Recent UBS quantitative research reveals that China's A-share market significantly outperforms the US market, demonstrating exceptional performance in both return magnitude and effectiveness breadth.

On September 4th, UBS research found that technical indicators based on price and volume dynamics in China's A-share market, particularly in the small-cap sector, exhibit remarkable effectiveness, generating excess returns (Alpha) that substantially exceed mature US markets in both "return magnitude" and "effective breadth."

UBS categorized technical indicators into five major types: Momentum, Volatility, Intraday Pattern, Volume, and Price-Volume Interaction, conducting backtests on their performance in the Chinese market.

Among the five categories, the "Candle Stick Shift" (KSFT) factor from the intraday pattern category dominated with a 39% annualized long-short return, while the "Price-Turnover Correlation" (PTC) factor from the price-volume interaction category tied for first place with a 1.7 risk-adjusted return.

UBS emphasized that the effectiveness of technical indicators is significantly amplified in small-cap stocks. For example, the KSFT factor achieved nearly 50% annualized returns in the CSI 2000 index, far exceeding the 33% in the CSI 300. This "small-cap premium" reflects higher turnover rates and stronger investor behavioral biases in this sector.

Additionally, the research noted that compared to the US market, technical indicators in China lead significantly in both absolute returns and strategy breadth. In the US, even the best-performing KSFT factor achieved only 7%-15% annualized returns, while several other indicators recorded negative returns.

**Intraday Sentiment Indicators Lead Five Major Categories**

UBS research categorized technical indicators into five major types: momentum, volatility, intraday patterns, volume, and price-volume interaction. Clear leaders emerged in each category:

**Momentum Category Champion**: The SLOPE indicator captures trend continuation, achieving 31% annualized long-short returns with a 1.4 risk-adjusted return.

**Volatility Category Champion**: The NATR (Normalized Average True Range) indicator shows that high volatility typically predicts lower future returns, with its long-short strategy achieving 300% cumulative returns over 15 years and 20% annualized returns.

**Intraday Pattern Category Champion**: KSFT (Candle Stick Shift) stands as the "return king" among all factors. By capturing the relative position of closing prices within the daily price range, KSFT achieved an impressive 39% annualized long-short return with a 1.7 risk-adjusted return.

**Volume Category Champion**: VMA (Volume Moving Average) calculates through smoothed volume data. Over the years, VMA consistently achieved double-digit positive returns, including 34% in 2010, 30% in 2016, and 29% in 2019, with 16% annualized long-short returns.

**Price-Volume Interaction Category Champion**: PTC (Price-Turnover Correlation) measures the consistency between price movements and trading activity. This factor performed exceptionally steadily, achieving not only 27% annualized long-short returns but also a 1.7 risk-adjusted return with a maximum drawdown of only -15%.

Crucially, the report noted that even after considering trading costs of 10 basis points per side, robust factors like KSFT and PTC remained profitable.

**A-Share Small Caps: Fertile Ground for Excess Returns**

UBS highlighted a significant "small-cap premium" for technical indicators in the Chinese market.

Simply put, these indicators perform far better on small-cap stocks (such as CSI 1000 and CSI 2000 constituents) than on large-cap stocks (such as CSI 300 constituents). UBS research findings include:

- **Candle Stick Shift Indicator (KSFT)**: Achieved nearly 50% annualized long-short returns in the CSI 2000 index with a 2.9 risk-adjusted return; while in the CSI 300 index, these figures were 33% and 1.3 respectively. - **Price-Turnover Correlation Indicator (PTC)**: Achieved an impressive 3.6 risk-adjusted return in small caps, compared to only 1.2 in large caps.

Furthermore, data shows that shorting small-cap portfolios can generate significant returns, indicating that technical indicators are particularly effective at identifying overvalued or speculative bubble small-cap stocks.

The report attributes this phenomenon to the unique ecosystem of China's small-cap market. Higher turnover rates and stronger behavioral biases from retail investor participation amplify technical indicators' ability to capture market sentiment and speculative behavior.

**China-US Comparison: China's Market Shows Significant Advantages**

When UBS quantitative analysts benchmarked China's market backtest results against the US market, the differences were stark.

Technical indicators in the Chinese market comprehensively outperformed in both "return magnitude" and "effective breadth."

**Return Magnitude Differences**: In the US market, even the best-performing KSFT indicator achieved only 7%-15% annualized long-short returns across different market cap segments, with risk-adjusted returns between 0.3-0.9. The PTC indicator's annualized returns were also only 7%-9%. This contrasts sharply with KSFT's consistent 30%+ returns in the Chinese market.

**Effective Breadth Differences**: In the Chinese market, multiple signals across all five categories can generate excess returns. However, in the US market, aside from KSFT and PTC showing reasonable performance, indicators like NATR and VMA even generated negative returns, demonstrating very limited effectiveness of technical signals.

The report attributes these substantial differences to structural factors between the two markets. China's market features higher retail participation, globally leading extremely high turnover rates (A-share small-cap stocks can achieve over 1900% annualized turnover compared to only 200-400% for US stocks), and consequently stronger behavioral biases, collectively creating more powerful profit opportunities for technical indicators.

In contrast, the US market is more institutionalized with higher price discovery efficiency, naturally leaving smaller arbitrage opportunities for technical signals.