The equity risk posed by the too-big-to-fail banks: a Foster–Hart estimation

Anand, Abhinav; Li, Tiantian; Kurosaki, Tetsuo; Kim, Young S.

doi:10.1007/s10479-016-2309-y

Cited by 14 publications

(9 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the minimum has a small estimate and a low t-value. This implies the FH performance measure is not sensitive to the maximal loss or the rare disaster, which has been used as the value of the FH extended riskiness or performance measure in some previous studies (cf., Kadan and Liu 2014;Anand et al 2016Anand et al , 2017Riedel and Hellmann 2015). This is evidence that the FH performance is more sensitive to losses of the underlying financial target compared to the AS performance measure but not excessively determined by the maximal loss.…”

Section: Discussionmentioning

confidence: 77%

“…Therefore, the FH performance measure is virtually determined by disaster risk or maximal loss. Hence, it is the most sensitive measure to disaster risk, which conforms to the previous studies of the FH performance measure (cf., Foster and Hart 2009;Kadan and Liu 2014;Anand et al 2016Anand et al , 2017Riedel and Hellmann 2015). Hence, the newly introduced performance measures of the AS and FH performance measures are both quite sensitive to losses of the underlying random variable.…”

Section: Numerical Examples Of the Performance Measuresmentioning

confidence: 99%

“…Miyahara 2014;Ban et al 2016;Hodoshima 2019). The FH performance measure is also known to be extremely sensitive to rare disasters or maximal loss (cf., Foster and Hart 2009;Kadan and Liu 2014;Anand et al 2016Anand et al , 2017Riedel and Hellmann 2015). We address the issue of sensitivity of the AS and FH performance measures to disaster risk in this study.…”

Section: Introductionmentioning

confidence: 99%

“…Kadan and Liu (2014) also remarked the FH performance measure is extremely sensitive to the maximal loss by considering a composite gamble with a small probability of a large loss, i.e., Proposition 8 of Kadan and Liu (2014). Anand et al (2016) and Anand et al (2017) use as the FH risk measure the extended FH risk given by Riedel and Hellmann (2015) for gambles with continuous distribution. In other words, Riedel and Hellmann (2015) extended the FH risk measure for a gamble with continuous distribution by the maximum loss L, i.e.,…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Sensitivity of Performance Indexes to Disaster Risk

Hodoshima

Yamawake

2021

Risks

View full text Add to dashboard Cite

We examine how sensitive the new performance indexes incorporating high moments and disaster risk are to disaster risk. The new performance indexes incorporating high moments and disaster risk are the Aumann-Serrano performance index and Foster-Hart performance index proposed by Kadan and Liu. These performance indexes provide evaluations sensitive to the underlying risk. We show, by numerical examples and empirical examples, how sensitive these indexes are to disaster risk. Although these indexes are known to be either quite sensitive or excessively sensitive to disaster risk or maximum loss in the literature, we show by the regression analysis of the index and summary statistics these indexes are in fact not excessively sensitive to maximum loss in representative stock data, which contain disastrous observations. The numerical estimate of the Foster-Hart performance index is found to be effective in showing the performance index. Our analysis suggests these indexes can handle various empirical data containing quite disastrous observations.

show abstract

Section: Discussionmentioning

confidence: 77%

Section: Numerical Examples Of the Performance Measuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sensitivity of Performance Indexes to Disaster Risk

Hodoshima

Yamawake

2021

Risks

View full text Add to dashboard Cite

show abstract

“…One way to approach this would be to employ historical return distributions, possibly in combination with a dynamic model as, for example, in Anand et al (2015). We, by contrast, extract risk-neutral densities from the information contained in call and put option prices written on the S&P 500 stock index.…”

mentioning

confidence: 99%

Option-implied objective measures of market risk

Leiss

Nax

2018

Journal of Banking & Finance

View full text Add to dashboard Cite

Foster and Hart (2009) introduce an objective measure of the riskiness of an asset that implies a bound on how much of one's wealth is 'safe' to invest in the asset while (a.s.) guaranteeing no-bankruptcy in the long run. In this study, we translate the Foster-Hart measure from static and abstract gambles to dynamic and applied finance using nonparametric estimation of risk-neutral densities from S&P 500 call and put option prices covering 2003 to 2013. This exercise results in an option-implied market view of objective riskiness. The dynamics of the resulting 'option-implied Foster-Hart bound' are analyzed and assessed in light of well-known risk measures including value at risk, expected shortfall and risk-neutral volatility. The new measure is shown to be a significant predictor of ahead-return downturns. Furthermore, it is able to grasp more characteristics of the risk-neutral probability distributions than other measures, furthermore exhibiting predictive consistency. The robustness of the risk-neutral density estimation method is analyzed via a bootstrap.

show abstract

Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model

Kim

2022

Ann Oper Res

View full text Add to dashboard Cite

The equity risk posed by the too-big-to-fail banks: a Foster–Hart estimation

Cited by 14 publications

References 22 publications

Sensitivity of Performance Indexes to Disaster Risk

Sensitivity of Performance Indexes to Disaster Risk

Option-implied objective measures of market risk

Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model

Contact Info

Product

Resources

About