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Background Health care providers have been playing important roles in supporting breastfeeding. Although there has been insufficient actual breastfeeding support from health care providers in China, little research has been conducted to understand Chinese health care providers’ perceived barriers to providing breastfeeding support, especially in rural China. This study aimed to identify health care providers’ perceived barriers to providing breastfeeding support in Northwestern rural China. Methods A total of 41 health care providers were recruited by purposive sampling in two Northwest rural counties in China. These included obstetrician-gynecologists, midwives, nurses, village doctors, and township and village maternal and child health workers. Data were collected using semi-structured, one-on-one in-depth interviews and focus group discussions with qualitative design. Transcripts were thematically analyzed. Results Data from the interviews revealed four themes that the participants perceived as barriers in supporting breastfeeding. The four themes include: (1) lack of medical resources, (2) unclear responsibility designation at the individual level, (3) incompetency of health care providers, and (4) difficulty in accessing mothers. Conclusions Multiple barriers were perceived by health care providers in providing breastfeeding support. The specific breastfeeding support roles of different health care providers who serve for women and children need to be further clarified. Skillful training and technical support on breastfeeding are needed to match different health care providers’ specific responsibilities. The approaches of mobile health-based interventions to support breastfeeding can be explored in the future.

Recently, there has been a fast-growing literature on the determinants of corporate bond returns, in particular, the driving force of cross-sectional return variation. In this review, we first survey recent empirical studies on this important topic. We discuss cross-sectional evidence as well as time-series evidence. We then present a model-based analysis of individual corporate bond returns using the structural approach for credit risk modeling. We show, among other things, that the expected corporate bond return implied by the Merton model predicts 1-month-ahead corporate bond returns in the cross section.

Silicon photonic integration has gained great success in many application fields owing to the excellent optical device properties and complementary metal-oxide semiconductor (CMOS) compatibility. Realizing monolithic integration of III-V lasers and silicon photonic components on single silicon wafer is recognized as a long-standing obstacle for ultra-dense photonic integration, which can provide considerable economical, energy efficient and foundry-scalable on-chip light sources, that has not been reported yet. Here, we demonstrate embedded InAs/GaAs quantum dot (QD) lasers directly grown on trenched silicon-on-insulator (SOI) substrate, enabling monolithic integration with butt-coupled silicon waveguides. By utilizing the patterned grating structures inside pre-defined SOI trenches and unique epitaxial method via hybrid molecular beam epitaxy (MBE), high-performance embedded InAs QD lasers with monolithically out-coupled silicon waveguide are achieved on such template. By resolving the epitaxy and fabrication challenges in such monolithic integrated architecture, embedded III-V lasers on SOI with continuous-wave lasing up to 85 oC are obtained. The maximum output power of 6.8 mW can be measured from the end tip of the butt-coupled silicon waveguides, with estimated coupling efficiency of approximately -7.35 dB. The results presented here provide a scalable and low-cost epitaxial method for realization of on-chip light sources directly coupling to the silicon photonic components for future high-density photonic integration.

We report 4th order colliding pulse mode-locked laser based on InAs/GaAs QD structure, which can generate ultra-stable optical frequency combs in O-band with 100 GHz spacing and a record-high 3 dB optical bandwidth of 11.5 nm (20 comb lines) at 25 °C. Single channel NRZ modulation rates of 70 Gb/s and PAM-4 of 40 GBaud/s are also demonstrated.

This paper examines how liquidity and investors’ heterogeneous liquidity preferences interact to affect asset pricing. Using data on insurers’ corporate bond holdings, we find that illiquidity of corporate bond portfolios varies widely and persistently across insurers and is related to insurers’ investment horizon and funding constraint, consistent with the notion of liquidity clientele. We further find that liquidity clientele affects corporate bond prices—specifically, liquidity premia are lower among corporate bonds heavily held by investors with weaker preference for liquidity. This paper was accepted by Neng Wang, finance.

