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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

This short stock-screening post combines a moving-average condition with rankings for trading activity and market attention. It proposes selecting equities where the 20-day moving average is above the 120-day average, then ordering candidates by a…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document describes a stock screen combining a minimum daily amplitude, MACD above zero, and a bounded ratio involving the previous day’s turnover rate, the current auction’s buy volume, and the prior day’s volume. It presents the screen as a way to find…

AkcijasTehniskie indikatoriCenas impulssStatistika
SuperMind

The screen selects listed Chinese A-shares with turnover between 3% and 12%, market capitalization below 10 billion yuan, positive income, and a positive daily MACD reading. The accompanying explanation interprets turnover as a filter for market activity,…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This A-share screening approach selects stocks with daily amplitude above 1, RSI below 65, and a daily percentage change below 2.6% but above -5%. The document frames the amplitude condition as finding stocks with notable price movement, while the RSI filter…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This A-share screening idea combines three conditions: RSI below 65, MACD above its zero line, and at least two limit-up moves within a 500-day lookback. The document interprets the RSI filter as avoiding overly heated conditions, the MACD condition as…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This selection method screens for stocks with amplitude above 1 and more than one year since listing, then ranks qualifying names by individual-stock heat and takes the top n. The accompanying rationale is that larger price movement may indicate market…

AkcijasTehniskie indikatoriCenas impulssTirgus noskaņojums
SuperMind

The proposed stock screen combines three conditions: amplitude above 1, at least one daily gain of 10% or more within the previous 25 trading days, and company scale above 200 million. The text frames these as filters for active price movement, recent…

AkcijasSvārstīgumsCenas impulssRiska pārvaldība
SuperMind

This stock-selection idea combines a turnover filter, a recent price-limit event, and MACD. It selects shares with turnover between 3% and 12%, at least one limit-up during the previous 25 days, and a MACD value below zero two days earlier. The accompanying…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This post proposes ranking Chinese equities by capital-flow strength while filtering for company scale and repeated limit-up sessions within a recent period. The rationale is that stronger flow may indicate investor attention, larger companies may be more…

AkcijasCenas impulssCenas izrāviensRīkojumu izpilde
SuperMind

This overview explains why financial institutions may consider digital assets and surveys market structure, asset categories, trading venues, and regulatory developments. It contrasts crypto markets with traditional finance, emphasizing continuous global…

KriptoaktīviTirgus mikrostruktūraArbitrāžaAtvasināto instrumentu cenu noteikšana
SuperMind

This Chinese-language post describes an equity screen combining a positive MACD reading, upward-moving short-term averages, and a measure intended to capture strong investor control or positioning on the prior day. It presents the conditions as signs of an…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock-screening rule combines three conditions: RSI below 65, positive price-to-earnings value, and the 20-day moving average above the 120-day average. The moving-average relationship acts as a broad trend filter, while RSI places an upper bound on the…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-screening article combines a positive MACD reading with seven consecutive falling closes and a shortening MACD histogram on a 15-minute chart. The proposed interpretation is that shrinking negative histogram bars may signal weakening…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This document describes a stock screen requiring RSI below 65, a daily gain greater than 1%, main-board listing, and a weekly price move above the 30-week moving average. The rationale combines a recent price advance and a moderate RSI reading with a…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This document proposes screening Chinese stocks in the beverage and alcohol import-export sector using turnover between 3% and 12% and a negative MACD reading from two days earlier. The author frames the turnover band as a way to focus on stocks with…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This document describes a China A-share screening rule that combines a turnover range of 3% to 12%, appearance on the previous day’s 龙虎榜 (a public list highlighting unusual trading activity), and an increase in the KDJ indicator’s K value. It also gives…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This note outlines a Chinese stock screen that combines a beverage and alcohol industry classification with a turnover-rate range and a specified share price. It presents the criteria as a way to focus on trading activity and a particular industry, then…

AkcijasĶīnas tirgi
SuperMind

This note describes a Chinese equity screen combining price movement, trading activity, an opening gap, and Bollinger Band position. It selects stocks with an amplitude above 1, current volume above 10,000 lots, a higher open, and a close between the middle…

AkcijasTehniskie indikatoriSvārstīgumsĶīnas tirgi
SuperMind

This proposed Chinese equity screen combines daily amplitude above one, large-order net volume above a stated threshold for three consecutive days, and association with the metaverse concept. The post provides indicator-style conditions and a rough Python…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

The proposed screen selects stocks with an amplitude above 1, MACD above the zero line, and a 9:25 a.m. price gain below 6% relative to the previous close. The document interprets larger amplitude as greater volatility, a positive MACD condition as…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This stock-selection rule filters for turnover rates between 3% and 12%, a rising K line from the KDJ oscillator, and a rising DEA line. The post’s sample formula also excludes stocks in industry type 1, which it identifies as the STAR Market. Its Python…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post describes an A-share stock screen that ranks shares by capital strength, then selects the five highest by the day’s auction amount. It also filters for companies whose 2021 revenue divided by 2018 revenue exceeds 1.1, which the…

AkcijasĶīnas tirgiFaktoru ieguldīšana
SuperMind

This post describes a stock screen using three conditions: daily amplitude above 1, a positive weekly MACD histogram, and a rising-bottom pattern. It offers example formulas and Python code that scan listed stocks, evaluate daily amplitude and weekly MACD,…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock-screening post combines three filters: RSI below 65, an industry concentration ratio above 70% or below 20%, and a shortening MACD histogram on a 15-minute chart. It presents the approach as a way to find stocks with improving momentum…

AkcijasTehniskie indikatoriCenas impulss