# AN ANALYSIS OF THE FINANCIAL CHARACTERISTICS OF FIRMS THAT EXPERIENCED HEAVY BUYING AND SELLING BY INSIDERS DURING A PERIOD OF ECONOMIC RECESSION

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5 An Analysis of the Financial Characteristics of Firms that Experienced Heavy Buying and Selling by Insiders During a Period of Economic Recession TEST AND RESULTS The discriminant function used has the form: Z j = V 1 X 1j + V 2 X 2j V n X nj (1) where: X ij is the company's value for the ith independent variable. V i is the discriminant coefficient for the ith variable. Z j is the jth individual's discriminant score. The function derived from the data in this study in equation 1 is: Z j = X X X X X X X 7 (2) Classification of firms is relatively simple. The values of the seven variables for each firm are substituted into equation (2). Thus, each firm in both groups receives a Z score. If a firm's Z score is greater than a critical value, the firm is classified in group two (HIS). Conversely, a Z score less than the critical value will place the firm in group one (HIB). The only exception is the measure for timeliness. The values for this variable are descending as securities are perceived to be more timely. Since the two groups are heterogeneous, the expectation is that randomly selected HIS firms will fall into one group and the randomly selected HIB firms will fall into the other. One of the assumptions of the MDA model is that the matrices of data are equal. The SPSS program tests for equality of matrices by means of Box s M statistic. In this study Box s M transformed to the more familiar F statistic of is less than the critical F with 1 and 2 degrees of freedom. Thus, the null hypothesis that the two matrices are equal cannot be rejected, and the midpoint value between the two group means can be defined as the critical Z value. Interpretation of the results of discriminant analysis is usually accomplished by addressing four basic questions: 1. Is there a significant difference between the mean vectors of variables for the two groups of firms? 2. How well did the discriminant function perform? 3. How well did the independent variables perform? 4. Will this function discriminate as well on any random sample of firms as it did on the original sample? To answer the first question, SPSS provides a Wilk s Lambda Chi Square transformation (Cooper and Schindler, 2001, 581). The calculated value of Chi-Square is That exceeds the critical value of Chi-Square , with 7 degrees of freedom. The null hypothesis that there is no significant difference between the financial profiles of the two groups is therefore rejected, and the first conclusion drawn from the analysis is that the two groups have significantly different financial characteristics. This result was of course, expected since one group s shares are being purchased by insiders and the other group s shares are being sold by insiders. 161

6 Southwestern Economic Review The discriminant function thus, has the power to separate the two groups. However, this does not mean that it will in fact separate them. The ultimate value of a discriminant model depends on the results obtained. That is, what percentage of firms were classified correctly and is that percentage significant? To answer the second question a test of proportions is needed. Of the 50 firms in the HIB group, 41 were classified correctly. Of the 50 firms in the HIS group, 33 were classified correctly. Thus, 74 firms or 74 percent were classified correctly. The results are shown in Table

9 An Analysis of the Financial Characteristics of Firms that Experienced Heavy Buying and Selling by Insiders During a Period of Economic Recession correctly by the validation test differs significantly from the 74 percent classified correctly in the original test. That is, is the difference in the two proportions classified correctly by the two tests due to bias? The objective is to see if this bias is significant. The jackknife validation resulted in the correct classification of 69 percent of the firms. There were 100 companies and two groups in the original sample. Since there are only two groups for analysis the binomial test is appropriate: (.74)/ [100 (.74) (.26)] 1/2 = < t (5) Thus, the null hypothesis that there is no significant difference between the proportion of firms classified correctly in the original test and the proportion classified correctly in the validation test cannot be rejected. Therefore, it can be concluded that while there may be some bias in the original analysis, it is not significant. The procedure will classify new firms as well as it did in the original analysis, and prediction on the basis of the explanatory variables is possible. To ensure that the model can be used in forecasting insider trading during a recession, further validation is needed. Thus, the split-sample method of validation was used. The sample of 100 firms was split into two samples, one of 75 and the other of 25. The larger sample was first used to train the MDA model, and that was used to predict the group membership of the unseen 25 cases. The sample used in training allowed on average fifteen cases per predicting variable. Such case-to-variable ratio is close enough to the general recommendation of twenty per variable. The validation result is produced in Table 3 Table 3 Classification Results Predicted Group Membership Total SELLBUY 0 1 Cases Selected Original Count % Cross-validated Count % Cases Not Selected Original Count % a. Cross validation is done only for those cases in the analysis. In cross validation, each case is classified by the functions derived from all cases other than that case. b. 74.7% of selected original grouped cases correctly classified. c. 80.0% of unselected original grouped cases correctly classified. d. 70.7% of selected cross-validated grouped cases correctly classified. The MDA model derived from the 75-case sample yielded a prediction rate of about 75%, and predicted 80% of the hold-out cases correctly. The leave-one-out cross validation procedure generated an accuracy rate of about 71%. The lowered prediction 165

