Predicting the Directional Change in Consumer Sentiment

Posted: 19 Apr 2013

See all articles by Juan Yao

Juan Yao

University of Sydney - Business School - Finance Discipline; Financial Research Network (FIRN)

Graham Partington

University of Sydney - School of Business - Finance Discipline; Financial Research Network (FIRN)

Maxwell Stevenson

University of Sydney - School of Business - Finance Discipline; Financial Research Network (FIRN)

Date Written: April 10, 2012

Abstract

The Consumer Sentiment Index (CSI) is a widely monitored economic indicator. The index measures consumer expectations, which contain information about potential future changes in consumer spending. Thus, any change in the dynamics of the sentiment index should contain important signals about future consumer behaviour, as well as changes in the real economy and stock returns. In this paper we use Cox’s proportional hazards model to estimate dynamic transition probabilities for a reversal in the CSI. We predict the probability of both positive and negative runs in sentiment surviving in the same state. Lagged changes in consumer sentiment and the frequency of recent reversals of sentiment are found to be significant predictors of a change in state. The model has substantial predictive ability, as measured by both categorical accuracy and a probability scoring rule, the Brier Score (Brier, 1950) out of sample. The predictive accuracy of the model is robust to the impact of the global financial crisis.

Keywords: consumer sentiment predictability, duration dependence, runs, survival analysis

Suggested Citation

Yao, Juan and Partington, Graham and Stevenson, Max, Predicting the Directional Change in Consumer Sentiment (April 10, 2012). Australian Journal of Management, Vol. 38, No. 1, 2013, Available at SSRN: https://ssrn.com/abstract=2253341

Juan Yao (Contact Author)

University of Sydney - Business School - Finance Discipline ( email )

P.O. Box H58
Sydney, NSW 2006
Australia
+61 2 93517650 (Phone)
+61 2 9351 6461 (Fax)

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Graham Partington

University of Sydney - School of Business - Finance Discipline ( email )

Building H69
Sydney NSW, 2006
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Max Stevenson

University of Sydney - School of Business - Finance Discipline ( email )

P.O. Box H58
Sydney, NSW 2006
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

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