This study is a theoretical and historical study of the combined issues of destabilizing speculation and financial crises. First, we critically examine the orthodox mathematical theory of a speculative bubble. This model, we determine, is inadequate for the empirical purposes of identifying and fully explaining a bubble. Next, we examine the 19th-century British Classical view of the mania-crisis phenomenon and compare it with some of the leading early 20th-century views. We find that the 20th-century writers maintained a distinctly Classical view of the issues and that this view is fundamentally different from the orthodox mathematical theory. We also find that the Classical theory, though richer than the mathematical theory, inadequately explains the phenomenon. We then turn to a comparative history of selected mania-crisis episodes. From a detailed analysis of these episodes, we establish those stylized facts which characterize unstable periods of financial activity. We complete the study with a new perspective on financial instability.

This study analyzes equity REIT returns between 2007 and 2015. After an examination, it concludes that systematic risk is conditional on broader market performance.

The last decade has witnessed a great deal of research in modelling volatility of financial asset returns, expressed by time-varying variances and covariances. The importance of modelling volatility lies in the dependence of any financial investment decision on the expected risk and return as formalized in classical asset pricing theory. Precise evaluation of volatilities is a compulsory step in order to perform correct options pricing according to recent theories of the term structure of interest rates and for the construction of dynamic hedge portfolios. Models of time varying volatility represent an important ground for the development of new estimation and forecasting techniques for situations not reconcilable with the Gaussian or, more generally, a linear time series framework. This is particularly true for the statistical analysis of time series with long range dependence in a nonlinear framework. The aim of this thesis is to introduce parametric nonlinear time series models with long memory, with particular emphasis on volatility models, and to provide a methodology which yields asymptotically exact inference on the parameters of the models. The importance of these results stems from: (i) rigorous asymptotics was lacking from the stochastic volatility literature; (ii) the statistical literature does not cover the analysis of the asymptotic behaviour of quadratic forms in nonlinear non-Gaussian variates that characterizes our problem.

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The purpose of this paper is to propose a new theory of civil liability to hold tax return preparers liable to their clients for tax malpractice, applying to understatements, overstatements, and non-optimal tax advice. This paper discusses the tax return preparer’s (TRPs, both signatory and nonsignatory) current liability to the government and to the client, specifically addressing Circular 230, AICPA rules, state boards of accountancy, federal regulations, and malpractice for professionals. It will then go through several case studies to establish current gaps in malpractice law for TRPs, showing how the government is usually favored in court while clients are not. Ultimately, I will explain a general theory of liability to apply nationally for TRPs to increase their accountability to their clients.

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