Kin Lam

A comparison of the prognostic significance of tumor diameter, length, width, thickness, area, volume, and clinicopathological features of oral tongue carcinoma

BACKGROUND The present study aims at evaluation of the prognostic value of tumor size including diameter, length, thickness, width, area, and volume in the prediction of nodal metastasis, local recurrence, and survival of oral tongue carcinoma. The results will have important implications for the management of patients. METHODS Eighty-five glossectomy specimens of oral tongue carcinoma were serially sectioned in 3 mm thickness for the tumor size evaluation with computer image analyzer. RESULTS Among all the tumor size parameters being evaluated, tumor thickness was the only significant factor for the prediction of local recurrence, nodal metastasis, and survival. With the use of 3 mm and 9 mm division, tumor of up to 3 mm thickness has 10% nodal metastasis, 0% local recurrence, and 100% 5-year actuarial disease-free survival; tumor thickness of more than 3 mm and up to 9 mm has 50% nodal metastasis, 11% local recurrence, and 77% 5-year actuarial disease free survival; tumor of more than 9 mm has 65% nodal metastasis, 26% local recurrence, and 60% 5-year actuarial disease-free survival. CONCLUSIONS Tumor thickness should be considered in the management of patients with oral tongue carcinoma.

Intraday price reversals for index futures in the US and Hong Kong

Abstract We observe intraday price reversals following large price changes at the opening of the S&P 500 Futures market and the HSI Futures market. We note that the magnitude of subsequent price reversals is positively related to the initial price changes, and that the price reversals are not caused by a bid–ask spread, or by panic among investors. We also note that such price reversals can be exploited to give rise to profitable opportunities after transaction costs, even though these may not be very significant. This study shows that investor overreaction may be a universal phenomenon and irrational investor behavior like overreaction may also exist among groups of sophisticated investors.

ESTIMATION OF PARAMETERS IN A TWO-PARAMETER EXPONENTIAL DISTRIBUTION USING RANKED SET SAMPLE

In situations where the experimental or sampling units in a study can be easily ranked than quantified, McIntyre (1952,Aust. J. Agric. Res.,3, 385–390) proposed that the mean ofn units based on aranked set sample (RSS) be used to estimate the population mean, and observed that it provides an unbiased estimator with a smaller variance compared to a simple random sample (SRS) of the same sizen. McIntyres concept ofRSS is essentially nonparametric in nature in that the underlying population distribution is assumed to be completely unknown. In this paper we further explore the concept ofRSS when the population is partially known and the parameter of interest is not necessarily the mean. To be specific, we address the problem of estimation of the parameters of a two-parameter exponential distribution. It turns out that the use ofRSS and its suitable modifications results in much improved estimators compared to the use of aSRS.

Single-stage interval estimation of the largest normal mean under heteroscedasnoty

Let there be given k(≥1) independent and normally distributed populations where πi has unknown mean μ1 and unknown variance . A single-stage sampling procedure is developed for constructing confidence intervals for the largest of the means. The method is to split up the single sample into two portions, the first consisting of n-1 observations for initial estimation and the second consisting of the remaining one for use as a spare in the final estimation. One-sided, two-sided, and asymptotically optimal confidence interval are considered. A numerical example to apply this procedure is given.

An examination of the determinants of stock price effects of US–Chinese joint venture announcements

This paper examines the announcement effects of US-Chinese joint ventures and explores several firm-specific factors which may affect the size of the abnormal returns. A sample of 103 joint ventures during the 1973-1993 period and eight variables, including current ratio, debt ratio, total asset turnover ratio, return on equity, industry classification, prior experience in China, location of headquarters and the date of the joint venture announcement, are used in the study. A significant 3-day cumulative abnormal return of 1.02% is found in the total sample. However, sub-sample and regression analyses show that none of the factors influence the size of the abnormal gains.

Cusum Techniques for Technical Trading in Financial Markets

It is discovered that the CUSUM techniques often used in the manufacturing industry can be adapted to yield a trading strategy in the financial market. The familiar filter trading strategy in finance is found to be a particular case of CUSUM procedures. A more general form of the CUSUM techniques will yield new trading strategies which have intuitive appeals. Trading characteristics of such strategies will be investigated using CUSUM techniques.

Estimation of Normal Variance Based on Balanced and Unbalanced Ranked Set Samples

In this paper we address the problem of estimation of the variance of a normal population based on a balanced as well as an unbalanced ranked set sample (RSS), which is a modification of the original RSS of McIntyre (1952).We have proposed several methods of estimation of variance by combining different unbiased between and within estimators, and compared their performances

A New Pseudo-Bayesian Model with Implications to Financial Anomalies and Investors’ Behaviors

Barberis, Shleifer and Vishny (1998) and others have developed Bayesian models to explain investors’ behavioral biases by using the conservatism heuristics and the representativeness heuristics in making decisions. To extend their work, Lam, Liu, and Wong (2010) have developed a model of weight assignments using a pseudo-Bayesian approach that reflects investors’ behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors’ conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors’ behavioral biases. This paper extends their work further by developing properties to explain some market anomalies including short-term underreaction, long-term overreaction, and excess volatility. We also explain in details the linkage between these market anomalies and investors’ behavioral biases.

Estimation of Location and Scale Parameters of a Logistic Distribution Using a Ranked Set Sample

In situations where the experimental or sampling units in a study can be more easily ranked than quantified, McIntyre (1952) proposed that the mean of n units based on a ranked set sample (RSS) be used to estimate the population mean. He observed that it provides an unbiased estimator with a smaller variance compared to the mean of a simple random sample (SRS) of the same size n. McIntyre’s concept of RSS is essentially nonparametric in nature in that the underlying population distribution is assumed to be completely unknown. Here we explore the concept of RSS to estimate the location, scale and quantiles of a logistic distribution. It turns out that the use of RSS and its suitable modifications result in much improved estimators compared to the use of an SRS in all the three cases.

Optimal market timing strategies under transaction costs

In this paper, we consider optimal market timing strategies under transaction costs. We assume that the assets return follows an auto-regressive model and use long-term investment growth as the objective of a market timing strategy which entails the shifting of funds between a risky asset and a riskless asset. We give the optimal trading strategy for a finite investment horizon, and analyze its limiting behavior. For a finite horizon, the optimal decision in each step depends on two threshold values. If the return today is between the two values, nothing needs to be done, otherwise funds will be shifted from one asset to another, depending on which threshold value is being exceeded. When investment horizon tends to infinity, the optimal strategy converges to a stationary policy, which is shown to be closely related to a well-known technical trading rule, called Momentum Index trading rule. An integral equation of the two threshold values is given. Numerical results for the limiting stationary strategy are presented. The results confirm the obvious guess that the no-transaction region increases as the transaction cost increase. Finally, the limiting stationary strategy is applied to data in the Hang Seng Index Futures market in Hong Kong. The out-of-sample performance of the limiting stationary strategy is found to be better than the simple strategy used in literature, which is based on an 1-step ahead forecast of return.