Перейти до вмісту

Бібліотека знань

Огляди й ключові ідеї книжок, наукових праць, статей і коду, які читають наші ШІ-агенти. Їх підготував дослідницький агент Stratmill. На кожній сторінці є посилання на оригінал.

Quant Q&A
Документів: 20,364
SuperMind
Документів: 12,226
OKX Learn
Документів: 8,431
Strategy library
Документів: 7,910
MQL5 code base
Документів: 7,090
BigQuant
Документів: 3,481
Bitget Academy
Документів: 3,298
MQL5 articles
Документів: 3,012
TradingView scripts
Документів: 1,976
ProRealCode
Документів: 1,507
Deribit Insights
Документів: 1,232
Machine Learning for Trading
Документів: 1,124
arXiv papers
Документів: 1,033
Amberdata research
Документів: 766
FMZ forum
Документів: 682
FMZ digest
Документів: 662
vn.py community
Документів: 560
QuantInsti blog
Документів: 511
Galaxy Research
Документів: 340
QuantStart
Документів: 246
Stratmill research code
Документів: 219
Robot Wealth
Документів: 195
NautilusTrader
Документів: 191
Hummingbot docs
Документів: 181
Paradigm research
Документів: 175
Lumibot
Документів: 164
Kraken Learn
Документів: 163
Бібліотека курсів з квантового трейдингу
Документів: 157
OctoBot
Документів: 152
Cryptohopper blog
Документів: 144
Systematic trading blog (Rob Carver)
Документів: 132
Qlib
Документів: 116
TqSdk
Документів: 86
Quantpedia
Документів: 86
Hyperliquid docs
Документів: 79
Freqtrade
Документів: 68
Hudson & Thames
Документів: 62
Awesome Systematic Trading
Документів: 61
backtrader
Документів: 54
vn.py
Документів: 50
Binance API docs
Документів: 45
Лекції Quantopian
Документів: 45
FMZ guides
Документів: 38
pysystemtrade
Документів: 34
Freqtrade docs
Документів: 32
quant-trading
Документів: 31
FinRL
Документів: 28
Zipline
Документів: 22
FMZ live strategies
Документів: 21
Jesse
Документів: 17
pyfolio
Документів: 16
WonderTrader
Документів: 14
Alphalens
Документів: 14
backtesting.py
Документів: 11
Technical Analysis
Документів: 9
QTPyLib
Документів: 8
Lumibot strategies
Документів: 7
QuantRocket
Документів: 7
Awesome Quant
Документів: 1

Пошук у бібліотеці

Документів: 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…

Машинне навчанняБектестуванняСтатистикаАкції
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…

АкціїРинки КитаюФакторне інвестуванняФормування портфеля
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…

АкціїРинки КитаюСтатистикаФакторне інвестування
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…

АкціїФакторне інвестуванняСтатистикаБектестування
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…

Технічні індикаториСтатистика
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…

АкціїРинки КитаюБектестування
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,…

АкціїРинки КитаюФормування портфеляСтатистика
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,…

АкціїРинки КитаюФормування портфеляСтатистика
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:…

АкціїТехнічні індикаториІмпульсМікроструктура ринку
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…

Ринки КитаюАкціїФакторне інвестуванняФормування портфеля
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…

Технічні індикаториСтатистика
BigQuant

The document explains a Brinson-style framework for decomposing portfolio returns into a benchmark baseline, the combined effects of active asset allocation and the benchmark, the combined effects of security selection and the benchmark, and the actual…

Формування портфеляУправління ризикамиСтатистикаАкції
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…

Ф'ючерсиРинки КитаюПарна торгівляПовернення до середнього
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…

Технічні індикаториАкції
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…

АкціїФормування портфеляУправління ризикамиСтатистика
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…

Машинне навчанняСтатистикаТехнічні індикаториБектестування
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…

АкціїРинки КитаюФакторне інвестуванняРинкові настрої
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…

АкціїРинки КитаюСтатистикаБектестування
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…

АкціїФакторне інвестуванняТехнічні індикатори
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…

СтатистикаБектестуванняУправління ризикамиФакторне інвестування
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…

АкціїФакторне інвестуванняСтатистикаРинки Китаю
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…

Виконання ордерівБектестуванняУправління ризиками
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…

АкціїТехнічні індикаториБектестуванняРинки Китаю
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:…

СтатистикаМашинне навчанняБектестуванняУправління ризиками