I propose a novel framework to quantify frequency-dependent risks in the factor zoo. Empirically, the linear stochastic discount factor (SDF) comprised of the first few low-frequency principal components (PCs) yields an out-of-sample monthly Sharpe ratio of 0.37, and other smaller low-frequency PCs are redundant. In contrast, the SDFs consisting of high-frequency and canonical PCs are dense and fail to identify slow-moving conditional information in asset returns. Moreover, I decompose the low-frequency SDF into two orthogonal priced components. The first component, linear in high-frequency PCs, is almost serially uncorrelated and relates to discount-rate news, intermediary factors, jump risk, and investor sentiment. The second component exhibits a persistent conditional dynamic and captures business-cycle risks related to consumption and GDP growth. Overall, asset pricing theory has frequency-dependent relevance.
{"title":"Frequency Dependent Risks in the Factor Zoo","authors":"Jiantao Huang","doi":"10.2139/ssrn.3948519","DOIUrl":"https://doi.org/10.2139/ssrn.3948519","url":null,"abstract":"I propose a novel framework to quantify frequency-dependent risks in the factor zoo. Empirically, the linear stochastic discount factor (SDF) comprised of the first few low-frequency principal components (PCs) yields an out-of-sample monthly Sharpe ratio of 0.37, and other smaller low-frequency PCs are redundant. In contrast, the SDFs consisting of high-frequency and canonical PCs are dense and fail to identify slow-moving conditional information in asset returns. Moreover, I decompose the low-frequency SDF into two orthogonal priced components. The first component, linear in high-frequency PCs, is almost serially uncorrelated and relates to discount-rate news, intermediary factors, jump risk, and investor sentiment. The second component exhibits a persistent conditional dynamic and captures business-cycle risks related to consumption and GDP growth. Overall, asset pricing theory has frequency-dependent relevance.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114654297","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}
This study investigates irreversible investment decisions when the exercise payoff is scale-dependent; thus, it is endogenously determined by the firm's risk management. We find that the scale-dependency gives rise to a speculative risk management strategy: a positive relationship between the firm's derivatives position and unhedged cash flow. Moreover, investment can be hastened or delayed as the underlying uncertainty increases depending on the economic conditions due to the speculative strategy. The main force driving these results, different from those known in the existing literature, is that the firm's risk management is designed to optimize the risk-return trade-off of the endogenous payoff.
{"title":"Valuing Real Options with Scale-dependent Payoff","authors":"Kyoung Jin Choi, Minsuk Kwak","doi":"10.2139/ssrn.3904545","DOIUrl":"https://doi.org/10.2139/ssrn.3904545","url":null,"abstract":"This study investigates irreversible investment decisions when the exercise payoff is scale-dependent; thus, it is endogenously determined by the firm's risk management. We find that the scale-dependency gives rise to a speculative risk management strategy: a positive relationship between the firm's derivatives position and unhedged cash flow. Moreover, investment can be hastened or delayed as the underlying uncertainty increases depending on the economic conditions due to the speculative strategy. The main force driving these results, different from those known in the existing literature, is that the firm's risk management is designed to optimize the risk-return trade-off of the endogenous payoff.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126106974","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}
Sodhi and Tang discuss focus the aspects of rethinking industry's role in a national emergency. The shortcomings of the US Strategic National Stockpile must be remedied before the next large-scale public health emergency. Photographs of doctors and nurses wearing garbage bags to protect themselves from infection are among the most indelible images of the COVID-19 pandemic. They also testify to the limitations of the US Strategic National Stockpile (SNS). Backup capacity is relatively easy to arrange, but gaining access to standby capability on a timely basis is the crucial missing link in the SNS's current approach to its mission. Developing an industrial commons will take an ecosystem of expertise to develop and manage a standby capability for pandemics and other major emergencies.
{"title":"Rethinking Industry’s Role in a National Emergency","authors":"M. Sodhi, Christopher S. Tang","doi":"10.2139/ssrn.3860974","DOIUrl":"https://doi.org/10.2139/ssrn.3860974","url":null,"abstract":"Sodhi and Tang discuss focus the aspects of rethinking industry's role in a national emergency. The shortcomings of the US Strategic National Stockpile must be remedied before the next large-scale public health emergency. Photographs of doctors and nurses wearing garbage bags to protect themselves from infection are among the most indelible images of the COVID-19 pandemic. They also testify to the limitations of the US Strategic National Stockpile (SNS). Backup capacity is relatively easy to arrange, but gaining access to standby capability on a timely basis is the crucial missing link in the SNS's current approach to its mission. Developing an industrial commons will take an ecosystem of expertise to develop and manage a standby capability for pandemics and other major emergencies.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117228336","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}
Abstract Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo algorithm for calculating VaR and ES based on Gaussian Mixture Models is introduced. Gaussian Mixture Models are able to cluster input data with respect to market’s conditions and therefore no correlation matrices are needed for risk computation. Sampling from each cluster with respect to their weights and then calculating the volatility-adjusted stock returns leads to possible scenarios for prices of assets. Our results on a sample of US stocks show that the Gmm-based VaR model is computationally efficient and accurate. From a managerial perspective, our model can efficiently mimic the turbulent behavior of the market. As a result, our VaR measures before, during and after crisis periods realistically reflect the highly non-normal behavior and non-linear correlation structure of the market.
