Realized Jump Test And Jumping Risk Measurement

In the21st century, the rapid development of IT is making the acquisition of intraday trading data much easier. The study of intraday features of asset returns by using high-frequency data becomes a new hot topic in financial field. Motivated both by mathematical tractability and the need to avoid introducing arbitrage opportunities in the model, some semi-martingale is employed. Some scholars using intraday high-frequency data and adopting non-parametric method to estimate the potential volatility, found that realized variance and range-based variance are unbiased and consistent estimation of integrated volatility.In the low-frequency environment, market micro structure noise is negligible. But at high frequencies, due to trading spreads, non-continuous trading, tick units and other microstructure factors, realized volatility consistently overestimated integrated volatility. Therefore,"noise reduction" research becomes a hot topic in financial econometrics. In addition to the micro-structure noise, jumps in asset price will result realized variance a consistent overestimation of the integrated volatility. So, some realized estimations, such as bi-power variation and Laplace transform of realized volatility, are robust for jumps, also unbiased and consistent for integrated volatility. For testing jumps in asset price, many scholars have put forward many statistics. Some jump tests are very robust to microstructure noise, such as ABD test and LM test, and some other jump tests get high test power, such as CPR test and PZ test. Following the idea of CPR test, we construct a new jump test by using realized estimation, and give the large sample properties constructively.Some jumps in fmancial asset prices, which are defined as heterogeneous jumps, are only impacted by the news of the company or industry. But some jumps in financial asset prices, which are defined as systematic jumps, are impacted by the news of whole market. Based on portfolio theory, the risks of those heterogeneous jumps only impacted by the news of the company or industry can be eliminated with a large enough portfolio. But the risks of those systematic jumps only impacted by the news of whole market can not be eliminated. If there exists jumps that can not be diversified in asset prices, then, existing asset pricing and risk management theories will suffer a huge challenge. Are there significant systematic jumps in capital markets, such as stock market in China? using index-stocks method and mcp method to test systematic jumps in A-share market, the results show that, the systematic jumps of the A-share market are significant, and the results of the two tests has little difference. We prove index-stocks test is rigorous, also, improve the equal weighted bi-power variation modified by threshold has better small sample properties.Considering systematic and heterogeneity jumps as tail events, we investigate the tail characteristics of distribution of stock return from the perspective of the extreme value theory. We use TOD method to eliminate intraday effect of high-frequency data, apply index-stock method to decompose systematic jumps and heterogeneity jumps, and adopt the POT method to estimate the left tail and right tail parameters. Empirical studies have shown that the intraday effect of A-share market possess apparent "L" type feature. There are significant systematic and heterogeneity jumps in each stock. And the tails of two types of jumps are obvious thick. The times and contributions of right tail jumps are larger than left in all stocks. This suggests that the frequent appearance of jumps and jump tail characteristics are an important reason for non-normal distribution of stock return. In order to investigate the features of time-varying betas in terms of systematic jumping risk, we apply realized method to decompose daily betas into continuous betas and jumping betas, and then, specifically test their stability. The results indicate that, the continuous betas are generally stable in medium and long term, but unstable in short term. But jumping betas are relatively poor in short, medium and long term. These results reflect that the main reason of time-varying betas in short term is continuous betas’instability. But the instability of betas in medium and long term is from systematic jumping risk.The jump in asset price is not only systematic, but also self-exciting. This paper investigates the dynamic characteristics, influencing factors and predictability of overnight risk in a new HAR-CJ-M framework. Specifically, BN-S method is used in order for decomposing intraday volatility into continuous and jumping components respectively, and ACH model is adopted to estimate jump’s unexpected degree. Furthermore, OLS and Quantile Regression approaches are applied to estimate the effects of intraday volatility and jump’s accidental degree on overnight risk. Our results show that continuous intraday volatility, jumping component of volatility and the lags of overnight risk have significant and asymmetric impacts on overnight risk. Moreover, the paper finds that intraday jumps have great effects on substantial overnight risk, which suggests the extended HAR-CJ-M model have good performance in forecasting such risk. This result reflects that intraday jumps forward conduct to overnight jumps. Therefore, self-exciting jumps are significant in A-share market.