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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 introductory example builds a daily A-share strategy around a five-day and twenty-day moving average. It selects one stock, retrieves recent closing prices, computes both averages, buys to a fully invested target when the shorter average is higher, and…

AkcijasTehniskie indikatoriSekošana tendenceiVēsturisko datu pārbaude
SuperMind

This A-share screening idea looks for metaverse-theme stocks that appeared on a trading leaderboard and whose closing prices fell over three consecutive sessions. The article describes the combination as a way to find potentially low-priced or reversal…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This short-term A-share screening idea selects stocks classified in the metaverse theme that appeared on the prior day's trading leaderboard and have positive large-order net flow. The article frames leaderboard activity and order-flow ranking as signs of…

AkcijasĶīnas tirgiTirgus noskaņojums
SuperMind

This stock-selection recipe targets A-share stocks when daily high-to-low amplitude exceeds one percent, a reversal or engulfing condition is present, and a morning-star candlestick signal appears. The article describes combining the filters to seek possible…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This Chinese equity screen targets stocks classified in the metaverse sector, with circulating share capital at or below 5.5 billion shares, that have recorded three consecutive declining sessions. The article frames the sequence of down days as a short-term…

Ķīnas tirgiAkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

The proposed screen selects Chinese shares where at least five moving averages converge, excludes Beijing-listed A shares, and requires the quoted 9:25 a.m. gain to be below 6%. The article interprets convergence as alignment among short- and long-term…

Ķīnas tirgiAkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This stock selection method combines three filters: rank shares by volume ratio and retain the top 100, rank them by previous-day net inflow attributed to major investors and retain the top 100, and require the 20-day moving average to exceed the 120-day…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This screen selects stocks with turnover between 3% and 12%, a listing in the prior day's trading-rank data, and a current increase in holdings above 5%. The article presents these criteria as proxies for trading activity, notable investor participation, and…

Ķīnas tirgiAkcijasTirgus mikrostruktūraCenas impulss
SuperMind

This stock-selection proposal combines an RSI below 65 with a positive price-to-earnings ratio and a historical filter tied to 2021. The final description specifies stocks in the upper half of that year's gain ranking, while the earlier explanation only says…

Ķīnas tirgiAkcijasTehniskie indikatoriStatistika
SuperMind

This proposed stock screen combines three filters: a rising 30-day moving average, convergence among at least five moving averages, and a non-empty name for an outstanding convertible bond. The example moving-average periods are 5, 10, 20, 60, and 120 days.…

Ķīnas tirgiAkcijasTehniskie indikatoriSekošana tendencei
SuperMind

This stock screen combines three signals: more than two limit-up sessions in the prior ten trading days, reported major-investor control on the previous day, and a current increase in holdings above 5%. The document describes the first condition as a marker…

Ķīnas tirgiAkcijasCenas impulssCenas izrāviens
SuperMind

This proposed screen targets Shenzhen main-board stocks with a price-to-earnings ratio from 0 to 29.01 and a price-to-book ratio from 0 to 3.11, alongside a 9:25 a.m. gain below 6% and a reported increase in holdings above 5%. The article interprets the flow…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTirgus noskaņojums
SuperMind

This proposed Chinese equity screen combines three signals: at least five moving averages described as overlapping, more than two limit-up sessions within ten days, and a 20-day moving average above the 120-day average. The article frames the limit-up count…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese equity screening proposal combines a 20-day moving average above the 120-day average with descending capital-flow strength and a company-type or industry classification. The moving-average relationship is presented as a sign that the…

AkcijasĶīnas tirgiSekošana tendenceiTehniskie indikatori
SuperMind

This note describes a Chinese equity screen combining a daily turnover band of 3% to 12%, appearance on the prior day’s 龙虎榜 (a public list of unusual trading activity), a listing age above 240 days, and exclusion of stocks that closed at the prior day’s…

AkcijasĶīnas tirgiTehniskie indikatori
SuperMind

This proposed stock screen selects shares whose largest decline for the day falls between four and five percent below zero. The article frames the move as a possible source of short-term rebound potential and adds filters for market capitalization,…

AkcijasĶīnas tirgiAtgriešanās pie vidējās vērtībasRiska pārvaldība
SuperMind

This proposed Chinese equity screen combines three signals: ten-day price appreciation above zero but below 35, positive afternoon net inflows from large orders, and ranking by capital intensity. The stated rationale is to find stocks with recent upward…

AkcijasĶīnas tirgiCenas impulssTirgus noskaņojums
SuperMind

This document proposes screening main-board stocks for turnover between 3% and 12%, a reversal or engulfing-style setup, and an auction-period return between -2% and 5%. The stated logic combines a minimum level of trading activity with a price-reversal…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This document describes a stock-selection idea that combines three signals: ranking stocks by trading-flow strength, identifying a newly formed KDJ bullish crossover, and looking for shortening MACD histogram bars on a 15-minute chart. It frames trading-flow…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This document outlines a short-term A-share stock screen combining turnover between 3% and 12%, appearance on the prior day’s trading-activity list, and a weekly morning-star pattern. It presents these filters as a way to find liquid, actively traded stocks…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screen pairs a reported daily position increase above 5% with three consecutive declining sessions. The article frames the flow measure as potential buying interest and the declining closes as short-term weakness, then proposes adding…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This stock-selection approach combines a daily increase in reported holdings greater than 5% with upward-moving averages and a rising 30-day average. The article interprets the position increase as evidence of buying and the average-line conditions as signs…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This Chinese equity screening proposal combines afternoon net inflows from large orders with a ranking by capital-flow intensity, using measures such as turnover and volume ratio. It also limits the universe to companies with market capitalization below 10…

AkcijasĶīnas tirgiRīkojumu izpildeRiska pārvaldība