{"title":"Portfolio Value-at-Risk and Expected-Shortfall Using an Efficient Simulation Approach Based on Gaussian Mixture Model","authors":"Seyed Mohammad Sina Seyfi, A. Sharifi, H. Arian","doi":"10.2139/ssrn.3710362","DOIUrl":"https://doi.org/10.2139/ssrn.3710362","url":null,"abstract":"Abstract Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo algorithm for calculating VaR and ES based on Gaussian Mixture Models is introduced. Gaussian Mixture Models are able to cluster input data with respect to market’s conditions and therefore no correlation matrices are needed for risk computation. Sampling from each cluster with respect to their weights and then calculating the volatility-adjusted stock returns leads to possible scenarios for prices of assets. Our results on a sample of US stocks show that the Gmm-based VaR model is computationally efficient and accurate. From a managerial perspective, our model can efficiently mimic the turbulent behavior of the market. As a result, our VaR measures before, during and after crisis periods realistically reflect the highly non-normal behavior and non-linear correlation structure of the market.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122934562","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}
Volatility persistence is an important channel for understanding rational momentum effects. Since risk premia are, ceteris paribus, proportional to the volatility of the aggregate market or individual assets, momentum in the risk premia is expected to be strong when the volatility is highly persistent. I present empirical evidence that volatility persistence could capture the autoregressive risk premium. It also suggests that momentum profits can be attributed to time-varying risk. Furthermore, after controlling for risk-based momentum effect, the relationship between past and current returns turns out to be unclear, meaning that momentum exists mostly at the risk premium level.
{"title":"Volatility Persistence and Momentum","authors":"Woongki Lee","doi":"10.2139/ssrn.3704671","DOIUrl":"https://doi.org/10.2139/ssrn.3704671","url":null,"abstract":"Volatility persistence is an important channel for understanding rational momentum effects. Since risk premia are, ceteris paribus, proportional to the volatility of the aggregate market or individual assets, momentum in the risk premia is expected to be strong when the volatility is highly persistent. I present empirical evidence that volatility persistence could capture the autoregressive risk premium. It also suggests that momentum profits can be attributed to time-varying risk. Furthermore, after controlling for risk-based momentum effect, the relationship between past and current returns turns out to be unclear, meaning that momentum exists mostly at the risk premium level.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122737451","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}
Abstract In this work we derive an exact formula to calculate the Expected Shortfall (ES) value for the one-factor delta-gamma approach which, to the best of our knowledge, was still missing in the literature. We then use the one-factor delta-gamma as a control variate to estimate the ES of the multi-factor delta-gamma approach. A one-factor delta-gamma approximation is used for each risk factor appearing in the problem. Since the expected values of control variates are computed by means of an exact formula, the additional effort of computation with respect to the naive estimator of the multi-factor delta-gamma can be neglected. With this method, we achieve a considerable reduction of the variance. We have established a theorem to prove that the variance is further reduced when we use all the risk factors instead of just some of them. We show that one of the main potential applications takes place in the insurance industry regulation within the Swiss solvency test framework. We perform a model risk analysis and illustrate these results with numerical experiments.
{"title":"Expected Shortfall Computation with Multiple Control Variates","authors":"L. Ortiz-Gracia","doi":"10.2139/ssrn.3422934","DOIUrl":"https://doi.org/10.2139/ssrn.3422934","url":null,"abstract":"Abstract In this work we derive an exact formula to calculate the Expected Shortfall (ES) value for the one-factor delta-gamma approach which, to the best of our knowledge, was still missing in the literature. We then use the one-factor delta-gamma as a control variate to estimate the ES of the multi-factor delta-gamma approach. A one-factor delta-gamma approximation is used for each risk factor appearing in the problem. Since the expected values of control variates are computed by means of an exact formula, the additional effort of computation with respect to the naive estimator of the multi-factor delta-gamma can be neglected. With this method, we achieve a considerable reduction of the variance. We have established a theorem to prove that the variance is further reduced when we use all the risk factors instead of just some of them. We show that one of the main potential applications takes place in the insurance industry regulation within the Swiss solvency test framework. We perform a model risk analysis and illustrate these results with numerical experiments.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116632119","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}
Risk management is an important and helpful process for investors, hedge funds, traders and market makers. One of its key points is the appropriate estimation of risk measures which can improve the investment decisions and trading strategies. The high volatility of cryptocurrencies turns them a really risky investment and consequently, appropriate risk measures estimation is extremely necessary.
In this paper, we deal with the estimation of two widely-used risk measures such as Value-at-Risk and Expected Shortfall in a cryptocurrency context. To face the presence of outliers and the correlation between cryptocurrencies, we propose a methodology based on vine copulas and robust volatility models. Our procedure is illustrated in a seven-dimensional equal-weight cryptocurrency portfolio and displays good performance.
