标题： 高斯链滤波器用于重尾噪声，并应用于检测股票市场中的大买家和大卖家 显示英文标题

标题： Gaussian-Chain Filters for Heavy-Tailed Noise with Application to Detecting Big Buyers and Big Sellers in Stock Market

摘要： 我们提出了一种新的重尾分布——高斯链（GC）分布，该分布受到社会机构中普遍存在的分层结构的启发。 我们确定了高斯链分布的均值、方差和峰度，以展示其重尾特性，并计算了尾部分布表，以提供具体的数字来说明重尾有多严重。 为了过滤出重尾噪声，我们基于最大似然原理构建了两个滤波器——二阶和三阶GC滤波器。 仿真结果表明，当噪声服从重尾分布时，GC滤波器的表现明显优于基准最小二乘算法。 利用GC滤波器，我们提出了一种名为“随情绪而行”的交易策略，通过检测市场中大买家和大卖家的行为，根据噪声的、重尾的价格数据来跟随市场的氛围。 将“随情绪而行”策略应用于最近两年内从2012年4月2日至2014年3月31日的五只恒生蓝筹股，结果显示其收益高于基准“买入并持有”策略和恒生指数基金的收益。 显示英文摘要

摘要： We propose a new heavy-tailed distribution --- Gaussian-Chain (GC) distribution, which is inspirited by the hierarchical structures prevailing in social organizations. We determine the mean, variance and kurtosis of the Gaussian-Chain distribution to show its heavy-tailed property, and compute the tail distribution table to give specific numbers showing how heavy is the heavy-tails. To filter out the heavy-tailed noise, we construct two filters --- 2nd and 3rd-order GC filters --- based on the maximum likelihood principle. Simulation results show that the GC filters perform much better than the benchmark least-squares algorithm when the noise is heavy-tail distributed. Using the GC filters, we propose a trading strategy, named Ride-the-Mood, to follow the mood of the market by detecting the actions of the big buyers and the big sellers in the market based on the noisy, heavy-tailed price data. Application of the Ride-the-Mood strategy to five blue-chip Hong Kong stocks over the recent two-year period from April 2, 2012 to March 31, 2014 shows that their returns are higher than the returns of the benchmark Buy-and-Hold strategy and the Hang Seng Index Fund.