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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

The document presents a stock screen for securities whose codes begin with the specified Shanghai prefix, whose daily trading range exceeds a threshold, and whose moving averages are described as diverging upward. It includes a technical formula and a Python…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The document describes a Chinese equity selection rule combining turnover, the ratio of market buy volume to market sell volume, and institutional net buying. It filters for turnover between the stated bounds, a buy-to-sell volume ratio above the specified…

AkcijasĶīnas tirgiCenas impulssTirgus mikrostruktūra
SuperMind

The document proposes a stock screen that combines price amplitude above one, a rising sequence of recent lows, and a positive price-to-earnings ratio. It presents these as technical and fundamental filters intended to identify shares with substantial…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This short programming example shows how to screen daily stock data with several conditions at once, then select only the desired columns. The example combines a date cutoff, a minimum trading amount, and a maximum closing price using boolean masks joined…

AkcijasĶīnas tirgi
SuperMind

This stock-selection rule screens companies associated with the metaverse theme, requiring a volume ratio above 1.5 and below 6, alongside circulating market value above 10 billion yuan. The rationale is to combine a thematic industry filter with relatively…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This post describes an equity screen that combines membership in the metaverse concept group with two price conditions: the close must exceed the previous session’s low, and the open must fall within ten percent above or below the ten-day simple moving…

AkcijasTehniskie indikatoriĶīnas tirgiRiska pārvaldība
SuperMind

This post describes a China A-share screening idea focused on stocks in the metaverse sector. It adds two filters: a morning price-change condition below six percent and a measure intended to indicate that large participants controlled trading on the prior…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese-language post outlines a stock screen combining three conditions: price amplitude above one, prior-day turnover above 60 million, and MACD above its zero line. It frames amplitude as a measure of price movement, turnover as a gauge of activity,…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

The article describes a stock screen that excludes Beijing-listed shares, selects stocks with a daily high-low range above one percent, and applies a filter based on the prior day's turnover and the ratio of current opening-auction volume to the previous…

AkcijasĶīnas tirgiSvārstīgumsTehniskie indikatori
SuperMind

This stock selection rule screens companies in the metaverse theme for a closing price above the five-day moving average, trading volume above the stated threshold, and an opening price above the previous close. The article presents these conditions as a way…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This article proposes screening stocks with turnover between three and twelve percent, displayed best-bid volume greater than best-ask volume, and a prior-day condition described as a 9:15 matched price at the daily limit-down. The first two filters are…

Ķīnas tirgiAkcijasTirgus mikrostruktūraRiska pārvaldība
SuperMind

This brief article presents ten questions about common assumptions in quantitative research. They concern whether researchers must be highly skilled in statistics, whether borrowed methods can be adopted without adaptation, and whether more variables, more…

StatistikaVēsturisko datu pārbaude
SuperMind

This article outlines a Chinese equity screen for stocks in the metaverse sector. It combines bullish technical signals, including MACD and short moving-average crossovers, with a filter intended to exclude stocks that hit the daily price limit on the…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The proposed stock screen filters for amplitude above 1 and a closing price below 20, then ranks candidates by today's auction amount and selects the top five. The article also gives example indicator and Python logic, including a comparison of current and…

AkcijasTehniskie indikatoriĶīnas tirgiSvārstīgums
SuperMind

This stock screen combines three technical conditions: daily amplitude above 1, MACD above its zero line, and closing price above the five-day moving average. The document explains these as filters for price movement and recent upward direction, then gives…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

The document presents a Chinese equity screen that requires a 14-period RSI below 65, a circulating market value between 5 billion and 10 billion yuan, and exclusion of Beijing-listed A shares. The example code applies these filters and, when enough…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document describes a Chinese equity selection rule combining a daily range filter, afternoon large-order net inflow, and a score based on price change multiplied by a large-order volume measure. It ranks candidates by the resulting score and selects the…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The stated screen looks for stocks with turnover between 3% and 12%, a listing year of 2021, and ownership concentration below 20%. The article treats lower concentration as a sign of more dispersed ownership and suggests that the turnover band may help…

AkcijasĶīnas tirgiRiska pārvaldībaStatistika
SuperMind

The screen selects stocks with turnover between 3% and 12%, beginning with the Chinese stock-code prefix 60, and keeps companies whose 2021 revenue exceeded their 2018 revenue by more than 10%. The article describes this as a way to combine trading activity…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
SuperMind

This stock screen ranks companies by a measure of capital strength, such as net inflows or trading value, and requires at least two limit-up sessions within a 500-day window. The article frames the screen as targeting stocks with strong buying interest and…

AkcijasĶīnas tirgiCenas impulssStatistika
SuperMind

This Chinese stock-screening strategy combines a turnover range of 3% to 12%, at least one limit-up event in the prior 25 days, and positive net buying by major participants during the opening auction. The article presents a screening expression and a Python…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document describes a Chinese equity screen combining a daily price range above 1%, a condition that the prior session was not limit-up, and a recent three-session rise. It presents the screen as a way to find volatile stocks with positive price momentum…

AkcijasCenas impulssSvārstīgumsĶīnas tirgi
SuperMind

This Chinese-language post describes a short-term stock screen using three conditions: a 14-period RSI below 65, first-level buy volume greater than first-level sell volume, and prior-day trading value above 60 million. It frames the RSI as a price-condition…

AkcijasTehniskie indikatoriTirgus noskaņojumsStatistika
SuperMind

The document describes a Chinese equity screen combining daily price amplitude above 1%, membership in a robotics concept group, circulating market capitalization below 10 billion yuan, and a six-period RSI below 65. It gives example implementations in…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss