Asymmetric Effects (asymmetric + effects)

Distribution by Scientific Domains
Distribution within Business, Economics, Finance and Accounting


Selected Abstracts


Does Monetary Policy Have Asymmetric Effects on Stock Returns?

JOURNAL OF MONEY, CREDIT AND BANKING, Issue 2-3 2007
SHIU-SHENG CHEN
monetary policy; stock returns; Markov-switching This paper investigates whether monetary policy has asymmetric effects on stock returns using Markov-switching models. Different measures of a monetary policy stance are adopted. Empirical evidence from monthly returns on the Standard & Poor's 500 price index suggests that monetary policy has larger effects on stock returns in bear markets. Furthermore, it is shown that a contractionary monetary policy leads to a higher probability of switching to the bear-market regime. [source]


Financial Intermediaries and Interest Rate Risk: II

FINANCIAL MARKETS, INSTITUTIONS & INSTRUMENTS, Issue 5 2006
Sotiris K. Staikouras
The current work extends and updates the previous survey (Staikouras, 2003) by looking at other aspects of the financial institutions' yield sensitivity. The study starts with an extensive discussion of the origins of asset-liability management and the subsequent work to identify effective ways of measuring and managing interest rate risk. The discussion implicates both regulatory and market-based approaches along with any issues surrounding their applicability. The literature is enriched by recognizing that structural and regulatory shifts affect financial institutions in different ways depending on the size and nature of their activities. It is also noted that such shifts could change the bank's riskiness, and force banks to adjust their balance sheet size by altering their maturity intermediation function. Besides yield changes, market cycles are also held responsible for asymmetric effects on corporate values. Furthermore, nonstandard investigations are considered, where embedded options and basis risk are significant above and beyond the intermediary's rate sensitivity, while shocks to the slope of the yield curve is identified as a new variable. When the discount privilege is modeled as an option, it is shown that its value is incorporated in the equities of qualifying banks. Finally, volatility clustering is further established while constant relative risk aversion is not present in the U.S. market. Although some empirical findings may be quite mixed, there is a general consensus that all forms of systematic risk, risk premia, and the risk-return trade-off do exhibit some form of variability, not only over time but also across corporate sizes and segments. [source]


Macroeconomic News and Stock Returns in the United States and Germany

GERMAN ECONOMIC REVIEW, Issue 2 2006
Norbert Funke
Stock markets; macroeconomic news Abstract. Using daily data for the January 1997 to June 2002 period, we analyze similarities and differences in the impact of macroeconomic news on stock returns in the United States and Germany. We consider 27 different types of news for the United States and 12 different types of news for Germany. For the United States, we present evidence for asymmetric reactions of stock prices to news. In a boom (recession) period, bad (good) news on GDP growth and unemployment or lower (higher) than expected interest rates may be good news for stock prices. In the period under consideration there is little evidence for asymmetric effects in Germany. However, in the case of Germany, international news appears at least as important as domestic news. There is no evidence that US stock prices are influenced by German news. The analysis of bi-hourly data for Germany confirms these results. [source]


The physiological basis of human sexual arousal: neuroendocrine sexual asymmetry

INTERNATIONAL JOURNAL OF ANDROLOGY, Issue 2 2005
ION G. MOTOFEI
Summary Normal sexual arousal and response suppose an integrated process involving both physiological and psychological processes. However, the current understanding of sexual arousal does not provide a coherent model that accounts for the integration of multiple physiological systems that subsequently generate a coordinated sexual response at both the spinal peripheral and cerebral central levels. Herein we suggest a model that involves both sympathetic and parasympathetic activation during sexual arousal via the two classes of gonadal hormones, androgens and oestrogens. We discuss the manner in which gonadal hormones may activate such a system, transforming pre-pubertal (non-erotic) genital stimulation to post-pubertal erogenization of stimulation and subsequent sexual arousal. Finally, we indicate that the different balance of androgens and oestrogens in men and women may generate asymmetric effects on each of the components of the autonomic nervous system, thereby explaining some of the differences in patterns of sexual arousal and the responses cycle across the sexes. [source]