The realization of monolithic integration of a stable III–V laser on a standard silicon-on-insulator (SOI) substrate has been regarded as a challenging technology for silicon-based photonic integration circuits (PICs). Here, we successfully demonstrated the electrically pumped P-doped 1300 nm InAs/GaAs quantum dot (QD) laser epitaxially grown on {111}-faceted SOI hollow substrates. These III–V QD lasers, which are epitaxially grown on an SOI substrate, generally exhibit strong thermal accumulation due to the oxide layer underneath. By applying a double-side heat dissipation design, the maximum operation temperature of the SOI-based InAs/GaAs QD laser under a continuous-wave (CW) operation mode is ramped up to 35°C from 20°C. Moreover, the thermal profile simulation of three different structures has also been carried out to show the effectiveness of the top heat sink design in order to improve laser performance. An integrated thermal shunt design is proposed to improve heat dissipation without using the external top heat sink. The successful realization of room-temperature SOI-based InAs/GaAs QD lasers pave a viable way for integrating light sources in PICs.

Quantum dot lasers on silicon have gained significant interest over the past decade due to their great potential as an on-chip silicon photonic light source. Here, we demonstrate multi-wavelength injection locking of InAs/GaAs quantum dot Fabry–Perot (FP) lasers both on GaAs and silicon substrates by optical self-injection via an external cavity. The number of locked laser modes can be adjusted from a single peak to multiple peaks by tuning wavelength dependent phase and mode spacing of back-injected light through a Lyot filter. The multi-wavelength injection locked laser modes exhibit average optical linewidth of ∼ 20 kHz , which are narrowed by approximately three orders of magnitude from their free-running condition. Furthermore, multi-wavelength self-injection locking via an external cavity exhibits flat-top optical spectral properties with approximately 30 stably locked channels under stable operation over time, where the frequency detuning is less than 700 MHz within 40 min. Particularly, FP lasers by direct epitaxial growth on silicon substrates are self-injection locked as a flat-top comb source with tunable free spectral range from approximately 25 to 700 GHz. The reported results emphasize the great potential of multi-wavelength injection locked lasers as tunable on-chip multi-wavelength light sources.

There has been much debate about whether returns on financial assets, such as stock returns or commodity returns, are predictable; however, few studies have investigated cryptocurrency return predictability. In this article we examine whether bitcoin returns are predictable by a large set of bitcoin price-based technical indicators. Specifically, we construct a classification tree-based model for return prediction using 124 technical indicators. We provide evidence that the proposed model has strong out-of-sample predictive power for narrow ranges of daily returns on bitcoin. This finding indicates that using big data and technical analysis can help predict bitcoin returns that are hardly driven by fundamentals. Keywords: Bitcoin return prediction, High-dimensional classification, Decision tree classification, CART, Cryptocurrency, Bitcoin, Technical indicators

A quantum dot (QD) mode-locked laser as an active comb generator takes advantage of its small footprint, low power consumption, large optical bandwidth, and high-temperature stability, which is an ideal multi-wavelength source for applications such as datacom, optical interconnects, and LIDAR. In this work, we report a fourth-order colliding pulse mode-locked laser (CPML) based on InAs/GaAs QD gain structure, which can generate ultra-stable optical frequency combs in the O-band with 100 GHz spacing at operation temperature up to 100°C. A record-high flat-top optical comb is achieved with 3 dB optical bandwidth of 11.5 nm (20 comb lines) at 25°C. The average optical linewidth of comb lines is measured as 440 kHz. Single-channel non-return-to-zero modulation rates of 70 Gbit/s and four-level pulse amplitude modulation of 40 GBaud/s are also demonstrated. To further extend the comb bandwidth, an array of QD-CPMLs driven at separate temperatures is proposed to achieve 36 nm optical bandwidth (containing 60 comb lines with 100 GHz mode spacing), capable of a total transmission capacity of 4.8 Tbit/s. The demonstrated results show the feasibility of using the QD-CPML as a desirable broadband comb source to build future large-bandwidth and power-efficient optical interconnects.

This work demonstrated the first electrically pumped ground-state InAs QD narrow ridge lasers emission at 1310 nm (O-band) epitaxially grown on standard SOI substrate with continuous-wave (CW) current injection at room temperature.

A dynamic calibration method based on elliptical standard was put forward to further improve the calibration repeatability of measurement system of form measuring instruments. In this method, the radius difference of the major axis to the minor axis of elliptic contour acts as the standard value to calibrate the measuring system, and a low pass filter is used to filter the roughness, electrical noise and high frequency vibration signal which mixed into measurement data, the elliptic contour feature can be obtained accurately based on the low order harmonic properties. Compared with the traditional calibration method of flick standard, the proposed method ensure the calibration state is well consistent with the normal measuring state of the measuring system. Experimental results indicate that the calibration repeatability with 10nm can be achieved by measuring an elliptical standard. This method has been used in the calibration of measurement system of self-made ultra-precision cylindricity measuring instrument.

