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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
WonderTrader
Dokumentu skaits: 14
Alphalens
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

vn.py community

This short forum exchange addresses how to detect an invalid order price before submitting an order through VeighNa. The response says the framework does not generally filter prices in advance, although its graphical interface prevents users from entering…

Rīkojumu izpildeNākotnes līgumi
Hummingbot docs

This recap describes Hummingbot Miner’s first year, during which token issuers used rewards to attract decentralized market makers. It reports campaign participation, reward payouts, filled trading volume, and activity across Binance and a new KuCoin launch.…

KriptoaktīviTirgus veidošanaTirgus mikrostruktūraRīkojumu izpilde
SuperMind

The proposed screen selects main-board stocks with circulating market value between 5 billion and 10 billion yuan, turnover between 3% and 12%, and a stated daily maximum decline between 4% and 5%. The article presents the filters as a way to find stocks…

Ķīnas tirgiAkcijasTehniskie indikatoriRiska pārvaldība
MQL5 code base

This Expert Advisor trades when the ColorZeroLagTriX indicator cloud changes color. It forms a signal at bar close when the oscillator crosses its signal line, making the method dependent on a confirmed closing-bar crossover rather than an intrabar move. The…

Valūtu tirgusTehniskie indikatoriVēsturisko datu pārbaude
MQL5 code base

The indicator compares three moving averages whose configured periods must increase from the first average to the second and then the third. It colors the display green when all three averages are ordered from highest to lowest, and red when they are ordered…

Tehniskie indikatoriSekošana tendencei
SuperMind

This stock-selection post describes a screen using three short-term conditions: a positive ten-day return below 35%, daily amplitude above 1%, and a stated concentration measure below 20%. It frames these filters as a way to identify stocks with recent gains…

Ķīnas tirgiAkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This community post proposes a Chinese stock screen within the metaverse industry. It filters for prior-session actual turnover between 3% and 28%, an opening-auction price move ranked among the strongest in the market, and combined net buying by very large…

Ķīnas tirgiAkcijasTirgus mikrostruktūraRīkojumu izpilde
BigQuant

This weekly Chinese equity research note reviews long-short screens built from high-frequency and technical factors. The listed signals include return skewness, downside volatility share, opening-period buying interest and large-order flows, reversal,…

Ķīnas tirgiAkcijasAugstas frekvences tirdzniecībaFaktoru ieguldīšana
MQL5 code base

The Aroon Up and Down indicator tracks how recently a chart has made local highs and lows, using a configurable lookback period. Its lines can be used to identify when prices rise from a recent low or decline from a recent high, with line crossings presented…

Valūtu tirgusTehniskie indikatori
BigQuant

This article reviews global equity factor performance in the third quarter of 2021 and compares defensive factor positioning. It reports that momentum and low residual volatility led the pure factor results, while liquidity lagged. Regional index outcomes…

AkcijasFaktoru ieguldīšanaCenas impulssSvārstīgums
SuperMind

This article reviews global equity factor performance in the third quarter of 2021 and compares defensive factor positioning. It reports that momentum and low residual volatility led the pure factor results, while liquidity lagged. Regional index outcomes…

AkcijasFaktoru ieguldīšanaCenas impulssSvārstīgums
SuperMind

This Chinese-language article describes an equity screen for Shenzhen main-board stocks associated with the metaverse theme. It selects stocks with a positive return, positive price-to-earnings and price-to-book ratios, and upper bounds on both valuation…

AkcijasĶīnas tirgiFaktoru ieguldīšana
MQL5 code base

This chart indicator adapts the stochastic volatility concept to highlight periods when volatility is unusually low. It marks candidate bars with red lines in a separate indicator window and red candles on the price chart. The author suggests these periods…

SvārstīgumsTehniskie indikatori
SuperMind

This document outlines a stock-selection screen that ranks securities by capital strength and requires weekly MACD to be above zero, alongside a year-based filter referring to 2021. It explains capital strength through trading volume and value, and describes…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This document presents a Chinese equity screen for Shenzhen Main Board stocks, combining turnover from 3% to 12%, circulating market capitalization from 5 billion to 10 billion, price-to-earnings ratio from 0 to 29.01, and price-to-book ratio from 0 to 3.11.…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaStatistika
SuperMind

This document proposes screening stocks whose codes begin with 60, keeping those with turnover between 3% and 12%, then ranking them by a measure described as capital strength. The commentary presents the ranking as a way to identify actively financed market…

Ķīnas tirgiAkcijasRīkojumu izpilde
SuperMind

This document describes a Chinese stock screen using amplitude above 1, a stated K-line value below 20, and prior-day actual turnover between 3% and 28%. It presents these conditions as a way to find stocks with notable price movement and moderate trading…

Ķīnas tirgiAkcijasTehniskie indikatoriMašīnmācīšanās
ProRealCode

This indicator combines smoothed Heikin-Ashi candles with a stochastic oscillator and a moving-average condition to mark possible entries and exits. The described logic treats rising Heikin-Ashi candles as bullish and falling candles as bearish, while candle…

Tehniskie indikatoriCenas impulssOpcijasSekošana tendencei
SuperMind

The post proposes screening Chinese equities for elevated daily range, at least one daily gain of 10% or more during the past 25 trading days, and a pre-open price change below 6%. It then extends the screen with company and industry comparisons, including…

AkcijasĶīnas tirgiCenas impulssSvārstīgums
SuperMind

This Chinese A-share screening idea combines three technical conditions: at least five moving averages are described as converging, the KDJ indicator has just formed a bullish crossover, and the 20-day moving average is above the 120-day average. The post…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock screen combines a metaverse-concept filter with a simple price condition: the current close must be above the previous session’s low. It also excludes Beijing-listed A shares. The document gives corresponding indicator logic and a Python example,…

AkcijasĶīnas tirgiTehniskie indikatoriPozīcijas apjoma noteikšana
SuperMind

This Chinese-language post proposes screening stocks using turnover, displayed best-level bid and ask volume, and large-order net inflow. Its final selection rule requires turnover between 3% and 15%, bid volume greater than ask volume, and large-order net…

AkcijasTirgus mikrostruktūraTehniskie indikatoriStatistika
MQL5 code base

The Trend Risk indicator estimates a smoothed price and a smoothed high-low range, then uses a deviation multiplier to form upper and lower channel boundaries. A close above the upper boundary or below the lower boundary places the boundary value in a signal…

Tehniskie indikatoriSekošana tendenceiCenas izrāviensRiska pārvaldība