基于信用担保的资金约束供应链订货与定价决策

受自由现金流的限制, 中小企业需要外部融资来实现良性运营, 供应商信用担保贷款是一种有效手段. 考虑银行下侧风险控制的担保贷款模型, 根据供应链购销过程中的订货量和批发价参数决策, 评价供应链内部无风险资本转移过程. 通过建立供应商担保费率、风险担保比率设计和银行利率组合模型, 确定贷款担保系统的最优决策. 研究结果表明: 在具有贷款可获得性的资金约束供应链中, 存在最优订货量与批发价的组合, 且供应商销售收入存在最值; 在担保贷款过程中, 存在最优风险分担比例, 通过设计合理的风险控制模型, 可提高零售商资金水平, 达到供应链的协同.

     

A single-period inventory and payment model with partial trade credit

In this paper, we consider the ordering and payment issues for a retailer facing stochastic demand. We assume that the retailer can enjoy the partial trade credit from his supplier and borrow money from bank as well if needed, and he can also earn return by investing his superfluous on-hand cash (if any). The retailer’s objective is to maximize the expected cash level at the end of the selling period. We formulate the model of this problem by taking initial inventory and capital levels as the two-dimensional state. First, given the exogenous fraction of immediate payment, we show that unlike the critical fractile solution the retailer’s optimal ordering strategy is a two-threshold policy, which is independent of the retailer’s initial inventory level and capital level. Second, we consider an extensive model where the fraction of immediate payment is decided by the retailer. We employ the sequential optimization procedure to solve the extensive problem, and present the structure of the retailer’s optimal policies under different partial-trade-credit penalty rates. Numerical experiments show that if the fraction of immediate payment is exogenous, both partial trade credit and loan opportunity are detrimental to the capital-constrained retailer in many cases, although they can stimulate the retailer to order more.     

风险规避型双渠道供应链的融资和定价决策

在零售商资金约束下,基于CVaR准则构建了风险规避的供应商和零售商组成的双渠道供应链的定价模型。分析了零售商资金充足时,供应商和零售商的最优决策、资金约束情况下零售商的银行借贷融资、延期支付策略和组合融资时零售商和供应商的最优决策以及零售商和供应商的风险规避程度对最优决策变量和收益的影响。通过数值分析,进一步验证了零售商和供应商的风险规避度对三种融资模式下零售商和供应商的最优决策变量和利润的影响。研究表明：资金充足和延期支付策略下最优决策变量与风险规避度的关系一致;银行借贷和组合融资下最优决策变量与风险规避度的关系一致;单一延期支付策略和组合融资优于单一银行借贷融资;组合融资比例大于一定值时,优于单纯延期支付策略。     

Capital injections with negative surplus and delays: models and analysis

This work develops a new model to deal with the scenario that some companies can still run business even the surplus falls below zero temporarily. With such a scenario in mind, we allow the surplus process to continue in this negative-surplus period, during which capital injections will be ordered to assist in the stabilization of financial structure, until the financial status becomes severe enough to file bankruptcy. The capital injections will be modeled as impulse controls. By introducing the capital injections with time delays, optimal dividend payment and capital injection policies are considered. Using the dynamic programming approach, the value function obeys a quasi-variational inequality. With delays in capital injections, the company will be exposed to the risk of bankruptcy during the delay period. In addition, the optimal dividend payment and capital injection strategies should balance the expected cost of the possible capital injections and the time value of the delay periods. This gives rise to a stochastic control problem with mixed singular and delayed impulse controls. Under general assumptions, the lower capital injection barrier is determined, where bankruptcy occurs. The closed-form solution to the value function and corresponding optimal policies are obtained.     

