China A-Shares April: Risk Appetite Rebounds, Low Volatility and Value Factors Under Pressure

Overview

This report is UBS's monthly tracker on quantitative investment styles for China A-shares, focusing on the April investment environment, valuation levels, and long-short performance of various quantitative factors. The report notes that as market risk appetite recovered, the explanatory power of macro drivers for market returns strengthened significantly, with crude oil being the primary contributor; correlations between individual stocks decreased, but cross-sectional volatility rose, implying greater divergence in stock returns and increased stock selection opportunities. On the style front, defensive factors such as low volatility and low price beta, along with value and dividend factors, collectively underperformed, while momentum and earnings revision factors led significantly.

Core views

Macro and Market Environment: In April, the explanatory power of macro drivers for A-share returns rose significantly, with the impact of crude oil prices being particularly prominent. Meanwhile, average pairwise correlation among A-shares declined slightly, while cross-sectional volatility increased. UBS believes this indicates reduced synchronicity in stock prices and greater divergence in individual stock trends, which is more favorable for stock-picking strategies. Valuation Levels: Overall China A-share valuations rebounded to 15x 12-month forward PE, returning to year-to-date highs seen since January. By sector, Information Technology valuations remain higher than other industries; Real Estate valuations remain at historical highs. Factor Performance: Amid rising risk appetite, low-risk factors were the biggest drag in April, with the 12-month low price beta factor long-short return falling by approximately 18.5%. Value factors and their sub-factors also faced broad pressure, with the 12-month book-to-price long-short return dropping by approximately 9%. Conversely, momentum factors performed strongly, with both the momentum composite factor and 12-month price momentum recording long-short returns of approximately 15%; the 3-month forward EPS revision factor also rose by approximately 12%. Divergence within growth factors: 12-month expected EPS growth rose by approximately 10%, while the fundamental growth factor dipped slightly. Regarding size factors, large-caps remained resilient, recording positive returns of approximately 6%.

Analysis framework

UBS employs a systematic quantitative style tracking framework. First, it measures the explanatory power of macro factors on market returns by running rolling 52-week regressions of local market weekly returns against macro variables such as the USD Index, US 2-year yield, US AAA credit spread, US 10y-2y spread, gold price, and oil price. Second, it uses rolling 12-month weekly returns to calculate average pairwise stock correlation, combined with cross-sectional volatility calculated from daily returns, to determine whether the market is dominated by macro common factors or idiosyncratic stock factors. Finally, by constructing long-short factor portfolios, it tracks the monthly and historical performance of styles including low volatility, low beta, value, momentum, growth, quality, and size, and combines PE box plots to assess the valuation positioning of each style.

Methodology notes

• Quant / factor / portfolio theoryMulti-factor model

  Long-Short Factor Portfolio Return Attribution

  The report sorts stocks by style factors to construct long-short portfolios and calculates short- and long-term returns for each factor to identify which styles are generating profits or losses in the current market environment.

• Macroeconomic framework

  Regression of Macro Factor Explanatory Power on Market Returns

  Through rolling 52-week regressions, it measures changes in the explanatory power of macro variables like crude oil, USD, interest rates, and spreads on A-share weekly returns to judge whether the current market is driven by macro common factors or idiosyncratic stock factors.

• Quant / factor / portfolio theory

  Pairwise Correlation and Cross-Sectional Volatility

  High pairwise correlation implies stocks move together and macro factors dominate; high cross-sectional volatility implies dispersed individual stock returns and greater room for stock selection. Combining both helps determine if the market environment favors active stock picking.

• Valuation MethodologyPE/PEG valuation

  Market Forward PE Percentile and Style Valuation Box Plot

  Using market consensus forward PE and its historical distribution box plot to compare current valuation levels across styles and sectors, identifying areas where valuations are relatively high or low.

Key data

• A-Share 12-Month Forward PE15xRebounded in April to YTD high seen in Jan
• Low Price Beta (12M) Long-Short ReturnApprox. -18.5%Largest decline among low-risk factors
• Low Volatility (12M) Long-Short ReturnSignificant DeclineUnder pressure alongside Low Beta
• Book-to-Price (12M) Long-Short ReturnApprox. -9%Value factors overall underperformed
• Momentum Composite Factor Long-Short ReturnApprox. 15%One of the strongest performing styles in April
• 12M Price Momentum Long-Short ReturnApprox. 15%Led gains alongside Momentum Composite
• 3M Forward EPS Revision Factor Long-Short ReturnApprox. 12.4%Earnings momentum factors strong
• 12M Expected EPS Growth Factor Long-Short ReturnApprox. +10%Relatively better performance within Growth style
• Large-Cap Size Factor ReturnApprox. +6%Large-cap style maintained positive returns
• Stock Pairwise CorrelationSlight DeclineLatest indices approx. in 19%-26% range; macro synchronicity weakened
• Cross-Sectional VolatilityIncreasedGreater divergence in individual stock returns; favorable for stock picking

Impact & implications

The report suggests that in April, A-shares were in a phase of recovering risk appetite and warming risk sentiment: retail investor participation increased, defensive factors like low volatility and low beta, as well as value and dividend factors, significantly underperformed, while momentum and earnings revision factors became mainstream. This implies that in the current 'risk-on' environment, strategies chasing low risk or high dividends may face short-term pressure, whereas stock selection based on price momentum and earnings upgrades is more likely to generate alpha. Meanwhile, the strengthening of macro drivers, especially crude oil, reminds investors to pay closer attention to external macro variables when interpreting A-share volatility; the decline in stock correlation and rise in cross-sectional volatility suggest expanded room for stock selection and relatively increased opportunities for active management.

Risks

• Quantitative models rely on company financial reports, consensus estimates, and stock price data, which may contain errors and are sometimes unavoidable.
• Models use historical data to estimate the effectiveness of stock selection strategies and relationships between strategies, which may change in the future.
• Idiosyncratic corporate events may overwhelm the influence of systematic factors, causing factor signals to fail temporarily.