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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: 79,386

BigQuant

The post raises a reproducibility question: two strategy templates reportedly use the same model, factors, parameters, and data, yet produce substantially different backtest results. The author asks which result is correct and whether one template contains…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeStatistika
BigQuant

This report evaluates 18 financial-quality, price-volume, and analyst-expectation factors for Chinese equities. It compares factor-ranked portfolios, including high-ranked and low-ranked groups, considers the stability of their performance differences, and…

AkcijasFaktoru ieguldīšanaCenas impulssAtgriešanās pie vidējās vērtības
SuperMind

This note proposes screening stocks for daily amplitude above 1, a weekly five-period moving average crossing above the ten-period average, and a ratio of externally initiated buying volume to selling volume greater than 1.3. The combination is intended to…

AkcijasCenas impulssTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This note describes a stock-selection screen based on daily amplitude above 1, a positive weekly MACD histogram, and a ten-day return greater than zero but below 35%. The intended combination seeks stocks with active price movement, a positive weekly trend…

AkcijasCenas impulssSvārstīgumsTehniskie indikatori
SuperMind

This note proposes a Chinese equity screen combining three filters: a 14-period RSI below 65, circulating market capitalization of at least 200 million yuan, and a price gain below 6% at the 9:25 pre-open snapshot. The stated rationale is to select stocks…

AkcijasTehniskie indikatoriĶīnas tirgi
FMZ forum

The note explains four combinations of price direction and trading volume: rising prices with lower or higher volume, and falling prices with lower or higher volume. It frames volume as evidence of trading activity and uses a used-car market analogy to…

AkcijasTehniskie indikatoriTirgus mikrostruktūra
MQL5 code base

This document describes adding notifications to a semaphore-style indicator based on Williams Percent Range signals as the oscillator leaves overbought or oversold territory. The additions let a user choose the bar used for signal checks, enable sound,…

Tehniskie indikatoriRīkojumu izpilde
SuperMind

This stock-selection proposal screens Chinese A-share listings in the metaverse industry, ranks them by the day’s opening-auction amount, and selects those with simultaneous bullish crossovers in MACD, KDJ, and RSI. The text gives example indicator settings…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
BigQuant

The article examines whether the rise of the Chinese A-share market from 3,000 to 4,000 points marks a peak or the beginning of a larger bull market. It attributes the 2025 advance mainly to technology stocks and proposes looking beyond price charts to…

AkcijasĶīnas tirgiCenas impulssTirgus noskaņojums
SuperMind

This document outlines a short-term A-share screen for companies classified in the metaverse theme. It selects stocks that appeared on the prior day’s trading leaderboard, have current trading volume above the stated threshold, and open above the previous…

AkcijasCenas impulssCenas izrāviensĶīnas tirgi
FMZ forum

This discussion examines how starting portfolio composition can distort a simple account-value profit calculation for a cryptocurrency strategy. It compares two accounts following the same price move: one begins with a bitcoin and no cash, while the other…

KriptoaktīviStatistikaVēsturisko datu pārbaude
SuperMind

This document describes a Chinese A-share screening idea based on stocks with a daily price range above a stated threshold, more than one year since listing, and three consecutive limit-up sessions ending the previous day. It presents the run of limit-ups as…

AkcijasCenas impulssĶīnas tirgiTehniskie indikatori
SuperMind

The proposed stock screen selects shares with MACD above zero, a positive price-to-earnings ratio, and an intraday high–low range greater than one percent of the previous close. The article interprets these conditions as combining upward momentum, a positive…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
MQL5 code base

FitFul 13 is described as an expert advisor that calculates its main levels on the weekly timeframe, with level settings specified using two additional timeframe inputs. It limits the number of simultaneously open positions to three. The advisor obtains…

Valūtu tirgusTehniskie indikatoriRīkojumu izpildeRiska pārvaldība
MQL5 code base

The Nadaraya–Watson estimator, attributed here to Nadaraya and Watson in 1964, estimates values with a locally weighted average. A kernel function assigns the weights, producing a smoothed series that can help a reader visually assess a possible trend. The…

Tehniskie indikatoriStatistika
Qlib

Qlib is introduced as a modular platform for researching quantitative investment strategies with AI and machine learning. Its components are loosely coupled, so parts of the platform can be used independently. The architecture is organized into…

MašīnmācīšanāsPortfeļa veidošanaRīkojumu izpildeStatistika
MQL5 code base

The document describes a proposed dashboard indicator for monitoring active symbols and pairs in spread or equity trading. Its interface is meant to track changes in the selected symbols, retain settings during terminal changes, and let users set each pair's…

AkcijasPāru tirdzniecībaAtgriešanās pie vidējās vērtībasTehniskie indikatori
SuperMind

The document proposes a Chinese stock screen that combines three short-term signals: buying activity above 5%, a previous-day 9:15 matched price at the limit-down level, and a shrinking green histogram on the 15-minute MACD. It interprets the buying measure…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
Lumibot

This documentation explains how Lumibot represents cash flows separately from trading activity in strategy backtests and live broker data. It distinguishes deposits and withdrawals from performance while accounting for financing, dividends, fees, interest,…

Vēsturisko datu pārbaudeRiska pārvaldībaPortfeļa veidošanaRīkojumu izpilde
SuperMind

This Chinese equities selection concept ranks stocks by volume ratio and by prior-day net inflows attributed to major investors, retaining the top 100 in each ranking. It also states a 2021 start date, though the practical meaning of that date in the…

AkcijasĶīnas tirgiTirgus mikrostruktūra
SuperMind

This Chinese equities screen combines three chart-based conditions: an amplitude above 1, a rounded price shape, and a positive 10-day return below 35%. The accompanying formula represents the rounded-shape condition by comparing the previous close’s…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
BigQuant

This document indexes 50 articles published in 2017, grouped into topics such as computer vision, recommendation, games, speech, language processing, and prediction. The list includes a stock-price forecasting tutorial alongside examples from other fields,…

Mašīnmācīšanās
SuperMind

This Chinese-language document proposes a stock screen combining three conditions: amplitude above a stated threshold, a shrinking negative MACD histogram on a 15-minute interval, and the stock price above its five-day moving average. The rationale is to…

AkcijasTehniskie indikatoriCenas impulssStatistika
Amberdata research

The document explains how crypto data aggregators combine information from centralized and decentralized exchanges into normalized time series. It frames fragmentation across venues, trading pairs, and blockchains as an infrastructure problem for…

KriptoaktīviArbitrāžaVēsturisko datu pārbaudeRiska pārvaldība