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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
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: 12,226

SuperMind

The article introduces logistic regression as a binary classifier that maps a weighted combination of features to a probability. It outlines fitting the model by maximizing the likelihood of observed labels, equivalently minimizing a loss with gradient…

MašīnmācīšanāsAkcijasĶīnas tirgiFaktoru ieguldīšana
SuperMind

This post proposes selecting Chinese equities that combine a positive MACD reading, favorable company characteristics, and net buying by large orders in the afternoon. It describes the signals as complementary: MACD is used to identify positive price…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This post describes a Chinese equity screen for stocks in the metaverse industry. It requires relative volume to fall between 1.5 and 6 and uses a weekly five-period moving average crossing above the ten-period average as a trend filter. The rationale is to…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The document describes a stock screen combining amplitude above 1, a weekly five period moving average crossing above the ten period average, and positive returns. It presents these conditions as a way to find shares with larger price movement, an upward…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This document describes an equity screen for stocks with turnover between 3% and 12%, an IPO year of 2021, and a price below 12. Its rationale is to find relatively inexpensive, recently listed companies with moderate trading activity, while acknowledging…

AkcijasĶīnas tirgiFaktoru ieguldīšanaRiska pārvaldība
SuperMind

The document proposes a short-term stock screen requiring amplitude above 1, a shrinking negative MACD histogram on a 15-minute chart, and a price below 12. It presents the shrinking histogram as a possible sign of a change in direction and uses the…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This document outlines a Chinese equity screen using three conditions: price amplitude above 1, a 9:25 price increase below 6%, and recent revenue at least 1.1 times the 2018 revenue figure. It frames the revenue comparison as a growth filter and combines it…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
SuperMind

This document describes an A-share stock screen combining a 14-period RSI below 65, year-over-year net profit growth above 20% and no more than 100%, and a 9:25 price increase below 6%. Its accompanying query example adds positive net profit, a free-float…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This note outlines a Chinese equity screen using RSI below 65, float market value between 5 and 10 billion yuan, and daily price change between −5% and 2.6%. It combines a short-term technical indicator with company size and recent price movement, then…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This Chinese stock selection note describes a short-term screen requiring amplitude above 1, three moving-average crossovers to occur together, and exclusion of stocks that hit the daily limit the previous day. The crossover sequence uses moving averages…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

The document describes a stock selection rule combining three conditions: daily price amplitude above a threshold, circulating market capitalization above a threshold, and best bid volume greater than best ask volume. It presents the conditions as filters…

AkcijasĶīnas tirgiTirgus mikrostruktūraTehniskie indikatori
SuperMind

This document describes a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and volume ratio between 1.5 and 6. The stated rationale is to find stocks with…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This Chinese A-share screen selects stocks with MACD above zero, a qualitative business-character assessment, and a daily price change within a specified range. The article frames the rule as combining a technical momentum condition with a basic…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-selection rule combines three conditions: daily amplitude above a threshold, a weekly five-period moving average crossing above the ten-period average, and yesterday’s turnover rate above a stated level. The crossover is intended to…

AkcijasĶīnas tirgiSekošana tendenceiTehniskie indikatori
SuperMind

This Chinese A-share screening rule combines a metaverse industry filter and a maximum circulating share count with a measure based on yesterday’s turnover rate and today’s auction volume relative to yesterday’s trading volume. It selects stocks where the…

AkcijasĶīnas tirgiTirgus mikrostruktūraStatistika
SuperMind

The proposed screen targets Chinese stocks with prior-session amplitude above a threshold, a listing on the previous day’s Dragon-Tiger ranking, and no ST designation. It then selects up to five stocks that reach the daily limit-up before 10 a.m., sorting…

AkcijasĶīnas tirgiCenas impulssCenas izrāviens
SuperMind

The document describes a historical stock screen that selects non-KSTAR-board Chinese stocks on dates in 2021 when the daily high-low range exceeds 1% of the low. It presents the range as a measure of elevated price movement that may identify stocks with…

AkcijasĶīnas tirgiSvārstīgums
SuperMind

The document presents a stock screen combining membership in the metaverse industry, an arc-shaped price pattern, and a daily return between -5% and 2.6%. It frames the return band as a way to avoid stocks that have already moved too sharply, while the…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This screening idea selects stocks associated with the metaverse theme when three bullish technical crossovers occur together: MACD crosses its signal line, the 5-day average crosses the 10-day average, and the 5-day average crosses the 20-day average. It…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock-selection recipe combines a moving-average condition, an opening-price filter, and a revenue growth test. It targets Chinese equities whose 5-, 10-, 20-, 30-, and 60-day moving averages are described as overlapping, whose 9:25 a.m. gain is below…

AkcijasĶīnas tirgiTehniskie indikatoriSekošana tendencei
SuperMind

The proposed Chinese equity screen selects stocks with turnover between 3% and 12%, at least one limit-up event in the prior 25 days, and a stated circulating market value above 10 billion yuan. The accompanying explanation treats turnover as a measure of…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This article outlines a technical stock screen for the Chinese metaverse theme. It requires bullish crossovers in MACD and two short-term moving-average comparisons, along with the 20-day average above the 120-day average. The stated intent is to find stocks…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

The document describes a stock screen combining an RSI threshold below 65, membership in the beverage and alcohol import-export industry, and a condition it labels a rounded-arc pattern. The supplied formula defines that pattern as the five-period and…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

The study tests institutional ownership data as a quarterly stock-selection factor in Chinese equities. It measures ownership share, the number of institutions holding a stock, and average holdings per institution as a proxy for ownership concentration. For…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude