On the estimation and comparison of short-rate models using the generalised method of moments

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

Stochastic growth and monetary policy: the impacts on the term structure of interest rates

This paper builds a simple, empirically-verifiable rational expectations model for term structure of nominal interest rates analysis. It solves an stochastic growth model with investment costs and sticky inflation, susceptible to the intervention of the monetary authority following a policy rule. The model predicts several patterns of the term structure which are in accordance to observed empirical facts: (i) pro-cyclical pattern of the level of nominal interest rates; (ii) countercyclical pattern of the term spread; (iii) pro-cyclical pattern of the curvature of the yield curve; (iv) lower predictability of the slope of the middle of the term structure; and (v) negative correlation of changes in real rates and expected inflation at short horizons.

Poly lactic-co-glycolic acid controlled delivery of Disulfiram to target liver cancer stem-like cells

Disulfiram (DS), an anti-alcoholism drug, shows very strong cytotoxicity in many cancer types. However its clinical application in cancer treatment is limited by the very short half-life in the bloodstream. In this study, we developed a poly lactic-co-glycolic acid (PLGA)-encapsulated DS protecting DS from the degradation in the bloodstream. The newly developed DS-PLGA was characterized. The DS-PLGA has very satisfactory encapsulation efficiency, drug-loading content and controlled release rate in vitro. PLGA encapsulation extended the half-life of DS from shorter than 2 minutes to 7 hours in serum. In combination with copper, DS-PLGA significantly inhibited the liver cancer stem cell population. CI-isobologram showed a remarkable synergistic cytotoxicity between DS-PLGA and 5-FU or Sorafenib. It also demonstrated very promising anticancer efficacy and antimetastatic effect in liver cancer mouse model. Both DS and PLGA are FDA approved products for clinical application. Our study may lead to repositioning of DS into liver cancer treatment.

Age-Related Maximum Heart Rate Among Ischemic and Nonischemic Heart Failure Patients Receiving beta-Blockade Therapy

Background: Equations to predict maximum heart rate (HRmax) in heart failure (HF) patients receiving beta-adrenergic blocking (BB) agents do not consider the cause of HF. We determined equations to predict HRmax in patients with ischemic and nonischemic HF receiving BB therapy. Methods and Results: Using treadmill cardiopulmonary exercise testing, we studied HF patients receiving BB therapy being considered for transplantation from 1999 to 2010. Exclusions were pacemaker and/or implantable defibrillator, left ventricle ejection fraction (LVEF) >50%, peak respiratory exchange ratio (RER) <1.00, and Chagas disease. We used linear regression equations to predict HRmax based on age in ischemic and nonischemic patients. We analyzed 278 patients, aged 47 +/- 10 years, with ischemic (n = 75) and nonischemic (n = 203) HF. LVEF was 30.8 +/- 9.4% and 28.6 +/- 8.2% (P = .04), peak VO2 16.9 +/- 4.7 and 16.9 +/- 5.2 mL kg(-1) min(-1) (P = NS), and the HRmax 130.8 +/- 23.3 and 125.3 +/- 25.3 beats/min (P = .051) in ischemic and nonischemic patients, respectively. We devised the equation HRmax = 168 - 0.76 x age (R-2 = 0.095; P = .007) for ischemic HF patients, but there was no significant relationship between age and HRmax in nonischemic HF patients (R-2 = 0.006; P = NS). Conclusions: Our study suggests that equations to estimate HRmax should consider the cause of HF. (J Cardiac Fail 2012;18:831-836)

Are there non-linearities in short-term interest rates?

The present paper investigates the characteristics of short-term interest rates in several countries. We examine the importance of nonlinearities in the mean reversion and volatility of short-term interest rates. We examine various models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate.We find that different markets require different models. In particular, we find evidence of nonlinear mean reversion in some of the countries that we examine, linear mean reversion in others and no mean reversion in some countries. For all countries we examine, there is strong evidence of the need for the volatility of interest rate changes to be highly sensitive to the level of the short-term interest rate. Out-of-sample forecasting performance of one-factor short rate models is poor, stemming from the inability of the models to accommodate jumps and discontinuities in the time series data.