Volatility forecasting with double Markov switching GARCH models

JOURNAL OF FORECASTING, Issue 8 2009
Cathy W. S. Chen
Abstract This paper investigates inference and volatility forecasting using a Markov switching heteroscedastic model with a fat-tailed error distribution to analyze asymmetric effects on both the conditional mean and conditional volatility of financial time series. The motivation for extending the Markov switching GARCH model, previously developed to capture mean asymmetry, is that the switching variable, assumed to be a first-order Markov process, is unobserved. The proposed model extends this work to incorporate Markov switching in the mean and variance simultaneously. Parameter estimation and inference are performed in a Bayesian framework via a Markov chain Monte Carlo scheme. We compare competing models using Bayesian forecasting in a comparative value-at-risk study. The proposed methods are illustrated using both simulations and eight international stock market return series. The results generally favor the proposed double Markov switching GARCH model with an exogenous variable. Copyright © 2008 John Wiley & Sons, Ltd. [source]


Does Monetary Policy Have Asymmetric Effects on Stock Returns?

JOURNAL OF MONEY, CREDIT AND BANKING, Issue 2-3 2007
SHIU-SHENG CHEN
monetary policy; stock returns; Markov-switching This paper investigates whether monetary policy has asymmetric effects on stock returns using Markov-switching models. Different measures of a monetary policy stance are adopted. Empirical evidence from monthly returns on the Standard & Poor's 500 price index suggests that monetary policy has larger effects on stock returns in bear markets. Furthermore, it is shown that a contractionary monetary policy leads to a higher probability of switching to the bear-market regime. [source]


The Effects of Household Income Volatility on Divorce

AMERICAN JOURNAL OF ECONOMICS AND SOCIOLOGY, Issue 3 2010
John M. Nunley
We extend the literature on the effects of earnings shocks on divorce by identifying separately the effects of transitory and permanent household income shocks and by allowing the shocks to have asymmetric effects across education and racial groups. The econometric evidence suggests negative (positive) transitory household income shocks increase (decrease) the probability of divorce, while there is only weak evidence that positive (negative) permanent household income shocks raise (lower) the probability of divorce. Some differences in the effects of household income shocks on divorce propensities arise for subsamples selected by education and race. [source]


Spot-futures spread, time-varying correlation, and hedging with currency futures

THE JOURNAL OF FUTURES MARKETS, Issue 10 2006
Donald Lien
This article investigates the effects of the spot-futures spread on the return and risk structure in currency markets. With the use of a bivariate dynamic conditional correlation GARCH framework, evidence is found of asymmetric effects of positive and negative spreads on the return and the risk structure of spot and futures markets. The implications of the asymmetric effects on futures hedging are examined, and the performance of hedging strategies generated from a model incorporating asymmetric effects is compared with several alternative models. The in-sample comparison results indicate that the asymmetric effect model provides the best hedging strategy for all currency markets examined, except for the Canadian dollar. Out-of-sample comparisons suggest that the asymmetric effect model provides the best strategy for the Australian dollar, the British pound, the deutsche mark, and the Swiss franc markets, and the symmetric effect model provides a better strategy than the asymmetric effect model in the Canadian dollar and the Japanese yen. The worst performance is given by the naïve hedging strategy for both in-sample and out-of-sample comparisons in all currency markets examined. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:1019,1038, 2006 [source]


Modelling financial time series with threshold nonlinearity in returns and trading volume

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4 2007
Mike K. P. So
Abstract This paper investigates the effect of past returns and trading volumes on the temporal behaviour of international market returns. We propose a class of nonlinear threshold time-series models with generalized autoregressive conditional heteroscedastic disturbances. Using Bayesian approach, an implementation of Markov chain Monte Carlo procedure is used to obtain estimates of unknown parameters. The proposed family of models incorporates changes in log of volumes in the sense of regime changes and asymmetric effects on the volatility functions. The results show that when differences of log volumes are involved in the system of log return and volatility models, an optimum selection can be achieved. In all the five markets considered, both mean and variance equations involve volumes in the best models selected. Our best models produce higher posterior-odds ratios than that in Gerlach et al.'s (Phys. A Statist. Mech. Appl. 2006; 360:422,444) models, indicating that our return,volume partition of regimes can offer extra gain in explaining return-volatility term structure. Copyright © 2007 John Wiley & Sons, Ltd. [source]