Volatility persistence and time-varying betas in the UK real estate market

This paper investigates the degree of return volatility persistence and the time-varying behaviour of systematic risk (beta) for 31 market segments in the UK real estate market. The findings suggest that different property types exhibit differences in volatility persistence and time variability. There is also evidence that the volatility persistence of each market segment and its systematic risk are significantly positively related. Thus, the systematic risks of different property types tend to move in different directions during periods of increased market volatility. Finally, the market segments with systematic risks less than one tend to show negative time variability, while market segments with systematic risk greater than one generally show positive time variability, indicating a positive relationship between the volatility of the market and the systematic risk of individual market segments. Consequently safer and riskier market segments are affected differently by increases in market volatility

Stock Market Regulations and Internacional Financial Integration: the case of Spain

International financial integration effects on the Spanish stock market are studied, both for the conditional mean and conditional variance. New institutional regulations in Spain are taken into account and their efficiency consequences are addressed. Results suggest an increasing international integration but nontrivial opportunities for financial diversification may still be relevant.Publicad

Stock market regulations and international financial integration: the case of Spain

International financial integration effects on Spanish stock market are studied, both for the conditional mean and conditional variance. New institutional regulations in Spain are taken into account and its efficiency consequences are addressed. Results suggest an increasing international integration but nontrivial opportunities for financial diversification may still be relevant

An extended yield curve model for bond option pricing using a Jump/Garch-m forward rate process

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1991.Includes bibliographical references (leaves 110-119).by Shigeyuki Akita and Hiroshi Maruyama.M.S

Intraday Evidence of the Informational Efficiency of the Yen/Dollar Exchange Rate

The informational efficiency of the yen/dollar exchange rate is investigated in five market segments within each business day from 1987 to 2007. Among the results, we first find that the daily exchange rate has a cointegrating relationship with the cumula-tive price change of the segment for which the London and New York markets are both open, but not with that of any other segments. Second, the cumulative price change of the London/N.Y. segment is the most persistent among the five market segments in the medium- and long-run. These results suggest that the greatest concentration of informed traders is in the London/N.Y. segment where intraday transactions are the highest. This is consistent with the theoretical prediction by Admati and Pfleiderer (1988) that prices are more informative when trading volume is heavier.Informational efficiency; Market segments; Yen/dollar exchange rate

Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review

Autoregressive Conditional Heteroscedasticity (ARCH) models have successfully been employed in order to predict asset return volatility. Predicting volatility is of great importance in pricing financial derivatives, selecting portfolios, measuring and managing investment risk more accurately. In this paper, a number of univariate and multivariate ARCH models, their estimating methods and the characteristics of financial time series, which are captured by volatility models, are presented. The number of possible conditional volatility formulations is vast. Therefore, a systematic presentation of the models that have been considered in the ARCH literature can be useful in guiding one’s choice of a model for exploiting future volatility, with applications in financial markets

Econometric Techniques to Examine Volatility in PEX Bulls and Bears and the Causal Relationship between PEX, ASE and TASE

