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Quantifying Systemic Risk Using Bayesian Networks 使用贝叶斯网络量化系统风险
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-26 DOI: 10.2139/ssrn.3525739
Sumit Sourabh, Markus Hofer, D. Kandhai
{"title":"Quantifying Systemic Risk Using Bayesian Networks","authors":"Sumit Sourabh, Markus Hofer, D. Kandhai","doi":"10.2139/ssrn.3525739","DOIUrl":"https://doi.org/10.2139/ssrn.3525739","url":null,"abstract":"We develop a novel framework using Bayesian networks to capture distress dependence in the context of counterparty credit risk. This allows us to calibrate the probability of distress of an entity conditional on the distress of a different entity. We apply our methodology to wrong-way risk model proposed by Turlakov and stress scenario testing. Our results show that stress propagation in an interconnected financial system can have a significant impact on counterparty credit exposures.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76329817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Research on Listed Companies’ Credit Ratings, Considering Classification Performance and Interpretability 考虑分类绩效和可解释性的上市公司信用评级研究
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-09 DOI: 10.21314/JRMV.2020.232
Zhe Li, Guotai Chi, Ying Zhou, Wenxuan Liu
{"title":"Research on Listed Companies’ Credit Ratings, Considering Classification Performance and Interpretability","authors":"Zhe Li, Guotai Chi, Ying Zhou, Wenxuan Liu","doi":"10.21314/JRMV.2020.232","DOIUrl":"https://doi.org/10.21314/JRMV.2020.232","url":null,"abstract":"Any credit evaluation system must be able not only to identify defaults, but also to be interpretable and provide reasons for defaults. Therefore, this study uses the correlation coefficient and F -test to select the initial features of a credit evaluation system, and then a validity index for a second selection to ensure that the feature system has the optimum ability to discriminate in determining default status. We omit one feature in each iteration by replacing each feature, calculating the changes in validity index values after deleting this feature and, finally, calculating the ratio of the change value to the sum of all change values. This ratio is then used as the feature’s weight. This study also introduces a data gravity model in predicting defaults, as predicting a validation set’s default status derives the classification threshold to maximize classification accuracy. An empirical analysis of the listed company samples reveals that the feature system selected from 610 features can distinguish between both defaults and nondefaults. Compared with eight other models, our data gravity model not only exhibits good classification performance, but also has interpretability; further, this model can provide at least five-year-ahead forecasting, and can offer a timely risk warning for banks.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90738605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Overnight Indexed Swap-Implied Interest Rate Expectations 隔夜指数掉期隐含利率预期
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-08 DOI: 10.1016/j.frl.2020.101430
Simon P. Lloyd
{"title":"Overnight Indexed Swap-Implied Interest Rate Expectations","authors":"Simon P. Lloyd","doi":"10.1016/j.frl.2020.101430","DOIUrl":"https://doi.org/10.1016/j.frl.2020.101430","url":null,"abstract":"","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76104606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Separating Information about Cash Flows from Information about Risk in Losses 将现金流量信息与损失风险信息分离
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-06 DOI: 10.2139/ssrn.2197550
Bin Li
{"title":"Separating Information about Cash Flows from Information about Risk in Losses","authors":"Bin Li","doi":"10.2139/ssrn.2197550","DOIUrl":"https://doi.org/10.2139/ssrn.2197550","url":null,"abstract":"Prior literature interprets the weak earnings response coefficient (ERC) of accounting losses as a manifestation either of lack of forward-looking information in losses or of market mispricing of losses. Based on return decomposition theory, I predict that losses contain information not only about future cash flows (i.e., cash flow news) but also, about risk (i.e., expected returns and discount rate news). However, these informational components have offsetting valuation effects, resulting in a muted ERC. Consistent with the prediction, I show that, after controlling for information about risk (mainly expected returns), the ERC of losses becomes statistically significant with more negative returns for larger losses when returns are measured either annually or around earnings announcements. Moreover, loss firms will continue to have poor future earnings and operating cash flows, and larger losses are associated with more negative analyst forecast revisions in the loss-reporting year. I also document that losses provide more negative cash flow information when they are not because of research and development expensing, when they trigger operational curtailments, and when they are less likely to reverse to profits. Further tests confirm the robustness of my findings to considering future return drifts/reversals, alternative proxies for expected returns and discount rate news, alternative test portfolios, and alternative model specifications. Overall, my paper provides new insights into the information content of losses. This paper was accepted by Suraj Srinivasan, accounting.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86419357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
On Sources of Risk Premia in Representative Agent Models 代表性代理模型中风险溢价的来源研究
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-01 DOI: 10.2139/ssrn.3452743
Tyler Beason, David Schreindorfer
{"title":"On Sources of Risk Premia in Representative Agent Models","authors":"Tyler Beason, David Schreindorfer","doi":"10.2139/ssrn.3452743","DOIUrl":"https://doi.org/10.2139/ssrn.3452743","url":null,"abstract":"We use options and return data to decompose unconditional risk premia into different parts of the return state space. In the data, the entire equity premium is attributable to monthly returns below -11.3%, but returns in the extreme left tail matter very little. In contrast, leading asset pricing models based on habits, long-run risks, and rare disasters attribute the premium almost exclusively to returns above -11.3%, or to the extreme left tail. We find that model extensions with a larger quantity of tail risk cannot account for the data, while models with a higher price of tail risk can.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79499730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market 已实现贝塔值的持久性:西班牙股市的一些证据
