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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
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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
Dokumentu skaits: 28
Zipline
Dokumentu skaits: 22
FMZ live strategies
Dokumentu skaits: 21
Jesse
Dokumentu skaits: 17
pyfolio
Dokumentu skaits: 16
WonderTrader
Dokumentu skaits: 14
Alphalens
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

These reading notes explain how futures can offset exposure to changes in commodity prices, exchange rates, or other market variables. A short hedge suits a party that benefits when an asset price rises and loses when it falls, such as a producer planning a…

Nākotnes līgumiRiska pārvaldībaIzejvielasValūtu tirgus
SuperMind

This stock screen combines price movement and recent trading activity. It looks for amplitude above 1, at least one daily gain of 10% or more during the past 25 trading days, and more than two limit-up days within the past 10 days. The document frames these…

AkcijasCenas impulssSvārstīgumsTehniskie indikatori
SuperMind

This note outlines a Chinese equity screen that combines membership in the metaverse theme with positive net buying by large traders during the auction and a relatively low shareholding concentration measure. It presents these as three filters for…

AkcijasĶīnas tirgiTirgus mikrostruktūraTehniskie indikatori
SuperMind

This note describes a Chinese equity screening rule combining daily price amplitude, turnover, and the direction of the 30-day moving average. It selects stocks with amplitude of at least 1%, turnover above 2% and below 9%, and a 30-day average close that…

AkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This stock-screening proposal selects equities whose 5-, 10-, 20-, 30-, and 60-day moving averages converge, with turnover above 2% and below 9%, and a dividend payout ratio above 25% for 2019. The author interprets clustered short- and medium-term averages…

AkcijasTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This overview organizes common machine learning methods in two ways: by their form or function, and by how they learn from data. It surveys regression, instance-based methods, regularization, decision trees, Bayesian methods, clustering, association rules,…

MašīnmācīšanāsStatistika
SuperMind

The document describes a short-term stock screen combining daily price range, company size, profitability, and a reversal pattern called a bearish-to-bullish “wraparound” or reversal setup. Its proposed criteria include a daily range above one percent,…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasRiska pārvaldība
SuperMind

The document presents a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, displayed first-level bid volume greater than ask volume, and reported holder concentration below 20%. The candidates are then ranked by price change,…

AkcijasĶīnas tirgiTirgus mikrostruktūraVēsturisko datu pārbaude
SuperMind

The document presents a method for moderating drawdowns by reducing the capital base used to size trades as portfolio value falls. It first defines maximum drawdown as the largest peak-to-later-trough decline relative to the earlier value. Its adjustment…

Riska pārvaldībaPozīcijas apjoma noteikšanaVēsturisko datu pārbaudeAkcijas
SuperMind

This note proposes screening Chinese mainboard stocks using an RSI below 65, a daily gain above 1%, and prior-day trading value above 60 million yuan. The stated intent is to combine a moderate RSI reading, recent upward price movement, and a liquidity…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This note describes a Chinese equity screen combining daily price range, free-float market capitalization, and the direction of the 30-day moving average. It selects stocks with an intraday range of at least 1%, free-float capitalization above 10 billion…

AkcijasĶīnas tirgiSekošana tendenceiTehniskie indikatori
SuperMind

This short-term A-share screening idea focuses on stocks classified in the metaverse theme that appeared on the prior day’s exchange trading-activity list, while excluding stocks that reached the stated near-limit-up threshold. The article expresses these…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaTirgus noskaņojums
SuperMind

This A-share stock selection idea combines a turnover filter with a short-term price decline and a longer-term trend condition. It screens for stocks with turnover between 3% and 12%, seven consecutive down days, and weekly MACD above zero. The article…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This note proposes a Chinese equity screen requiring price amplitude above 1%, a reversal or engulfing-style pattern, and positive net buying attributed to major participants during the opening auction. It explains the signals as indicators of short-term…

AkcijasTehniskie indikatoriCenas impulssTirgus noskaņojums
SuperMind

This note describes a simple Chinese equity screen combining daily price amplitude above 1%, a closing price of 18.5 yuan, and a positive return below 35% over ten days. It frames the filters as a way to find volatile stocks with moderate prices and recent…

AkcijasCenas impulssSvārstīgumsTehniskie indikatori
SuperMind

This Chinese equity screening idea combines three filters: a daily increase in positions above 5%, previous-day actual turnover between 3% and 28%, and a dividend ratio above 25% for 2019. The accompanying explanation treats position growth as a sign of…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
SuperMind

This document outlines a Chinese equity screening rule that combines daily price movement with a short moving average and a lower low. The stated final criteria are amplitude above 1, the close crossing above a five-day moving average, and today’s low…

AkcijasTehniskie indikatoriSvārstīgumsVēsturisko datu pārbaude
SuperMind

This stock-screening example combines a technical condition with reported earnings growth and trading activity. It selects A-share stocks with a 14-period RSI below 65, year-over-year growth in parent-company net profit from above 20% through 100%, and a…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This screening concept selects stocks tagged with the metaverse theme, whose close is above the prior day's low, and whose weekly five-period moving average has crossed above the weekly ten-period average. The article interprets the industry label as a…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock-screening idea combines three conditions: MACD above zero, upward-moving averages, and price above the five-day moving average. The accompanying Python example calculates MACD from exponential moving averages and compares the five-day average with…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This stock-selection screen combines three conditions: daily range as a percentage of the prior close above a threshold, the current high equal to the highest high over the current and previous day, and the 20-day moving average above the 120-day moving…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

This post outlines a short-term Chinese stock screen that requires amplitude above 1, ranks stocks by the day’s auction amount, keeps the top five, and requires the closing price to exceed the previous day’s low. The suggested interpretation is that elevated…

Ķīnas tirgiAkcijasSvārstīgumsTehniskie indikatori
SuperMind

This document describes a Chinese stock screen using daily price movement and convertible bond information. It selects stocks with an amplitude above 1, a nonempty name for outstanding convertible debt, and a daily return between negative 5% and positive…

Ķīnas tirgiAkcijasSvārstīgumsTehniskie indikatori
SuperMind

This document proposes a daily pre-open stock screen centered on MACD being above the zero line, then ranks qualifying names by a measure of individual-stock attention. It also includes a listing-age filter, described as favoring companies that have been…

AkcijasCenas impulssTehniskie indikatoriTirgus noskaņojums