This study is empirically aimed at conducting three tests; testing volatility persistent in PEX bulls and bears, testing market efficiency for PEX, ASE, and TASE, and testing the causality relationship between the three markets. That is, it attempts to explore whether stock market volatility present a different behavior during PEX bulls and bears phases and explore whether PEX, ASE, and TASE are efficient at weak level. For this purpose, long memory measure is used to indicate volatility persistence and market efficiency. In order to define bull and bear phases, we employed the 200-day moving average, already used by practioners and we found three cycles including 3 bulls and 3 bears. Thus, the study employed Rescaled Range (R/S) to calculate the values of difference parameter d to find evidence of long memory behavior for the daily data observations from August, 1997 to March, 2012. In addition to a long memory measure, the study used nonparametric ADF and PP tests to test market efficiency of PEX, ASE, and TASE at weak level. According to Jarque–Bera test, the closing values of Al-Quds Index of PEX in each bull and bear don’t follow the normal probability distribution. So, the study used nonparametric tests of ADF and PP to determine whether the time series are stationary. The time series are found to be non stationary at level in each phase implying that PEX is efficient at weak level in each phase. Further, according to R/S results, the study found that the estimates of parameter d are above 0 and below 0.5 for bear phases, while the values are above 0.5 for the bull phases implying long memory stationarity for the volatility process. This means that volatility is more persistent in the PEX bears markets than in the PEX bull markets. Further, the PEX bears markets are longer than PEX bulls markets. As a result, volatility persistent in PEX bears and risk associated with it should be considered by investors. Added to this, the overall market-adjusted performance measurement indicates that PEX has average levels of returns and risk more than ASE and TASE. To avoid that, investors and other decision makers should consider both fundamental and technical analysis. For market efficiency test, ADF and PP test are also used to find whether time series data of Al-Quds index, ASE index and TA-100 index are stationarity. In the three cases, means and variances seem to be not constant. This indicates that the three indices are found to be nonstationary at level implying that the three markets are efficient at weak level. For further investigation, R/S statistic is used to calculate the difference parameter to indicate market efficiency. The estimates of d are above 0.5 for the PEX and TASE cases implying that time series data are non-stationary, and there is no evidence of long memory behavior (long range dependence) in the time series data. For ASE, the value of d is above 0 and below 0.5 implying that the time series has long memory behavior. This indicates that ASE isn’t efficient at weak level. So, we accept that PEX, and TASE are efficient at weak level but ASE isn’t. Therefore, regulators and policy makers should support market efficiency.The study further investigates correlation and causality relationship among PEX, ASE and TASE. It analyzes whether there is a long run linkage or interdependency between the three markets. The data sample includes daily observations for the January, 2000-March, 2012 time period. As mentioned before, the data are non-stationary at level, while the data are stationary at first difference and therefore conducting Granger causality tests isn’t restricted. The correlation matrix indicates that the three markets aren’t highly correlated. The correlation is verified for the direction of influence by the Granger causality test between the three markets. However, the study found that there is no significant causal relationship between the three markets except theunilateral causality relationship of ASE over PEX, and the relationship of TASE over ASE, whereas reverse causality doesn’t hold true. In general, the study finds that there is no multilateral causal relationship among the three markets and they are being highly correlated. Therefore, Palestinian investors don’t have to consider changes in TASE index, while changes in ASE index must be considered.This study is empirically aimed at conducting three tests; testing volatility persistent in PEX bulls and bears, testing market efficiency for PEX, ASE, and TASE, and testing the causality relationship between the three markets. That is, it attempts to explore whether stock market volatility present a different behavior during PEX bulls and bears phases and explore whether PEX, ASE, and TASE are efficient at weak level. For this purpose, long memory measure is used to indicate volatility persistence and market efficiency. In order to define bull and bear phases, we employed the 200-day moving average, already used by practioners and we found three cycles including 3 bulls and 3 bears. Thus, the study employed Rescaled Range (R/S) to calculate the values of difference parameter d to find evidence of long memory behavior for the daily data observations from August, 1997 to March, 2012. In addition to a long memory measure, the study used nonparametric ADF and PP tests to test market efficiency of PEX, ASE, and TASE at weak level. According to Jarque–Bera test, the closing values of Al-Quds Index of PEX in each bull and bear don’t follow the normal probability distribution. So, the study used nonparametric tests of ADF and PP to determine whether the time series are stationary. The time series are found to be non stationary at level in each phase implying that PEX is efficient at weak level in each phase. Further, according to R/S results, the study found that the estimates of parameter d are above 0 and below 0.5 for bear phases, while the values are above 0.5 for the bull phases implying long memory stationarity for the volatility process. This means that volatility is more persistent in the PEX bears markets than in the PEX bull markets. Further, the PEX bears markets are longer than PEX bulls markets. As a result, volatility persistent in PEX bears and risk associated with it should be considered by investors. Added to this, the overall market-adjusted performance measurement indicates that PEX has average levels of returns and risk more than ASE and TASE. To avoid that, investors and other decision makers should consider both fundamental and technical analysis. For market efficiency test, ADF and PP test are also used to find whether time series data of Al-Quds index, ASE index and TA-100 index are stationarity. In the three cases, means and variances seem to be not constant. This indicates that the three indices are found to be nonstationary at level implying that the three markets are efficient at weak level. For further investigation, R/S statistic is used to calculate the difference parameter to indicate market efficiency. The estimates of d are above 0.5 for the PEX and TASE cases implying that time series data are non-stationary, and there is no evidence of long memory behavior (long range dependence) in the time series data. For ASE, the value of d is above 0 and below 0.5 implying that the time series has long memory behavior. This indicates that ASE isn’t efficient at weak level. So, we accept that PEX, and TASE are efficient at weak level but ASE isn’t. Therefore, regulators and policy makers should support market efficiency.The study further investigates correlation and causality relationship among PEX, ASE and TASE. It analyzes whether there is a long run linkage or interdependency between the three markets. The data sample includes daily observations for the January, 2000-March, 2012 time period. As mentioned before, the data are non-stationary at level, while the data are stationary at first difference and therefore conducting Granger causality tests isn’t restricted. The correlation matrix indicates that the three markets aren’t highly correlated. The correlation is verified for the direction of influence by the Granger causality test between the three markets. However, the study found that there is no significant causal relationship between the three markets except theunilateral causality relationship of ASE over PEX, and the relationship of TASE over ASE, whereas reverse causality doesn’t hold true. In general, the study finds that there is no multilateral causal relationship among the three markets and they are being highly correlated. Therefore, Palestinian investors don’t have to consider changes in TASE index, while changes in ASE index must be considered

Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review

Autoregressive Conditional Heteroscedasticity (ARCH) models have successfully been employed in order to predict asset return volatility. Predicting volatility is of great importance in pricing financial derivatives, selecting portfolios, measuring and managing investment risk more accurately. In this paper, a number of univariate and multivariate ARCH models, their estimating methods and the characteristics of financial time series, which are captured by volatility models, are presented. The number of possible conditional volatility formulations is vast. Therefore, a systematic presentation of the models that have been considered in the ARCH literature can be useful in guiding one’s choice of a model for exploiting future volatility, with applications in financial markets