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| 2. |
- Luo, Cuicui, et al.
(författare)
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A deep learning approach for credit scoring using credit default swaps
- 2017
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Ingår i: Engineering applications of artificial intelligence. - : Elsevier BV. - 0952-1976 .- 1873-6769. ; 65, s. 465-470
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Tidskriftsartikel (refereegranskat)abstract
- After 2007-2008 crisis, it is clear that corporate credit scoring is becoming a key role in credit risk management. In this paper, we investigate the performances of credit scoring models applied to CDS data sets. The classification performance of deep learning algorithm such as deep belief networks with Restricted Boltzmann Machines are evaluated and compared with some popular credit scoring models such as logistic regression, multi-layer perceptron and support vector machine. The performance is assessed using the classification accuracy and the area under the receiver operating characteristic curve. It is found that DBN yields the best performance.
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| 3. |
- Wu, Dexiang, et al.
(författare)
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A decision support approach for two-stage multi-objective index tracking using improved lagrangian decomposition
- 2020
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Ingår i: Omega. - : Elsevier BV. - 0305-0483 .- 1873-5274. ; 91
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Tidskriftsartikel (refereegranskat)abstract
- We present a decision support approach for a network structured stochastic multi-objective index tracking problem in this paper. Due to the non-convexity of this problem, the developed network is modeled as a Stochastic Mixed Integer Linear Program (SMILP). We also propose an optimization-based approach to scenario generation to protect against the risk of parameter estimation for the SMILP. Progressive Hedging (PH), an improved Lagrangian scheme, is designed to decompose the general model into scenario based sub-problems. Furthermore, we innovatively combine tabu search and the sub-gradient method into PH to enhance the tracking capabilities of the model. We show the robustness of the algorithm through effectively solving a large number of numerical instances.
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| 4. |
- Wu, Dexiang, et al.
(författare)
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A Robust Decision Support Approach to Portfolio Risk Reduction Based on Credit Default Swap
- 2018
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Ingår i: Journal of Fixed Income. - : Pageant Media US. - 1059-8596 .- 2168-8648. ; 27:3, s. 86-95
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Tidskriftsartikel (refereegranskat)abstract
- We construct portfolios from the credit default swap (CDS) market by incorporating cardinality and solvency constraints into mean-variance and conditional value at risk (CVaR) models. Cardinality constraints are applied to limit the portfolio size and improve the allocation structure, while the solvency constraint is used to insulate the default risks of the portfolios under worst scenarios. CDS-based portfolios involve uncertainties that stem from spread changing and jump-to-default volatilities. We show that these uncertainties can be identified and managed using our developed systematic approach. Market data analysis from the CDS portfolios shows that using cardinality constraints reduces counterparty risks significantly. The proposed cardinality constrained CVaR model has robust performance in terms of the portfolio Sharpe ratio and one other metric, and also generally outperforms the associated mean-variance strategy.
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| 5. |
- Wu, Dexiang, et al.
(författare)
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An enhanced decision support approach for learning and tracking derivative index
- 2019
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Ingår i: Omega. - : Elsevier BV. - 0305-0483 .- 1873-5274. ; 88, s. 63-76
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Tidskriftsartikel (refereegranskat)abstract
- Tracking the movement of an index involves the parameter learning from data and algorithm design for solving the decision model. In this paper, we present a factor induced robust index tracking model to protect against the parameter estimation error and immunize both systematic and default risks of tracking portfolios. A Lagrangian-based algorithm is applied to approximate optimal solutions and enhance the capacity of the decision model. Two types of inequalities are derived to strengthen the Lagrangian lower bound and speed up the whole Lagrangian Relaxation (LR) method. With the designed system, we investigate large Credit Default Swap (CDS) dataset that includes 1246 daily observations across near 500 individual contracts. We show that the fluctuation range of portfolio out-of-sample returns can be shrunk significantly by using the proposed robust counterpart, e.g. from [-12%, 12%] to [-4%, 4%] in the second half of 2013, and other comparison metrics such as Sharpe ratio and tracking error to transaction costs (TE/TC) ratio could also be consistently improved.
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| 6. |
- Wu, Dexiang, et al.
(författare)
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Credit risk control and management using limited diversification
- 2021
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Ingår i: Journal of Risk Research. - : Informa UK Limited. - 1366-9877 .- 1466-4461. ; 24:8, s. 958-971
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Tidskriftsartikel (refereegranskat)abstract
- The diversified strategy can reduce the systematic risk efficiently, but may fail to account for emergent and default risk that many decision-makers usually face at large-scale level. Modern data-driven methodologies allow optimizing both systematic and non-systematic risks in a unified framework. In this article, we demonstrate an approach to analyze and compare partial-diversified portfolios of Credit Default Swap. We classify and investigate different metrics of credit risks and integrate them with limited diversification and other performance objectives. We test the developed approach in a study of hundreds of business contract investments over the recent financial crisis. The results indicate that the decisions using limited diversification are more robust in terms of allocation structure and out-of-sample downside risks reduction. Therefore, the partial-diversified optimization models provide alternatives to support a variety of problems involving unknown risks.