Association of follicle stimulating hormone receptor promoter with ovarian response in IVF-ET patients

Background: Poor ovarian response phenomenon has been observed in some of the in vitro fertilization-embryo transfer patients. Some investigations found that follicle stimulating hormone receptor (FSHR) gene plays a role in the process, but no direct evidence shows the correlation between genotypes of FSHR and ovarian response. Objective: Exploring the molecular mechanism behind the mutation of FSHR promoter association with ovarian granulosa cells and poor ovarian response. Materials and Methods: This cross sectional study was performed using 158 women undergoing the controlled short program ovarian stimulation for IVF treatment. The 263 bp DNA fragments before the follicle stimulating hormone (FSH) receptor 5' initiation site were sequenced in the patients under IVF cycle, 70 of which had poor ovarian response and 88 showed normal ovarian responses. Results: With a mutation rate of 40%, 63 in 158 cases showed a 29th site G→A point mutation; among the mutated cases, the mutation rate of the poor ovarian responders was significantly higher than the normal group (60% versus 23.9%; χ2=21.450, p<0.001). Besides, the variability was also obvious in antral follicle count, and ovum pick-ups. The estradiol peak values and the number of mature eggs between the two groups had significant difference. However, there was no obvious variability (t=0.457, p=0.324) in the basic FSH values between the two groups (normal group, 7.2±2.3 U/L; mutation group, 7.1±2.0 U/L). Conclusion: The activity of FSHR promoter is significantly affected by the 29th site G→A mutation that will weaken promoter activity and result in poor response to FSH.

An empirical investigation of the level effect in Australian interest rates

An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

Jackknife for bias reduction in predictive regressions

One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

Dynamical behavior in the nonlinear rheology of surfactant solutions

Several surfactant molecules self-assemble in solution to form long, flexible wormlike micelles which get entangled with each other, leading to viscoelastic gel phases. We discuss our recent work on the rheology of such a gel formed in the dilute aqueous solutions of a surfactant CTAT. In the linear rheology regime, the storage modulus G′(ω) and loss modulus G″(ω) have been measured over a wide frequency range. In the nonlinear regime, the shear stress σ shows a plateau as a function of the shear rate math above a certain cutoff shear rate mathc. Under controlled shear rate conditions in the plateau regime, the shear stress and the first normal stress difference show oscillatory time-dependence. The analysis of the measured time series of shear stress and normal stress has been done using several methods incorporating state space reconstruction by embedding of time delay vectors. The analysis shows the existence of a finite correlation dimension and a positive Lyapunov exponent, unambiguously implying that the dynamics of the observed mechanical instability can be described by that of a dynamical system with a strange attractor of dimension varying from 2.4 to 2.9.

Yield stress, thixotropy and shear banding in a dilute aqueous suspension of few layer graphene oxide platelets

We demonstrate a rigidity percolation transition and the onset of yield stress in a dilute aqueous dispersion of graphene oxide platelets (aspect ratio similar to 5000) above a critical volume fraction of 3.75 x 10(-4) with a percolation exponent of 2.4 +/- 0.1. The viscoelastic moduli of the gel at rest measured as a function of time indicate the absence of structural evolution of the 3D percolated network of disks. However a shear-induced aging giving rise to a compact jammed state and shear rejuvenation indicating a homogenous flow is observed when a steady shear stress (sigma) is imposed in creep experiments. We construct a shear diagram (sigma vs. volume fraction phi) and the critical stress above which shear rejuvenation occurs is identified as the yield stress sigma(y) of the gel. The minimum steady state shear rate (gamma) over dot(m) obtained from creep experiments agrees well with the end of the plateau region in a controlled shear rate flow curve, indicating a shear localization below (gamma) over dot(m). A steady state shear banding in the plateau region of the flow curve observed in particle velocimetry measurements in a Couette geometry confirms that the dilute suspensions of GO platelets form a thixotropic yield stress fluid.

Effect of Nb orientation and deformation on the growth of Nb3Sn intermetallic superconductor by bronze technique

The growth of Nb3Sn by bronze technique on single crystals and deformed Nb is studied. The grain boundary diffusion-controlled growth rate is found to be higher for Nb-(0 1 3) than Nb-(0 1 1) because of smaller grain size of Nb3Sn. The difference in grain size is explained with the help of surface energies leading to different nucleation barrier. Significantly finer grains and higher growth rate of the product phase is found for rolled Nb because of available defects acting as potential nucleation sites.