scholarly journals Monetary Policy Shocks, Set-identifying Restrictions, and Asset Prices: A Benchmarking Approach for Analyzing Set-identified Models

2016 ◽  
Author(s):  
GGbor B. Uhrin ◽  
Helmut Herwartz
Keyword(s):  
Monetary Policy ◽  
Asset Prices ◽  
Monetary Policy Shocks ◽  
Policy Shocks

scholarly journals The Time-Varying Effect of Monetary Policy on Asset Prices

2020 ◽  
Vol 102 (4) ◽  
pp. 690-704 ◽  
Author(s):  
Pascal Paul
Keyword(s):  
Monetary Policy ◽  
Asset Prices ◽  
House Prices ◽  
The United States ◽  
Model Parameters ◽  
Time Varying ◽  
Real Economy ◽  
Monetary Policy Shocks ◽  
Vector Autoregressive ◽  
Policy Shocks

This paper studies how monetary policy jointly affects asset prices and the real economy in the United States. I develop an estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks. This is achieved by integrating the surprises into a vector autoregressive model as an exogenous variable. I use current short-term rate surprises because these are least affected by an information effect. When allowing for time-varying model parameters, I find that compared to the response of output, the reaction of stock and house prices to monetary policy shocks was particularly low before the 2007–2009 financial crisis.

scholarly journals Monetary Policy Effects on Energy Sector Bubbles

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 472
Author(s):  
Petre Caraiani ◽  
Adrian Călin
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Asset Prices ◽  
The United States ◽  
Energy Sector ◽  
Monetary Policy Shocks ◽  
Policy Shocks ◽  
The Difference ◽  
The Interest Rate ◽  
The Impact

We investigate the effects of monetary policy shocks, including unconventional policy measures, on the bubbles of the energy sector, for the case of the United States. We estimate a time-varying Bayesian VAR model that allows for quantifying the impact of monetary policy shocks on asset prices and bubbles. The energy sector is measured through the S&P Energy Index, while bubbles are measured through the difference between asset prices and the corresponding dividends for the energy sector. We find significant differences in the impact of monetary policy shocks for the aggregate economy and for the energy sector. The findings seem sensitive to the interest rate use, i.e., whether one uses the shadow interest rate or the long-term interest rate.

Three essays on monetary and financial economics

2018 ◽  
Author(s):  
◽  
Xueli Cao
Keyword(s):  
Monetary Policy ◽  
Institutional Investors ◽  
Asset Prices ◽  
Institutional Ownership ◽  
Spillover Effects ◽  
Multivariate Garch ◽  
Time Varying ◽  
Monetary Policy Shocks ◽  
Conference Call ◽  
Policy Shocks

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This three-chapter dissertation focuses on the research topics in Monetary and Financial Economics. The first paper examines the time-varying impact of U.S. monetary policy shocks on asset prices. The monetary policy shock is identified using robust sign restrictions in a time-varying factor-augmented VAR (TVP-FAVAR). Time variations are found in both the variance of policy shocks and transmission to asset prices. The relative importance of monetary policy shocks rise significantly over time although the shock size of monetary policy shocks has declined in the sample. In terms of transmission mechanism, asset prices are more responsive in the latter part of the sample (post-1984Q1) when normalizing the shock size. We also document the effects of monetary policy on asset prices are significantly larger for recessionary periods. Finally, the paper also identifies the role of demand and supply shocks in determining the movements of asset prices. In the second paper, I investigate the spillover effects between the Growth Enterprises Market (GEM) and the Main Board stock market in China. Specifically, a multivariate GARCH model and a multivariate GARCH-in-mean model are estimated using daily data for the GEM Board and the Main Board over period June 1, 2010 - December 31, 2016. The results indicate that the Main Board leads the GEM Board in the first order and there is no mean overflow from the GEM Board to the Main Board. However, the quantile dependence, measured by cross-quantilogram, shows that there are asymmetry distributional spillover effects from the GEM Board to the Main Board. From the point of view of volatility, the GEM Board has effects on the Main Board, and it lasts a period of time in the future. The volatility of the GEM also affects the return of the Main Board negatively. Lastly, the GEM has a one-way effect on the Main Board in illiquidity. In the third paper, we document the effects of institutional investors on the qualitative information disclosure of earnings conference calls. Utilizing conference call and institutional ownership data between 2005 and 2016, we find that aggregate institutional ownership dampens conference call tone. The effects of institutional investors on tone are causal based on results from indexed firms. Consistent with hypotheses regarding investors horizon, short-term institutional investors are associated with greater conference call tone, as well as potentially opportunistic trading, while long-term investors decrease tone. Market participants can generally disentangle the impact of institutional investors on tone based on investor type.

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