{"title":"Value-at-Risk and Expected Shortfall in Cryptocurrencies' Portfolio: A Vine Copula-based Approach","authors":"Carlos Trucíos, A. Tiwari, Faisal Alqahtani","doi":"10.2139/ssrn.3441892","DOIUrl":"https://doi.org/10.2139/ssrn.3441892","url":null,"abstract":"Risk management is an important and helpful process for investors, hedge funds, traders and market makers. One of its key points is the appropriate estimation of risk measures which can improve the investment decisions and trading strategies. The high volatility of cryptocurrencies turns them a really risky investment and consequently, appropriate risk measures estimation is extremely necessary.<br><br>In this paper, we deal with the estimation of two widely-used risk measures such as Value-at-Risk and Expected Shortfall in a cryptocurrency context. To face the presence of outliers and the correlation between cryptocurrencies, we propose a methodology based on vine copulas and robust volatility models. Our procedure is illustrated in a seven-dimensional equal-weight cryptocurrency portfolio and displays good performance.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133980401","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}
In the recent Basel Accords, the expected shortfall (ES) replaces the value-at-risk (VaR) as the standard risk measure for market risk in the banking sector, making it the most popular risk measure in financial regulation. Although ES is—in addition to many other nice properties—a coherent risk measure, it does not yet have an axiomatic foundation. In this paper, we put forward four intuitive economic axioms for portfolio risk assessment—monotonicity, law invariance, prudence, and no reward for concentration—that uniquely characterize the family of ES. Therefore, the results developed herein provide the first economic foundation for using ES as a globally dominating regulatory risk measure, currently employed in Basel III/IV. Key to the main results, several novel notions such as tail events and risk concentration naturally arise, and we explore them in detail. As a most important feature, ES rewards portfolio diversification and penalizes risk concentration in a special and intuitive way, not shared by any other risk measure. This paper was accepted by Manel Baucells, decision analysis.
{"title":"An Axiomatic Foundation for the Expected Shortfall","authors":"Ruodu Wang, R. Zitikis","doi":"10.2139/ssrn.3423042","DOIUrl":"https://doi.org/10.2139/ssrn.3423042","url":null,"abstract":"In the recent Basel Accords, the expected shortfall (ES) replaces the value-at-risk (VaR) as the standard risk measure for market risk in the banking sector, making it the most popular risk measure in financial regulation. Although ES is—in addition to many other nice properties—a coherent risk measure, it does not yet have an axiomatic foundation. In this paper, we put forward four intuitive economic axioms for portfolio risk assessment—monotonicity, law invariance, prudence, and no reward for concentration—that uniquely characterize the family of ES. Therefore, the results developed herein provide the first economic foundation for using ES as a globally dominating regulatory risk measure, currently employed in Basel III/IV. Key to the main results, several novel notions such as tail events and risk concentration naturally arise, and we explore them in detail. As a most important feature, ES rewards portfolio diversification and penalizes risk concentration in a special and intuitive way, not shared by any other risk measure. This paper was accepted by Manel Baucells, decision analysis.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"26 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121009080","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}
Abstract In this paper we consider an alternative dividend payment strategy in risk theory, where the dividend rate can never decrease. This addresses a concern that has often been raised in connection with the practical relevance of optimal classical dividend payment strategies of barrier and threshold type. We study the case where once during the lifetime of the risk process the dividend rate can be increased and derive corresponding formulas for the resulting expected discounted dividend payments until ruin. We first consider a general spectrally-negative Levy risk model, and then refine the analysis for a diffusion approximation and a compound Poisson risk model. It is shown that for the diffusion approximation the optimal barrier for the ratcheting strategy is characterized by an unexpected relation to the case of refracted dividend payments. Finally, numerical illustrations for the diffusion case indicate that with such a simple ratcheting dividend strategy the expected value of discounted dividends can already get quite close to the respective value of the refracted dividend strategy, the latter being known to be optimal among all admissible dividend strategies.
{"title":"Dividends: From Refracting to Ratcheting","authors":"Hansjoerg Albrecher, N. Bäuerle, Martin Bladt","doi":"10.2139/ssrn.3169185","DOIUrl":"https://doi.org/10.2139/ssrn.3169185","url":null,"abstract":"Abstract In this paper we consider an alternative dividend payment strategy in risk theory, where the dividend rate can never decrease. This addresses a concern that has often been raised in connection with the practical relevance of optimal classical dividend payment strategies of barrier and threshold type. We study the case where once during the lifetime of the risk process the dividend rate can be increased and derive corresponding formulas for the resulting expected discounted dividend payments until ruin. We first consider a general spectrally-negative Levy risk model, and then refine the analysis for a diffusion approximation and a compound Poisson risk model. It is shown that for the diffusion approximation the optimal barrier for the ratcheting strategy is characterized by an unexpected relation to the case of refracted dividend payments. Finally, numerical illustrations for the diffusion case indicate that with such a simple ratcheting dividend strategy the expected value of discounted dividends can already get quite close to the respective value of the refracted dividend strategy, the latter being known to be optimal among all admissible dividend strategies.","PeriodicalId":131191,"journal":{"name":"DecisionSciRN: Risk Techniques (Sub-Topic)","volume":"225 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116852119","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}
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