Portfolios in the Ibex 35 before and after the Global Financial Crisis

Adame, Víctor M.; Rodríguez, Fernando Fernández; Sosvilla‐Rivero, Simón

doi:10.1080/00036846.2016.1145352

Cited by 5 publications

(4 citation statements)

References 57 publications

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“…Our findings are in line with those of Kirby and Ostdiek (2012) and Allen et al (2014b) for the hedge fund index, as well as the results reported by Adame et al (2016) in a similar study for the main Spanish stock index (Ibex 35). Thus, although in all empirical works the results obtained have to be taken with some degree of caution (since they are based on a particular index over a certain time period), our findings lead us to infer that the naive strategy of 1/N can provide good results if it is compared with the benchmark.…”

Section: Discussionsupporting

confidence: 94%

“…It should be noted that there exists an ongoing debate in the literature on whether the gains from optimization are reduced by estimation errors or uncertainty in the parameters, which influence in the portfolio optimization process. In this sense, there is no consensus in the literature on whether the naive diversification is more effective than other portfolio strategies, specially when there are not short-selling constraints (see recent contributions in this area, such as Tu and Zhou, 2011;Kirby and Ostdiek, 2012;Allen et al, 2014a, 2014band Adame et al, 2016.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Resolution of Optimization Problems and Construction of Efficient Portfolios: An Application to the Euro Stoxx 50 Index

2017

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Section: Discussionsupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Resolution of Optimization Problems and Construction of Efficient Portfolios: An Application to the Euro Stoxx 50 Index

2017

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“…Thirdly, CVaR is able to show excess losses. Fourth, CVaR has good computational properties [8]. Fifth, CVaR is easier to quantify than the other two methods [9].…”

Section: Literature Review 21 Supply Chain Finance and Risk Measureme...mentioning

confidence: 99%

Research on Decision Analysis with CVaR for Supply Chain Finance Based on Blockchain Technology

Ma,

Cai,

Wang

et al. 2024

Mathematics

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The application of blockchain has become a trend in the development of supply chain finance. Aiming to bridge the gap in the existing literature, this paper investigates a supply chain finance system based on blockchain technology which contains a manufacturer, a retailer and a financial institution and incorporates blockchain costs into the model. Firstly, this paper establishes a supply chain finance model based on blockchain technology and it presents a comparison with the process employed under the traditional model. Secondly, this paper establishes the revenue mathematical model of supply chain finance based on blockchain technology. Thirdly, the optimal decisions of each participant under centralized and decentralized decision-making are proved and obtained, respectively, and the influencing factors of the optimal decisions are analyzed. Finally, the conclusions are verified via simulations. This study finds that, when blockchain is used, the benefits of each participant in the chain are increased. In addition, centralized decision-making, which is more optimal in the traditional model, is also enhanced under blockchain. This paper demonstrates the superiority of blockchain-enabled supply chain finance in terms of model and revenue. This provides some suggestions for companies in the supply chain with regard to solving the problem of financing difficulties.

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“…VaR has also been criticized in recent years for some undesirable characteristics such as a lack of subadditivity and convexity. In addition, VaR is not a coherent risk measure (Artzner, Delbaen, Eber, & Heath, 1999) and it cannot measure the nature of extreme losses exceeding it (Lim, Shanthikumar, & Vahn, 2011;Adame, Fernando, & Simon, 2016).…”

Section: Risk Aversion Measurementmentioning

confidence: 99%

Optimal Financing Models Offered by Manufacturers with Risk Aversion and Market Competition Considerations

Liu

Feng

et al. 2020

Decision Sciences

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Trade credit finance (TCF), retailer independent finance (RIF), and partial credit guarantee (PCG) finance are all important financing tools for capital‐constrained retailers. Risk aversion has a significant impact on financing, but it is difficult to measure. This research investigates the manufacturer's financing provision strategies considering risk aversion and capital market competition. First, an ordinary least squares method with conditional value at risk criteria is proposed to measure the risk attitude of decision‐makers. Second, the equilibrium mode of financing provision and impacts of risk aversion and the retailer's initial capital are analyzed. Third, a laboratory experiment and numerical analysis are conducted to verify the risk aversion estimation method and other theoretical results. We draw the following conclusions. First, the equilibrium financing provision mode changes with the degree of risk aversion and retailer's initial capital. Although the manufacturer prefers TCF and PCG to RIF, the retailer chooses the RIF mode when its initial capital is low. A variable parameter guarantee mechanism is proposed to encourage more retailers to choose PCG instead of RIF. Second, the risk‐averse financing system realizes super‐centralization (i.e., utility in the decentralized system is larger than that in the centralized system) when the manufacturer is less risk averse than the other participants. A Pareto‐optimality mechanism is designed to realize super‐centralization and coordinate the decentralized financing system. This research provides financing providers with practical guidance on the efficient implementation of supply chain financing.

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Portfolios in the Ibex 35 before and after the Global Financial Crisis

Cited by 5 publications

References 57 publications

Resolution of Optimization Problems and Construction of Efficient Portfolios: An Application to the Euro Stoxx 50 Index

Resolution of Optimization Problems and Construction of Efficient Portfolios: An Application to the Euro Stoxx 50 Index

Research on Decision Analysis with CVaR for Supply Chain Finance Based on Blockchain Technology

Optimal Financing Models Offered by Manufacturers with Risk Aversion and Market Competition Considerations

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