A self-calibration method of coupling error is presented for 3-DOF displacement measurement of a planar moving stage based on two planar gratings. The self-calibration method using Fourier series is developed to extract the periodic systematic errors from the coupling errors. The extracted periodic systematic errors are compensated. Experiments are conducted to validate the validity of the self-calibration method and experimental results indicate that the coupling errors in x and y directions are reduced by 2 and 1.5 times respectively. It can be therefore concluded that the self-calibration method is suitable for the 3-DOF displacement measurement of a planar moving stage to improve the positioning accuracy.

Aim We report the clinical characteristics and experience of the surgical management of ureteral endometriosis in our institution. Methods We retrospectively reviewed the data of patients with hydronephrosis resulting from ureteral endometriosis. Results Forty-six patients with different degrees of hydronephrosis were included in the study; 35% had urinary tract symptoms. Concomitant involvement of the ipsilateral ovary occurred in more than two-thirds of the patients. Four patients had nephrectomy, one of which involved ureterolysis because of hydronephrosis recurrence six months later. Conclusions Hydronephrosis may be caused by uncommon reasons, such as ureteral endometriosis, which can even cause silent loss of renal function. Routine ultrasound scanning of the upper urinary tract for severe stages of endometriosis is very important in order to detect any potential ureteral lesions. Ureterolysis should be considered as the first surgical step, not only to avoid iatrogenic ureteral injuries but also to better evaluate ureter involvement for further procedures. To warrant tension-free and lesion-free anastomosis, it is wise to perform ureteroneocystostomy for long-term sound results.

This paper investigates the impact of debt covenant protection on the cross section of equity returns with a firm-level covenant index and four subindices. We find that firms with weaker covenant protection (lower covenant index levels) earn significantly higher risk-adjusted equity returns than do those firms with greater covenant protection. These results are stronger for covenant indices that are related to investments, subsequent financing, and event risk. The difference between high and low covenant index stocks is more pronounced when agency problems between shareholders and debtholders are more severe, suggesting that the covenant effect arises from an inability to control shareholder risk taking. This paper was accepted by Wei Jiang, finance.

Using security-level credit spread data in eight developed economies, we document a large cross-country difference in credit spreads conditional on credit ratings and other default risk measures. The standard structural models not only fail to explain this cross-country variation in spreads but also have difficulty predicting credit spreads accurately. We implement an extended structural model that incorporates endogenous liquidity in the secondary market and find that this model largely explains credit spreads in the cross section and over time, as well as significantly reduces pricing errors. Therefore, default risk itself is an unlikely explanation for international corporate bond spreads.

Insurance firms are a key player in the corporate bond market. In this study, we consider the role of life insurers as "rainy day" liquidity providers who improve liquidity in stressful conditions due to the nature of long-term buy-and-hold investments. To this end, we present evidence that insurers' corporate bond purchases improve bond liquidity during the financial crisis and among downgraded bonds facing selling pressure. Life insurers are net purchasers of downgraded bonds within investment grades. Downgraded bonds with greater purchases from life insurers are significantly better priced.

This paper studies the dynamics of cryptocurrency volatility using a stochastic volatility model with simultaneous and correlated jumps in returns and volatility. We estimate the model using an efficient sequential learning algorithm that allows for learning about multiple unknown model parameters simultaneously, with daily data on four popular cryptocurrencies. We find that these cryptocurrencies have quite different volatility dynamics. In particular, they exhibit different return-volatility relationships: While Ethereum and Litecoin show a negative relationship, Chainlink displays a positive one and interestingly, Bitcoin’s one changes from negative to positive in June 2016. We also provide evidence that the sequential learning algorithm helps better detect large jumps in the cryptocurrency market in real time. Overall, incorporating volatility jumps helps better capture the dynamic behavior of highly volatile cryptocurrencies.

