113 research outputs found
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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
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