Market-crash forecasting based on the dynamics of the alpha-stable distribution
#MMPMID32834434
Molina-Muñoz J
; Mora-Valencia A
; Perote J
Physica A
2020[Nov]; 557
(?): 124876
PMID32834434
show ga
This paper investigates on the alpha-stable distribution capacity to capture the
probability of market crashes by means of the dynamic forecasting of its alpha
and beta parameters. On the basis of the GARCH-stable model, we design a market
crash forecasting methodology that involves three-stepwise procedure: (i)
Recursively estimation the GARCH-stable parameters through a rolling window; (ii)
alpha-stable parameters forecasting according to a VAR model; and (iii) Crash
probabilities forecasting and analysis. The model performance for alternative
crash definitions is assessed in terms of different accuracy criteria, and
compared with a random walk model as benchmark. Our applications to a wide
variety of stock indexes for developed and emerging markets reveals a high degree
of accuracy and replicability of the results. Hence the model represents an
interesting tool for risk management and the design of early warning systems for
future crashes.
free
free
free
