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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
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: 79,386

SuperMind

This Chinese stock-screening post combines three filters: rank stocks by a measure of capital inflow, require weekly MACD to be above its zero line, and keep stocks whose ten-day gain is positive but below 35%. The author frames the filters as a way to find…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This Chinese equity screen selects stocks with daily amplitude above 1, turnover between 2% and 9%, and displayed first-level bid volume greater than first-level ask volume. The article frames amplitude and turnover as activity and liquidity measures, with…

Ķīnas tirgiAkcijasTirgus mikrostruktūra
ProRealCode

This indicator plots a conventional RSI of closing prices alongside an RSI calculated from a multi-vote On-Balance Volume series. The OBV component assigns directional votes based on changes in the high, close, and low, averages those votes, weights them by…

AkcijasTehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screening method combines daily amplitude above 1, a weekly crossover of the five-period moving average above the ten-period average, and a positive change in the KDJ K value. The article presents the conditions as a way to identify…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
SuperMind

This Chinese equity screen combines daily price amplitude above 1, a positive weekly MACD reading, and a market-cap rank between the 20th and 70th percentiles. The article also describes ranking candidates by volume relative to its 20-period average, then…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
MQL5 code base

This expert advisor uses a moving average to generate directional entries. Four consecutive declining moving-average values establish a downward trend condition, with a price rebound above the latest average triggering a sell; four rising values establish an…

Valūtu tirgusTehniskie indikatoriPozīcijas apjoma noteikšanaRiska pārvaldība
MQL5 code base

This indicator presents the standard Relative Strength Index as a histogram after rounding its readings to configurable increments. The described settings range from no rounding to progressively coarser groupings, including a three-level display at zero, the…

Tehniskie indikatoriAkcijasValūtu tirgus
SuperMind

This Chinese-language post describes an equity screening rule combining price amplitude above a threshold, a rounded or arc-like price pattern, and a signal that the stock was controlled by major traders on the previous day. It presents the combination as a…

AkcijasTehniskie indikatoriRiska pārvaldība
ProRealCode

This long-only daily strategy seeks short-term rebounds in equity index CFDs while limiting entries to prices above a 200-period moving average. It sums RSI readings over the most recent two periods and enters when this cumulative measure falls below 35,…

AkcijasAtgriešanās pie vidējās vērtībasTehniskie indikatoriRiska pārvaldība
BigQuant

This brief request proposes a factor based on the correlation between a benchmark’s returns and an individual stock’s returns over a three-day window. It names the intended inputs and lookback, but provides no code, worked example, explanation of how to…

AkcijasStatistikaFaktoru ieguldīšana
SuperMind

This stock-selection idea combines three filters: a daily trading range above one percent of the previous close, a stock code beginning with 60, and a positive afternoon large-order flow signal. The code example operationalizes the range and code filters,…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
BigQuant

This April 2020 market note reviews a sharp decline in Chinese equities amid weakening fundamentals and falling investor sentiment. It reports that large- and small-cap indexes had similar declines, while consumer and utility sectors held up better and…

AkcijasĶīnas tirgiPortfeļa veidošanaRiska pārvaldība
MQL5 code base

This programming note explains how an object-oriented trading advisor can manage its configurable inputs as a structured set. It contrasts manually declaring fields and writing string conversion methods with a macro-based library that generates parameter…

Rīkojumu izpildeVēsturisko datu pārbaudePortfeļa veidošana
SuperMind

This note describes a Chinese equity screen for stocks associated with the metaverse concept. It requires turnover between 3% and 12% and at least one limit-up event during the prior 25 days. The accompanying examples translate these conditions into…

AkcijasĶīnas tirgiCenas impulssCenas izrāviens
SuperMind

This note outlines a screen for Chinese equities associated with the robotics concept. It combines turnover between 3% and 12%, floating market capitalization below 10 billion yuan, and a ratio of 2021 revenue to 2018 revenue above 1.1. The post includes…

AkcijasĶīnas tirgiFaktoru ieguldīšanaRiska pārvaldība
SuperMind

This note describes a Chinese A-share filter combining a turnover rate between 3% and 12%, a Dragon-Tiger list appearance the previous day, and a floating market capitalization between 5 billion and 10 billion yuan. It presents this as a way to find actively…

AkcijasĶīnas tirgiTirgus mikrostruktūraRiska pārvaldība
MQL5 code base

The method treats signals from an indicator as candidate highs or lows rather than immediate trade entries. It uses zigzag-style logic to connect candidate pivots and checks whether each candidate can form a geometrically plausible leg. A candidate that…

Tehniskie indikatoriCenas izrāviensRiska pārvaldība
BigQuant

This note explains how to handle low-frequency financial or analyst factors alongside daily price and volume factors when constructing nonlinear models. One approach is to merge monthly or quarterly fundamentals with daily market data and carry the latest…

MašīnmācīšanāsFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
SuperMind

This stock-selection approach combines a positive MACD reading with a company-type condition and circulating market capitalization above 10 billion yuan. The document presents the screen as a way to find stocks with upward price trends, sound fundamentals,…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This post outlines a Chinese A-share stock screen combining an RSI below 65, seven consecutive down days, and a weekly five-period moving average crossing above the ten-period average. It presents the conditions as a way to identify stocks with a potentially…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
BigQuant

This brief note describes a feature-selection exercise based on a random forest template. The author says they ranked 37 stock factors by random forest importance and retained the nine factors with the highest importance scores. The document does not…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsStatistika
BigQuant

This Chinese-language research summary discusses forecasting stock-selection factor returns after commonly used factors became more volatile. It focuses on screening timing variables with Lasso and Elastic Net regression, then extending factor timing with…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

The post raises a backtesting concern: a user observes that a stock delisted on one date still appears sellable on a later scheduled rebalance date. A reply explains the platform behavior as a special backtest-engine rule: when a strategy does not handle a…

Vēsturisko datu pārbaudeAkcijasRiska pārvaldība
SuperMind

The post describes a proposed screen for main-board Chinese stocks. It combines a turnover-rate band, membership in the robotics concept, float market value below a stated threshold, and a prior-day 9:15 matching price at the daily limit down. The author…

Ķīnas tirgiAkcijasAtgriešanās pie vidējās vērtībasRiska pārvaldība