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10.1016/j.physa.2020.124876 http://scihub22266oqcxt.onion/10.1016/j.physa.2020.124876 C7320685!7320685!32834434     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Physica+A 2020 ; 557 (ä): 124876 Nephropedia Template TP {{tp|p=32834434|t=2020. Market-crash forecasting based on the dynamics of the alpha-stable distribution |pdf=|usr=}}{{32834434}} gab.com Text Market-crash forecasting based on the dynamics of the alpha-stable distribution JO: Physica A http://www.kidney.de/pget.php?&tw=1&pmid=32834434 #FOAvip 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. Twit Text FOAVip Market-crash forecasting based on the dynamics of the alpha-stable distribution ????Physica A http://www.kidney.de/pget.php?&tw=1&pmid=32834434 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834434 #FOAvip English Wikipedia <ref>{{Cite pmid|32834434}}</ref> 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 (ä): 124876 PMID32834434show 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. äMarket-crash forecasting based on the dynamics of the alpha-stable dis(epmc).pdf DeepDyve Pubget Overpricing