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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
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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
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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
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
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Binance API docs
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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: 12,226

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
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
SuperMind

This short-term stock screen combines amplitude above a stated threshold with a 15-minute MACD histogram that remains below zero but is getting shorter, alongside a rising DEA signal. The document interprets the amplitude condition as a way to find active…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock-screening proposal selects shares with turnover between 3% and 12%, first-level bid volume greater than first-level ask volume, and previous-session trading activity above the stated threshold. It then takes the first ten qualifying symbols. The…

AkcijasĶīnas tirgiTirgus mikrostruktūraTehniskie indikatori
SuperMind

The document describes a stock selection rule that filters for turnover between 3% and 12%, companies listed in 2021, and an observation at 9:25 with a price increase below 6%. It presents the screen as a way to refine entry timing and avoid buying after a…

AkcijasĶīnas tirgiTehniskie indikatoriVēsturisko datu pārbaude
SuperMind

This Chinese-language post proposes a short-term stock screen combining turnover between 3% and 12%, a reversal or engulfing-style pattern, and auction-period buying attributed to large and very large orders. The stated flow threshold is more than 0.7…

AkcijasCenas impulssTirgus mikrostruktūraTirgus noskaņojums
SuperMind

This Chinese-language post proposes screening stocks in the metaverse sector when KDJ has just crossed upward and a rounded chart pattern is present. It limits selection to before 10:00 on each trading day and says eligible stocks are intended for same-day…

AkcijasTehniskie indikatoriCenas impulssVēsturisko datu pārbaude
SuperMind

This proposed stock screen combines three signals: a historical dividend payout condition, high capital-flow intensity, and low concentration of those flows. The article interprets the flow measures as indicating substantial but broadly distributed inflows,…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTirgus noskaņojums
SuperMind

This stock-selection screen combines a price-movement condition, a small-company size limit, positive net profit, and an upward weekly trend condition described as crossing above a 30-week moving average. The article presents the combination as a way to find…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This proposed Chinese equity screen selects stocks in the metaverse sector that had at least one limit-up day during the preceding 25 days and traded more than 60 million yuan in value on the previous day. The article says to run the selection before 10 a.m.…

AkcijasĶīnas tirgiCenas izrāviens
SuperMind

This stock selection idea combines three filters: at least five moving averages clustered together, a newly formed KDJ bullish crossover, and 2021 revenue more than 1.1 times 2018 revenue. The author interprets clustered averages as a sign of relatively…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

The article describes a Chinese stock selection screen combining turnover between 3% and 12%, appearance on the prior day's Dragon-Tiger list, and a concentration measure. It frames turnover and the listing as signals of liquidity and market attention, while…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese equity screening note selects stocks with turnover between 3% and 12%, three consecutive declining sessions, and MACD above its zero line. It presents the pattern as a way to identify shares with possible short-term downside while retaining…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screening note combines three filters: daily amplitude above a stated threshold, a 2019 dividend ratio above 25%, and exclusion of STAR Market stocks. It argues that larger price ranges identify more volatile shares, while high dividends…

AkcijasĶīnas tirgiSvārstīgumsTehniskie indikatori
SuperMind

This Chinese A-share screening proposal selects stocks using three stated conditions: amplitude greater than one, a dividend payout ratio above 25% in 2019, and at least one limit-up move during the preceding month. The accompanying discussion interprets the…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese equity screening proposal combines a positive MACD reading, an upward moving-average condition, and a newly formed bullish KDJ crossover. The post interprets these conditions as signs of positive direction and momentum. It supplies indicator…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This post describes a Chinese equity selection rule combining daily price amplitude, an upward-moving-average condition, and the prior day’s turnover relative to the current day’s volume. Its rationale is to identify stocks with favorable short-term price…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

The post describes a Chinese equity screening rule using three conditions: the stock’s daily high-low range exceeds a threshold, it did not hit the upper price limit on the previous day, and the best bid quantity is greater than the best ask quantity. The…

AkcijasTehniskie indikatoriTirgus mikrostruktūraĶīnas tirgi