Regime switching model for financial data: Empirical risk analysis

A Regime Switching Independent Component Analysis Method for Temporal Data

A mixture of independent component analysis method for temporal data is presented in this paper. The method is derived by modeling the observations as a mixture of ICA (mICA). mICA model has been applied to data classification and image processing. However, it is hard to use mICA in assigning class memberships of temporal data. In the proposed method, memberships of the data are modified accord...

Volatility Risk for Regime Switching Models

Regime switching models have proven to be well-suited for capturing the time series behavior of many financial variables. In particular, they have become a popular framework for pricing equity-linked insurance products. The success of these models demonstrates that realistic modeling of financial time series must allow for random changes in volatility. In the context of valuation of contingent ...

Fuzzy model for risk analysis

The goal of this paper is to show how the concept of fuzzy logic can be used to establish a degree to which an investment project belongs to a class of risk. Also, the probability of the fuzzy event is presented and is ap-plied to calculate the probability of the fuzzy event “the project X is a good investment”. This process has to enable the decision maker to compare several alternative invest...

The frequency of regime switching in financial market volatility

Article history: Received 30 May 2014 Received in revised form 11 January 2015 Accepted 16 March 2015 Available online xxxx Themechanismof risk responses tomarket shocks is considered as stagnant in recent financial literature, whether during normal or stress periods. Since the returns are heteroskedastic, a little considerationwas given to volatility structural breaks and diverse states. In th...

Corporate Financial Distress: An Empirical Analysis of Distress Risk