A nonparametric method for term structure fitting with automatic smoothing

We present a nonparametric method for fitting the term structure of interest rates from bond prices. Our method is a variant of the smoothing spline approach, but within our framework we are able to determine the smoothing coefficient automatically from data using the generalized cross-validation or maximum likelihood estimates. We present an effective numerical algorithm to simultaneously find the term structure and the optimal smoothing coefficient. Finally, we compare the proposed nonparametric fitting method with other parametric and nonparametric methods to find its superior performance. We find that existing term structure fitting methods perform well in liquid markets while illiquid markets present new challenges, which we address in this article.     

Optimal money and debt management: Liquidity provision vs tax smoothing

Conventional wisdom on public debt management says that liquidity demand should be satiated and that tax rates should be smoothed. Conflicts between the two can arise when government bonds provide liquidity. Smoothing taxes causes greater variability in fiscal balances, and therefore in the supply of government liabilities. When prices are flexible, and can jump to absorb fiscal shocks, the tradeoff between liquidity provision and tax smoothing is eased; when they conflict, optimal policy subordinates tax smoothing to satiating liquidity demand. When price fluctuations impose real costs, conflicts necessarily arise and optimal policy gives primacy to neither goal.     

Stable Shareholdings,the Decision Horizon Problem and Earnings Smoothing

Prior studies argue that stable shareholders do not encourage firm managers to manage their earnings to achieve short‐term earnings goals. They also state that firm managers with stable shareholders have an incentive to report smooth earnings to maintain long‐term relationships with such shareholders. We focus on cross‐shareholdings and stable shareholdings owned by financial institutions as stable shareholdings in Japan, and investigate the effect of these ownership structures on earnings management patterns. Specifically, we hypothesize that stable shareholdings are positively associated with the informational components of earnings smoothing. Consistent with our hypothesis, we first find that as stable shareholdings increase, managers are more likely to conduct earnings smoothing that provides useful information to stable shareholders. Further, our additional analysis shows that stable shareholdings reduce incentives for managers to cut discretionary expenditures to meet short‐term earnings benchmarks, implying that stable shareholdings could reduce the possibility of a myopic problem. These results suggest that managers with stable shareholdings tend to report smoother and less volatile earnings, and do not tend to pursue earnings management to attain short‐term earnings targets.     

浅谈季节性指数平滑法在供水管网漏损预测中的应用

给水管网的漏损是不可避免的,但每月的漏损量与温度有关。根据原始数据,通过季节性指数平滑法对每月的漏损管件数进行预测,对管网未来的漏损程度进行估计。     

Environmental uncertainty and the market pricing of earnings smoothness

Environmental uncertainty induces variability in an organization's reported earnings, and accentuates the information asymmetry between its managers and outside stakeholders. Managers operating in an environment of high uncertainty, therefore, have an incentive to reduce such variability by smoothing income numbers. We investigate the stock market response to earnings smoothness for firms operating in an environment of high uncertainty. We measure income smoothing by the negative correlation of a firm's change in discretionary accruals with its change in pre-managed earnings as per Tucker and Zarowin (2006). Using future earnings response coefficient (FERC) methodology to measure the informativeness of smoothed earnings, and two measures of environmental uncertainty, this paper documents that current stock price incorporates more information about future earnings for firms operating in high uncertain environments, thus supporting the informational value view of income smoothing.     

Maximum likelihood estimation for dynamic factor models with missing data

This paper concerns estimating parameters in a high-dimensional dynamic factor model by the method of maximum likelihood. To accommodate missing data in the analysis, we propose a new model representation for the dynamic factor model. It allows the Kalman filter and related smoothing methods to evaluate the likelihood function and to produce optimal factor estimates in a computationally efficient way when missing data is present. The implementation details of our methods for signal extraction and maximum likelihood estimation are discussed. The computational gains of the new devices are presented based on simulated data sets with varying numbers of missing entries.     

组合模型在公路客运量预测中的应用

针对公路客运量预测问题,在建立灰色GM(1,1)模型和三次指数平滑模型的基础上,利用最优加权系数法建立组合模型来对客运量进行预测。以此来避免单一模型的不足,从而提高模型的预测精度。通过2005-2009年安顺到贵阳的贵黄高速客运量模型的检验,证明组合模型是合理、可行的,并且具有较高的预测精度。     

中国人均GDP时间序列建模与相关分析

人均GDP是衡量一个国家和地区经济发展水平和综合经济实力的重要指标。本文在相关背景下收集了1978-2008年中国人均GDP时间序列数据,应用了SPSS软件进行数据分析并建立时间序列模型,利用模型预测了2009,2010年人均GDP数值,对制定相应的宏观调控政策有十分重要的意义。     

A Comparison of Forecasting Techniques for Predicting Exchange Rates

Forecasting exchange rates accurately helps policy makers and businesses to plan more appropriately. Exchange rates provide information for policy makers about a country's mde position relative to that of ocher nations. In addition, accurate informaticm about future exchange rates helps to improve the quality of many management decisions. This study illustrates the use of different forecasting methods in predicting exchange rates f a the British Pound, German Mark and Japanese Yen. A number of accuracy measures are used to judge the performance of these methods. The results show that simple time series techniques can perfam as well as some complex and costly techniques in forecasting exchange rates.     

Banks' Funding Stress,Lending Supply,and Consumption Expenditure

We employ a unique identification strategy linking survey data on household consumption expenditure to bank-level data to estimate the effects of bank funding stress on consumer credit and consumption expenditures. We show that households whose banks were more exposed to funding shocks report lower levels of nonmortgage liabilities. This, however, only translates into lower levels of consumption for low-income households. Hence, adverse credit supply shocks are associated with significant heterogeneous effects.