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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
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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
Dokumentu skaits: 682
FMZ digest
Dokumentu skaits: 662
vn.py community
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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
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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: 12,226

SuperMind

This Chinese stock-selection approach narrows its universe to metaverse-related companies, then applies a positive institutional-flow condition and a threshold for the ratio of external to internal trading volume. The article’s prose gives a ratio threshold…

AkcijasĶīnas tirgiTirgus noskaņojumsTirgus mikrostruktūra
SuperMind

This Chinese equity screen combines current turnover, year-over-year net profit growth attributable to parent-company shareholders, and the previous day’s turnover. It selects stocks with turnover from 3% through 12%, profit growth above 20% and no more than…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
SuperMind

The document presents a Chinese equity screening idea focused on metaverse-related stocks. Its initial criteria combine a volume ratio between 1.5 and 6 with a stated prior-year return threshold. The post then proposes adding a market-cap floor, a forecast…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This document describes a Chinese stock screen that selects shares with turnover between 3% and 12%, a listing year of 2021, and a MACD value below zero two trading days earlier. It presents the conditions as a way to combine a liquidity filter with a…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This document describes a Chinese stock screen that combines an intraday price range filter with a 15-minute MACD histogram condition, limited to 2021. The accompanying examples implement the filters in indicator and Python workflows. The intended use is to…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This stock screen selects companies with strong money-flow readings, share prices below 12 yuan, market capitalization under 10 billion yuan, and no reported losses. The proposed ranking orders candidates from strongest to weakest by money-flow intensity.…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
SuperMind

This A-share stock screen combines three technical conditions: a 14-period RSI below 65, MACD above its zero line, and a rising 30-day moving average. The stated rationale is to find stocks with moderate momentum and an upward price trend. The article also…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post describes a stock-selection rule focused on the metaverse sector. It screens for positive returns and prior-day auction turnover above a stated threshold, then proposes adding a positive return over the preceding six months. The rationale is that…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This post outlines an A-share stock screen combining a metaverse-sector classification, positive recent returns, and positive auction turnover. It proposes an additional six-month positive-return filter, and later suggests valuation and trend conditions such…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document proposes screening Chinese stocks for three conditions: association with the metaverse theme, a rounded chart pattern, and company scale above 200 million yuan. It frames the rounded pattern as a technical signal and company size as a rough…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

The document describes a Chinese stock screen combining a daily amplitude threshold, membership in a robotics concept group, a circulating market value below 10 billion yuan, and an outside-volume to inside-volume ratio above 1.3. It also presents example…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This Chinese equity screen combines a daily amplitude threshold with a prior-day 9:15 matching-price limit-down condition, robot-industry membership, and a circulating market value below 10 billion yuan. The final version adds a price-to-earnings ratio below…

AkcijasTehniskie indikatoriĶīnas tirgiVēsturisko datu pārbaude
SuperMind

This stock screen combines a price-range filter with two momentum conditions. It looks for a range above 1%, a contracting negative MACD histogram on a 15-minute chart, and a KDJ value below 20. The document interprets the shrinking negative histogram as a…

AkcijasTehniskie indikatoriCenas impulssAtgriešanās pie vidējās vērtības
SuperMind

This stock screen combines daily price movement with a recent high and a volatility-compression condition. It selects stocks whose intraday range exceeds 1%, whose high is the highest of the current and previous day, and whose Bollinger-band variability is…

AkcijasTehniskie indikatoriSvārstīgumsRiska pārvaldība
SuperMind

This stock screen combines three filters: price amplitude greater than 1, free float no more than 5.5 billion shares, and company size above 200 million. The article interprets the amplitude condition as a way to find more volatile stocks that may suit…

AkcijasSvārstīgumsTehniskie indikatoriRiska pārvaldība
SuperMind

This stock selection method searches the metaverse industry for shares showing simultaneous bullish crossovers in MACD and two moving average pairs: the 5-period average over the 10-period and 20-period averages. It adds a condition that the KDJ indicator…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This Chinese stock screen combines trading activity, thematic classification, market capitalization, and fundamental filters. It seeks stocks with amplitude above 1, elevated same-day control, a robotics association, and circulating market value below 10…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This post describes a Chinese equity screening rule combining a large daily high-low range, at least one strong up day in the recent trading window, and a close above the previous day’s low. The accompanying discussion frames these conditions as filters for…

AkcijasĶīnas tirgiSvārstīgumsCenas impulss
SuperMind

This post outlines a stock-selection idea combining a short-versus-long moving-average trend filter with measures of daily position increases and large-order net flow. The initial logic highlights a positive position-increase share, the product of price…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This post describes a Chinese A-share screening rule that combines daily price range, a newly formed KDJ crossover, and relative volume. Stocks enter a watchlist when the range exceeds the stated threshold and volume ratio falls within the specified band.…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post proposes a stock screen using daily price range, closing price, and the ratio of outside to inside trading volume. Its stated core thresholds are amplitude above 1, close below 20, and outside volume divided by inside volume above…

AkcijasTehniskie indikatoriTirgus mikrostruktūraĶīnas tirgi
SuperMind

This document describes an A-share stock screen that selects Shenzhen main-board shares with daily price amplitude above 1%, a nonempty outstanding convertible-bond name, positive price-to-earnings ratio below 29.01, and positive price-to-book ratio below…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTehniskie indikatori
SuperMind

This document describes an A-share screen using three conditions: a rising 30-day moving average, a prior-day 9:15 matched price at the limit-down level, and a current increase in the stated position-building ratio above 5%. Its proposed interpretation is…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss