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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
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SuperMind
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OKX Learn
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Strategy library
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MQL5 code base
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BigQuant
Документів: 3,481
Bitget Academy
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MQL5 articles
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TradingView scripts
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ProRealCode
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Deribit Insights
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Machine Learning for Trading
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arXiv papers
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Amberdata research
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FMZ forum
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FMZ digest
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vn.py community
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QuantInsti blog
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Galaxy Research
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QuantStart
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Stratmill research code
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Robot Wealth
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NautilusTrader
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Hummingbot docs
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Paradigm research
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Lumibot
Документів: 164
Kraken Learn
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Бібліотека курсів з квантового трейдингу
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OctoBot
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Cryptohopper blog
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Systematic trading blog (Rob Carver)
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Qlib
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TqSdk
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Quantpedia
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Hyperliquid docs
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Freqtrade
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Hudson & Thames
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Awesome Systematic Trading
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backtrader
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vn.py
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Binance API docs
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Лекції Quantopian
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FMZ guides
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pysystemtrade
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Freqtrade docs
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quant-trading
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FinRL
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Zipline
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FMZ live strategies
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Jesse
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pyfolio
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Alphalens
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WonderTrader
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backtesting.py
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Technical Analysis
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QTPyLib
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QuantRocket
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Lumibot strategies
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Awesome Quant
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Пошук у бібліотеці

Документів: 3,481

BigQuant

This research surveys how several forms of Chinese Level 2 market data can support equity signals: minute bars, order-book snapshots and queues, and transaction-level records. It describes factors based on intraday return shape, downside variation,…

АкціїВисокочастотна торгівляФакторне інвестуванняМікроструктура ринку
BigQuant

This research describes a bond-fund selection method built around return attribution. It expands the Campisi framework—which separates income, government-rate, credit-spread, and security-selection effects—with convertible-bond and monetary-policy effects.…

Інструменти з фіксованим доходомФакторне інвестуванняФормування портфеляБектестування
BigQuant

This 2018 weekly report reviews a sharp post-holiday decline in Chinese equities, noting that large-cap leaders held up better than smaller companies. It interprets price structure, valuation, and long-term support as signs that the market was in a potential…

АкціїРинки КитаюФакторне інвестуванняФормування портфеля
BigQuant

This discussion explains a mismatch in which a simulated trading run produces no signal even though a backtest does. The reported cause is a SQL query using a one-row lead on closing prices. At date t, that field requires the closing price from t+1, which is…

БектестуванняВиконання ордерівСтатистика
BigQuant

This post describes a revised rolling machine-learning training workflow, reporting that its code was reorganized for clarity, model parameters were adjusted, and memory monitoring was added. The author says the parameter changes increased backtest speed…

Машинне навчанняБектестуванняСтатистика
BigQuant

The article argues that individual investors should not expect consumer AI tools to compete with professional high-frequency trading. It points to differences in computing location, market data access, and technical resources, and describes an alleged…

АкціїВисокочастотна торгівляМашинне навчанняУправління ризиками
BigQuant

The document explains how to generate moving-average features in BigQuant when only selected lookback windows are wanted. It contrasts a range-based list comprehension, which the platform accepts, with a list of chosen values, which it says is unsupported in…

Технічні індикаториСтатистика
BigQuant

This guide outlines a workflow for preparing a factor research report for a quantitative trading competition. It recommends generating factor data, then using BigQuant’s FactorLens v4 to calculate single-factor results. The platform returns ranking metrics…

Факторне інвестуванняСтатистикаБектестування
BigQuant

This text introduces market efficiency as a contested idea whose meaning shapes how investors approach investing and valuation. It says the chapter offers a basic definition and considers what efficient markets would imply for investors. It also points…

СтатистикаБектестуванняАкції
BigQuant

This short forum post asks whether a linear equity strategy can compare a stock’s ranking when purchased with its current ranking and sell after sufficient deterioration. The example uses a small-capitalization strategy holding ten stocks: a stock bought at…

