Accomplishment Based Renewal of: Autoregressive Conditional Duration, Arch, Common Features, and Cointegration

9730062随着计算机能力和内存的增加，以越来越高的频率收集和分析数据成为可能。记录每一笔交易的数据集--尽可能高的频率--现在存在于许多金融数据集以及由计算机记录的微观经济交易，如电话和信用卡购买。对这种数据集的分析提出了新的和有趣的经济挑战，其中之一是选择适当的时间间隔来汇总数据，以便生成一个观测值均匀分布的数据集。固定区间分析的问题是，它可能会给调查者留下许多没有信息的数据点，或者掩盖最感兴趣的时期。这一基于成果的更新继续研究并应用于金融微观数据，以替代由调查者开发的固定区间分析。这种方法被称为自回归条件持续期(ACD)。事务之间的间隔变成了要分析的随机变量，而不是选择固定的间隔来分析数据。因此，数据集成为每个交易的持续时间和特征的列表。此过程直接对时间间隔建模，而不使用辅助数据或对时间流的原因强加假设。之前的拨款使用了ACD模型来分析股票交易的价格、交易量和持续时间过程。交易、订单提交和报价修改的时间安排是新提议的计量经济学研究的重点。从这些分析中，有可能推断出金融市场的关键行为方面。流动性一词经常被用来描述有效运作的市场。有了买卖价差、市场深度和交易价格影响等更准确的市场质量实证衡量标准，就有可能考察市场流动性的起伏。这对于评估市场的S能力，以及寻求大额交易的机构来说，显然很重要。该项目使用TORQ、TAQ、QEX期权、S期货以及可能的其他数据集，衡量市场流动性的各个维度，检验这些指标的时间序列行为、可预测性和经济决定因素。?？

9730062 Engle As computers increase in power and memory it becomes feasible to collect and analyze data at higher and higher frequencies. Data sets that record every transaction - the highest frequency possible - now exist for many financial data sets as well as microeconomic transactions such as telephone calls and credit card purchases that are recorded by computers. The analysis of such data sets poses new and interesting economic challenges, one of them being the choice of the proper interval of time within which to aggregate the data so as to generate a data set with observations spaced evenly part. The problem with fixed interval analysis is that it can leave the investigator with many uninformative data points or disguise the periods of most interest. This Accomplishment Based Renewal continues the study and application to financial microdata of an alternative to fixed interval analysis developed by the investigator. This approach is called Autoregressive Conditional Duration (ACD). Instead of selecting a fixed interval for analyzing the data, the interval between transactions becomes a random variable to be analyzed. Thus the data set becomes a list of durations and characteristics of each transaction. This procedure models the time intervals directly without using auxiliary data or imposing assumptions on the causes of the time flow. The previous grant used the ACD model to analyze the price, volume and duration process of stock transactions. The timing of transactions, order submissions and quote revisions are the focus of new proposed econometric studies. From these analyses it is possible to infer key behavioral aspects of financial markets. The term liquidity is often used to describe effectively functioning markets. With more precise empirical measures of market quality such as the bid ask spread, the depth of the market and the price impact of trade, it is possible to examine the ebb and flow of market liquidity. This is clearly important for assessing the s tability of markets and for institutions seeking to trade large volumes. Using TORQ, TAQ, QEX options, S&P Futures and potentially other data sets, this project measures various dimensions of market liquidity, examines the time series behavior, forecastability, and economic determinants of these measures. ??