Corporations often use affiliated firms as guarantors when issuing guaranteed bonds, thus combining external financing with internal credit enhancements. In this study, we empirically examine the potential determinants of corporate guaranteed debt issuance. We find evidence that issuers with fewer tangible assets, lower credit ratings, more pronounced debt overhang and/or greater managerial agency problems are more likely to issue guaranteed bonds. Moreover, we find that while firms generally issue guaranteed bonds with different motives, alternative incentives for guaranteed bond uses are largely captured by bond prices at issuance.

This paper studies the continuous-time dynamics of VIX with stochastic volatility and jumps in VIX and volatility. Built on the general parametric affine model with stochastic volatility and jumps in the logarithm of VIX, we derive a linear relationship between the stochastic volatility factor and the VVIX index. We detect the existence of a co-jump of VIX and VVIX and put forward a double-jump stochastic volatility model for VIX through its joint property with VVIX. Using the VVIX index as a proxy for stochastic volatility, we use the MCMC method to estimate the dynamics of VIX. Comparing nested models of VIX, we show that the jump in VIX and the volatility factor are statistically significant. The jump intensity is also stochastic. We analyse the impact of the jump factor on VIX dynamics.

This study establishes the competitive production-inventory models with vendor’s imperfect production processes by using game theory. The imperfect production processes can be improved by capital investment which is shared out between the vendor and the buyer jointly. In addition, the inspection process is assumed to be imperfect and Type I and Type II inspection errors occur during product quality inspection. We first develop the total cost per unit time of the buyer and vendor, respectively and then seek the optimal buyer’s order quantity, vendor’s shipping times and defective rate of the product where the system achieves a Nash equilibrium. The necessary and sufficient conditions of the existence and uniqueness of the optimal solutions for the buyer and the vendor respectively are shown. Furthermore, we develop a algorithm to find the optimal solutions. Finally, an numerical example are presented to demonstrate the solution procedure.

This paper tests the technical trading rule of moving average (MA) in a long-only portfolio using exchange traded funds (ETFs). We also propose a quasi-intraday version of the MA strategy (QUIMA) that allows investors to trade immediately upon observing MA crossover signals. We find that 1) this QUIMA strategy outperforms the traditional version of the MA strategy that only trades at the close of a trading day, when the long-term MA lag length is not too long, 2) the documented profitability of MA strategy on indices is greatly reduced on ETFs, mainly due to more frequent and larger opening gaps on ETF prices than those on indices, and 3) relative to the buy-and-hold strategy, MA strategies have lower return, but better risk-adjusted performance measures such as the CAPM alpha. In addition, we find that among various long-term MA lengths, the 10-day MA turns out to be overly exploited by investors as its performance is significantly lower than those of surrounding MA lengths. Overall, our findings indicate that profitability of the MA trading rule reduces on tradable ETFs than on non-tradable indices.

We construct a theoretical framework to investigate the impact of liquidity risk, in the secondary corporate debt market, on corporate risk-taking preferences. Using closed-form solutions, our model shows that equity holders choose to adopt high-risk projects upon the arrival of illiquidity shocks. This effect is more pronounced for firms with weaker fundamentals. Empirically, we confirm the positive relationship between liquidity risk and corporate risk-taking. We also document that the impact of liquidity risk on corporate risk-taking preferences is more pronounced for smaller firms and firms with lower profits and higher rollover risk. In addition, we use the introduction of the Trade Reporting and Compliance Engine (TRACE) as a natural exogenous liquidity shock and find a decrease of firms’ risk-taking preferences after the TRACE is implemented. Our findings shed light on the managerial behavior literature, which shows that the frictions of the secondary bond market have a real impact on firms’ risk-taking behaviors.

We investigate the effects of short sale constraints on asset mispricing in the corporate bond market. Consistent with Miller (1977)’s theory that short sale constraints can lead to asset overpricing, we document a significant positive relation between changes in ownership breadth (a proxy for short sale constraints) and the cross-section of future corporate bond returns. The return predicative power of changes in breadth is shown to be relatively short-lived in the corporate bond market, possibly due to the bounded upside payoffs of debt. Further analysis shows that the return predictability of changes in breadth is stronger among bonds with higher credit risk and during periods of high investor sentiment, and is mainly driven by bond overpricing rather than underpricing. Overall, the impact of short sale constraints on bond mispricing appears to be more pronounced when overpricing is more likely.

