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This paper examines the relationships between flows and returns for five exchange traded funds (ETF) in the U.S. energy sector. Four alternative hypotheses are tested, including the price pressure hypothesis, information (or price release) hypothesis, feedback trading hypothesis, and smoothing hypothesis. The five ETF are the Energy Select Sector SPDR Fund (XLE), iShares U.S. Energy ETF (IYE), iShares Global Energy ETF (IXC), Vanguard Energy ETF (VDE), and PowerShares Dynamic Energy Exploration & Production Portfolio (PXE). A vector autoregressive (VAR) model is used to analyze the relationships between energy flows and returns. The empirical results show that energy ETF flows and subsequent returns have a negative relationship, thereby supporting the smoothing hypothesis. Moreover, the smoothing effect exists for XLE and IYE during the global financial crisis. Regardless of whether the whole sample period or the sub-samples before, during and after the global financial crisis are used, no evidence is found in support of the price pressure hypothesis, information hypothesis, or feedback trading hypothesis.

Polycystic ovary syndrome (PCOS) is characterized by oligo- or anovulation, polycystic ovary, and/or hyperandrogenism. In addition, many PCOS patients present with dyslipidemia, insulin resistance, and obesity. Due to the complexity of this disorder, the causes of PCOS remain to be identified.Because many PCOS patients have a propensity to develop dyslipidemia, we hypothesized that the brown adipose-differentiation factor, irisin, and the glucose-dependent insulinotropic peptide (GIP) play a role in the development of PCOS.Serum hormone levels in 202 PCOS patients and 47 healthy women were investigated.Patients were stratified based on the presence/absence of metabolic syndrome risk factors, as defined by the National Cholesterol Education Program's Adult Treatment Panel III report (ATPIII [+] and ATPIII [-]), or body mass index (healthy-weight and overweight).We measured serum irisin, GIP, LH, anti-Mullerian hormone (AMH), and androgens as well as metabolic indices including homeostasis model assessment-insulin resistance, Matsuda's sensitivity index, and quantitative insulin-sensitivity check index.PCOS patients exhibited hyperandrogenism, dyslipidemia, and hyperinsulinism, as well as elevated LH and AMH levels. In addition, fasting irisin level (P.001) and glucose-induced GIP response (P = .013) in PCOS patients were significantly elevated as compared to those of control women. Remarkably, levels of fasting irisin and glucose-induced GIP response remained significantly elevated in ATP III [-] PCOS and healthy-weight PCOS patients when compared to matched controls. Analysis of the effect size indicated that both fasting irisin and glucose-induced GIP response are significant risk factors for PCOS with odds ratios of 6.63 and 4.21, respectively.Although there is as yet no evidence for a causal link between irisin and/or GIP and PCOS, it is conceivable that irisin and GIP might contribute to the development of PCOS and may also represent novel PCOS biomarkers.

This paper examines the determinants of very low birth weight infant (or neonatal) mortality using the Taiwan National Health Insurance Research database from 1997 to 2009. After infants are discharged from hospital, it is not possible to track their mortality, so the Cox proportional hazard model is used to analyze the very low birth weight infant mortality rate. In order to clarify treatment responsibility and to avoid selective referral effects, we use the number of infants treated in the preceding five years to observe the effect of a physician’s and hospital’s medical experience on the mortality rate of hospitalized minimal birth weight infants. The empirical results show that, given disease control variables, a higher infant weight, higher quality hospitals, increased hospital medical experience, and higher investment in pediatrics can reduce the mortality rate significantly. However, an increased physician’s medical experience does not seem to influence significantly the very low birth weight infant mortality rate.

The paper is concerned with ranking academic journal quality and research impact in Finance, based on the widely-used Thomson Reuters ISI (2013) Web of Science citations database (hereafter ISI). The paper analyses the 89 leading international journals in the ISI category of "Business–Finance" using quantifiable Research Assessment Measures (RAMs). The analysis highlights the similarities and differences in various RAMs, all of which are based on alternative transformations of journal citations and impact. Alternative RAMs may be calculated annually or updated daily to determine the citations frequency of published papers that are cited in journals listed in ISI. The RAMs include the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy including journal self citations, Eigenfactor (or Journal Influence), Article Influence (AI), h-index, Papers Ignored-By Even The Authors (PI-BETA), Self-citation Threshold Approval Rating (STAR), 5YD2 (namely, 5YIF divided by 2YIF), Escalating Self Citations (ESC) and Index of Citation Quality (ICQ). The paper calculates the harmonic mean (HM) of the ranks of up to 16 RAMs. It is shown that emphasizing 2YIF to the exclusion of other informative RAMs can lead to a misleading evaluation of journal quality and impact relative to the HM of the ranks. The analysis of the 89 ISI journals in Finance makes it clear that there are three leading journals in Finance, namely Journal of Finance, Journal of Financial Economics and Review of Financial Studies, which form an exclusive club in terms of the RAMs that measure journal quality and impact based on alternative measures of journal citations. The next two journals in Finance in terms of overall quality and impact are Journal of Accounting and Economics and Journal of Monetary Economics. As Accounting does not have a separate classification in ISI, the tables of rankings given in the paper are also used to rank the top 3 journals in the sub-category of Accounting in the ISI category of "Business – Finance", namely Journal of Accounting and Economics, Accounting Review, and Journal of Accounting Research.

The paper uses monthly data on financial stock index returns, tourism stock sub-index returns, effective exchange rate returns and interest rate differences from April 2005 – August 2013 for Taiwan that applies Chang’s (2014) novel approach for constructing a tourism financial indicator, namely the Tourism Financial Conditions Index (TFCI). The TFCI is an adaptation and extension of the widely-used Monetary Conditions Index (MCI) and Financial Conditions Index (FCI) to tourism stock data. However, the method of calculation of the TFCI is different from existing methods of constructing the MCI and FCI in that the weights are estimated empirically. The empirical findings show that TFCI is estimated quite accurately using the estimated conditional mean of the tourism stock index returns. The new TFCI is straightforward to use and interpret, and provides interesting insights in predicting the current economic and financial environment for tourism stock index returns that are based on publicly available information. In particular, the use of market returns on the tourism stock index as the sole indicator of the tourism sector, as compared with the general activity of economic variables on tourism stocks, is shown to provide an exaggerated and excessively volatile explanation of tourism financial conditions.

The paper uses daily data on financial stock index returns, tourism stock sub-index returns, exchange rate returns and interest rate differences from 1 June 2001–28 February 2014 for Taiwan to construct a novel latent daily tourism financial indicator, namely the Tourism Financial Conditions Index (TFCI). The TFCI is an adaptation and extension of the widely-used Monetary Conditions Index (MCI) and Financial Conditions Index (FCI) to tourism stock data. However, the method of calculation of the daily TFCI is different from existing methods of constructing the MCI and FCI in that the weights are estimated empirically. Alternative versions of the TFCI are constructed, depending on the appropriate model and method of estimation, namely Ordinary Least Squares (OLS) or Quasi-Maximum Likelihood Estimation (QMLE) of alternative conditional volatility models. Three univariate conditional volatility models are considered, namely GARCH, GJR and EGARCH, in an attempt to capture the inherent volatility in the daily tourism stock index returns. The empirical findings show that TFCI is estimated quite accurately using the estimated conditional mean of the tourism stock index returns, especially when conditional volatility is incorporated in the overall specification. The new daily TFCI is straightforward to use and interpret, and provides interesting insights in predicting the current economic and financial environment for tourism stock index returns, especially as it is based on straightforward calculations and interpretations of publicly available information.

The paper analyses academic journal quality and research impact using quality weighted citations versus total citations, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). A new Index of Citations Quality (ICQ) is presented, based on quality weighted citations. The new index is used to analyse the leading 500 journals in both the Sciences and Social Sciences using quantifiable Research Assessment Measures (RAMs) that are based on alternative transformations of citations. It is shown that ICQ is a useful additional measure to 2YIF and other well known RAMs for the purpose of evaluating the impact and quality, as well as ranking, of journals as it contains information that has very low correlations with the information contained in the well known RAMs for both the Sciences and Social Sciences.

See also the article in the Review of Economics (2014). Volume 65(1), pages 35-52. The paper analyses academic journal quality and impact using quality weighted citations that are based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). A recently developed Index of Citations Quality (ICQ), based on quality weighted citations, is used to analyse the top 276 Economics and top 10 Econometrics journals in the ISI Economics category using alternative quantifiable Research Assessment Measures (RAMs). It is shown that ICQ is a useful additional measure to the 2-Year Impact Factor (2YIF) and other well known RAMs available in ISI for the purpose of evaluating journal impact and quality, as well as ranking, of Economics and Econometrics journals as it contains information that has very low correlations with the information contained in alternative well-known RAMs. Among other findings, the top Econometrics journals have some of the highest ICQ scores in the ISI category of Economics.

This paper uses monthly data from April 2005 to August 2013 for Taiwan to propose a novel tourism indicator, namely the Tourism Conditions Index (TCI). TCI accounts for the spillover weights based on the Granger causality test and estimates of the multivariate BEKK model for four TCI indicators to predict specific tourism and economic environmental indicators for Taiwan. The foundation of the TCI is the Financial Conditions Index (FCI), which is derived from the Monetary Conditions Index (MCI). The empirical findings show that TCI weighted by spillovers reveal greater significance in forecasting the Composite Index (CI), an economic environmental indicator, than the Tourism Industry Index (TII), which is an existing indicator for the tourism industry that is listed on the Taiwan Stock Exchange (TWSE). Moreover, previous values of the alternative TCI and TII are shown to contain useful information in predicting both tourism and economic environmental factors. Overall, the new Tourism Conditions Index is straightforward to use and also provides useful insights in predicting tourism arrivals and the current economic environment.

The Basel III Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one of a range of alternative risk models to forecast Value-at-Risk (VaR). The risk estimates from these models are used to determine the daily capital charges (DCC) and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realized losses exceed the estimated VaR. In this paper we define risk management in terms of choosing sensibly from a variety of risk models and discuss the optimal selection of financial risk models. A previous approach to model selection for predicting VaR proposed combining alternative risk models and ranking such models on the basis of average DCC. This method is based only on the first moment of the DCC distribution, supported by a restrictive evaluation function. In this paper, we consider uniform rankings of models over large classes of evaluation functions that may reflect different weights and concerns over different intervals of the distribution of losses and DCC. The uniform rankings are based on recently developed statistical tests of stochastic dominance (SD). The SD tests are illustrated using the prices and returns of VIX futures. The empirical findings show that the tests of SD can rank different pairs of models to a statistical degree of confidence, and that the alternative (recentered) SD tests are in general agreement.

A 31-year-old woman had secondary infertility of 4 years' duration. Hysterosalpingography revealed bilateral distal tubal occlusion with bilateral hydrosalpinx-like appearance. At laparoscopy, both oviducts were occluded with marked hydropic change. Salpingoplasty was performed to correct bilateral hydrosalpinges and reform the fimbriated tubal ends. The procedure was performed uneventfully by an experienced surgeon in 45 minutes. Nine hours after the operation an emergency exploratory laparotomy was performed due to massive intraabdominal bleeding. The cause was a small tear, 3 cm long and 1 cm deep, with active bleeding in the inferior splenic tail. The laceration was repaired successfully with 1–0 chromic suture. The etiology of splenic laceration during laparoscopic surgery is uncertain. Many complications of laparoscopy are physiologic, and this one might have occurred while establishing pneumoperitoneum. Distortion and stretching of small vascular adhesions of the spleen with the abdominal wall also may have played a role. Gynecologists must be aware of the physiologic insult to patients during laparoscopy.

A 65-year-old man with benign prostatic hyperplasia presented with abdominal fullness and constipation for one week. He did not report any nausea, vomiting or abdominal pain but he mentioned having decreased urine output for the past few days. He recalled that he took some over-the-countermedication for common cold last week. Physical examination revealed a rounded, non-pulsatile mass, more than 15 cm in size, over the lower abdomen with dullness on percussion. Abdominal radiograph showed a huge, ‘full moon’ shadow in the lower abdomen, with severe compression of the adjacent colon (Fig. 1).

The initial resistance of chemiresistive gas sensors could be affected by temperature, humidity, and background odors. In a sensing system, the traditional interface circuit always requires an ADC to convert analog signal to digital signal. In this paper, we propose an ADC-free adaptive interface circuit for a resistive gas sensor to read sensor signal and cancel the baseline drift. Furthermore, methanol was used to test the proposed interface circuit, which was connected with a FIGARO® gas sensor. This circuit was fabricated by TSMC 0.18 µm CMOS process, and consumed 86.41 µW under 1 V supply voltage.

The paper focuses on the robustness of rankings of academic journal quality and research impact of 10 leading econometrics journals taken from the Thomson Reuters ISI Web of Science (ISI) Category of Economics, using citations data from ISI and the highly accessible Research Papers in Economics (RePEc) database that is widely used in economics, finance and related disciplines. The journals are ranked using quantifiable static and dynamic Research Assessment Measures (RAMs), with 15 RAMs from ISI and five RAMs from RePEc. The similarities and differences in various RAMs, which are based on alternative weighted and unweighted transformations of citations, are highlighted to show which RAMs are able to provide informational value relative to others. The RAMs include the impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. The paper highlights robust rankings based on the harmonic mean of the ranks of 20 RAMs, which in some cases are closely related. It is shown that emphasizing the most widely-used RAM, the two-year impact factor of a journal, can lead to a distorted evaluation of journal quality, impact and influence relative to the harmonic mean of the ranks. Some suggestions regarding the use of the most informative RAMs are also given.

This discussion paper resulted in a publication in The North American Journal of Economics and Finance (2014). Volume 29(C), pages 381-401. This paper investigates the stock returns and volatility size effects for firm performance in the Taiwan tourism industry, especially the impacts arising from the tourism policy reform that allowed mainland Chinese tourists to travel to Taiwan. Four conditional univariate GARCH models are used to estimate the volatility in the stock indexes for large and small firms in Taiwan. Daily data from 30 November 2001 to 27 February 2013 are used, which covers the period of Cross-Straits tension between China and Taiwan. The full sample period is divided into two subsamples, namely prior to and after the policy reform that encouraged Chinese tourists to Taiwan. The empirical findings confirm that there have been important changes in the volatility size effects for firm performance, regardless of firm size and estimation period. Furthermore, the risk premium reveals insignificant estimates in both time periods, while asymmetric effects are found to exist only for large firms after the policy reform. The empirical findings should be useful for financial managers and policy analysts as it provides insight into the magnitude of the volatility size effects for firm performance, how it can vary with firm size, the impacts arising from the industry policy reform, and how firm size is related to financial risk management strategy.

With the advent of globalization, economic and financial interactions among countries have become widespread. Given technological advancements, the factors of production can no longer be considered to be just labor and capital. In the pursuit of economic growth, every country has sensibly invested in international cooperation, learning, innovation, technology diffusion and knowledge. In this paper, we use a panel data set of 40 countries from 1981 to 2008 and a negative binomial model, using a novel set of cross-border patents and joint patents as proxy variables for technology diffusion, in order to investigate such diffusion. The empirical results suggest that, if it is desired to shift from foreign to domestic technology, it is necessary to increase expenditure on R&D for business enterprises and higher education, exports and technology. If the focus is on increasing bilateral technology diffusion, it is necessary to increase expenditure on R&D for higher education and technology.

In mammals, carcinoembryonic antigen cell adhesion molecules (CEACAMs) and pregnancy-specific glycoproteins (PSGs) play important roles in the regulation of pathogen transmission, tumorigenesis, insulin signaling turnover, and fetal-maternal interactions. However, how these genes evolved and to what extent they diverged in humans remain to be investigated specifically. Based on syntenic mapping of chordate genomes, we reveal that diverging homologs with a prototypic CEACAM architecture-including an extracellular domain with immunoglobulin variable and constant domain-like regions, and an intracellular domain containing ITAM motif-are present from cartilaginous fish to humans, but are absent in sea lamprey, cephalochordate or urochordate. Interestingly, the CEACAM/PSG gene inventory underwent radical divergence in various vertebrate lineages: from zero in avian species to dozens in therian mammals. In addition, analyses of genetic variations in human populations showed the presence of various types of copy number variations (CNVs) at the CEACAM/PSG locus. These copy number polymorphisms have 3-80% frequency in select populations, and encompass single to more than six PSG genes. Furthermore, we found that CEACAM/PSG genes contain a significantly higher density of nonsynonymous single nucleotide polymorphism (SNP) compared to the chromosome average, and many CEACAM/PSG SNPs exhibit high population differentiation. Taken together, our study suggested that CEACAM/PSG genes have had a more dynamic evolutionary history in vertebrates than previously thought. Given that CEACAM/PSGs play important roles in maternal-fetal interaction and pathogen recognition, these data have laid the groundwork for future analysis of adaptive CEACAM/PSG genotype-phenotypic relationships in normal and complicated pregnancies as well as other etiologies.

This paper examines the issue of coercive journal self-citations and the practical use¬fulness of two recent journal performance metrics, namely the Eigenfactor score, which may be interpreted as measuring “Journal Influence”, and the Article Influence score, using the Thomson Reuters ISI Web of Science (hereafter ISI) data for 2009 for the 200 most highly cited journals in each of the Sciences and Social Sciences. The paper also compares the two new bibliometric measures with two existing ISI metrics, namely Total Citations and the 5-year Impact Factor (5YIF) (including journal self-citations) of a journal. It is shown that the Sciences and Social Sciences are different in terms of the strength of the relationship of journal performance metrics, although the actual relationships are very similar. Moreover, the journal influence and article influence journal performance metrics are shown to be closely related empirically to the two existing ISI metrics, and hence add little in practical usefulness to what is already known, except for eliminating the pressure arising from coercive journal self-citations. These empirical results are compared with existing results in the bibliometrics literature.

Macro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average, as the actual value is approached. Otherwise, forecast updates would be neutral. The paper proposes a methodology to test whether forecast updates are progressive and whether econometric models are useful in updating forecasts. The data set for the empirical analysis are for Taiwan, where we have three decades of quarterly data available of forecasts and updates of the inflation rate and real GDP growth rate. The actual series for both the inflation rate and the real GDP growth rate are always released by the government one quarter after the release of the revised forecast, and the actual values are not revised after they have been released. Our empirical results suggest that the forecast updates for Taiwan are progressive, and can be explained predominantly by intuition. Additionally, the one-, two- and three-quarter forecast errors are predictable using publicly available information for both the inflation rate and real GDP growth rate, which suggests that the forecasts can be improved.

See the article in the Annals of Financial Economics (2013). Volume 8(1), pages 1-30. Experts possess knowledge and information that are not publicly available. The paper is concerned with forecasting academic journal quality and research impact using a survey of international experts from a national project on ranking academic finance journals in Taiwan. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance (hereafter Finance) category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. The harmonic mean of the ranks of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A linear regression model is used to forecast expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal. The robustness of the rankings is also analysed.

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, ARDL model, and alternative volatility models, including GARCH, EGARCH, and GJR models, are used to investigate the relationship between crude oil price and six global fertilizer prices. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price while the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods.

Azimuthal angle-dependent second harmonic generation is carried out to reveal the near surface band bending due to the surface state induced by Se vacancy in Bi 2 Se 3 . The surface band bending can be removed by tuning the Se molar ratio.

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modelling and Management” (RMM2011). The papers cover the following topics: currency hedging strategies using dynamic multivariate GARCH, risk management of risk under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes via Gaussian mixture models, GFC-robust risk management under the Basel Accord using extreme value methodologies, volatility spillovers from the Chinese stock market to economic neighbours, a detailed comparison of Value-at-Risk estimates, the dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value-at-risk with a duration-based POT method, and extreme market risk and extreme value theory.

See the article in The North American Journal of Economics and Finance (2013). Volume 26(C), pages 217-226. Research papers in empirical finance and financial econometrics are among the most widely cited, downloaded and viewed articles in the discipline of Finance. The special issue presents several papers by leading scholars in the field on “Recent Developments in Financial Economics and Econometrics”. The breadth of coverage is substantial, and includes original research and comprehensive review papers on theoretical, empirical and numerical topics in Financial Economics and Econometrics by leading researchers in finance, financial economics, financial econometrics and financial statistics. The purpose of this special issue on “Recent Developments in Financial Economics and Econometrics” is to highlight several novel and significant developments in financial economics and financial econometrics, specifically dynamic price integration in the global gold market, a conditional single index model with local covariates for detecting and evaluating active management, whether the Basel Accord has improved risk management during the global financial crisis, the role of banking regulation in an economy under credit risk and liquidity shock, separating information maximum likelihood estimation of the integrated volatility and covariance with micro-market noise, stress testing correlation matrices for risk management, whether bank relationship matters for corporate risk taking, with evidence from listed firms in Taiwan, pricing options on stocks denominated in different currencies, with theory and illustrations, EVT and tail-risk modelling, with evidence from market indices and volatility series, the economics of data using simple model free volatility in a high frequency world, arbitrage-free implied volatility surfaces for options on single stock futures, the non-uniform pricing effect of employee stock options using quantile regression, nonlinear dynamics and recurrence plots for detecting financial crisis, how news sentiment impacts asset volatility, with evidence from long memory and regime-switching approaches, quantitative evaluation of contingent capital and its applications, high quantiles estimation with Quasi-PORT and DPOT, with an application to value-at-risk for financial variables, evaluating inflation targeting based on the distribution of inflation and inflation volatility, the size effects of volatility spillovers for firm performance and exchange rates in tourism, forecasting volatility with the realized range in the presence of noise and non-trading, using CARRX models to study factors affecting the volatilities of Asian equity markets, deciphering the Libor and Euribor spreads during the subprime crisis, information transmission between sovereign debt CDS and other financial factors for Latin America, time-varying mixture GARCH models and asymmetric volatility, and diagnostic checking for non-stationary ARMA models with an application to financial data.

See the publication in the North American Journal of Economics and Finance (2013). Vol. 26(SI), 519-534. This paper examines the size effects of volatility spillovers for firm performance and exchange rates with asymmetry in the Taiwan tourism industry. The analysis is based on two conditional multivariate models, BEKK-AGARCH and VARMA-AGARCH, in the volatility specification. Daily data from 1 July 2008 to 29 June 2012 for 999 firms are used, which covers the Global Financial Crisis. The empirical findings indicate that there are size effects on volatility spillovers from the exchange rate to firm performance. Specifically, the risk for firm size has different effects from the three leading tourism sources to Taiwan, namely USA, Japan, and China. Furthermore, all the return series reveal quite high volatility spillovers (at over sixty percent) with a one-period lag. The empirical results show a negative correlation between exchange rate returns and stock returns. However, the asymmetric effect of the shock is ambiguous, owing to conflicts in the significance and signs of the asymmetry effect in the two estimated multivariate GARCH models. The empirical findings provide financial managers with a better understanding of how firm size is related to financial performance, risk and portfolio management strategies that can be used in practice.

This paper examines the inter-relationships among gold prices in five global gold markets, namely London, New York, Japan, Hong Kong (since 1 July 1997, a Special Administrative Region (SAR) of China), and Taiwan. We investigate the linkages between Taiwan and the other global gold markets to provide insights for useful investment strategies. The augmenting level-VAR models proposed by Toda and Yamamoto (1995) show that the empirical results find bi-directional causality between the London and New York gold markets, and uni-directional causality from New York to the other markets. In this sense, the New York market has gained a leading role in affecting global gold markets. This empirical finding serves as a predictor for the gold price in global markets.

Electronic noses (e-nose) have been studied for several years and extensively applied; however, they are limited by their volume and high manufacturing cost. Portable devices have become popular in recent years; therefore, it is crucial to integrate e-noses in portable devices (e.g., mobile phones). This study used TSMC 90nm 1P9M CMOS MSG technology to develop a front-end system-on-chip (SoC) for an electronic nose. The SoC contained interdigitated electrodes, multi-channel sensor interface circuits, an analog to digital converter, and a digital continuous restricted Boltzmann machine (CRBM). Various conducting-polymer materials were titrated on the interdigitated electrodes to form an on-chip sensor array. This SoC was controlled through an external microcontroller to perform odor identification and analysis. The simulation results of the SoC and gas classification show that this chip is suitable for portable applications and further integration.

As the preponderance of journal rankings becomes increasingly more frequent and prominent in academic decision making, such rankings in broad discipline categories is taking on an increasingly important role. The paper focuses on the robustness of rankings of academic journal quality and research impact using on the widely-used Thomson Reuters ISI Web of Science citations database (ISI) for the Statistics & Probability category. The paper analyses 110 ISI international journals in Statistics & Probability using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs, which are based on alternative transformations of citations and influence. Alternative RAMs may be calculated annually or updated daily to determine When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c), Chang et al. (2012)). The RAMs are grouped in four distinct classes that include impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. These classes include the most widely used RAMs, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Eigenfactor (or Journal Influence), Article Influence, h-index, PI-BETA (Papers Ignored - By Even The Authors), 5YD2 (= 5YIF/2YIF) as a measure of citations longevity, and Escalating Self Citations (ESC) as a measure of increasing journal self citations. The paper highlights robust rankings based on the harmonic mean of the ranks of RAMs across the 4 classes. It is shown that focusing solely on the 2-year impact factor (2YIF) of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal quality, impact and influence relative to the more robust harmonic mean of the ranks.

This paper estimates a long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat, rubber, and palm oil. The class of fractional GARCH models, namely the FIGARCH model of Baillie et al. (1996), FIEGARCH model of Bollerslev and Mikkelsen (1996), and FIAPARCH model of Tse (1998), are modelled and compared with the GARCH model of Bollerslev (1986), EGARCH model of Nelson (1991), and APARCH model of Ding et al. (1993). The estimated d parameters, indicating long-term dependence, suggest that fractional integration is found in most of agricultural commodity futures returns series. In addition, the FIGARCH (1,d,1) and FIEGARCH(1,d,1) models are found to outperform their GARCH(1,1) and EGARCH(1,1) counterparts.

C4 plants evolved from C3 plants through a series of complex evolutionary steps. On the basis of the evolution of key C4 enzyme genes, the evolution of C4 photosynthesis has been considered a story of gene/genome duplications and subsequent modifications of gene function. If whole-genome duplication has contributed to the evolution of C4 photosynthesis, other genes should have been duplicated together with these C4 genes. However, which genes were co-duplicated with C4 genes and whether they have also played a role in C4 evolution are largely unknown. In this study, we developed a simple method to characterize the historical profile of the paralogs of a gene by tracing back to the most recent common ancestor (MRCA) of the gene and its paralog(s) and then counting the number of paralogs at each MRCA. We clustered the genes into clusters with similar duplication profiles and inferred their functional enrichments. Applying our method to maize, a familiar C4 plant, we identified many genes that show similar duplication profiles with those of the key C4 enzyme genes and found that the functional preferences of the C4 gene clusters are not only similar to those identified by an experimental approach in a recent study but also highly consistent with the functions required for the C4 photosynthesis evolutionary model proposed by S.F. Sage. Some of these genes might have co-evolved with the key C4 enzyme genes to increase the strength of C4 photosynthesis. Moreover, our results suggested that most key C4 enzyme genes had different origins and have undergone a long evolutionary process before the emergence of C4 grasses (Andropogoneae), consistent with the conclusion proposed by previous authors.

The Thomson Reuters ISI Web of Science citations database (hereafter ISI) category of Economics has one of the largest numbers of journals, at 304, of any ISI discipline, and hence has wide coverage. The paper analyses the leading international journals in the Economics sub-disciplines of Energy, Environmental and Resource Economics using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in alternative RAMs. The RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self- citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for one of the 20 journals considered, 13 RAMs are analysed for 19 highly-cited journals in Energy, Environmental and Resource Economics in the ISI category of Economics. Harmonic mean rankings of the 13 RAMs for the 19 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings.

This paper analyzes the responsiveness of Thai outbound tourism to East Asian destinations, namely China, Hong Kong, Japan, Taiwan and Korea, to changes in effective relative price of tourism, total real total tourism expenditure, and one-off events. The nonlinear and linear Almost Ideal Demand (AID) models are estimated with monthly data to identify the price competitiveness and interdependencies of tourism demand for competing destinations in both long run (static) and short run error correction (dynamic) specifications. The homogeneity and symmetry restricted long run and short run AID models are estimated to calculate elasticities. The income elasticities, and the compensated and uncompensated own-price and cross-price elasticities, provide useful information for public and private tourism agents at the various destinations to maintain and improve price competitiveness. The empirical results show that price competitiveness is important for tourism demand for Japan, Korea and Hong Kong in the long run, and for Hong Kong and Taiwan in the short run. With regard to long run cross-price elasticities, the substitution effect can be found in the following pairs of destinations: China-Korea, Japan-Hong Kong, Taiwan-Hong Kong, Japan-Korea, and Taiwan-Korea. In addition to the substitution effect, the complementary effect can be found in the following pairs of destinations: China-Hong Kong, China-Japan, China- Taiwan, Japan-Taiwan, and Korea-Hong Kong. Contrary to the findings obtained from the long run AID specification, Japan-Korea and Taiwan-Korea are complements in the short run. Furthermore, the real total tourism expenditure elasticities indicate that China's share of real total tourism expenditure is inelastic in response to a change in real total tourism expenditure, while Korea's share of real total tourism expenditure is most sensitive to changes in expenditure in the long run. The greatest impact on the share of real total tourism expenditure in the short run is tourism demand for Taiwan.

The objectives of this study were to determine phytochemical compositions, chemiluminescence antioxidant activities, and neuroprotective effects on PC12 cells for water, methanol, and 95% ethanol extracts of the air-dried fruit ofTerminalia chebulaRetzius. The water extract afforded the greatest yield, and total phenolic and tannin content. The methanol extract yielded the greatest total triterpenoid content. Based on four chemiluminescence antioxidant assays, the three extracts showed various degrees of antioxidant activity. The methanol extract showed good antioxidant activity based on the horseradish peroxidase-luminol-hydrogen peroxide (H2O2) assay. The water extract appeared to have good antioxidant activities in cupric sulfate-Phen-Vc-H2O2and luminol-H2O2assays. Pyrogallol-luminol assay showed the 95% ethanol extract to have good antioxidant activity. The methanol and water extracts presented neuroprotective activities on H2O2-induced PC12 cell death at 0.5–5.0 μg/mL. Further investigations are necessary to verify these activitiesin vivo.

Experts possess knowledge and information that are not publicly available. The paper is concerned with the ranking of academic journal quality and research impact using a survey of experts from a national project on ranking academic finance journals. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI- BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. Harmonic mean rankings of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A simple regression model is used to predict expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal.

Although the technological change in medicine has been widely recognized as the major driver of rising healthcare costs, there is very little research that directly estimates this effect. This paper uses both a single-equation and a simultaneous equations approach to empirically investigate the interactive relationship between technological innovation and the growth of health expenditure in the context of the pharmaceutical market in Taiwan. Based on observing 182 therapeutic groups between 1997 and 2006, we find evidence to support the argument that technological innovation and health expenditure are simultaneously determined as technological innovation and the growth of health expenditure are endogenous rather than exogenous. Specifically, we find that therapeutic groups associated with higher pharmaceutical expenditure are likely to attract more new products to the market. Meanwhile, therapeutic groups with more new products are associated with higher pharmaceutical expenditures. An important implication of the paper is that the cost containment policy will not only affect the growth of health expenditure, but will also affect the progress of technological innovation in the health sector.

Background To test whether a site-specific hysteroscopic biopsy-induced injury in the endometrium during the controlled ovarian hyperstimulation cycle improves subsequent embryo implantation in patients with repeated implantation failure, a total of 30 patients who have had good responses to controlled ovulation stimulation but have failed to achieve pregnancy after two or more transfers of good-quality embryos were recruited in this prospective study. Methods A single, site-specific hysteroscopic biopsy-induced injury was generated on the posterior endometrium at midline 10-15 mm from the fundus during the D4-D7 period of the ongoing controlled ovarian hyperstimulation cycle in six patients. Results Patients received endometrial biopsy protocol achieved a pregnancy rate of 100%. By contrast, only 46% of patients with similar clinical characteristics (N = 24) achieved pregnancy without the hysteroscopic biopsy-induced endometrium injury (p < 0.05). Conclusions Our proof-of-concept study demonstrates that a site-specific hysteroscopic endometrium injury performed during the ongoing in vitro fertilization (IVF) cycle, instead of injuries received during prior cycles, significantly improves clinical outcomes in patients with repeated implantation failure.

It is well known that the Basel II Accord requires banks and other Authorized Deposit-taking Institutions (ADIs) to communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models, whether individually or as combinations, to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. Previous papers proposed a new approach to model selection for predicting VaR, consisting of combining alternative risk models, and comparing conservative and aggressive strategies for choosing between VaR models. This paper, using Bayesian and non-Bayesian combinations of models addresses the question of risk management of risk, namely VaR of VIX futures prices, and extends the approaches given in previous papers to examine how different risk management strategies performed during the 2008-2009 global financial crisis (GFC). The use of time-varying weights using Bayesian methods, allows dynamic combinations of the different models to obtain a more accurate VaR forecasts than the estimates and forecasts that might be produced by a single model of risk. One of these dynamic combinations is endogenously determined by the pass performance in terms of daily capital charges of the individual models. This can improve the strategies to minimize daily capital charges, which is a central objective of ADIs. The empirical results suggest that an aggressive strategy of choosing the Supremum of single model forecasts, as compared with Bayesian and non-Bayesian combinations of models, is preferred to other alternatives, and is robust during the GFC.

This paper examines the short- and long-run daily relationships for a grain-energy nexus that includes the prices of corn, crude oil, ethanol, gasoline, soybeans, and sugar, and their open interest. The empirical results demonstrate the presence of these relationships in this nexus, and underscore the importance of ethanol and soybeans in all these relationships. In particular, ethanol and be considered as a catalyst in this nexus because of its significance as a loading factor, a long-run error corrector and a short-run adjuster. Ethanol leads all commodities in the price discovery process in the long run. The negative cross-price open interest effects suggest that there is a money outflow from all commodities in response to increases in open interest positions in the corn futures markets, indicating that active arbitrage activity takes place in those markets. On the other hand, an increase in the soybean open interest contributes to fund inflows in the corn futures market and the other futures markets, leading to more speculative activities in these markets. In connection with open interest, the ethanol market fails because of its thin market. Finally, it is interesting to note that the long-run equilibrium (cointegrating relationship), speeds of adjustment and open interest across markets have strengthened significantly during the 2009-2011 economic recovery period, compared with the full and 2007-2009 Great Recession periods.

This paper examines risk transmission and migration among six US measures of credit and market risk during the full period 2004-2011 period and the 2009-2011 recovery subperiod, with a focus on four sectors related to the highly volatile oil price. There are more long-run equilibrium risk relationships and short-run causal relationships among the four oil-related Credit Default Swaps (CDS) indexes, the (expected equity volatility) VIX index and the (swaption expected volatility) SMOVE index for the full period than for the recovery subperiod. The auto sector CDS spread is the most error-correcting in the long run and also leads in the risk discovery process in the short run. On the other hand, the CDS spread of the highly regulated, natural monopoly utility sector does not error correct. The four oil-related CDS spread indexes are responsive to VIX in the short- and long-run, while no index is sensitive to SMOVE which, in turn, unilaterally assembles risk migration from VIX. The 2007-2008 Great Recession seems to have led to “localization” and less migration of credit and market risk in the oil-related sectors.

The Basel II Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. McAleer, Jimenez-Martin and Perez- Amaral (2009) proposed a new approach to model selection for predicting VaR, consisting of combining alternative risk models, and comparing conservative and aggressive strategies for choosing between VaR models. This paper addresses the question of risk management of risk, namely VaR of VIX futures prices. We examine how different risk management strategies performed during the 2008-09 global financial crisis (GFC). We find that an aggressive strategy of choosing the Supremum of the single model forecasts is preferred to the other alternatives, and is robust during the GFC. However, this strategy implies relatively high numbers of violations and accumulated losses, though these are admissible under the Basel II Accord.

This paper examines the effectiveness of using futures contracts as hedging instruments of: (1) alternative models of volatility for estimating conditional variances and covariances; (2) alternative currencies; and (3) alternative maturities of futures contracts. For this purpose, daily data of futures and spot exchange rates of three major international currencies, Euro, British pound and Japanese yen, against the American dollar, are used to analyze hedge ratios and hedging effectiveness resulting from using two different maturity currency contracts, near-month and next-to-near-month contract. Following Chang et al. [17], we estimate four multivariate volatility models (namely CCC, VARMA-AGARCH, DCC and BEKK), and calculate optimal portfolio weights and optimal hedge ratios to identify appropriate currency hedging strategies. The hedging effectiveness index suggests that the best results in terms of reducing the variance of the portfolio are for the USD/GBP exchange rate. The empirical results show that futures hedging strategies are slightly more effective when the near-month future contract is used for the USD/GBP and USD/JPY currencies. Moreover, the CCC and AGARCH models provide similar hedging effectiveness, which suggests that dynamic asymmetry may not be crucial empirically, although some differences appear when the DCC and BEKK models are used.

This paper examines the roles of futures prices of crude oil, gasoline, ethanol, corn, soybeans and sugar in the energy-grain nexus. It also investigates the own- and cross-market impacts for lagged grain trading volume and open interest in the energy and grain markets. According to the results, the conventional view, for which the impacts are from oil to gasoline to ethanol to grains in the energy-grain nexus, does not hold well in the long run because the oil price is influenced by gasoline, soybeans and oil. Moreover, gasoline is preceded by only the oil price and ethanol is not foreshadowed by any of the prices. However, in the short run, two-way feedback in both directions exists in all markets. The grain trading volume effect across oil and gasoline is more pronounced in the short run than the long run, satisfying both the overconfidence/disposition and new information hypotheses across markets. The results for the ethanol open interest shows that money flows out of this market in both the short and long run, but no results suggest across market inflows or outflows to the other grain markets.

The Basel II Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. McAleer, Jimenez-Martin and Perez-Amaral (2009) proposed a new approach to model selection for predicting VaR, consisting of combining alternative risk models, and comparing conservative and aggressive strategies for choosing between VaR models. This paper addresses the question of risk management of risk, namely VaR of VIX futures prices. We examine how different risk management strategies performed during the 2008-09 global financial crisis (GFC). We find that an aggressive strategy of choosing the Supremum of the single model forecasts is preferred to the other alternatives, and is robust during the GFC. However, this strategy implies relatively high numbers of violations and accumulated losses, though these are admissible under the Basel II Accord.

This paper examines the short- and long-run daily relationships for a grain-energy nexus that includes the prices of corn, crude oil, ethanol, gasoline, soybeans, and sugar, and their open interest. The empirical results demonstrate the presence of these relationships in this nexus, and underscore the importance of ethanol and soybeans in all these relationships. In particular, ethanol and be considered as a catalyst in this nexus because of its significance as a loading factor, a long-run error corrector and a short-run adjuster. Ethanol leads all commodities in the price discovery process in the long run. The negative cross-price open interest effects suggest that there is a money outflow from all commodities in response to increases in open interest positions in the corn futures markets, indicating that active arbitrage activity takes place in those markets. On the other hand, an increase in the soybean open interest contributes to fund inflows in the corn futures market and the other futures markets, leading to more speculative activities in these markets. In connection with open interest, the ethanol market fails because of its thin market. Finally, it is interesting to note that the long-run equilibrium (cointegrating relationship), speeds of adjustment and open interest across markets have strengthened significantly during the 2009-2011 economic recovery period, compared with the full and 2007-2009 Great Recession periods.

Modelling, monitoring and forecasting volatility are indispensible to sensible portfolio risk management. The volatility of an asset of composite index can be traded by using volatility derivatives, such as volatility and variance swaps, options and futures. The most popular volatility index is VIX, which is a key measure of market expectations of volatility, and hence also an important barometer of investor sentiment and market volatility. Investors interpret the VIX cash index as a “fear” index, and of VIX options and VIX futures as derivatives of the “fear” index. VIX is based on S&P500 call and put options over a wide range of strike prices, and hence is not model based. Speculators can trade on volatility risk with VIX derivatives, with views on whether volatility will increase or decrease in the future, while hedgers can use volatility derivatives to avoid exposure to volatility risk. VIX and its options and futures derivatives has been widely analysed in recent years. An alternative volatility derivative to VIX is the S&P500 variance futures, which is an expectation of the variance of the S&P500 cash index. Variance futures are futures contracts written on realized variance, or standardized variance swaps. The S&P500 variance futures are not model based, so the assumptions underlying the index do not seem to have been clearly understood. As variance futures are typically thinly traded, their returns and volatility are not easy to model accurately using a variety of model specifications. This paper analyses the volatility in S&P500 3-month variance futures before, during and after the GFC, as well as for the full data period, for each of three alternative conditional volatility models and three densities, in order to determine whether exposure to risk can be incorporated into a financial portfolio without taking positions on the S&P500 index itself.

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand, respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese tourists to New Zealand and Taiwan are different, and indicate that the former has an asymmetric effect on risk from positive and negative shocks of equal magnitude, while the latter has no asymmetric effect. Moreover, there is a leverage effect in the monthly growth rate of Japanese tourists to New Zealand, whereby negative shocks increase volatility but positive shocks of similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics, and hence the issues related to risk and leverage effects, are also applicable to international tourism flows.