The supplier's optimal guarantee policy in newsvendor finance

The retailer is a capital‐constrained newsvendor and can borrow money from the bank if necessary. To help the retailer get a bank loan at a lower interest rate, the supplier provides guarantee for the retailer's loan up to a prespecified amount. In a Stackelberg game, the supplier decides the wholesale price and the guarantee amount as a leader, and then the retailer determines the order quantity and the amount of the loan as a follower. The supplier is risk‐neutral while the retailer's risk preference is reflected by a spectral risk measure (risk‐neutral, risk‐averse, or risk‐seeking). For a given wholesale price and guarantee amount, the retailer's objective function is quasi‐concave in the order quantity. The optimal solutions for the supplier and the retailer are derived. The supplier's expected profit with optimized wholesale price increases with the guarantee amount, and thus the supplier's optimal policy is to provide a full guarantee for the retailer's loan. When the supplier can limit his guarantee responsibility by a proportion of the outstanding loan obligation, the supplier's optimal policy is also to provide a full guarantee. Even if the retailer incurs bankruptcy costs in the event of repayment default, the supplier's optimal guarantee policy remains the same in these two different forms of limited guarantee. However, when the wholesale price is exogenous, that is, not a decision variable, the full guarantee is not necessarily optimal for supplier.     

Determination of Loan Interest Rate Considering Bankruptcy and Mortgage Collection Costs

Particularly in Japan, risk management relating to bankruptcy of financed enterprises has become very important to a bank after the collapse of a bubble economy. To obtain suitable revenues, a bank has to apply high interest rates to the enterprises with high risk. When enterprises which have made a secure loan from a bank go bankrupt, a bank forecloses such enterprises from its mortgage to recover the loss incurred. However, in actual circumstances, it may need much cost and effort to do so in Japan. This paper proposes a stochastic model to determine an adequate interest rate, taking account of the probabilities of bankruptcy and mortgage collection, and their costs. Numerical examples are given to illustrate this model and a loan interest rate is determined.     

Financing strategies for a capital‐constrained manufacturer in a dual‐channel supply chain

This study investigates a co‐opetition‐type dual‐channel supply chain that consists of a competitive supplier (CS) and a capital‐constrained manufacturer (CCM). The CCM procures key components from and simultaneously competes with the CS in the consumer market. To address the CCM's capital constraint, we consider three financing strategies, namely, trade credit, bank loan, and hybrid financing (i.e., combined use of bank loan and equity financing). Game models are established to characterize the interactions between the CS and CCM. The corresponding equilibria are derived under each strategy. Then, comparative analyses are conducted, and the CS's and CCM's preference structures regarding the three strategies are revealed. On this basis, the equilibrium strategy can be concluded as either trade credit or hybrid financing, but never bank loan. Specifically, when the equity financing ratio is small or large, trade credit is an equilibrium strategy. When the equity financing ratio is medium, the equilibrium strategy between trade credit and hybrid financing is determined by consumers’ product preference and loan interest rate.     

Multi–objective Evolutionary Algorithms for the Risk–return Trade–off in Bank Loan Management

Multi–criteria decision–making is an increasingly accepted tool for decision–making in management. In this work, we highlight the application of a novel multi–objective evolutionary algorithm, NSGA–II, to the risk–return trade–off for a bank–loan portfolio manager. The manager of a bank operating in a competitive environment faces the standard goal of maximizing shareholder wealth. Specifically, this attempts to maximize the net worth of the bank, which in turn involves maximizing the net interest margin of the bank (among other factors, such as non–interest income). At the same time, there are significant regulatory constraints placed on the bank, such as the maintenance of adequate capital, interest–rate risk exposure, etc. The genetic algorithm–based technique used here obtains an approximation to the set of Pareto–optimal solutions which increases the decision flexibility available to the bank manager, and provides a visualization tool for one of the trade–offs involved. The algorithm is also computationally efficient and is contrasted with a traditional multi–objective function — the epsilon–constraint method.     

Dynamic Network Model of Managing Investment Portfolio under Random Stepwise Changes in Volatilities of Financial Assets

The problem of managing a portfolio of risk (ordinary shares) and no-risk (bank account, reliable bonds) investments was considered. The portfolio model was described in the state space by a system of stochastic differential (or difference) equations with random stepwise parameters. Management of the investment portfolio was formulated as a dynamic problem of tracking some reference portfolio with an investor-defined yield. An approach to determining the optimal management strategy with quadratic criterion-based feedback was proposed. Results of numerical modeling were presented.