论文检索

微观结构先于宏观？总量非流动性对股票收益与经济活动的预测力AI 解读

This paper constructs and analyzes various measures of trading costs in US equity markets covering the period 1926–2015. These measures contain statistically and economically significant predictive signals for stock market returns and real economic activity. We decompose illiquidity proxies into a component capturing aggregate volatility and a residual. The predictive content of these components differs in important ways. Specifically, we find strong evidence that the…

“似曾相识的波动”：利用宏观变量预测股票市场总体波动率AI 解读

Aggregate stock return volatility is both persistent and countercyclical. This paper tests whether it is possible to improve volatility forecasts at monthly and quarterly horizons by conditioning on additional macroeconomic variables. I find that several variables related to macroeconomic uncertainty, time-varying expected stock returns, and credit conditions Granger cause volatility. It is more difficult to find evidence that forecasts exploiting macroeconomic variables…

高频收益、跳跃与正态混合假说AI 解读

Previous empirical studies find both evidence of jumps in asset prices and that returns standardized by 'realized volatility' are approximately standard normal. These findings appear to be contradictory. Using a sample of high-frequency returns for 20 heavily traded US stocks, we show how microstructure noise distorts the standard deviation and kurtosis of returns normalized using realized variance. When returns are standardized using a recently developed realized kernel…