Asset price volatility and trading volume with rational beliefs

2004 ◽  
Vol 23 (4) ◽  
pp. 795-829 ◽  
Author(s):  
Ho-Mou Wu ◽  
Wen-Chung Guo
Keyword(s):  
Trading Volume ◽  
Asset Price ◽  
Price Volatility ◽  
Rational Beliefs

Fifty years of UK asset price volatility

2000 ◽  
Vol 2 (3) ◽  
pp. 63-77 ◽  
Author(s):  
Nicola Anderson ◽  
Francis Breedon
Keyword(s):  
Asset Price ◽  
Price Volatility

U.K. Asset Price Volatility Over the Last 50 Years

1996 ◽  
Author(s):  
Nicola Anderson ◽  
Francis Breedon
Keyword(s):  
Asset Price ◽  
Price Volatility

scholarly journals News Shocks and Asset Price Volatility in General Equilibrium

2011 ◽  
Author(s):  
Akito Matsumoto ◽  
Pietro Cova ◽  
Massimiliano Pisani ◽  
Alessandro Rebucci
Keyword(s):  
General Equilibrium ◽  
Asset Price ◽  
Price Volatility ◽  
News Shocks

scholarly journals Fund Managers, Career Concerns, and Asset Price Volatility

2009 ◽  
Author(s):  
Veronica Guerrieri ◽  
Péter Kondor
Keyword(s):  
Asset Price ◽  
Price Volatility ◽  
Career Concerns ◽  
Fund Managers

Returns and volume

2020 ◽  
Vol 37 (3) ◽  
pp. 457-473
Author(s):  
Panos Fousekis
Keyword(s):  
Trading Volume ◽  
Time Series Data ◽  
Price Volatility ◽  
Statistical Testing ◽  
Model Specification ◽  
Series Data ◽  
Causal Order ◽  
Content Type ◽  
Daily Data ◽  
The Usa

Purpose The relationship between returns and trading volume is central in financial economics because it has both a theoretical interest and important practical implications with regard to the structure of financial markets and the level of speculation activity. The aim of this study is to provide new insights into the association between returns and trading volume by investigating their kernel (instantaneous) causality. The empirical analysis relies on time series data from 22 commodities futures markets (agricultural, energy and metals) in the USA. Design/methodology/approach Non-parametric (local linear) regressions are applied to daily data on returns and on trading activity; generalized correlation measures are computed and their differences are subjected to formal statistical testing. Findings The results suggest that raw returns are likely to kernel-cause volume and volume is likely to kernel-cause price volatility. The patterns of causal order are generally in line with what is stipulated by the relevant theory, they provide guidance for model specification and they appear to explain the empirical evidence on temporal (lag-lead) causality between the same pairs of variables obtained in earlier works. Originality/value The concept of kernel causality has very recently become a part of the toolkit for econometric/statistical analysis. To the best of the author’s knowledge, this is the first study that relies on the notion of kernel (instantaneous) causality to provide new evidence on a relationship that is of keen interest to investors, professional economists and policymakers.

What Can Explain the Price, Volatility and Trading Volume of Bitcoin?

2018 ◽  
Author(s):  
Halvor Aalborg ◽  
Peter Molnár ◽  
Jon Erik de Vries
Keyword(s):  
Trading Volume ◽  
Price Volatility

Asset Price and the Optimal Monetary Policy: Model and Simulation

2011 ◽  
Vol 422 ◽  
pp. 466-469
Author(s):  
Hai Cheng Peng ◽  
Lu Li
Keyword(s):  
Monetary Policy ◽  
Asset Price ◽  
Price Volatility ◽  
Reaction Function ◽  
Optimal Monetary Policy ◽  
Policy Objective ◽  
Policy Model ◽  
Model And Simulation ◽  
Wide Range ◽  
Decision Making Model

The validity and merits of the monetary policy is reflected in the level of the attainment of its ultimate goal. We build up a decision-making model of central bank and deduce the optimal money supply reaction function of considering and ignoring asset price. In order to clarify the relationship between the optimal monetary policy and asset price volatility, we simulate the macroeconomic performance of optimal reaction function of considering and ignoring asset price in a wide range of monetary policy objective. We conclude that monetary policy should respond to volatility of asset price directly.

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