АкціїФакторне інвестуванняВиконання ордерівБектестування
BigQuant

This monthly review evaluates equity factors using information coefficient (IC) relationships with subsequent prices and market- and industry-neutral long-short returns. It reports that growth and turnover factors were relatively consistent over the latest…

АкціїРинки КитаюФакторне інвестуванняСтатистика
BigQuant

The document presents volatility of volatility (VoV) as a proxy for uncertainty about an asset’s probability distribution, distinct from ordinary risk. It argues that investors tend to avoid stocks with greater ambiguity and may favor stocks whose prospects…

АкціїВолатильністьФакторне інвестуванняВисокочастотна торгівля
BigQuant

This report reviews China’s digital finance industry as user growth matures and competition shifts toward retaining and serving customers and merchants. It compares finance apps across user scale, growth, market concentration, and engagement, and describes…

Мультиактивна торгівляРинки КитаюАкції
BigQuant

This article explains risk parity as an allocation approach that assigns comparable risk contributions across assets or risk factors, unlike capital-weighted mixes such as a conventional stock and bond portfolio. It lays out assumptions behind the method,…

Мультиактивна торгівляФормування портфеляУправління ризикамиВолатильність
BigQuant

This research summary examines whether trading behavior can serve as a proxy for speculative intensity in Chinese A-shares. It studies four measures: idiosyncratic volatility, idiosyncrasy, price delay, and size-adjusted turnover. The proposed intuition is…

АкціїФакторне інвестуванняСтатистикаРинки Китаю
BigQuant

The document describes how to build daily return data for level-two industries and use it in stock selection. It proposes joining stock industry classifications with daily returns and float market capitalizations, then grouping by industry and date. Each…

АкціїМашинне навчанняІмпульсФормування портфеля
BigQuant

This brief summary of a 2018 Chinese new-share market review reports that IPO issuance slowed while subscription winning rates remained stable. It also says that new-share subscription returns differed by investor category: A- and B-class investors…

АкціїРинки КитаюТоргівля на подіях
BigQuant

This overview explains active learning as a way to reduce the cost of building supervised or semi-supervised models when expert labels are scarce. A model repeatedly identifies candidate examples for human review, incorporates the resulting labels through…

Машинне навчанняСтатистика
BigQuant

This forum post raises a factor-construction question about accessing older financial statement observations beyond a platform's precomputed factors. The example is operating revenue: the author understands the suffix-zero field to represent the latest…

Факторне інвестуванняАкціїСтатистика
BigQuant

This Chinese research note examines the common practice of relating price-to-earnings ratios to expected earnings growth, including the assumption that a PEG ratio of one indicates fair value. Its hypothetical comparison shows that companies with PE and…

АкціїФакторне інвестуванняСтатистикаРинки Китаю
BigQuant

This overview surveys empirical research on pricing stock-index options, focusing on how systematic stochastic volatility and jump risk affect option values and returns. It describes the evolution from Black–Scholes–Merton assumptions, in which the…

ОпціониВолатильністьОцінювання вартості деривативівСтатистика
BigQuant

This research summary describes using machine learning to predict equity returns from alpha factors. It compares LASSO, support vector machines, boosted decision trees, and random forests, selecting random forests for their relatively simple structure,…

АкціїРинки КитаюМашинне навчанняФакторне інвестування
BigQuant

This research summary describes equity signals built from timestamped order submissions and cancellations, which can reveal more of the trading process than completed trades alone. It focuses mainly on Shenzhen exchange data because that venue had a longer…

АкціїФакторне інвестуванняМікроструктура ринкуРинки Китаю
BigQuant

The document presents a pairs-trading question about two stocks believed to have a long-run cointegrating relationship. It describes fitting a linear relationship between their prices, then standardizing a series associated with that relationship using a…

Парна торгівляПовернення до середньогоСтатистикаАкції