What does the tail of the distribution of current stock prices tell us about future economic activity?

• Author: José Vicente,Gustavo Araujo
• Date: 01 July 2018
• DOI: http://doi.org/10.1002/for.2516
• Published date: 01 July 2018

Received: 16 June 2016 Revised: 26 December 2017 Accepted: 27 December 2017

DOI: 10.1002/for.2516

RESEARCH ARTICLE

What does the tail of the distribution of current stock prices

tell us about future economic activity?

José Vicente Gustavo Araujo

Departamento de Estudos e Pesquisas

(DEPEP), Banco Central do Brasil, Rio de

Janeiro, Brazil

Correspondence

José Vicente, Departamento de Estudos e

Pesquisas (DEPEP), Banco Central do

Brasil, Rio de Janeiro, Brazil.

Email: jose.valentim@bcb.gov.br

Abstract

This paper proposes three leading indicators of economic conditions esti-

mated using current stock returns. The assumption underlying our approach

is that current asset prices reflect all the available information about future

states of economy. Each of the proposed indicators is related to the tail of the

cross-sectional distribution of stock returns. The results show that the leading

indicators have strong correlation with future economic conditions and usually

make betterout-of- sample predictionsthan two traditional competitors (random

walk and the average of previous observations). Furthermore, quantile regres-

sions reveal that the leading indicators have strong connections with low future

economic activity.

KEYWORDS

crisis, economic activity, leading economic indicator, tail risk

1INTRODUCTION

Although business cycles are part of economic dynamics,

the effects of these fluctuations can be damaging. There-

fore, predicting cycles is an important task for policymak-

ers to enable actions to attenuate these effects. While the

term “cycle” might suggest periodicity, economic contrac-

tions or expansions do not follow a clear pattern, which

makes it hard to anticipate them. In light of this, lead-

ing economic activity indicators (LEI) are a relevant topic

of investigation. A LEI is simply an index or factor that

changes before economic activity starts following a new

trend or path. Most of the work about LEIs relies on time

series models estimated from monetary aggregates and/or

asset prices. In this paper, we propose three LEIs that are

based on stock prices at a given point in time. In particu-

lar, our indicators are different attributes of the tail of the

cross-sectional distribution of stock returns.

Economic theory states that the price of an asset reflects

its expected present value of future earnings adjusted by

risk. This statement, together with the market efficiency

hypothesis, tells us that any information about the future

states of nature should be reflected in prices. Therefore, it

is reasonable to imagine that current prices provide rele-

vant information to build LEIs. Moreover, as pointed out

by Bloom (2009), an increase in uncertainty leads firms

to postpone investment decisions, production, and hiring.

Since tail risk measures are related to uncertainty, one

can expect that they are correlated with macroeconomic

activity.As our main aim is to study falls in economic activ-

ity, we define an LEI as a measure of the left tail of the

distribution of current stock returns.

Cross-sectional data have been used to infer future eco-

nomic activity plunges. For instance, Allen, Bali, and Tang

(2012) derive a catastrophic risk measure from an extreme

lower percentile of stock returns at each point in time.

They show that this measure forecasts macroeconomic

downturns six months ahead. Moreover, another strand

of the literature connects tail events to asset pricing. This

literature tries to provide explanations for some financial

puzzles.1Kelly and Jiang (2014) propose an economy-wide

1See Tsaiand Wachter (2015) for a survey of recent models of disaster risk

that provide explanations for some puzzles in finance.

506 Copyright © 2018 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/for Journal of Forecasting. 2018;37:506–516.