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Heteroskedastic Regression and Persistence in Random Walks at Tokyo Stock Exchange

机译:东京证券交易所随机游走的异方差回归和持续性

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A set of 180 high quality stock titles is analyzed on hourly and daily time scale for conditional heteroskedastic behavior of individual volatility, further accompanied by bivariate GARCH(1,1) regression with index volatility over the three-year period of 2000/7/4 to 2003/6/30. Persistence of individual prices with respect to randomly chosen initial values (individual persistence) is compared to the collective persistence of the entire set of data series, which exhibits stylized polynomial behavior with exponent of about -0.43. Several modified approaches to quantifying individual and index-wide persistence are also sketched. The inverted fat tail series of standard persistence are found to be a useful predictor of substantial inversions of index trend, when these are used to compute the moving averages in a time window sized 200 steps. This fact is also emphasized by an empirical evidence of possible utilization in hedging strategies.
机译:在每小时和每天的时间尺度上分析了一组180种高质量股票,以分析个体波动的条件异方差行为,并进一步伴随2000/7/4三年期间的指数波动的双变量GARCH(1,1)回归到2003/6/30。将相对于随机选择的初始值的单个价格的持久性(个体持久性)与整个数据系列集的总体持久性进行比较,这显示出程式化的多项式行为,其指数约为-0.43。还概述了几种量化个体和索引范围持久性的改进方法。当使用标准余辉的倒脂肪尾系列来预测指数趋势的实质倒置时,这些倒数序列可用于在大小为200步的时间窗口中计算移动平均值。对冲策略可能利用的经验证据也强调了这一事实。

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