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This study aimed to determine the optimal functional movement screen (FMS) cut score for assessing the risk of sport injury, and to investigate the correlations between functional movement quality and sprint and jump performance. Twenty-four (N = 24) athletes performed all tests in one day at 10–30 min intervals, and the FMS test was performed first, without a warm-up session. After a standard warm-up, athletes then completed the Y-balance Test (YBT), sprint, counter-movement jump (CMJ), and standing long jump (SLJ), in turn. For each test, the best of three attempts was recorded for further analysis. A receiver operating characteristic (ROC) curve and area-under-the-curve (AUC) were used to determine the optimal FMS cut score for assessing the risk of sport injuries, and Spearman's rank correlation analysis was used to quantify associations between functional movement scores and athletic performance. The average FMS score was 16.2 and the optimal FMS cut score for assessing the risk of sport injuries was 14.5. There were moderate relationships between total FMS score and 10–20 m sprint time (r = −0.46, p < 0.05), between In-line Lunge and 0–20 m sprint time (r = −0.47, p < 0.05), between Shoulder Mobility and 0–10 m sprint time (r = −0.48, p < 0.05), and between Trunk-stability Push-up and 10–20 m sprint time (r = −0.47, p < 0.05). Moreover, Hurdle Step score was largely correlated with 0–10 m time (r = −0.51, p < 0.05). For Y-balance, moderate correlations were observed between CMJ height and anterior asymmetry score (r = −0.47, p < 0.05) and posteromedial asymmetry score (r = −0.44, p < 0.05). However, there were no significant associations between YBT performance (asymmetric in three directions and composite score) and sprint performance (p > 0.05). Taken together, the results indicate that a FMS score of 14 is not a gold standard for assessing the risk of injury in all populations; we recommend that the FMS cut score of 14.5 should be the optimal score for assessing risk of injury in young female elite soccer players. Moreover, the FMS and YBT were introduced to assess the quality of functional movements, and they cannot be used to assess sprint and jump performance. Practitioners can use components of the FMS that have similar characteristics to specific sports to assess athletic performance. [ABSTRACT FROM AUTHOR]

This study explores the forecasting ability of jump, jump intensity, and leverage effect for an emerging futures market, China's crude oil futures market, using different kinds of HAR‐type models. From an in‐sample perspective, we find that the HAR components, monthly leverage effect, jump size, and jump intensity have positive effects on future oil volatility. Moreover, out‐of‐sample results show that a forecasting model with jump and jump intensity cannot only achieve a superior forecasting performance under low volatility level but also increase the economic value. Subsequently, we examine the effect of decompositions of jump information, the results show signed jump components can improve the accuracy. Finally, we extend our empirical analysis considering different forecast horizons, COVID‐19 pandemic, and different trading hours. Our empirical results are robust and consistent. [ABSTRACT FROM AUTHOR]

This article investigates the performance of time series models considering the jumps, permanent component of volatility, and asymmetric information in predicting value-at-risk (VaR). We use evaluation statistics including size and variability, accuracy, and efficiency to determine some suitable VaR measures for the Chinese stock index and its futures. The results reveal that models with jumps can provide VaR series that are less average conservative and have higher variability. Furthermore, additional considering the permanent component of volatility and asymmetric effect can induce more accurate and efficient risk measure in the long and short positions of the stock index and its futures. [ABSTRACT FROM AUTHOR]

In this article, we investigate the relationships among intraday serial correlation, jump-robust volatility, positive and negative jumps based on Shanghai composite index high frequency data. We implement variance ratio test to quantify intraday serial correlation. We also measure the continuous part of realized volatility using jump-robust MedRV estimator and disentangle positive and negative jumps using Realized Downside Risk Measure and Realized Upside Potential Measure proposed by Bi et al., (2013). We find that intraday serial correlation are positively correlated with jump-robust volatility and negatively correlated with negative jumps which confirm the LeBaron effect. [ABSTRACT FROM AUTHOR]

In this article, we implement the Variance Ratio test to study on the intraday serial correlation of Shenzhen component index return series. The empirical research indicates significant positive serial correlation in China's stock market. For a better understanding of the dynamics of intraday serial correlation in China's stock market, we first investigate the presence of autocorrelation mode of serial correlation. Then, we construct the VR-HAR-RV and VR-HAR-RV-CJ models to explore the links between serial correlation and volatility. We find both the VR-HAR-RV and VR-HAR-RV-CJ models can partially explain the links between serial correlation and volatility, but the VR-HAR-RV-CJ model is more powerful than the VR-HAR-RV model. [ABSTRACT FROM AUTHOR]

This study applies the ARJI-trend model in conjunction with the procedure proposed by Bai and Perron (2003) to investigate the coexistence of permanent and transitory components and time-varying jumps in the A and B stock market indices of the Shanghai and Shenzhen Stock Exchanges. Although the response to outside innovations is greater within the transitory component, it is short-lived; conversely, though there is a high level of persistence in the trend, new information has only a lesser effect on the permanent component. Jump variance can also affect total variance, though the effect is far lower than the variance for generalized autoregressive conditional heteroskedasticity. Accordingly, the market risk appears small. The reaction to news is heterogeneous within the Shanghai and Shenzhen indices; this may be the result of various market characteristics. During event periods, the permanent component, transitory components, and jump intensity are larger than their averages. After an upward trend, markets return to regular conditions over time. In sum, the total long-run risks within China's market seem low, though speculators can use the sizable transitory component of market fluctuation to engage in arbitrage activities. However, from the viewpoint of asset allocation regarding the trading noise in the Shenzhen B market, we suggest that rational investors deploy more funds in this market and less in the Shanghai A market to avoid a high degree of risk. [ABSTRACT FROM AUTHOR]