• Management Science and Financial Engineering
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• v.21 no.2
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• pp.13-23
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• 2015

This study addresses the question as to whether the option prices have useful predictive information on the direction of stock markets by investigating a forecasting power of volatility curvatures and skewness premiums implicit in S&P 500 index option prices traded in Chicago Board Options Exchange. We begin by estimating implied volatility functions and risk neutral price densities every minute based on non-parametric method and then calculate volatility curvature and skewness premium using them. The rationale is that high volatility curvature or high skewness premium often leads to strong bullish sentiment among market participants. We found that the rate of return on the signal following trading strategy was significantly higher than that on the intraday buy-and-hold strategy, which indicates that the S&P500 index option prices have a strong forecasting power on the direction of stock index market. Another major finding is that the information contents of S&P 500 index option prices disappear within one minute, and so one minute-delayed signal following trading strategy would not lead to any excess return compared to a simple buy-and-hold strategy.

• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.252-258
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• 2019

In this paper, the time history of the surface elevation measured at the Draupner platform in the North Sea in 1995 is used to examine the statistical characteristics of the wave data. The wave statistics for 48 surface measurements, which contain three freak wave occurrences, are summarized. The quartiles, boxplots, correlations, and pair plots of 15 variables, along with the abnormality index, are presented. The kurtosis and skewness of the surface elevation are two variables that are highly correlated with the abnormality index, which defines freak waves. Principal coordinate analysis showed that the direction of the changes in the abnormality index agreed with the changes in the kurtosis and skewness. In addition, various wave heights, except the maximum wave height, showed a similar direction for the height changes, and various wave periods showed a similar direction for the period changes. Based on the correlations and PCA analysis, the kurtosis and skewness of the surface profiles are the two most important variables to predict the abnormality index.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.171-179
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• 1992

본고에서는 그래프를 이용하여 stable law분포의 index, skewness, scale, location 모수들에 대한 추정방법을 제시한다. 먼저, order statistics의 함수인 tail length statistic $K_{t}$ , skewness statistic $K_{s}$ 를 이용하여 index .alpha., scale .betha.를 추정한다. 다음에는, 추정된 .alpha., .betha.를 index로 하여 개발된 그래프들로 부터 scale .sigma., location .mu.추정에 필요한 order statistics의 함수를 결정한다. 몇가지 예를 마지막에 예시한다.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.867-873
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• 2001

In this paper we propose a family of skew- f distributions. The family is derived by a scale mixtures of skew-normal distributions introduced by Azzalini (1985) and Henze (1986). The salient features of the family are mathematical tractability and strict inclusion of the normal law. Further it includes a shape parameter, to some extent, controls the index of skewness. Necessary theory involved in deriving the family of distributions is provided and main properties of the family are also studied.

• Management Science and Financial Engineering
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• v.2 no.1
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• pp.103-122
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• 1996

This paper presents an easily used graphical procedure for simultaneous estimation of the index, skewness, scale, and location parameters of the stable laws. First, the index $\alpha$ and skewness $\beta$ are estimated through the joint use of a tail length statistic $\widetilde{K_t}$ and a skewness statistic $\widetilde{K_s}$, both of which are functions of order statistics. Next, the function of order statistics needed for estimation of scale $\sigma$ and location $\mu$ are determined from a nomogram indexed on the estimates of $\alpha$ and $\beta$. Some applications and examples are provided.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.41-59
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• 2016

There have been continuous improvements in human life expectancy. Life expectancy is as a key factor in an aging population and can wreak severe damage on the financial integrity of pension providers. Hence, the projection of the accurate future mortality is a critical point to prevent possible losses to pension providers. However, improvements in future mortality would be overestimated by a typical mortality projection method using the Lee-Carter model since it underestimates the mortality index ${\kappa}_t$. This paper suggests a mortality projection based on the projection of the skewness of the mortality versus the typical mortality projection of the Lee-Carter model based on the projection of the mortality index, ${\kappa}_t$. The paper shows how to indirectly estimate future t trend with the skewness of the mortality and compares the results under each estimation method of the mortality index, ${\kappa}_t$. The analysis of the results shows that mortality projection based on the skewness presents less improved mortality at an elderly ages than the original projection.

• Corrosion Science and Technology
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• v.7 no.5
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• pp.296-299
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• 2008

High order statistical parameters were evaluated using the electrochemical noise data collected during corrosion of type 430 stainless steel coupled to a inert, platinum electrode in 3.5% NaCl solution. High order statistical parameters are shown to predict uniform corrosion properly. However, Localization index, skewness of current, kurtosis and skewness of potential are capable of predicting pitting corrosion only when the transients are large with long life time. Of the high order statistical parameters evaluated, kurtosis of current is found to be the most sensitive parameter for detecting uniform and pitting corrosion.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.869-878
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• 2007

In this paper a new process capability index $C_{psks}$ is introduced for non-normal process. $C_{psks}$ that is proposed by transformation of the $C_{psks}$ incorporates an additional skewness correction factor in the denominator of $C_{psks}$. The use of each technique is illustrated by reference to a distribution system which includes the Pearson and Johnson functions. Accordingly, $C_{psks}$ is proposed as the process capability measure for non-normal process.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.255-266
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• 2006

This paper proposes a class of distributions which is useful in making inferences about the sum of values from a normal and a doubly truncated normal distribution. It is seen that the class is associated with the conditional distributions of truncated bivariate normal. The salient features of the class are mathematical tractability and strict inclusion of the normal and the skew-normal laws. Further it includes a shape parameter, to some extent, controls the index of skewness so that the class of distributions will prove useful in other contexts. Necessary theories involved in deriving the class of distributions are provided and some properties of the class are also studied.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1171-1181
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• 2014

Different power quality (PQ) disturbance sources can have major impacts on the power supply grid. This study proposes, for the first time, an early warning approach to identifying PQ problems and providing early warning prompts based on the monitored data of PQ disturbance sources. To establish a steady-state power quality early warning index system, the characteristics of PQ disturbance sources are analyzed and summed up. The higher order statistics anomaly detection (HOSAD) algorithm, based on skewness and kurtosis, and hierarchical power quality early warning flow, were then used to mine limit-exceeding and abnormal data and analyze their severity. Cases studies show that the proposed approach is effective and feasible, and that it is possible to provide timely power quality early warnings for limit-exceeding and abnormal data.