We document a strong low-price effect for Chinese initial public offerings (IPOs). Namely, IPOs with low offer prices have higher initial returns, followed by even stronger after-market performance. This low-price effect cannot be fully explained by risks and IPO undervaluation. A long-only secondary market trading strategy investing in low-price IPOs can beat the buy-and-hold market benchmark using several performance measures and under a wide range of parameter settings. Our findings suggest investor preference for low-priced stocks can be quite profitable in the Chinese IPO market as low-priced IPOs outperform initially and in after-market trading.

We present a comprehensive analysis to calculate the Basel III liquidity coverage ratio (LCR) and the net stable funding ratio (NSFR) of U.S. commercial banks using Call Report data over the period 2001–2011, and provide indirect empirical evidence on net cash outflow rates of certain liability categories. In addition, we examine potential links between Basel III liquidity risk measures and bank failures using a model that differentiates between idiosyncratic and systemic liquidity risks. We find that while both the NSFR and the LCR have limited effects on bank failures, the systemic liquidity risk is a major contributor to bank failures in 2009 and 2010. This finding suggests that an effective framework of liquidity risk management needs to target liquidity risk at both the individual level and the system level.

Corporate bond spreads are affected by both credit risk and liquidity and it is difficult to disentangle the two factors empirically. In this paper we separate out the credit risk component by examining bonds that are issued by the same firm and that trade on the same day. Our sample of bond pairs provides two yield spreads which, if they differ, vary only because of differences in liquidity. We then investigate the determinants of the differences in yield spreads. We find that standard liquidity measures do a poor job of explaining spreads, and that incorporating the information from other bonds issued by the firm and from bonds of other firms can significantly improve the explanatory power of those liquidity measures. Still, a significant portion of the spread is left unexplained and it is largely driven by a common unknown factor. We conclude that good proxies for the liquidity component of corporate bond spreads remain elusive.

This study examines the ability of government bond fund managers to time the bond market, based on their monthly or quarterly holdings of Treasury securities during the 1997–2006 period. We find that, on average, government bond funds exhibit significantly positive timing ability at the one-month horizon under an unconditional holdings-based timing measure. However, our results indicate that managers' actions based on public information can explain the documented positive timing ability—namely, the average government bond fund has neutral or even slightly negative conditional market timing ability once public information is controlled for. Nonetheless, we find evidence that fund managers specializing in Treasury securities can better interpret public information than general government bond fund managers do. This paper was accepted by Wei Xiong, finance.

We report the clinical characteristics and experience of the surgical management of ureteral endometriosis in our institution.We retrospectively reviewed the data of patients with hydronephrosis resulting from ureteral endometriosis.Forty-six patients with different degrees of hydronephrosis were included in the study; 35% had urinary tract symptoms. Concomitant involvement of the ipsilateral ovary occurred in more than two-thirds of the patients. Four patients had nephrectomy, one of which involved ureterolysis because of hydronephrosis recurrence six months later.Hydronephrosis may be caused by uncommon reasons, such as ureteral endometriosis, which can even cause silent loss of renal function. Routine ultrasound scanning of the upper urinary tract for severe stages of endometriosis is very important in order to detect any potential ureteral lesions. Ureterolysis should be considered as the first surgical step, not only to avoid iatrogenic ureteral injuries but also to better evaluate ureter involvement for further procedures. To warrant tension-free and lesion-free anastomosis, it is wise to perform ureteroneocystostomy for long-term sound results.

We show that credit risk accounts for only a small fraction of yield spreads for investment-grade bonds of all maturities, with the fraction lower for bonds of shorter maturities, and that it accounts for a much higher fraction of yield spreads for high-yield bonds. This conclusion is shown to be robust across a wide class of structural models. We obtain such results by calibrating each of the models to be consistent with data on the historical default loss experience and equity risk premia, and demonstrating that different models predict similar credit risk premia under empirically reasonable parameter choices.

Recent evidence has shown that structural models fail to capture interest rate sensitivities of corporate debt. We consider a structural model that incorporates a three-factor dynamic term structure model (DTSM) into the Merton (1974) model. We show that the proposed model largely captures the interest rate exposure of corporate bonds. We also find that for investment-grade bonds, hedging effectiveness substantially improves under the proposed model. Our results indicate that to better capture and hedge the interest rate exposure of corporate bonds, we need to incorporate a more realistic DTSM in the existing structural models.