11 An Analysis of the Financial Characteristics of Firms that Experienced Heavy Buying and Selling by Insiders During a Period of Economic Recession investors sold their shares in companies that had high three year returns to total capital. Given that they were buying shares in firms that were showing high one year returns, it may be concluded that inside investors were valuing short term returns more highly than returns over a three year period. Neither past short term nor past long term returns are relevant for investment decision making. The investor is interested in marginal returns, and to the extent, if any, that one year returns are a better indicator of marginal returns, it may aid in explaining a result that was unexpected. Secondly, insiders were selling shares in companies that showed high returns on equity. This defies logic unless the levels of systematic risk in those companies were high enough to offset the higher returns to equity. In the eight month recession period under study, systematic risk generally increased, and there was a general feeling of pessimism among investors as the market declined. There will be no attempt here to analyze why the variable profile is as it is, but given the interest and timeliness of the subject of inside trading, both in the literature and in practice, it is an area that certainly deserves further study. This study has resulted in a contribution toward the construction of a theory that describes the risk-return characteristics of companies that are identified by Value Line as experiencing either heavy inside buying, or heavy inside selling during a period of economic recession. Construction of a complete theory would aid managers, investors, and investment counselors in identifying the merits, or lack of merits in using profiles such as the one developed here for investment and other managerial decisions. 167

12 Southwestern Economic Review ENDNOTES 1 Essentially, illegal trading occurs when; 1) issuers of nonpublic information make selective disclosure, 2) with the use or knowing possession of nonpublic information, and 3) when the breach of a duty of trust gives rise to a liability under the misappropriation theory (SEC Fact Sheet, August 10, 2000). REFERENCES Altman, Edward I. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance, 23, no.4, September 1968, Associated Press, It s Official: The Recession s Over. July 17, Cooper, Donald R., and Pamela S. Shindler. Business Research Methods, Boston: McGraw-Hill Irwin, Dash, Eric., Lisa Munoz, and Jessica Sung. You Bought They Sold. Fortune, September 2, 2002, Durand, David D. "Risk Elements in Consumer Installment Financing." Studies In Consumer Installment Financing. New York: National Bureau of Economic Research, 1941, Edmister, Robert O. "An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction? Journal of Financial and Quantitative Analysis 7, no.2, March 1982, Hair, Joseph F., Ralph E. Anderson, Ronald L. Tatham, and William C. Black. Multivariate Data Analysis, New York: Macmillian Publishing Company, Payne, Bruce C. Aden Daghestani, and Hugo Hervitz An Analysis of the Financial Characteristics and Price Earnings Ratios of Firms Identified by Value Line as Having the Greatest Three to Five Year Growth Potential. Journal of Business and Economic Perspectives, XXVII 2 Fall Winter 2001, Robbins, Michael. Take A Tip from Company Insiders. MSN Money, June 26, Treschmann, James S., and George E. Pinches. "A Multivariate Model for Predicting Financially Distressed Property-Liability Insurers." Journal of Risk and Insurance, 40, no.3: September 1973, United States Securities and Exchange Commission, Fact Sheet, August 10, 2000, 1. Van Horne, James C. Financial Management and Policy, New York: Prentice-Hall Publishing,

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