Stock Daily Price Regime Model Detection using Markov Switching Model

tehran stock exchange dynamics in a markov regime switching egarch-in-mean model

this paper examines regime shifts in tedpix return and volatility and the effects of positive and negative crude oil shocks and gold price fluctuations on stock market shifts behavior using markov switching egarch model with student’s t-distribution. we detect two episodes of series behavior, one relative to low mean/high variance regime namely bear state and the other to high mean/low variance...

Intrusion Detection Using Evolutionary Hidden Markov Model

Intrusion detection systems are responsible for diagnosing and detecting any unauthorized use of the system, exploitation or destruction, which is able to prevent cyber-attacks using the network package analysis. one of the major challenges in the use of these tools is lack of educational patterns of attacks on the part of the engine analysis; engine failure that caused the complete training,  ...

A Regime-switching Model of Long-term Stock Returns*

In this paper I first define the regime-switching lognormal model. Monthly data from the Standard and Poor’s 500 and the Toronto Stock Exchange 300 indices are used to fit the model parameters, using maximum likelihood estimation. The fit of the regime-switching model to the data is compared with other common econometric models, including the generalized autoregressive conditionally heteroskeda...

Power Prices – A Regime - Switching Spot / Forward Price Model

Abnormality Detection in a Landing Operation Using Hidden Markov Model

The air transport industry is seeking to manage risks in air travels. Its main objective is to detect abnormal behaviors in various flight conditions. The current methods have some limitations and are based on studying the risks and measuring the effective parameters. These parameters do not remove the dependency of a flight process on the time and human decisions. In this paper, we used an HMM...