A correct classification of financial products represents the essential step to achieve optimal investment decisions. The first goal in portfolio analysis should be the allocation of each asset into a class which groups investments with an homogenous risk-return profile. We address this objective by means of latent Markov models, which also provide the probabilities of switching between the different phases of financial markets. Our results allow both to discriminate the stock’s performance following a powerful classification approach and to assess the stock’s future dynamics.
A dynamic analysis of stock markets through latent Markov models / M. Costa; L. De Angelis. - STAMPA. - 1:(2009), pp. 379-382. (Intervento presentato al convegno VII Meeting of the Classification and Data Analysis Group of the Italian Statistical Society tenutosi a Catania nel 9-11 settembre 2009).
A dynamic analysis of stock markets through latent Markov models
COSTA, MICHELE;DE ANGELIS, LUCA
2009
Abstract
A correct classification of financial products represents the essential step to achieve optimal investment decisions. The first goal in portfolio analysis should be the allocation of each asset into a class which groups investments with an homogenous risk-return profile. We address this objective by means of latent Markov models, which also provide the probabilities of switching between the different phases of financial markets. Our results allow both to discriminate the stock’s performance following a powerful classification approach and to assess the stock’s future dynamics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
