least 200 million. The document presents the screen as a way to find larger…

AkcijasĶīnas tirgiFaktoru ieguldīšana
OctoBot

This guide explains how OctoBot scripts obtain historical market data for backtesting. It describes requesting candle history by symbol and timeframe, with optional controls for the starting timestamp, exchange, and market type. The default exchange is…

Vēsturisko datu pārbaudeKriptoaktīvi
MQL5 code base

This document describes an indicator that presents the Center of Gravity method associated with J. F. Ehlers as a colored OSMA histogram. The histogram is formed from a smoothed difference between the main Center of Gravity line and its signal line, offering…

Tehniskie indikatori
SuperMind

This stock-selection recipe filters Shenzhen main-board listings using turnover between 3% and 12%, year-over-year growth in net profit attributable to parent-company shareholders above 20% and up to 100%, price-to-earnings ratios from 0 to 29.01, and…

AkcijasFaktoru ieguldīšanaRiska pārvaldība
SuperMind

This stock screen combines a daily range filter, a qualitative company-quality condition, and a trend rule requiring the 20-day moving average to exceed the 120-day average. The article interprets the moving-average relationship as evidence that recent price…

AkcijasSekošana tendenceiTehniskie indikatori
FMZ forum

The article argues that frequent, impulsive trades can erode capital and damage a trader’s discipline. It defines low-value trading as entering on minor price moves or vague possibilities without assessing likely reward against the planned stop. Since…

Riska pārvaldībaPozīcijas apjoma noteikšana
SuperMind

This stock screen combines a daily price-amplitude threshold, a MACD condition above the zero line, and year-over-year growth in net profit attributable to parent-company shareholders. The stated profit-growth range is above 20% and up to 100%. The rationale…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
BigQuant

This Chinese research note examines the common practice of relating price-to-earnings ratios to expected earnings growth, including the assumption that a PEG ratio of one indicates fair value. Its hypothetical comparison shows that companies with PE and…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
BigQuant

This overview surveys empirical research on pricing stock-index options, focusing on how systematic stochastic volatility and jump risk affect option values and returns. It describes the evolution from Black–Scholes–Merton assumptions, in which the…

OpcijasSvārstīgumsAtvasināto instrumentu cenu noteikšanaStatistika
SuperMind

The article proposes a Chinese stock screen combining three price-based conditions: amplitude above a threshold, a rising bottom pattern, and at least one limit-up move within the prior 25 days. It frames wide swings and rising lows as technical signals and…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
MQL5 code base

This document describes an MT4 expert advisor designed to manage trades using virtual take-profit, stop-loss, breakeven, and trailing-stop levels. Because these levels are maintained by the advisor rather than sent as broker-side orders, the page says the…

Rīkojumu izpildeRiska pārvaldībaPozīcijas apjoma noteikšana
MQL5 code base

DMX is described as an oscillator derived from the positive and negative directional indicator lines used in ADX. It normalizes their difference by their sum, producing a bipolar value, and adds a signal line calculated as a moving average of DMX. The source…

Tehniskie indikatoriStatistika
ProRealCode

The Double Seven method is presented as a long-only daily strategy for ETF or futures index markets. It first requires the close to be above its 200-day moving average. An entry occurs when the day’s low reaches or falls below the lowest close over the…

AkcijasNākotnes līgumiSekošana tendenceiTehniskie indikatori
SuperMind

This stock-screening approach ranks shares by reported buy and sell amounts in the previous day’s trading leaderboard, then filters for names with leaderboard activity and a 20-day moving average above the 120-day average. The ranking is intended to…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese equity-screening note selects stocks with MACD above zero, positive price-to-earnings ratio, and turnover between three and twelve percent. It interprets the MACD condition as an upward trend filter, positive PE as a basic valuation sanity…

Ķīnas tirgiAkcijasTehniskie indikatoriFaktoru ieguldīšana
ProRealCode

This indicator guide explains how to identify potential reversal patterns by finding price pivots, connecting them into a zigzag, and checking whether successive peaks or troughs fall within a configurable tolerance. The described defaults use a five-bar…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasRiska pārvaldībaVēsturisko datu pārbaude
SuperMind

This Chinese stock-screening note combines three conditions: daily trading range above one percent of the previous close, weekly MACD above zero, and a prior-day 9:15 matching price at the lower price limit. It presents the screen as a way to find stocks…

Ķīnas tirgiAkcijasTehniskie indikatoriSvārstīgums
BigQuant

This research summary describes using machine learning to predict equity returns from alpha factors. It compares LASSO, support vector machines, boosted decision trees, and random forests, selecting random forests for their relatively simple structure,…

AkcijasĶīnas tirgiMašīnmācīšanāsFaktoru ieguldīšana
SuperMind

This document describes a Chinese A-share screening rule combining three conditions: amplitude above 1, MACD below zero two days earlier, and a gain below 6% around 9:25. It presents the screen as a way to combine a volatility measure, a trend signal, and a…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
MQL5 code base

This trading script opens a limit order at the price of a specially labeled chart line when triggered by a hotkey. A line above the current price produces a buy limit, while one below produces a sell limit. The user configures the lot size, maximum stop-loss…

Rīkojumu izpildePozīcijas apjoma noteikšanaRiska pārvaldībaValūtu tirgus
MQL5 code base

The expert advisor combines the Commodity Channel Index with a moving average to condition CCI entry thresholds on the moving average’s direction. When the average rises, the system uses one pair of CCI levels for buying and selling; when it falls, it…

Tehniskie indikatoriSekošana tendenceiValūtu tirgus