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Bounded chaos in equity markets: Seasonality, information effects, and the SEC filings.

机译:股市的混乱局面:季节性,信息影响和SEC备案。

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摘要

Several branches of the finance literature motivate this research: the efficient market hypothesis, informational efficiency, dynamic systems, and behavioral finance. Analysis of seasonal regularities and fundamental information effects suggests a dynamic equity market model that incorporates the complementary aspects of these other market models: information, behavior, time, and market responses. This research focuses on the relationship between three characteristics of fundamental information, market responses, and seasonal variations.; Returns, volume, or volatility are generally used to analyze information effects. This research uses two aspects of each variable, its level and monthly percentage change. The dependent variables are: price level, returns, excess return to a centered moving average, excess returns to a capital asset pricing model, trading volume, change in trading volume, price volatility, and change in price volatility. The distinction between levels and changes is significant. Each variable exhibits significant monthly seasonality, but gives scant support to the January or turn-of-the-year effect. A seasonal regularity in volume and volatility implies seasonality in liquidity and risk.; The companies studied are associated with the S&P 500, S&P 400, and S&P 600 indexes. The independent variables are months and the information releases represented by the SEC filings: 10-K, 10-Q, 11-K, 8-K, annual report to shareholders, prospectus, and 1 proxy. The filings exhibit strong seasonality roughly corresponding to the seasonal in returns. Whether analyzed as an event study or linear model, they display information effects for all dependent variables, which vary substantially with company size and time period.; The interactions are significant between the monthly seasonal and information effects in a multivariate analysis. The 10-Q filing is associated with seasonality. The 10-K and 10-Q have opposite effects on returns. All of the SEC filings relate significantly with variable levels more than changes, indicating upper or lower boundaries. They behave like the coherent attractors described in dynamic systems models and counterbalance the chaotic, self-referral fractal characteristics of non-information periods. Investors can use seasonality, information, and their interactions to track market or companies' divergence from fundamental values, liquidity, and risk. This is also useful in evaluating the effectiveness of regulations promoting corporate disclosure.
机译:金融文献的几个分支推动了这项研究:有效的市场假设,信息效率,动态系统和行为金融。对季节性规律和基本信息影响的分析表明,动态股票市场模型包含了其他市场模型的互补方面:信息,行为,时间和市场反应。这项研究的重点是基本信息,市场反应和季节性变化三个特征之间的关系。收益,数量或波动率通常用于分析信息影响。本研究使用每个变量的两个方面,即变量的水平和每月百分比变化。因变量是:价格水平,收益,中心移动平均线的超额收益,资本资产定价模型的超额收益,交易量,交易量变化,价格波动性和价格波动性变化。级别和更改之间的区别很明显。每个变量都表现出显着的每月季节性,但对一月或年度变化的影响却很少。数量和波动率的季节性规律性意味着流动性和风险的季节性性。所研究的公司与S&P 500,S&P 400和S&P 600指数相关。自变量是月份,SEC档案代表的信息发布是:10-K,10-Q,11-K,8-K,向股东提交的年度报告,招股说明书和1个代理人。这些文件显示出强劲的季节性,大致对应于回报的季节性。无论是作为事件研究还是线性模型进行分析,它们都显示所有因变量的信息效果,这些因变量会随着公司规模和时间段的不同而有很大差异。在多变量分析中,月度季节影响与信息影响之间的相互作用非常明显。 10-Q备案与季节性相关。 10-K和10-Q对回报的影响相反。所有SEC文件与可变水平的关系远大于变化,表明上限或下限。它们的行为就像动态系统模型中描述的相干吸引子,并抵消了非信息周期的混沌,自引用分形特征。投资者可以利用季节性,信息及其相互作用来跟踪市场或公司与基本价值,流动性和风险的差异。这对于评估促进公司披露的法规的有效性也很有用。

著录项

  • 作者

    Roney, Robert P.;

  • 作者单位

    Nova Southeastern University.;

  • 授予单位 Nova Southeastern University.;
  • 学科 Economics Finance.; Business Administration Accounting.; Business Administration Management.
  • 学位 D.B.A.
  • 年度 2003
  • 页码 382 p.
  • 总页数 382
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 财政、金融;财务管理、经济核算;贸易经济;
  • 关键词

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