The computation of three stage least squares estimates

Liquid financial markets, such as the options market of the S&P 500 index, create vast amounts of data every day, i.e., so-called intraday data. However, this highly granular data is often reduced to single-time when used to estimate financial quantities. This under-utilization of the data may reduce the quality of the estimates. In this paper, we study the impacts on estimation quality when using intraday data to estimate dividends. The methodology is based on earlier linear regression (ordinary least squares) estimates, which have been adapted to intraday data. Further, the method is also generalized in two aspects. First, the dividends are expressed as present values of future dividends rather than dividend yields. Second, to account for heteroscedasticity, the estimation methodology was formulated as a weighted least squares, where the weights are determined from the market data. This method is compared with a traditional method on out-of-sample S&P 500 European options market data. The results show that estimations based on intraday data have, with statistical significance, a higher quality than the corresponding single-times estimates. Additionally, the two generalizations of the methodology are shown to improve the estimation quality further.

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A Robust Regression by Using Huber Estimator and Tukey Bisquare Estimator for Predicting Availability of Corn in Karanganyar Regency, Indonesia

Indonesian Journal of Applied Statistics ◽

10.13057/ijas.v1i1.24090 ◽

2018 ◽

Vol 1 (1) ◽

pp. 37

Author(s):

Hasih Pratiwi ◽

Yuliana Susanti ◽

Sri Sulistijowati Handajani

Keyword(s):

Least Squares ◽

Robust Regression ◽

Likelihood Estimation ◽

Corn Production ◽

Least Squares Fit ◽

Class Of Estimators ◽

M Estimation ◽

Heavy Tailed ◽

Least Squares Estimates ◽

Huber Estimator

Linear least-squares estimates can behave badly when the error distribution is not normal, particularly when the errors are heavy-tailed. One remedy is to remove influential observations from the least-squares fit. Another approach, robust regression, is to use a fitting criterion that is not as vulnerable as least squares to unusual data. The most common general method of robust regression is M-estimation. This class of estimators can be regarded as a generalization of maximum-likelihood estimation. In this paper we discuss robust regression model for corn production by using two popular estimators; i.e. Huber estimator and Tukey bisquare estimator.<br />Keywords : robust regression, M-estimation, Huber estimator, Tukey bisquare estimator

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Financial disclosure and performance of microfinance institutions

Journal of Accounting & Organizational Change ◽

10.1108/jaoc-12-2011-0067 ◽

2014 ◽

Vol 10 (3) ◽

pp. 314-337 ◽

Cited By ~ 20

Author(s):

Shakil Quayes ◽

Tanweer Hasan

Keyword(s):

Financial Performance ◽

Least Squares ◽

Least Squares Method ◽

Financial Disclosure ◽

Microfinance Institutions ◽

Content Type ◽

Three Stage Least Squares ◽

And Performance ◽

The Impact ◽

The Relationship

Purpose – The purpose of this paper is to analyze the relationship between financial disclosure and the financial performance of microfinance institutions (MFIs). Design/methodology/approach – The paper utilizes ordinary least squares method to analyze the impact of disclosure on financial performance, an ordered probit model to investigate the possible effect of financial performance on disclosure and utilizes a three-stage least squares method to delineate the endogenous relationship between disclosure and financial performance of MFIs. Findings – The paper finds that better disclosure has a statistically significant positive impact on operational performance of MFIs; second, it also shows that improved financial performance results in better financial disclosure. Keeping the endogenous nature of the relationship between disclosure and performance, the paper uses a three-stage least squares method to show that disclosure and financial performance positively affect each other simultaneously. Research limitations/implications – The paper attempts to delineate a positive association between better disclosure on financial performance of MFIs, which can be used for developing a better disclosure policy by management, formulating more effective guidelines for disclosure by the stakeholders and mandating more appropriate laws and uniform disclosure practice by regulators. Originality/value – This is the first study that uses a large number of MFIs from 75 countries; second, it uses a uniform scale of designating a disclosure rating (assigned by MIX Market) to show the relationship between disclosure and performance. Finally, it uses three-stage least squares method to address the possible endogeneity between disclosure and performance.

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