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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: 3,481

BigQuant

This post describes a Chinese equity factor inspired by a research report. Its volume component divides the trading session into five-minute intervals, measures each stock’s share of market volume, and uses Shannon entropy to characterize how that activity…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaStatistika
BigQuant

This example queries Chinese stock valuation data for a specified date and examines the distribution of total market capitalization. It trims observations below the second percentile and above the ninety-eighth percentile, divides the remaining values into…

AkcijasĶīnas tirgiStatistika
BigQuant

This report discusses how China’s changing investor mix may alter equity factor behavior, using earnings momentum as its example. It argues that institutionalization and international investment can support fundamental factors over the long term, while…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaCenas impulss
BigQuant

The document asks how to rebalance an existing stock portfolio to a fixed target weight per holding. Its proposed sequence is to sell positions removed from the selection, adjust retained positions back to the target allocation, and then buy newly selected…

AkcijasPortfeļa veidošanaPozīcijas apjoma noteikšanaRīkojumu izpilde
BigQuant

This research note proposes a price-spread deviation factor intended to measure whether a stock is relatively expensive or cheap compared with similar stocks. It frames the signal as a relative reversal measure: stocks that have recently lagged peers are…

AkcijasAtgriešanās pie vidējās vērtībasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This stock-screening proposal selects companies assigned to a metaverse industry category, requires a positive return condition, and looks for at least one limit-up event during the preceding 25 days. It gives both a platform formula and a Python-oriented…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
BigQuant

This document summarizes an investment research paper on incorporating environmental, social, and governance risks into emerging-market analysis. Its central argument is that these markets can be more exposed to issues such as extreme weather, resource…

AkcijasRiska pārvaldībaPortfeļa veidošana
BigQuant

The document describes Panoptic, a decentralized protocol that offers perpetual options linked to Uniswap liquidity pools. It explains how concentrated liquidity ranges can serve as strike selection and how liquidity provision can create option-like…

KriptoaktīviOpcijasSvārstīgumsDeFi
BigQuant

This research summary describes combining order-book data, which may reflect traders’ unexecuted intentions, with transaction-level data showing completed trades. The authors use both intuitive signal construction and machine learning to turn different types…

AkcijasAugstas frekvences tirdzniecībaMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

The document explains beta as an asset’s sensitivity to market returns and gives the covariance of asset and market returns divided by market-return variance as its calculation. It illustrates the calculation with a short set of monthly portfolio and…

StatistikaRiska pārvaldībaFaktoru ieguldīšana
BigQuant

This brief support exchange addresses whether StockRanker’s tree model can use L1 or L2 regularization and how to improve model stability. The response says that StockRanker does not currently expose regularization as a way to prevent overfitting. It…

MašīnmācīšanāsRiska pārvaldība
BigQuant

This overview surveys the use of large language models and other AI methods across quantitative investing. It describes extracting sentiment and information from financial text, combining text with time-series data for market and risk forecasts, supporting…

MašīnmācīšanāsTirgus noskaņojumsPortfeļa veidošanaRīkojumu izpilde
BigQuant

This brief forum exchange asks how to interpret a random forest model’s predicted label after returns have been divided into twenty classes. The question is whether the output represents a class identifier or a return value, and whether regression metrics…

MašīnmācīšanāsStatistikaAkcijas
BigQuant

This practitioner essay presents risk management as a process spanning strategy research, deployment, live operation, and review. It recommends examining a strategy’s behavior in severe historical drawdowns, including whether losses remain controlled,…

Riska pārvaldībaVēsturisko datu pārbaudeRīkojumu izpildePortfeļa veidošana
BigQuant

This forum post raises questions about translating factor functions from BigQuant version 1.0 to version 3.0. It asks whether the RSI function retains its name or uses a prefixed variant, and whether ranking should use a cross-sectional or unprefixed…

Faktoru ieguldīšanaTehniskie indikatoriStatistika
BigQuant

The document reproduces a pandas performance warning raised during a backtest while data is being written to HDF storage through PyTables. The warning says that a block of columns contains mixed object types that PyTables cannot map directly to its native C…

Vēsturisko datu pārbaudeRīkojumu izpildeStatistika
BigQuant

This support note addresses an error encountered while extracting basic features for Chinese convertible bonds. The reported failure says the feature extraction module does not recognize the CN_CONBOND market. The response recommends connecting through the…

Ķīnas tirgiFiksēta ienākuma instrumenti
BigQuant

This overview describes how to read simulated strategy performance based on historical data. It defines several commonly reported measures: total return and annualized return for gains over time, maximum drawdown for peak-to-trough loss, Sharpe ratio for…

Vēsturisko datu pārbaudeRiska pārvaldībaStatistika
BigQuant

This opinion article argues that quantitative trading can intensify volatility in China’s A-share market and disadvantage investors who lack comparable speed or technology. It attributes these effects to strategies that respond to market rules and short-term…

Ķīnas tirgiAkcijasAugstas frekvences tirdzniecībaTirgus mikrostruktūra
BigQuant

This broad educational overview introduces mathematical tools used in stock analysis and algorithmic trading. It covers descriptive statistics, including measures of central tendency and dispersion, and explains how visualizations can help reveal…

AkcijasStatistikaTehniskie indikatoriRiska pārvaldība
BigQuant

This research review presents the frog-in-the-pan hypothesis: investors may respond less promptly to a sequence of small, gradual price moves than to a similarly sized change concentrated in a few sharp moves. It describes an information-discreteness measure…

AkcijasCenas impulssStatistikaTirgus noskaņojums
BigQuant

This document describes a local tool for reviewing trading records produced by the Wanhe file-order system. The user selects the system’s service log folder, runs an analysis, and views account trading logs, an account equity curve, trade history, and daily…

AkcijasRīkojumu izpildeRiska pārvaldība
BigQuant

This tutorial explains how to aggregate one-minute bars into longer intraday bars, using a Chinese stock session as its example. It shows the standard time-series resampling approach: assign open from the first observation, high and low from the extrema, and…

AkcijasNākotnes līgumiStatistikaTirgus mikrostruktūra
BigQuant

The report examines how changes in market interest rates can affect listed companies’ net profits through interest expense. It compares industries by the importance of financial expenses relative to net profit, finding higher exposure in areas such as light…

AkcijasFiksēta ienākuma instrumentiStatistikaRiska pārvaldība