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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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Bitget Academy
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Machine Learning for Trading
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Бібліотека курсів з квантового трейдингу
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OctoBot
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Zipline
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Jesse
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pyfolio
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backtesting.py
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Awesome Quant
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Пошук у бібліотеці

Документів: 3,481

BigQuant

The document describes a macro allocation framework built from six risk factors covering growth, inflation, rates, credit, foreign exchange, and term spreads. It combines momentum signals with cycle-phase estimates, maps the resulting states into…

Мультиактивна торгівляАкціїСировинні товариІмпульс
BigQuant

This research summary compares monthly factors built from price and volume data with quarterly factors built from financial statements. It reports that market data factors were more often effective in long-short portfolios, and examines their relationship…

Ринки КитаюАкціїФакторне інвестуванняБектестування
BigQuant

This post describes a Chinese equity screen combining a daily amplitude threshold, exclusion of stocks that closed at a limit-up the prior day, and a positive MACD reading. The stated rationale is to favor stocks with room to move that also show positive…

АкціїРинки КитаюІмпульсТехнічні індикатори
BigQuant

The report outlines a multi-asset allocation framework that links macroeconomic risks to broad asset classes, styles, and industries. It identifies economic growth, interest rates, exchange rates, inflation, and credit as five central risk factors. A…

Мультиактивна торгівляФормування портфеляУправління ризикамиСтатистика
BigQuant

The research note studies tail dependence between individual stocks and the broader market. Using copulas, it estimates upper-tail and lower-tail correlation, which describe whether assets tend to move together during extreme outcomes. The reported…

АкціїФакторне інвестуванняСтатистика
BigQuant

The discussion explains a rolling sequence window as a way to assemble recent observations into a single training example. For instance, a model can receive a window of past factor values spanning several days, with the window advancing through time to…

Машинне навчанняСтатистикаАкції
BigQuant

This tutorial introduces recurrent neural networks as models for sequential data, then explains long short-term memory networks as a design intended to address the difficulty ordinary RNNs have retaining information across long sequences. It describes the…

Машинне навчанняАкціїСтатистикаТехнічні індикатори
BigQuant

This strategy description applies a simple price rule to one Chinese stock. It defines a reference high as the highest closing price over the past 20 days and a reference low as the lowest closing price over the past 10 days. The stated entry condition is…

АкціїРинки КитаюСлідування за трендомТехнічні індикатори
BigQuant

Average True Range (ATR), developed by J. Welles Wilder, measures price volatility rather than direction. The document defines true range as the greatest of the current high–low range and the distances from the previous close to the current high or low. ATR…

Технічні індикаториВолатильністьУправління ризиками
BigQuant

This Chinese equity screen selects stocks with amplitude above 1 and previous-day turnover above 8%, while excluding Beijing-listed shares. The article presents amplitude as a way to locate more volatile stocks and turnover as a sign of recent trading…

АкціїРинки КитаюВолатильністьВиконання ордерів
BigQuant

This Chinese-language strategy note tests a simple stock screen for mainland China A-shares. It selects companies using three annual-report criteria: net profit growth above a threshold, return on equity above a threshold for three consecutive years, and a…

АкціїРинки КитаюФакторне інвестуванняБектестування
BigQuant

This introductory tutorial explains machine learning concepts and linear regression with finance examples. It distinguishes features from labels, outlines training, validation, and test data, and contrasts supervised with unsupervised learning,…

Машинне навчанняСтатистикаФакторне інвестуванняБектестування
BigQuant

This research review applies conditional generative adversarial networks (cGANs) to multi-asset allocation. It conditions the model on recent asset-return sequences and random inputs to generate possible future paths, then estimates expected returns and…

Мультиактивна торгівляМашинне навчанняФормування портфеляУправління ризиками
BigQuant

The document raises a position-management idea for an equity holding: after a stock gains 10%, sell half the shares to secure some of the unrealized profit while leaving the rest invested for further gains. Its example starts with 1,000 shares and proposes…

АкціїРозмір позиціїУправління ризикамиБектестування
BigQuant

This research summary describes two strategies using constituents of the Shanghai 50. The momentum version ranks stocks by their return over the previous three trading days, selects the three strongest, weights them equally, and holds each cohort for nine…

АкціїРинки КитаюІмпульсПовернення до середнього
BigQuant

This brief Chinese-language entry describes a lecture on deep reinforcement learning by researcher Matteo Hessel. It introduces general value functions (GVFs) as auxiliary tasks and mentions methods for handling scaling problems in reinforcement learning…

Машинне навчання
BigQuant

This weekly report compares stock selection portfolios built with several artificial intelligence methods across broad Chinese A-share and index-constituent universes. It separates results for unconstrained selection, industry-neutral portfolios, and…

АкціїМашинне навчанняБектестуванняРинки Китаю
BigQuant

This report evaluates momentum based sector allocation in Chinese equities. It compares ordinary lookback return ranking with risk-adjusted alternatives, including Sharpe ratio, information ratio, and a path-adjusted measure that divides return by the sum of…

АкціїІмпульсФакторне інвестуванняБектестування
BigQuant

This report summarizes quantitative approaches to enhancing returns over Chinese equity benchmarks while managing tracking error. It frames enhancement as a blend of active and passive investing and describes a top-down range of choices: market exposure,…

АкціїРинки КитаюФакторне інвестуванняФормування портфеля
BigQuant

This document outlines a monthly long-only stock selection strategy for the Chinese A-share market. It ranks the universe using a market-cap rank and a 20-day average of price changes, combines the two into a score, then holds 50 equally weighted stocks with…

Ринки КитаюАкціїФакторне інвестуванняІмпульс
BigQuant

This research note explores additional technical factors for stock selection in the CSI 500 universe. It groups candidate measures into turnover behavior, illiquidity, and combined volume-price information. Turnover candidates include stability, coefficient…

АкціїРинки КитаюФакторне інвестуванняТехнічні індикатори
BigQuant

This report describes an initial step in building a multi-factor equity model: choosing which factors to combine. It proposes reducing the factor search space by including exposure relative to a benchmark as one screening criterion, alongside the strength of…

АкціїФакторне інвестуванняФормування портфеляСтатистика
BigQuant

This example strategy searches Chinese A-shares for stocks that recently had a long run of consecutive limit-up sessions and then broke the streak. It further requires positive average returns over the three days after the break, excludes several board…

Ринки КитаюАкціїІмпульсБектестування
BigQuant

The page explains a practical issue in BigTrader’s simulated-trading workflow: strategy calculations run in a container on a daily schedule, so in-memory values may not carry over between runs. If a strategy needs to retain information such as its net asset…

Виконання ордерівУправління ризиками