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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
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 discussion addresses how to use a daily stock popularity ranking obtained through a query interface in a backtest when the research environment returns a dataframe but the backtest environment does not behave the same way. One suggested workflow is to…

AkcijasĶīnas tirgiVēsturisko datu pārbaudeRīkojumu izpilde
SuperMind

This post describes a stock screen restricted to a designated metaverse industry group. Within that group, it selects shares whose average price is above the five-day moving average and whose daily MACD is positive. The stated intent is to combine an…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese-language post outlines an equity screening idea that combines three signals: rank stocks by relative volume, require the 5-, 10-, and 20-day moving averages to be aligned upward, and look for a 15-minute MACD histogram that is shrinking while…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This stock-selection proposal combines a price-range filter, a historical dividend-yield condition, and a turnover-related condition. The stated screen looks for stocks with amplitude above 1%, a 2019 dividend ratio above 25%, and a turnover measure between…

AkcijasĶīnas tirgiFaktoru ieguldīšanaSvārstīgums
SuperMind

This stock selection concept combines moderate trading activity, recent price strength, and a technical trigger. It seeks stocks with turnover between 3% and 12%, at least one limit-up event in the preceding 25 days, and a newly formed KDJ golden cross. The…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The proposed Chinese equity screen combines three conditions: a recent increase in reported holdings or inflow, a weekly five-period moving average crossing above the ten-period average, and at least two limit-up sessions during the past 500 days. The post…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The article explains how to estimate the probability of a binary outcome using Bayesian inference. It uses coin flips to introduce a Bernoulli likelihood for observations and a Beta distribution as a prior for the unknown success probability. Because these…

StatistikaRiska pārvaldība
SuperMind

The document describes a stock screen that selects shares with a prior-day price range above 1%, more than a year since listing, and prior-day turnover above 8%. It explains the intended rationale: range and turnover are treated as signs of activity, while…

AkcijasĶīnas tirgiTehniskie indikatoriVēsturisko datu pārbaude
SuperMind

This document proposes a Chinese stock screen using three signals: a high volume ratio, a rounded price pattern approximated through Bollinger Band contraction or expansion, and at least two limit-up events over 500 days. It describes ranking stocks by…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This document describes a simple screen for Chinese metaverse-related equities. It selects stocks with circulating market capitalization above the stated cutoff and a ten-day price gain that is positive but below a specified upper bound. The accompanying…

Ķīnas tirgiAkcijasCenas impulssFaktoru ieguldīšana
SuperMind

This document presents a screen for Chinese metaverse-related stocks using prior-day turnover, current trading volume, and a positive opening gap. Its stated final version adds market capitalization ranking and earnings filters: stocks should rank in the top…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This document outlines a short-term Chinese stock screen combining large price ranges, at least two limit-up events over a 500-day window, and recent net buying attributed to institutions. It gives example indicator conditions for each filter and a Python…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This stock screen looks for names with turnover in a specified range, three consecutive declining sessions, a following close above the prior three day highs, and two consecutive positive sessions. It combines a liquidity filter with a pullback pattern and a…

AkcijasĶīnas tirgiTehniskie indikatoriCenas izrāviens
SuperMind

This stock screen selects equities with an amplitude above a threshold, excludes stocks that closed at the limit the prior day, and targets names whose daily percentage change falls within a narrow negative range. The stated rationale is that amplitude…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This note outlines an equity selection approach that filters for price amplitude above 1%, ranks stocks by market heat, and restricts the sample to trading dates in 2021. It explains amplitude as a sign of trading activity and treats high ranking by…

AkcijasĶīnas tirgiSvārstīgumsTehniskie indikatori
SuperMind

This note describes an A-share stock screen using a turnover ratio between 3% and 12%, at least one limit-up event in the previous 25 days, and exclusion of the STAR Market. It presents the criteria as a way to find moderately traded stocks with recent sharp…

AkcijasĶīnas tirgiCenas izrāviensTehniskie indikatori
SuperMind

This stock-screening approach combines a daily amplitude threshold with weekly MACD conditions: MACD should be above zero, and its histogram should be positive and growing relative to the prior week. The document describes these as a way to identify stocks…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

The document describes a Chinese equity screen that ranks stocks by reported capital-flow strength and selects those with more than two limit-up sessions in the past ten days and a rising 30-day moving average. It presents the flow measure as a proxy for…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

The post describes a stock-selection screen that combines daily price range, opening-auction trading amount, and recent limit-up frequency. Its stated final logic adds a recent low-amplitude condition: select stocks with amplitude above one, rank among the…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This A-share stock screen combines a technical condition with company earnings growth and a basic price check. It selects stocks with RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no greater than…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This note describes a Chinese stock screen that combines price and volume conditions. It seeks shares with amplitude above 1, a rising price bottom, current trading volume above 10,000 lots, and an opening price more than 3 percent above the previous close.…

AkcijasTehniskie indikatoriCenas izrāviensTirgus mikrostruktūra
SuperMind

This note outlines a Chinese equity screen for companies associated with the metaverse theme. It looks for a limit-up session within the preceding 25 trading days and a current control ratio above 21 percent. The stated rationale is to combine a recent…

AkcijasCenas izrāviensTehniskie indikatoriTirgus noskaņojums
SuperMind

This note describes a short-term Chinese stock screen combining price movement with recent momentum. It selects shares with an amplitude above 1, a positive but limited ten-day gain, and three consecutive limit-up sessions on the previous day. The…

AkcijasCenas impulssCenas izrāviensTehniskie indikatori