Financial Econometrics and Forecasting

这个基于成就的更新是有理由的，因为在之前的NSF奖（SBR 95-20966）下，在宏观经济学、金融学、劳动经济学和农业经济学方面做出了令人印象深刻的方法和实质性贡献。这次更新的重点是金融经济学和预测之间的联系。本研究从计量经济学的角度深化和细化了这种联系，并在以下方面取得了进展：(1)测量（例如，资产收益波动的参数和非参数估计的新方法和结果）(2)模型（例如，资产市场信息到达的长记忆来源，对资产收益波动动态的影响）(3)工具(例如，用于多变量密度预测的评估、校准、(4)实质性知识（例如，是否可以从期权和相关衍生品市场评估崩溃概率，并成功地将其建模为可观察的基本原理的函数，从而产生可行的“预警系统”）。对坠机概率的研究。基本面和衍生品市场尤为重要。由于显而易见的原因，最近越来越多的论文关注于货币危机的早期预警系统。大多数文献要么集中在领先指标方法上，这种方法传达了关于崩溃概率的信息，即使这些概率没有明确建模，要么集中在明确的概率模型上，如logistic。这个项目采用了一种不同的、互补的、强大的方法，它利用期权价格中包含的丰富的市场信息来推断市场评估的崩溃概率。

This Accomplishment Based Renewal is warranted because of the impressive methodological and substantive contributions made under the previous NSF award (SBR 95-20966) to macroeconomics, finance, labor economics, and agricultural economics. This renewal focuses on the connection between financial economics and forecasting. The research deepens and refiner that connection from an econometric perspective, as it advances:(1) measurement (e.g., new methods and results for both parametric and nonparametric estimation of asset return volatility)(2) models (e.g., for the sources of long memory in asset market information arrival, with implications for asset return volatility dynamics)(3) tools (e.g., for multivariate density forecast evaluation, calibration, and structural change detection)(4) substantive knowledge (e.g., can crash probabilities be assessed from options and related derivatives markets and successfully modeled as functions of observable fundamentals, resulting in a workable "early warning system").The research on crash probabilities. fundamentals and derivatives markets is especially significant. For obvious reasons, a growing number of very recent papers focus on early warning systems for currency crises. Most of that literature focuses either on leading indicator methods, which convey information about crash probabilities even if those probabilities are not explicitly modeled, or explicit probability models such as the logistic. This project takes a different, complementary, and powerful approach, which makes use of the rich market-based information contained in options prices to infer market-assessed crash probabilities.