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Weekly Data (weekly + data)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	71%

Selected Abstracts

Permanent and Transitory Driving Forces in the Asian-Pacific Stock Markets

FINANCIAL REVIEW, Issue 1 2002
Ali F. Darrat
This paper uses weekly data from November 1987 through May 1999 to examine whether U.S. or the Japan stock market (or both) is the main driving force behind major movements in eleven emerging Asian-Pacific stock markets. We find a robust cointegrating relation linking each of the emerging market with the two matured markets of the U.S. and Japan. The results also show that the U.S., rather than Japan, is the main permanent force driving the equilibrium relations across all Asian-Pacific markets. In contrast, the effect of the Japanese market on the Asian-Pacific region is only transitory. Therefore, strategic asset portfolios in the Asian-Pacific region should include Japanese stocks to diversify any country specific risks. As to U.S. investors, the persistent influence of the U.S. market may limit long-run diversification gains from Asian-Pacific stocks. [source]

Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System

FINANCIAL REVIEW, Issue 1 2000
Colm Kearney
C32/F31/G15 Abstract We construct a series of 3-, 4- and 5-variable multivariate GARCH models of exchange rate volatility transmission across the important European Monetary System (EMS) currencies including the French franc, the German mark, the Italian lira, and the European Currency Unit. The models are estimated without imposing the common restriction of constant correlation on both daily and weekly data from April 1979,March 1997. Our results indicate the importance of checking for specification robustness in multivariate Generalized Autoregressive Conditional Heleroskedasticity (GARCH) modeling, we find that increased temporal aggregation reduces observed volatility transmission, and that the mark plays a dominant position in terms of volatility transmission. [source]

Winter diatom blooms in a regulated river in South Korea: explanations based on evolutionary computation

FRESHWATER BIOLOGY, Issue 10 2007
DONG-KYUN KIM
Summary 1. An ecological model was developed using genetic programming (GP) to predict the time-series dynamics of the diatom, Stephanodiscus hantzschii for the lower Nakdong River, South Korea. Eight years of weekly data showed the river to be hypertrophic (chl. a, 45.1 ± 4.19 ,g L,1, mean ± SE, n = 427), and S. hantzschii annually formed blooms during the winter to spring flow period (late November to March). 2. A simple non-linear equation was created to produce a 3-day sequential forecast of the species biovolume, by means of time series optimization genetic programming (TSOGP). Training data were used in conjunction with a GP algorithm utilizing 7 years of limnological variables (1995,2001). The model was validated by comparing its output with measurements for a specific year with severe blooms (1994). The model accurately predicted timing of the blooms although it slightly underestimated biovolume (training r2 = 0.70, test r2 = 0.78). The model consisted of the following variables: dam discharge and storage, water temperature, Secchi transparency, dissolved oxygen (DO), pH, evaporation and silica concentration. 3. The application of a five-way cross-validation test suggested that GP was capable of developing models whose input variables were similar, although the data are randomly used for training. The similarity of input variable selection was approximately 51% between the best model and the top 20 candidate models out of 150 in total (based on both Root Mean Squared Error and the determination coefficients for the test data). 4. Genetic programming was able to determine the ecological importance of different environmental variables affecting the diatoms. A series of sensitivity analyses showed that water temperature was the most sensitive parameter. In addition, the optimal equation was sensitive to DO, Secchi transparency, dam discharge and silica concentration. The analyses thus identified likely causes of the proliferation of diatoms in ,river-reservoir hybrids' (i.e. rivers which have the characteristics of a reservoir during the dry season). This result provides specific information about the bloom of S. hantzschii in river systems, as well as the applicability of inductive methods, such as evolutionary computation to river-reservoir hybrid systems. [source]

The demand impacts of chicken contamination publicity,a case study

AGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 4 2002
Roger A. Dahlgran
Adverse publicity regarding food contamination can depress demand, causing lost producer revenue. This study addresses the magnitude of those losses through the analysis of the impact of TV and print news coverage of bacterial contamination of chicken in the United States. An inverse demand model for chicken is estimated using weekly data from 1982 through 1991. Our findings indicate adverse publicity about salmonella contamination of chicken depressed the demand for chicken, but that the effect was small, less than 1% during the period of maximum exposure. Further, consumers soon forget this news as they reverted to prior consumption patterns in a matter of weeks. [EconLit citation: D120] © 2002 Wiley Periodicals, Inc. [source]

Volatility and commodity price dynamics

THE JOURNAL OF FUTURES MARKETS, Issue 11 2004
Robert S. Pindyck
Commodity prices are volatile, and volatility itself varies over time. Changes in volatility can affect market variables by directly affecting the marginal value of storage, and by affecting a component of the total marginal cost of production, the opportunity cost of producing the commodity now rather than waiting for more price information. I examine the role of volatility in short-run commodity market dynamics and the determinants of volatility itself. I develop a structural model of inventories, spot, and futures prices that explicitly accounts for volatility, and estimate it using daily and weekly data for the petroleum complex: crude oil, heating oil, and gasoline. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:1029,1047, 2004 [source]

Modelling the process of incoming problem reports on released software products

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2004
Geurt Jongbloed
Abstract For big software developing companies, it is important to know the amount of problems of a new software product that are expected to be reported in a period after the date of release, on a weekly basis. For each of a number of past releases, weekly data are present on the number of such reports. Based on the type of data that is present, we construct a stochastic model for the weekly number of problems to be reported. The (non-parametric) maximum likelihood estimator for the crucial model parameter, the intensity of an inhomogeneous Poisson process, is defined. Moreover, the expectation maximization algorithm is described, which can be used to compute this estimate. The method is illustrated using simulated data. Copyright © 2004 John Wiley & Sons, Ltd. [source]

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

AUSTRALIAN ECONOMIC PAPERS, Issue 3 2010
INDIKA KARUNANAYAKE
This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997,98 and 2008,09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992,June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time-varying co-volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only. [source]