THE TRADE DISCOUNT DECISION: A MARKOV CHAIN APPROACH*
用马尔可夫链模型分析不同贸易信用政策如何影响企业的风险与回报，发现即使销量不增加，贸易折扣也能改善风险回报特征。
ABSTRACT Economic theory indicates that higher returns are required from investments that have higher risk. Two major reasons for offering trade discounts are to stimulate sales and to speed up cash receipts. Both sales increases and the earlier receipt of cash impact the risk/return characteristics of a firm. This study uses a Markov chain model to demonstrate how alternative trade credit policies impact the risk and required returns of a firm. The amount of risk and return per credit sale is calculated, and the coefficient of variation is used as a risk/return measure per credit sale. The study concludes that trade discounts can have a favorable impact on the risk/return characteristics of a firm, even in the absence of increased sales volume. Other discount decision factors which are either directly or indirectly determined in this paper include: (1) the average number of periods for which an account is outstanding, (2) the probability of collection and bad‐debt losses over the average account period, (3) the average speed of payment, and (4) the average amount of cash tied up in accounts receivable.