One way to test a corporate bond pricing model is to examine its predictions for the shape of credit yield spread curves. However, existing empirical studies along this line are known to be problematic because of not controlling properly for the credit quality of bonds (an exception is Helwege and Turner [1999] who study the slope of credit spread curves for high yield coupon bonds). In this article we examine credit spread curves for both zero-coupon and coupon bonds and for both investment grade and high yield bonds. We find that the term structure of credit spreads is usually upward sloping, regardless of credit quality or coupon.

We analyze common factors that affect returns on S&P 500 index options and find that 93% of the variation in option returns can be explained by three factors, which respectively account for 87%, 4%, and 2% of the variation in option returns. Furthermore, we test diffusion option pricing models by using mean–variance spanning properties implied in the models. The spanning tests reject one-factor diffusion models, as well as the hypothesis that the underlying asset and an equally weighted option index span options. Our results fail to reject that the underlying asset and an at-the-money option can span out-of-the-money options, but does reject that they span in-the-money options.

This paper studies the continuous-time dynamics of VIX with stochastic volatility and jumps in VIX and volatility. Built on the general parametric affine model with stochastic volatility and jumps in the logarithm of VIX, we derive a linear relationship between the stochastic volatility factor and the VVIX index. We detect the existence of a co-jump of VIX and VVIX and put forward a double-jump stochastic volatility model for VIX through its joint property with VVIX. Using the VVIX index as a proxy for stochastic volatility, we use the MCMC method to estimate the dynamics of VIX. Comparing nested models of VIX, we show that the jump in VIX and the volatility factor are statistically significant. The jump intensity is also stochastic. We analyze the impact of the jump factor on VIX dynamics.

Credit risk is also the subject of this article by Huang and Kong. There are numerous credit risk models in which the relevant stochastic variables for pricing a risky bond are obtained from the term structure of interest rates, and perhaps from firm-level capital structure data. In this article, the authors look at option-adjusted spreads on corporate bond indexes for different credit ratings classes. They find that term structure variables alone are limited in their ability to explain yield spreads, but adding macroeconomic variables, like an index of leading economic indicators, and equity market variables, including the return on the Russell 2000 index and the Fama-French “high minus low” factor, can contribute significant explanatory power, especially for lower rated bonds.

The forward measure is convenient in calculating various contingent claim prices under stochastic interest rates. We demonstrate that caution needs to be drawn when the forward measure is used to price contingent claims that involve multiple cash flows. We also derive partial different equations for the forward price to demonstrate how forward contracts can be used for dynamic hedging and how hedges can be conducted if the payoff of a contingent claim depends on the forward price.

High-dimensional data analysis is becoming more and more important to both academics and practitioners in finance and economics but is also very challenging because the number of variables or parameters in connection with such data can be larger than the sample size. Recently, several variable selection approaches J.-Z. Huang • Z. Shi Smeal College of Business, Penn State University, University Park, PA, USA e-mail: jxh56@psu.edu; zus116@psu.edu W. Zhong (*) Wang Yanan Institute for Studies in Economics and Department of Statistics, School of Economics, Xiamen University, Xiamen, China e-mail: wzhong@xmu.edu.cn C.-F. Lee, J. Lee (eds.), Handbook of Financial Econometrics and Statistics, DOI 10.1007/978-1-4614-7750-1_77, # Springer Science+Business Media New York 2015 2093 have been developed and used to help us select significant variables and construct a parsimonious model simultaneously. In this chapter, we first provide an overview of model selection approaches in the context of penalized least squares. We then review independence screening, a recently developed method for analyzing ultrahigh-dimensional data where the number of variables or parameters can be exponentially larger than the sample size. Finally, we discuss and advocate multistage procedures that combine independence screening and variable selection and that may be especially suitable for analyzing high-frequency financial data. Penalized least squares seek to keep important predictors in a model while penalizing coefficients associated with irrelevant predictors. As such, under certain conditions, penalized least squares can lead to a sparse solution for linear models and achieve asymptotic consistency in separating relevant variables from irrelevant ones. Independence screening selects relevant variables based on certain measures of marginal correlations between candidate variables and the response.