Time-varying correlations between trade balance and stock prices in the United States over the period 1792 to 2013

The relationship between stock prices and the trade balance can be either negative or positive, depending on the signs of the wealth effect channel and the exchange rate channel. While previous studies examined this relationship in a time-invariant framework, we employ a time-varying approach so as to examine the dynamic correlations of trade balance and stock prices in the United States over the period 1792–2013. The results of our empirical analysis, which remain robust to alternative specifications, reveal that correlations between the trade balance and stock prices in the United States are indeed not constant, but evolve heterogeneously overtime. In particular, the correlations are, in general, significantly positive between 1800 and 1870, while significantly negative thereafter. The policy implications of these findings are then discussed.https://link.springer.com/journal/121972019-10-01hj2018Economic

Has the correlation of inflation and stock prices changed in the United States over the last two centuries?

The relationship between stock prices and the inflation can be either negative or positive, depending on the strengths of various theoretical channels at work. In this study, we examine the dynamic conditional correlations of stock prices and inflation in the United States over the period of 1791–2015 under a time-varying framework. The results of our empirical analysis reveal that correlations between the inflation and stock prices in the United States evolve heterogeneously overtime. In particular, the correlations are significantly positive in the 1840s, 1860s, 1930s and 2011, and significantly negative otherwise. The policy implications of these findings are then discussed.http://www.elsevier.com/locate/ribaf2018-12-30hj2018Economic

Are stock returns an inflation hedge for the UK? Evidence from a wavelet analysis using over three centuries of data

This paper analyzes the relationship between stock returns and the inflation rates for the UK over a long time period (February 1790-February 2017) and at different frequencies, by employing a wavelet analysis. We also compare the results for the UK economy with those for the US and two developing countries (India and South Africa). Overall, our results tend to suggest that, while the relationship between stock returns and inflation rates varies across frequencies and time periods, there is no evidence of stock returns acting as an inflation hedge, irrespective of whether we look at the two developed or the two developing markets in our sample

Testing the white noise hypothesis in high-frequency housing returns of the United States

Utilizing a daily dataset of aggregate housing market returns of the United States, we test whether housing market returns are white noise using the blockwise wild bootstrap in a rolling-window framework. We investigate the dynamic evolution of housing market efficiency and find that the white noise hypothesis is accepted in most windows associated with non-crisis periods. However, for some periods before the burst of the housing market bubbles, and during the subprime mortgage crisis, European sovereign debt crisis and the Brexit, the white noise hypothesis is rejected, indicating that the housing market is inefficient in periods of turbulence.  Our results have important implications for economic agents

A Structural VAR analysis of Fiscal shocks on current accounts in Greece

The present study is, in particular, an attempt to test the relationship between budget deficit and current account balance in Greece, from 1976 to 2009, using a structural autoregressive (SVAR) model. We focused on Greece because this country has presented in the last years seriously fiscal changes, and severely damage in the level of macroeconomic variables. We find that in case of Greece there is no long run relationship between budget deficit and current account deficit either in the presence or in absence of structural breaks in the data set. Further, Impulse Response Functions (IRFs) calculated in the framework of SVAR shows that increase in budget deficit increases the current account deficit, which is consistent with the twin deficit hypothesis

A Historical Analysis of the US Stock Price Index Using Empirical Mode Decomposition over 1791–2015

In this paper, the dynamics of Standard and Poor's 500 (S&P 500) stock price index is analysed within a time-frequency framework over a monthly period 1791:08–2015:05. Using the Empirical Mode Decomposition technique, the S&P 500 stock price index is divided into different frequencies known as intrinsic mode functions (IMFs) and one residual. The IMFs and the residual are then reconstructed into high frequency, low frequency and trend components using the hierarchical clustering method. Using different measures, it is shown that the low frequency and trend components of stock prices are relatively important drivers of the S&P 500 index. These results are also robust across various subsamples identified based on structural break tests. Therefore, US stock prices have been driven mostly by fundamental laws rooted in economic growth and longterm returns on investment.http://www.economics-ejournal.org/economics/discussionpapers/2016-9am2016Economic

A Historical Analysis of the US Stock Price Index using Empirical Mode Decomposition over 1791–2015

In this paper, the dynamics of Standard and Poor's 500 (S&P 500) stock price index is analysed within a time-frequency framework over a monthly period 1791:08–2015:05. Using the Empirical Mode Decomposition technique, the S&P 500 stock price index is divided into different frequencies known as intrinsic mode functions (IMFs) and one residual. The IMFs and the residual are then reconstructed into high frequency, low frequency and trend components using the hierarchical clustering method. Using different measures, it is shown that the low frequency and trend components of stock prices are relatively important drivers of the S&P 500 index. These results are also robust across various subsamples identified based on structural break tests. Therefore, US stock prices have been driven mostly by fundamental laws rooted in economic growth and long-term returns on investment

Testing the white noise hypothesis in high-frequency housing returns of the United States

Utilizing a daily dataset of aggregate housing market returns of the United States, we test whether housing market returns are white noise using the blockwise wild bootstrap in a rolling-window framework. We investigate the dynamic evolution of housing market efficiency and find that the white noise hypothesis is accepted in most windows associated with non-crisis periods. However, for some periods before the burst of the housing market bubbles, and during the subprime mortgage crisis, European sovereign debt crisis and the Brexit, the white noise hypothesis is rejected, indicating that the housing market is inefficient in periods of turbulence.  Our results have important implications for economic agents

Volatility spillovers across global asset classes: Evidence from time and frequency domains

This paper analyzes the volatility spillovers across four global asset classes namely, stock, sovereign bonds, credit default swaps (CDS) and currency from September 2009 to September 2016, using both a time-domain and a frequency-domain framework. When the Diebold and Yilmaz (2012) methodology is applied, the estimated total connectedness index is 5.08%, suggesting a low level of connection among the four markets. Furthermore, the results show that the stock and CDS markets are net transmitters of volatility, while foreign exchange and bond markets are net receivers of the spillovers. When the Barunik and Krehlik (2018) frequency-domain analysis is carried out, the results indicate, first, that at higher frequencies, the degree of connectedness increases, and, second, that the net transmitter of volatility spillovers across the markets is contingent on the frequency under consideration