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: 3,481

BigQuant

The article answers practical questions about machine-learning stock strategies. It says the platform separates training and test periods by time, with the test interval serving as the backtest, and describes a setup without a separate validation set. It…

MašīnmācīšanāsVēsturisko datu pārbaudeStatistikaAkcijas
BigQuant

This research note reviews the CSI Dividend Index and the Bosera CSI Dividend ETF, which tracks it. The index draws 100 Shanghai and Shenzhen A-shares from stocks with high average after-tax cash dividend yields over the prior two years, then weights them by…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This monitoring framework tracks valuation measures and fund holdings across major Chinese equity indexes, industry groups, and selected large companies. It covers price-to-earnings, growth-adjusted valuation, price-to-book, dividend yields, and fund…

AkcijasĶīnas tirgiStatistikaFaktoru ieguldīšana
BigQuant

This research note studies value-based stock selection in Hong Kong equities, using the Hang Seng Composite as its universe. Because Hong Kong main-board companies are not required to publish quarterly reports and may change their fiscal year-end, the…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The discussion asks how to detect whether a value, such as a closing price or trading volume, has risen or fallen continuously over a chosen number of days. It points to a pair of time-series functions: one counts consecutive rises, and a corresponding…

Tehniskie indikatoriStatistika
BigQuant

The discussion explains how to interpret a Chinese stock daily-bar dataset that stores fully back-adjusted prices. It says the dataset includes a back-adjustment factor and describes recovering the underlying market price by dividing the adjusted close by…

AkcijasĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This report summary examines Chinese public mutual funds around the second quarter of 2018, focusing on actively managed equity funds. It describes falling scale and share counts for active equity products, differences in reported returns across fund types,…

AkcijasĶīnas tirgiPortfeļa veidošanaStatistika
BigQuant

This report summary examines Chinese public mutual funds around the second quarter of 2018, focusing on actively managed equity funds. It describes falling scale and share counts for active equity products, differences in reported returns across fund types,…

AkcijasĶīnas tirgiPortfeļa veidošanaStatistika
BigQuant

The document presents eight discretionary rules for interpreting stock price action. It treats steady small advances as possible accumulation and repeated sharp gains as a potential overextension. It also compares each stock’s behavior with the broad market:…

AkcijasTehniskie indikatoriCenas impulssTirgus mikrostruktūra
BigQuant

The document groups common Chinese A-share factors into style, technical, and fundamental categories. Style factors include market, size, and value; technical factors include reversal, low turnover, and low volatility; fundamental factors cover profitability…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

The document introduces the Commodity Channel Index (CCI), a technical indicator calculated from high, low, and close prices. It first derives typical price as the average of those three values, then compares typical price with its moving average and scales…

Tehniskie indikatoriStatistika
BigQuant

This project outlines a mean-reversion pairs strategy for Chinese futures. It screens candidate contract pairs for cointegration with an Augmented Dickey-Fuller test, estimates a changing hedge ratio with a Kalman filter, and measures spread behavior with…

Nākotnes līgumiĶīnas tirgiPāru tirdzniecībaAtgriešanās pie vidējās vērtības
BigQuant

This short description presents TEMACandle, an indicator that displays a price series as candlesticks after processing it with the Triple Exponential Moving Average (TEMA) algorithm. The transformation applies TEMA smoothing to the underlying price data and…

Tehniskie indikatoriAkcijas
BigQuant

This research summary describes a multi-factor investment workflow that combines alpha forecasts, a risk model, transaction-cost estimates, portfolio optimization, and performance attribution. It argues that simple score-based selection or sector and…

AkcijasPortfeļa veidošanaRiska pārvaldībaStatistika
BigQuant

This brief Chinese-language support note explains a prediction-data problem traced to missing values in a rolling price-range factor. The example factor compares a short moving average of the high-low range with a longer moving average. According to the…

MašīnmācīšanāsStatistikaTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

The report asks whether exposure to macroeconomic policy uncertainty is priced in Chinese A-shares. It describes a news-based economic policy uncertainty index and estimates each stock’s EPU beta through time-series regression. Stocks are sorted into five…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTirgus noskaņojums
BigQuant

This study examines whether price-to-earnings ratios, cyclically adjusted P/E (CAPE), and the bond-stock earnings yield measure (BSEYD) can signal major downturns in the Shanghai and Shenzhen composite indexes. It also describes return features in the two…

AkcijasĶīnas tirgiStatistikaVēsturisko datu pārbaude
BigQuant

This troubleshooting note describes a SQL binder error that occurs when a normalization function is used in a query joining two stock-factor tables. Both tables contain a date column, so passing an unqualified date reference to the function leaves the…

AkcijasFaktoru ieguldīšanaTehniskie indikatori
BigQuant

This discussion examines why published quantitative findings and attractive backtests may fail to reproduce or translate into tradable returns. It explains how publication incentives, selective reporting, repeated testing, flexible data choices, and…

StatistikaVēsturisko datu pārbaudeRiska pārvaldībaFaktoru ieguldīšana
BigQuant

The document explains how to construct factors grouped by Chinese stock market concepts when a built-in grouping expression does not recognize the concept field. For standard industry groupings, it gives a group-mean example using a level-two industry…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
BigQuant

The document describes a problem encountered when using an initialization module to set a day counter and prevent duplicate daily trades. In backtests, the counter reportedly advanced across several days, but in simulated trading the same first-day trade ran…

Rīkojumu izpildeVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

This short forum post asks how to add market-timing conditions to a strategy backtest. The author has seen strategies reduce or alter exposure after several consecutive market declines and is interested in alternatives based on whether the Shanghai Composite…

AkcijasTehniskie indikatoriVēsturisko datu pārbaudeĶīnas tirgi
BigQuant

This brief introductory response defines quantitative investing as finding patterns in historical data, translating them into a model and strategy, and using software to execute trades according to the resulting rules. It highlights discipline as a benefit:…

StatistikaMašīnmācīšanāsVēsturisko datu pārbaudeRiska pārvaldība