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-01 DOI: 10.2139/ssrn.3564876
G. Caporale, L. Gil‐Alana, M. Martin-Valmayor
{"title":"Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market","authors":"G. Caporale, L. Gil‐Alana, M. Martin-Valmayor","doi":"10.2139/ssrn.3564876","DOIUrl":"https://doi.org/10.2139/ssrn.3564876","url":null,"abstract":"This paper examines the stochastic behaviour of the realized betas within the one-factor CAPM for the six companies with the highest market capitalization included in the Spanish IBEX stock market index. Fractional integration methods are applied to estimate their degree of persistence at the daily, weekly and monthly frequency over the period 1 January 2000 – 15 November 2018 using 1, 3 and 5-year samples. On the whole, the results indicate that the realized betas are highly persistent and do not exhibit mean-reverting behaviour. However, the findings are rather sensitive to the choice of frequency and time span (number of observations).","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88824596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Risk Premium Shocks Can Create Inefficient Recessions 风险溢价冲击可能造成低效衰退
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2020-01-01 DOI: 10.3386/w26721
Sebastian Di Tella, R. Hall
{"title":"Risk Premium Shocks Can Create Inefficient Recessions","authors":"Sebastian Di Tella, R. Hall","doi":"10.3386/w26721","DOIUrl":"https://doi.org/10.3386/w26721","url":null,"abstract":"\u0000 We develop a simple flexible-price model of business cycles driven by spikes in risk premiums. Aggregate shocks increase firms’ uninsurable idiosyncratic risk and raise risk premiums. We show that risk shocks can create quantitatively plausible recessions, with contractions in employment, consumption, and investment. Business cycles are inefficient—output, employment, and consumption fall too much during recessions, compared to the constrained-efficient allocation. Optimal policy involves stimulating employment and consumption during recessions.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80607520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
The Early Exercise Risk Premium 早期运动风险溢价
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2019-12-21 DOI: 10.2139/ssrn.3465453
K. Aretz, A. Gazi
{"title":"The Early Exercise Risk Premium","authors":"K. Aretz, A. Gazi","doi":"10.2139/ssrn.3465453","DOIUrl":"https://doi.org/10.2139/ssrn.3465453","url":null,"abstract":"We study the asset pricing implications of being able to optimally early exercise a plain-vanilla put option, contrasting the expected returns of equivalent American and European put options. Standard pricing models with stochastic volatility and asset-value jumps suggest the expected return spread between those option types is positive, can be economically sizable, and widens with a higher early exercise probability, as induced through a higher moneyness, shorter time-to-maturity, or lower underlying-asset volatility. Studying single-stock American put options and equivalent synthetic European options formed from applying put-call parity to American call options on zero-dividend stocks, our empirical work supports our predictions.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76393735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Data Snooping in Equity Premium Prediction 股票溢价预测中的数据窥探
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2019-11-24 DOI: 10.2139/ssrn.2972011
H. Dichtl, W. Drobetz, A. Neuhierl, Viktoria-Sophie Wendt
{"title":"Data Snooping in Equity Premium Prediction","authors":"H. Dichtl, W. Drobetz, A. Neuhierl, Viktoria-Sophie Wendt","doi":"10.2139/ssrn.2972011","DOIUrl":"https://doi.org/10.2139/ssrn.2972011","url":null,"abstract":"Abstract We analyze the performance of a comprehensive set of equity premium forecasting strategies. All strategies were found to outperform the mean in previous academic publications. However, using a multiple testing framework to account for data snooping, our findings support Welch and Goyal (2008) in that almost all equity premium forecasts fail to beat the mean out-of-sample. Only few forecasting strategies that are based on Ferreira and Santa-Clara’s (2011) sum-of-the-parts approach generate robust and statistically significant economic gains relative to the historical mean even after controlling for data snooping and accounting for transaction costs.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79026250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Inf-convolution and Optimal Allocations for Tail Risk Measures 尾部风险测度的卷积与最优分配
Econometric Modeling: Capital Markets - Risk eJournal Pub Date : 2019-11-19 DOI: 10.2139/ssrn.3490348
Fangda Liu, Tiantian Mao, Ruodu Wang, Linxiao Wei
{"title":"Inf-convolution and Optimal Allocations for Tail Risk Measures","authors":"Fangda Liu, Tiantian Mao, Ruodu Wang, Linxiao Wei","doi":"10.2139/ssrn.3490348","DOIUrl":"https://doi.org/10.2139/ssrn.3490348","url":null,"abstract":"Inspired by the recent developments in risk sharing problems for the Value-at-Risk (VaR), the Expected Shortfall (ES), or the Range-Value-at-Risk (RVaR), we study the optimization of risk sharing for general tail risk measures. Explicit formulas of the inf-convolution and Pareto-optimal allocations are obtained in the case of a mixed collection of left and right VaRs, and in that of a VaR and another tail risk measure. The inf-convolution of tail risk measures is shown to be a tail risk measure with an aggregated tail parameter, a phenomenon very similar to the cases of VaR , ES and RVaR. Optimal allocations are obtained in the setting of elliptical models,<br>and several results are established for tail risk measures and risk sharing problems in the presence of model uncertainty. The technical conclusions are quite general without assuming any form of convexity of the tail risk measures. Our analysis generalizes in several directions the recent literature on quantile-based risk sharing.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83699542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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