Pāriet uz saturu

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 Chinese-language post outlines a historical stock-selection rule: select shares with turnover between 3% and 12% that recorded seven consecutive daily declines during 2021. It presents this as a way to identify possible rebound candidates after a…

AkcijasĶīnas tirgiAtgriešanās pie vidējās vērtībasTehniskie indikatori
SuperMind

This Chinese-language post presents a stock screen for companies in the metaverse industry. It combines a newly formed bullish KDJ crossover with a long-term price filter: the prior day’s closing price is described as being above the 250-day moving average.…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post describes a technical screen for stocks in the metaverse industry. It calls for three indicators to form bullish crossovers at the same time and for the closing price to exceed the previous session's low. The post's concrete formula and code…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post proposes screening Chinese equities for turnover between 3% and 12%, a newly formed KDJ bullish crossover, and at least one daily gain of 10% or more during the prior 25 trading sessions. It frames turnover as a measure of trading activity, the…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post describes a Chinese stock-selection screen combining three conditions: current amplitude above a threshold, a prior-day 9:15 indicative auction price at the limit-down price, and prior-day turnover above 60 million. It frames these filters as a way…

AkcijasĶīnas tirgiTirgus noskaņojumsTehniskie indikatori
SuperMind

This overview explains chip distribution as the estimated quantity of shares held across different purchase-price ranges. A distribution chart is presented as a way to infer where investors’ costs cluster, how concentrated holdings may be, and how those…

AkcijasTirgus mikrostruktūraTirgus noskaņojumsTehniskie indikatori
SuperMind

This stock-selection note combines three filters: amplitude above 1, at least one daily gain of 10% or more in the previous 25 trading days, and actual turnover on the prior day between 3% and 28%. The author frames these conditions as a way to find…

AkcijasCenas impulssSvārstīgumsĶīnas tirgi
SuperMind

This Chinese stock-screening note describes selecting shares with an amplitude above 1 and a ratio of yesterday’s turnover rate multiplied by today’s auction volume divided by yesterday’s volume between 0.5 and 2. It also requires recent trading data, with…

AkcijasSvārstīgumsĶīnas tirgi
SuperMind

This Chinese stock-selection note describes a screen using price amplitude above one percent, company scale above 200 million, and a ten-day return greater than zero but below 35 percent. Its expanded version also requires a positive price-to-earnings ratio…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This Chinese A-share screening idea combines three conditions: daily price amplitude above one percent, at least one limit-up event during the preceding 25 days, and a positive institutional-direction measure. The accompanying discussion treats volatility as…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

The document describes buying already-listed Chinese convertible bonds at lower prices and selling them higher, including the appeal of same-day trading and lower stated transaction fees than stocks. It contrasts this approach with bond subscriptions and…

Ķīnas tirgiFiksēta ienākuma instrumentiArbitrāžaRiska pārvaldība
SuperMind

The proposed Chinese stock screen combines a 20-day moving average above the 120-day average with RSI below 65 and a revenue ratio above 1.1 for 2021 compared with 2018. It presents the moving-average relationship as a filter for an upward trend, alongside…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The document describes a zero-lag moving average intended to reduce the delay of a conventional moving average. It forms the indicator by taking twice a first moving average of price and subtracting a second moving average applied to that smoothed series.…

Tehniskie indikatoriStatistika
SuperMind

This research summary describes style drift in active equity mutual funds: departures from a fund’s stated investment mandate that can expose investors to unintended risks. It characterizes style along size, value versus growth, and momentum dimensions, and…

AkcijasFaktoru ieguldīšanaCenas impulssRiska pārvaldība
SuperMind

This stock screen combines turnover, prior-day leaderboard inclusion, and Bollinger Band position. It selects shares with turnover between 3% and 12% whose close is above the middle band but below the upper band, using the conditions as a proxy for trading…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

This stock screen selects shares with an intraday high-low range greater than 1%, a newly formed KDJ golden cross, and a price pattern characterized as arc-shaped. The article interprets the range condition as evidence of volatility, the KDJ cross as a…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This A-share screening idea combines three conditions: RSI below 65, a circulating market value between 5 billion and 10 billion yuan, and at least one daily gain of 10% or more during the previous 25 trading days. The article explains these as a blend of a…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese-language post describes a stock screen combining a positive MACD reading, a favorable but undefined company-quality condition, and a rising sequence of short- to longer-term moving averages. Its indicator formula specifies MACD above zero and…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post presents a stock-selection screen for companies in the metaverse sector. It requires yesterday’s turnover rate to exceed 8% and current best-bid quantity to be greater than best-ask quantity. The author interprets the order-book…

Ķīnas tirgiAkcijasTirgus mikrostruktūraTirgus noskaņojums
SuperMind

The document proposes a stock screen using turnover between 3% and 12%, a K value below 20, and a positive rise in the KDJ K line. It frames low K as an oversold-style filter and rising K as a short-term improvement signal, then recommends considering…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
SuperMind

The document presents a stock screen combining daily price movement with two momentum indicators. It selects shares whose amplitude exceeds 1%, whose KDJ K value is below 20, and whose RSI is below 65. The accompanying examples describe calculating these…

AkcijasTehniskie indikatoriVēsturisko datu pārbaudeRiska pārvaldība
SuperMind

This A-share stock-selection rule screens for turnover between 3% and 12%, a positive return below 35% over ten days, and at least five overlapping moving averages. The accompanying formula describes five averages with periods of 5, 10, 20, 30, and 60 days,…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese A-share screening example selects stocks with daily amplitude above 1%, rising short-term moving-average behavior, a robotics theme, and circulating market capitalization below 10 billion yuan. It outlines the idea in prose and gives…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība