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We reinvestigate the major factors in the low origination rate of home equity conversion mortgages (HECMs) in the United States from 2010 to 2017. We use panel data analysis to consider the variation in time and region and investigate the main determinants of the HECM origination rate. We examine five categories of variables: demographics, home equity, home debt level, retirement income, and taxes. We first filter out key variables and then consider the interactions among these factors. The empirical outcomes confirm the significance of including interactions and provide detailed observations to resolve several disputed issues and make policy recommendations, such as debt priority of mortgage and credit card, applying HECM as a personal or household decision, and the dominance of property tax over inheritance tax.

This paper first gauges the level of firm efficiency using the Stochastic Nonparametric Envelopment of Data (StoNED) approach. Our firm efficiency score closely reflects a firm’s actual operating conditions when using the statistical foundations of both Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis. Secondly, we estimate the nonlinear effects of intellectual capital on StoNED-based firm efficiency using the Generalized Additive Model (GAM). This model lets us depict the possible nonlinear relationship between explanatory variables and the explained variables in an additive manner. Our analysis of 1898 firm-year observations for U.S.-listed firms from 1999 to 2019 indicates that (i) our sample firms generally have about 65% of room left for improvement that could transform resources into wealth, and (ii) of the three major components of intellectual capital, human capital exhibits a concave-up curve, while structural capital and relational capital both demonstrate an upward trend, with each having an inflection in the middle of that curve. The GAM results remain qualitatively similar even after we re-estimate firm efficiency using the network slacks-based measure DEA model, and (iii) we discuss these comparisons and the respective implications of the three components.

With a refined version of almost stochastic dominance (ASD), we explore the performance-comparison issues between traditional markets and Islamic markets in terms of industry and business condition...

We theoretically analyze the transmission characteristics of a magnon–photon coupling system based on ultrastrong optomechanical-like coupling via the cross-Kerr interaction. We use the definition of group delay to characterize the fast and slow light effects. It is found that the group delay of our system can be significantly improved by two to three orders of magnitude compared to previous studies in magnon–photon coupling systems, which means slow light effect can be significantly enhanced. By adjusting the driving power and frequency detuning of the microwave cavities, the magnitude and bandwidth of the group delay and transmittance can be adjusted precisely. Moreover, frequency control of slow light can be achieved by manipulating the strength of magnetic field. The influence of the cross-Kerr coupling strength of cavities on the system is also discussed in detail. The group delay of the system is close to milliseconds, while the transmittance is greatly improved. The result from this paper hopes to bring new development possibilities for the fabrication of optical memory and the construction of all-optical networks.

Computer vision has penetrated many domains, for instance, security, sports, health and medicine, agriculture, transportation, manufacturing, retail, and so like. One of the computer vision tasks is character recognition. In this work, a visually similar handwritten Chinese character dataset is collected. Subsequently, an enhanced convolutional neural network is proposed for the recognition of visually similar handwritten Chinese characters. The convolutional neural network is enhanced by the dropout regularization and early stopping mechanism to reduce the overfitting problem. The Adam optimizer is also leveraged to accelerate and optimize the training process of the convolutional neural network. The empirical results demonstrate that the enhanced convolutional neural network achieves a 97% accuracy, thus corroborate it has better discriminating power in visually similar handwritten Chinese character recognition.

This study investigates whether the power laws and the associated generalized Pareto distribution (GPD) exist in the extreme tail behavior of financial return series. We include 10 series of five m...

This study reexamines gold and government bonds as potential safe‐haven assets (SHAs) during market turmoil from daily data in 16 international markets over the past 20 years. We apply the extremal quantile regression model by Chernozhukov and Chernozhukov and Fernandez‐Val for empirical investigation. The outcomes indicate that a government bond is more likely to be qualified an active SHA, which can increase in value during market turmoil. Gold can be generally evaluated as a passive SHA, which is uncorrelated with market slumps. However, at the extremal 0.001 quantile level, neither asset can be qualified as a SHA. Since both assets exhibit a similar number of cases of being qualified as SHAs, we cannot significantly differentiate the “flight‐to‐liquidity” and “flight‐to‐quality” hypotheses. In terms of market selection, United States and Singapore are the top two choices while France and Hungary are the least commended markets to invest their local gold market as SHA.

We examine the extreme behaviors at both the lower 5% and 1% quantile levels of the three exchange rates series (Japanese yen, Korean won, and New Taiwan dollar) against the US dollar between 2002 and 2017. We employ two econometric tools for specific purposes: (1) to determine the bootstrap goodness of fit test for the Generalized Pareto distribution (GPD) of the tail behaviors proposed by Villasenor-Alva and Gonzalez-Estrada (2009); and (2) to identify, estimate, and test the hidden Markov model (HMM). The testing outcomes mostly reject the GPD assumption for this study. HMM estimation outcomes provide the detailed pictures. They evidence the multiple structural breaks in the returns and the gaps between the qualified extremes. The respective properties of the exchange markets are revealed in the comparisons of the estimation outcomes in terms of transition matrix, response parameter, and bivariate analysis. In general, Japanese yen is evaluated as a resilient safe haven currency. Korean won exhibits longer distress duration. New Taiwan dollar occurs with heavier losses with longer gaps.

Hofstede’s six measures of national culture (Hofstede in Culture’s consequence. Sage Publications, New York, 1980; Bond and Hofstede in Organ Dyn 16(4):4–21, 1988; Hofstede et al. in Cultures and organizations: software of the mind, 3rd edn. McGraw-Hill, New York, 2010) are applied to study the implied volatility levels in 15 international major equity markets. The cross-sectional analysis, based on the Generalized Additive Model, confirms that all the six measures play an intuitive role in explaining the volatility levels in the respective equity markets. This study confirms the significant long-term role of national culture. The outcomes contribute to provide the specific intuitive patterns of the six measures in explaining the implied volatility levels in the international equity markets.

We review the Generalized Almost Stochastic Dominance definition in Tsetlin et al. (Oper Res 63(2):363–377, 2015). We follow the classic concept of stochastic dominance in minimizing specific assumptions about decision makers’ risk attitudes as highlighted by Levy (Manag Sci 38(4):555–593, 1992). We refine the definition of almost stochastic dominance by Leshno and Levy (Manag Sci 48(8):1074–1085, 2002) to secure economic intuition. We then present our definitions of almost stochastic dominance with an extension to the higher degrees. Our definition satisfies both expected utility maximization property and hierarchy property while minimizing assumption and securing economic intuition.

We theoretically analyze the transmission characteristics of a magnon–photon coupling system with N cascaded microwave cavities. The influences of the magnon–photon coupling strength and cavity number on the transmission characteristics are the main focus of this research. With an increase in the cascaded cavity number, the slow light effect should be greatly enhanced. By changing the cavity lengths slightly in a staggered way, the group delay could be increased by an order of magnitude with a well guaranteed transmission amplitude. Group delay should be flexibly controlled because of the existence of magnon and the conversion of fast and slow light can be realized. Moreover, by properly adjusting the cavity length, we can control the frequency shifting of the output slow light and narrow the bandwidth of the output slow light, which can aid in the design of high-quality light-storage devices. We believe the results will have applications in the all-optical communications network.

Cutlassfish (Lepturacanthus savala) is a commercially important fish species that is distributed in the tropical coastal area throughout the Indo-West Pacific Oceans. However, there have been few genetic studies on this species. Therefore, based on mitochondrial COI gene and thirteen microsatellite DNA markers that have been successfully developed by predecessors, the objective of this study is to assess the genetic diversity and structure of L savala for the first time, using 172 individuals collected from six locations along the coast of mainland China during 2019. High levels of haplotype diversity (0.94) in mitochondrial DNA and the average number of alleles among the six populations ranged from 10.3 to 14.0 in microsatellite DNA data, which showed that all population exhibited a high level of genetic diversity. Analysis of molecular variance (AMOVA) showed that did not indicate any significant genetic differentiation among groups with no relation to the geographic area. The significant genetic differentiation was found in LYG and BH populations revealed that the prevention of gene flow caused by the Yangtze River and the Qiongzhou Strait. The results of STRUCTURE suggested that all populations were admixtures of two clusters, which could be explained only by the high migratory ability of L. savala resulting in extensive gene flow. Analysis of demographic history revealed that L. savala undergo historical lineage diversification and admixture due to the secondary contact based on ABC analysis, and no evidence for recent population bottlenecks were detected. Such study is both practical and theoretical value for genetic improvement, conservation, management, and sustainable resource utilization.

This paper contributes to applying the time-varying symmetrized Joe–Clayton copula to study the dynamic linkage among possible safe haven assets (SHAs) in the major international markets over the past 34 years. We re-examine four major asset types (long-term government bonds, equity indices, oil, and gold) and test whether they are qualified individually as a safe haven asset against when paired against each other in a specific market. The empirical analyses indicate that: (1) Government bonds are generally confirmed SHAs. (2) Gold and oil are overwhelming SHAs against government bond across the markets. (3) US and East Asian markets (Japan, Australia and New Zealand) have more SHA options than the other regions against equity index.

To analyze the spatial and temporal variation characteristics of PM

This paper selects stochastic volatility (SV) as the uncertainty or volatility measure to re-examine the Samuelson hypothesis of maturity effect (SHME) (Samuelson, 1965). Stochastic dominance is used to examine whether the stochastic volatility level dominates with respect to maturity. The empirical analyses of energy-futures price series generally provide mild support for this hypothesis in terms of the first two degrees of stochastic dominance. Each type of futures has its own properties with respect to the maturity effect. SV levels play a role in determining the testing outcome. The hypothesis is more likely to hold at low SV levels. The higher the volatility level, the less likely the SHME will hold because SV surges to its peak level regardless of maturity.

The solvent-controlled difluoromethylation of 2′-hydroxychalcones using the shelf-stable reagent difluoromethylene phosphabetaine for divergent synthesis of 2′-difluoromethoxychalcones and 2,2-difluoro-3-styryl-2,3-dihydrobenzofuran-3-ols is developed. When difluoromethylation was performed in p-xylene, 2′-difluoromethoxychalcones were the major product with 47–97% yields, while 2,2-difluoro-3-styryl-2,3-dihydrobenzofuran-3-ols were obtained in 21–75% yields using acetonitrile as solvent. A plausible reaction mechanism was proposed according to the experimental results.

This article proposes to use the three multivariate skew distributions (generalized hyperbolic distribution, multivariate skew normal distribution, and multivariate skew Student-t distribution) for estimating the minimum variance hedge ratio in a dynamic setting. Three criteria for measuring hedge effectiveness are employed: hedging instrument effectiveness, overall hedge effectiveness, and relative-to-optimal hedge ratio effectiveness (RHRE). Three portfolios of spot and futures series are formed for empirical analysis. The outcomes confirm that the three multivariate skew distributions are more helpful in deciding the minimum variance hedge ratio, especially the generalized hyperbolic distribution, than the symmetrical normal and Student-t distributions. This outperformance is significant especially at critical market moments and it is indicated by three hedge effectiveness measures. This advantage is held without the cost of lowering portfolio return. In addition, there is speculation possibility exist...

The maturity effect (ME) of futures prices postulated by Samuelson (1965) is re-examined using three nonparametric tests. The consistent entropy asymmetry test by Racine and Maasoumi (2007) indicates that variance is an appropriate risk or uncertainty measure for ME, and value-at-risk and expected shortfall are also adopted. The Kolmogorov–Smirnov dominance test and Wilcoxon rank sum and signed rank test are employed to rank the estimates of the three risk measures under a moving-window framework. The testing outcomes are contingent on futures type, testing method and risk measures. The testing outcomes show mild support for ME.

This paper examines the statistical relation between the Chinese Farmer's Calendar (CFC) and public market information in 10 East Asian equity markets during 1995–2004. CATREG and CART, two data mining techniques, are employed and the implications of the outcomes are discussed. The outcomes confirm that the CFC plays a supplementary role to market information in predicting the market rate of return. In addition to confirmation of lunar calendar effect by the CFC, CATREG outperforms in three markets: Taiwan, South Korea and Singapore. According to CART analyses, all the three markets value the funeral category of the CFC advice and this pattern coincides with the traditional wisdom of astrological knowledge. The latter two markets share the same set of CFC items while Taiwan has its own. This contrast indicates the market-dependent observance and different interpretation of the CFC items for determining an auspicious date for equity trading. The lunar calendar effect in the three equity markets is confirmed.

Extreme Value Theory (EVT) is heavily applied in modelling tail behaviour. Previous literature uses the tail index to test for Structural Breaks (SBs) in the tails. This study presents another more reliable approach and relies on the outperformance of the Generalized Pareto Distribution (GPD) in modelling tails. The transformed GPD is treated as a classical Ordinary Least Square (OLS) regression and the generalized M-fluctuation test (Zeileis, 2005, 2006) is applied because it is a unified approach based on Maximum Likelihood (ML) scores (Andrews and Ploberger, 1994), F-statistics (1989, 1992), and OLS residuals (Ploberger and Kramer, 1992). The outcomes indicate that there are multiple SBs not only in all of the three exchange return series considered (UK Pound, Japanese Yen and New Taiwan Dollar, all versus US Dollar) but also GPD parameter estimation at extreme quantile levels. Based on these empirical analyses, it is advisable that EVT should be used with caution at extreme quantile levels.

The solvent-controlled difluoromethylation of 2′-hydroxychalcones using the shelf-stable reagent difluoromethylene phosphabetaine for divergent synthesis of 2′-difluoromethoxychalcones and 2,2-difluoro-3-styryl-2,3-dihydrobenzofuran-3-ols is developed. When difluoromethylation was performed in p-xylene, 2′-difluoromethoxychalcones were the major product with 47–97% yields, while 2,2-difluoro-3-styryl-2,3-dihydrobenzofuran-3-ols were obtained in 21–75% yields using acetonitrile as solvent. A plausible reaction mechanism was proposed according to the experimental results.

This paper empirically tests for convergence in consumer price indices across 17 major cities in US over the 1918–2008 period. By using the novel OLS estimator introduced by Bao, Y., Dhongde, S., 2009. Testing convergence in income distribution. Oxford Bulletin of Economics and Statistics 71, 295–302, we find overwhelming evidences in support of price level convergence over time.

This paper investigates the relation between the nonstationary sound source and the frequency domain magnitude ratio of two microphones based on short-term frequency analysis. The fluctuation level of nonstationary sound sources is modeled by the exponent of polynomials from the concept of moving pole model. According to this model, the sufficient condition for utilizing the fluctuation level and magnitude ratio to estimate the time delay between two microphones is suggested. Simulation results are presented to show the performance of the suggested method.

This paper examines the inflation-hedging behavior of the Hong Kong securitized real estate market between April 1986 and April 2007. The monthly series of the Hang Seng Property Index (HSPI) is selected as the proxy of the Hong Kong securitized real estate market due to its comprehensive coverage and availability of rich data. We find that the vector autoregressive forecast error method, which is introduced by Den Haan (2000), outperforms the traditional linear vector autoregressive model and vector error correction model techniques in depicting the comovement between the HSPI and inflation rate. The comovement estimates show a positive correlation between the HSPI and inflation rate in the short-term and a negative correlation in the long term which indicates that the Hong Kong securitized real estate market can serve as an inflation hedge in the short term, but becomes a perverse inflation hedge in the long run. This inflation-hedging pattern differs from those of its neighboring major East Asian markets. This study demonstrates that the inflation-hedging capability of securitized real estate is not a static issue, but rather, depends on the length of the forecast horizon.

This paper examines the inflation-hedging behavior of the Hong Kong securitized real estate market between April 1986 and April 2007. The monthly series of the Hang Seng Property Index (HSPI) is selected as the proxy of the Hong Kong securitized real estate market due to its comprehensive coverage and availability of rich data. We find that the vector autoregressive forecast error method, which is introduced by Den Haan (2000), outperforms the traditional linear vector autoregressive model and vector error correction model techniques in depicting the comovement between the HSPI and inflation rate. The comovement estimates show a positive correlation between the HSPI and inflation rate in the short-term and a negative correlation in the long term which indicates that the Hong Kong securitized real estate market can serve as an inflation hedge in the short term, but becomes a perverse inflation hedge in the long run. This inflation-hedging pattern differs from those of its neighboring major East Asian markets. This study demonstrates that the inflation-hedging capability of securitized real estate is not a static issue, but rather, depends on the length of the forecast horizon.

In this work, an indoor sound field feature matching method is proposed and is applied to detect a mobile robot's location and orientation. The sound field feature, captured from a sound source to a pair of microphones, contains the dynamic of the propagation path. Because of the complexity of indoor environment, the features from different path can be distinguished using appropriate models. Gaussian mixture models are utilized in this paper to characterize the phase difference and magnitude ratio distributions between the microphone pair in consecutive data frames. The application provides an alternative thinking compared with traditional methods such as direction of arrival (DOA) using propagation delay. They usually suffer from reverberation, non-line-of-sight and microphone mismatch problems. The experimental results show the method not only has a high recognition rate for robot's location and orientation, but also is robust against environmental noise.

A two-dimensional model was formulated to describe the pressure-flow behavior of compressible stationary phases for protein chromatography at different temperatures and column scales. The model was based on the assumption of elastic deformation of the solid phase and steady-state Darcy flow. Using a single fitted value for the empirical modulus parameters, the model was applied to describe the pressure-flow behavior of several adsorbents packed using both fluid flow and mechanical compression. Simulations were in agreement with experimental data and accurately predicted the pressure-flow and compression behavior of three adsorbents over a range of column scales and operating temperatures. Use of the described theoretical model potentially improves the accuracy of the column scale-up process, allowing the use of limited laboratory scale data to predict column performance in large scale applications.

This paper employs real option analysis to evaluate the investment project to adopt energy saving and carbon emission reduction technology. Sensitivity analysis and simulation outcomes highlight the respective roles of carbon price level and government support in the investment decision. That is, government support lies in two major directions to encourage the adoption of carbon emission reduction technology: to increase the subsidy to lower the cost for the firm and encourage adoption of the green technology, and to increase the risk-free return rate. The candidate measures to lower the investment threshold lie three major directions: stabilizing energy price, lowering operation cost, and increasing risk-free return rate. In addition, market expectation and its interactions among the key variables play their significant roles in the optimization process.