Purely Sequential and Two-Stage Fixed-Accuracy Confidence Interval Estimation Methods for Count Data from Negative Binomial Distributions in Statistical Ecology: One-Sample and Two-Sample Problems

2014 ◽  
Vol 33 (2) ◽  
pp. 251-285 ◽  
Author(s):  
Nitis Mukhopadhyay ◽  
Swarnali Banerjee
Keyword(s):  
Confidence Interval ◽  
Count Data ◽  
Negative Binomial ◽  
Interval Estimation ◽  
Estimation Methods ◽  
Two Stage ◽  
Binomial Distributions ◽  
Confidence Interval Estimation ◽  
Purely Sequential ◽  
Statistical Ecology

scholarly journals The use of the bootstrap method for the assessment of investment effectiveness and risk – the case of confidence intervals estimation for the Sharpe ratio and TailVaR

2020 ◽  
Vol 1/2020 (13) ◽  
pp. 40-50
Author(s):  
Jarno Klaudia ◽  
◽  
Smaga Łukasz ◽  
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Stock Exchange ◽  
Bootstrap Method ◽  
Interval Estimation ◽  
Sharpe Ratio ◽  
Estimation Methods ◽  
Bootstrap Confidence Interval ◽  
Warsaw Stock Exchange ◽  
Confidence Interval Estimation

This paper is aimed at presenting application of bootstrap interval estimation methods to the assessment of financial investment’s effectiveness and risk. At first, we give an overview of various methods of bootstrap confidence interval estimation, i.e. bootstrap-t interval, percentile interval and BCa interval. Then, bootstrap confidence interval estimation methods are used to estimate confidence intervals for the Sharpe ratio and TailVaR of the Warsaw Stock Exchange sectoral indices. The results show that the bootstrap confidence intervals of different types are quite similarly positioned for each of the analysed index and measure. Taking into the account the locations of confidence intervals for both the Sharpe ratio and TailVaR, the real estate sector tends to be the most advantageous from the investor’s viewpoint.

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