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| 7. |
- Wu, Dexiang, et al.
(författare)
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Optimising data-driven network under limited resource : a partial diversification approach
- 2019
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Ingår i: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; 57:21, s. 6875-6892
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Tidskriftsartikel (refereegranskat)abstract
- This paper describes a cardinality constrained network flow structure whose special characteristics are used to analyse different risk aspects under an environment of uncertainty. The network structure developed is a suitable alternative to support financial planning and many other decision-making problems with limited resources. By setting a diversification level, we can manage systematic and non-systematic risks under a stochastic mixed integer linear programming framework. A dual decomposition method, Progressive Hedging (PH), is applied to more efficiently accommodate instances with large numbers of scenarios. We studied the impact of the level of the diversification on transaction costs and considered different factors that influence the performance of the algorithm. In particular, a Lagrangian bound is embedded to enhance the capacity of the method. Numerical results show the effectiveness of the proposed decision support approach.
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| 8. |
- Baron, Opher, et al.
(författare)
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Bargaining within the Supply Chain and Its Implications in an Industry
- 2016
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Ingår i: Decision Sciences. - : Wiley. - 0011-7315 .- 1540-5915. ; 47:2, s. 193-218
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Tidskriftsartikel (refereegranskat)abstract
- Our main objective is to investigate the influence of the bargaining power within a chain on its industry. As a building block, we first discuss the implications of bargaining within a single chain by considering an asymmetric Nash bargaining over the wholesale price (BW). We show that both Manufacturer Stackelberg (MS) and vertical integration (VI) strategies are special cases of the BW contract. We then develop the Nash equilibrium in an industry with two supply chains that use BW. We identify the profit-maximizing (coordinating) bargaining power within this industry. We show that when a chain is not monopolistic, VI does not coordinate the chain and that the MS contract, where the manufacturer has all the bargaining power, is coordinating when competition is intense. We find that the main determinant of the equilibrium in mature industries is to respond well to the actions of the competing chain rather than to directly maximize the profit of each chain. That is, the equilibrium does not necessarily maximize the profit of the entire industry. While a coordination of the industry could then increase the profitability of both chains, such a coordination is likely against antitrust law. Moreover, if one chain cannot change its actions, the other chain may unilaterally improve its profitability by deviating from the equilibrium. Our results lead to several predictions supported by empirical findings, such as that in competitive industries chains will work close to the MS contract.
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| 9. |
- Cao, Yuan, et al.
(författare)
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Debt risk analysis of non-financial corporates using two-tier networks
- 2020
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Ingår i: Industrial management & data systems. - 0263-5577 .- 1758-5783. ; 120:7, s. 1287-1307
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Tidskriftsartikel (refereegranskat)abstract
- Purpose Non-financial corporate debt is one of the important sources of systematic risk in the real economy. Assessing a measure of systematic risk in corporation debt is currently a key challenge. In this regard, we propose a two-tier risk contagion networks model. Design/methodology/approach Assessing a measure of systematic risk in corporation debt is currently a key challenge. In this regard, we propose a two-tier risk contagion networks model based on four dimensions: concept definition, data structure, risk contagion network construction, and risk measurement indicators construction. We take the Jiangsu bond issuer guarantee network as a sample area. Findings Taking the Jiangsu bond issuer guarantee network as a sample area, we find that there is a strong correlation between the debts of non-financial corporation in China, and it is easy to become a potential regional systematic risk source. In addition, our empirical research also reveals that external risk exposure and node degree of network are two key indicators when identifying key risk-contagion enterprises. Originality/value The main contributions of this study are two-fold. First, this article proposes a two-tier risk contagion networks model to measure systematic risk in non-financial corporation. Second, this article describes the structure of the corporate risk contagion network.
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| 10. |
- Chai, Limeng, et al.
(författare)
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Pricing strategy for B&M store in a dual-channel supply chain based on hotelling model
- 2021
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Ingår i: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; 59:18, s. 5578-5591
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Tidskriftsartikel (refereegranskat)abstract
- We use hotelling model to analyse store brands as a strategy for B&M (brick-and-mortar) retailers to combat showrooming. We investigate how national-brand product mismatch and store-brand awareness affect supply chain's performance. We reach four major conclusions. First, store-brand strategy may be an effective means for B&M stores to mitigate showrooming. However, it's better to introduce premium store brands. Second, the B&M store's profit grows - and the online store's profit declines - as national-brand product mismatch increases in breadth. When many consumers feel the national-brand product does not match their needs, a product positioning strategy for the store brand can help B&M retailers improve profit margins. Third, as national-brand product mismatch increases in depth, the B&M store's profit rises and online store's profit falls. If national-brand products lack many features that consumers need, a product differentiation strategy can be implemented to use store brands to fill in the gaps left by national brands. Finally, the growth of store-brand awareness will not necessarily benefit the B&M store. The impact of store-brand awareness on the B&M store's profit depends on the hassle cost factort, and a brand promotion strategy will reduce the loss of B&M retailer's profit.
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