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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: 12,226

SuperMind

The article explains hidden Markov models as a way to infer unobserved market regimes from observable data. It illustrates the idea with Chinese equities, treating market conditions such as bull, bear, and sideways phases as hidden states and returns and…

AkcijasMašīnmācīšanāsStatistikaĶīnas tirgi
SuperMind

This educational article introduces operations on matrices and vectors as groundwork for understanding deep learning. It defines elementwise matrix addition, adding a scalar to each matrix element, and broadcasting a vector across matrix rows. It then…

MašīnmācīšanāsStatistika
SuperMind

This note describes a short-term A-share screen combining a positive but limited ten-day return, a circulating market value between 5 and 10 billion yuan, and a same-day increase in holdings above five percent. The intended idea is to find stocks with recent…

AkcijasĶīnas tirgiCenas impulssRiska pārvaldība
SuperMind

This document outlines a short-term A-share screen using capital-strength rankings, stocks appearing on the previous day’s 龙虎榜, and more than two limit-up sessions during the prior ten days. The rationale is that strong capital activity and limit-up…

AkcijasĶīnas tirgiCenas impulssTirgus noskaņojums
SuperMind

This note describes a Chinese A-share screen combining an intraday amplitude above one, exclusion of ST-designated stocks, selection before 10 a.m., a five-part limit-up method, and exclusion of Beijing-listed shares. Its example translates these ideas into…

AkcijasĶīnas tirgiTehniskie indikatoriCenas izrāviens
SuperMind

This Chinese equity screen combines a metaverse industry classification with a rising 30-day moving average and a revenue growth condition. It requires the current 30-day average to exceed its prior value and the stated 2021-to-2018 revenue ratio to be…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screen combines a daily price range filter, a weekly MACD condition, and relative trading volume. It selects stocks whose daily high-low range exceeds 1% of the previous close, whose weekly MACD is above zero with the MACD line above its…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screening approach combines three conditions: today’s increase in holdings must exceed 5%, the weekly price must cross above its 30-week moving average, and the 30-day moving average must be rising. Together, these are intended to capture…

AkcijasĶīnas tirgiSekošana tendenceiTehniskie indikatori
SuperMind

This stock screen combines three filters: membership in the metaverse industry, a positive institutional-flow measure, and a seven-session sequence of declining closes. The article presents the idea as a way to find weak recent price action in a sector while…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus noskaņojums
SuperMind

The document describes a Chinese stock-selection screen combining a robot-related company label, a 2021 listing year, a circulating market capitalization below 10 billion, and turnover between 3% and 12%. Its accompanying indicator example calculates average…

AkcijasĶīnas tirgiTehniskie indikatoriStatistika
SuperMind

This post describes a Chinese A-share screen for metaverse-related stocks with circulating share count no greater than 5.5 billion and more than two limit-up events during the previous ten trading days. It frames the screen as a way to find stocks with…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese-language post outlines an A-share screen for stocks with an intraday amplitude above 1%, a robotics concept classification, and circulating market value below 10 billion yuan. It ranks qualifying names by that day’s auction amount and selects…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This document describes a Chinese stock screening rule focused on companies classified in the metaverse industry. It seeks stocks whose opening price is near the 10-day moving average and whose turnover falls between 2% and 9%. The article gives example…

Ķīnas tirgiAkcijasTehniskie indikatori
SuperMind

This Chinese stock-selection method screens for a positive MACD reading, an external-to-internal volume ratio above a stated threshold, and a positive ten-day return below an upper bound. Stocks meeting all conditions are then ranked by their ten-day gains.…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese equity screen combines three technical conditions: daily price amplitude above a threshold, a positive weekly MACD histogram, and a rising DEA-related measure. The article describes these as signs of price activity and technical strength, then…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock screen combines membership in the metaverse sector, a minimum threshold for circulating market value, and a prior-day measure of main-investor control. The accompanying explanation interprets a high control reading as a sign that…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese stock-screening example selects shares in the metaverse industry when the KDJ indicator has just crossed bullishly and the stock ranks among the top ten for large-order net volume. It proposes running the screen before 10 a.m. on each trading…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock-selection screen combines a positive MACD reading, a share price below a stated threshold, and a ranking based on large-order net volume. It is intended to run before market open on each trading day. The accompanying rationale is that a positive…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

The document describes a stock selection rule combining three technical conditions: an amplitude threshold, rising bottoms, and a weekly crossover of the five-period moving average above the ten-period average. It presents the rule as a way to identify…

AkcijasTehniskie indikatoriSekošana tendenceiĶīnas tirgi
SuperMind

The post describes a Chinese equity screening rule that selects stocks with turnover between three and twelve percent, a prior-day appearance on the broker ranking list, and a limit-up event within the preceding twenty-five days. It includes example formula…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document presents a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, at least one limit-up event during the prior 25 days, and previous-day trading value above 60 million. It includes a formula-style expression and a…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This A-share selection proposal combines price range, turnover, and a price-change measure multiplied by net flow attributed to very large orders. The stated screen requires a range above one percent, turnover between two and nine percent, and a positive…

AkcijasĶīnas tirgiTirgus mikrostruktūraTehniskie indikatori