دانلود رایگان مقاله انگلیسی توانایی پیش بینی چرخه کسب و کار با نقدینگی بازار بورس و نوسان پذیری - امرالد 2018

Abstract

Purpose – The purpose of this paper is to predict real gross domestic product (GDP) growth and business cycles by using information from both liquidity and volatility measures. Design/methodology/approach – The paper estimates liquidity and volatility measures from over 5,000 NYSE rms and extracts a common factor, which the paper calls uncertainty. In-sample and out-ofsample forecasting tests are used to determine the ability of the uncertainty factor to predict growth in real GDP, industrial production, consumer price index, real consumption and changes in real investment. Findings – The paper finds that on average, positive shocks to the uncertainty factor occur in the quarters preceding and at the beginning of a recession. During the quarters toward the end of recessions, there are negative shocks to uncertainty on average. Originality/value – Previous research has explored using either liquidity or volatility to forecast economic activity. The paper bridges the two branches of research and finds a link to real GDP growth and business cycles.

Conclusion

With the recent financial crisis, during which there was a noticeable link between the economic downturn and a reduction in liquidity, there has been a lot of research focusing on measuring liquidity and linking it to the overall state of the economy. Næs et al. (2011) show that a link between liquidity and GDP growth has existed in past recessions and that it isn’t limited to this most recent crisis. In this paper, we use the uncertainty measure of Carlston (2012), which is based on multiple measures of stock liquidity and volatility. The construction of this quarterly “uncertainty” measure relies on daily measures of liquidity and volatility and is based on the work of Korajczyk and Sadka (2008), who analyze several liquidity measures. It relies on various liquidity and volatility measures across 5281 NYSE firms from January 1947 to December 2012. A latent factor model is estimated across the collection of all liquidity and volatility measures, and from these factors, we obtain a measure of the commonality of liquidity and volatility, which we call “uncertainty”. Shocks to the measure of uncertainty have a correlation of 0.65 to changes in the uncertainty measure of Jurado et al. (2015). Then, we explore a possible link between real economic variables and this uncertainty measure. We find that the uncertainty measure exhibits both in-sample and out-of-sample predictive ability for real GDP growth. Furthermore, when examining the average shock to uncertainty with the average quarterly real GDP growth around NBER recession dates, we find evidence that they track each other. Additional statistical tests show that our uncertainty measure Granger causes real GDP growth in addition to other macroeconomic variables, including industrial production and real consumption. Out-of-sample forecasting tests show that while our uncertainty measure adds predictive power to a simple forecast based on an AR(1) model for GDP growth, Diebold and Mariano (1995) tests indicate that there is no significant improvement in forecasts based on our uncertainty measure from those based solely on liquidity measures. We conclude that while the common measure of liquidity and volatility risk correlates with the real economy, when forecasting economics variables there is no statistical difference between the accuracy of forecasts based on our uncertainty measure and those based solely on liquidity measures.