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Predicting and Capitalizing on Stock Market Bears in the U.S

Bertrand Candelon, Jameel Ahmed and Stefan Straetmans

No 2014-409, Working Papers from Department of Research, Ipag Business School

Abstract: his paper attempts to predict the bear conditions on the US stock market. To this aim we elaborate simple predictive regressions, static and dynamic binary choice (BCM) as well as Markov-switching models. The in- and out-of-sample prediction ability is evaluated and we compare the forecasting performance of various specifications across as well as within models. It turns out that various dynamic extensions of static versions of probit and logit models reveal additional predictive information for both in- and out-of-sample fit. We also find that binary models outperform the Markov-switching model. With respect to the macro-financial variables, terms spreads, inflation and money supply turn out to be useful predictors. The results lead to useful implications for investors practicing active portfolio and risk management and for policy makers as tools to get early warning signals.

Keywords: Bear stock market; S&P 500 Index; Macro-financial variables; Dynamic Binary Response models; Markov-switching model; Bry-Boschan algorithm; Active Trading Strategies. (search for similar items in EconPapers)
JEL-codes: C22 C25 C53 G11 G17 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2014-01-01
New Economics Papers: this item is included in nep-dcm, nep-fmk, nep-for, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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Working Paper: Predicting and capitalizing on stock market bears in the U.S (2012) Downloads
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