Value at risk (VaR) is adopted to measure the risk level in the electricity market. To estimate VaR at higher accuracy and reliability, the wavelet variance decomposed approach for value at risk estimates (WVDVaR) is ...Value at risk (VaR) is adopted to measure the risk level in the electricity market. To estimate VaR at higher accuracy and reliability, the wavelet variance decomposed approach for value at risk estimates (WVDVaR) is proposed. Empirical studies conduct in five Australian electricity markets, which evaluate the performances of both the proposed approach and the traditional ARMA-GARCH approach using the Kupiec backtesting procedure. Experimental results suggest that the proposed approach measures electricity market risks at higher accuracy and reliability than the bench mark ARMA-GARCH approach, as indicated by the higher p values during the Kupiec backtesting procedure. In addition, the new approach also provides more insight into the risk evolution process over time and helps in adjusting VaR estimates to the time horizons that best suit investor interests. The distribution of risk according to investor preferences is shown by decomposing VaR across different time horizons. This also provides important information for the appropriate aggregation of risk measures based on investor investment preferences.展开更多
This study investigates the factors of Bitcoin’s tail risk,quantified by Value at Risk(VaR).Extending the conditional autoregressive VaR model proposed by Engle and Manganelli(2004),I examine 30 potential drivers of ...This study investigates the factors of Bitcoin’s tail risk,quantified by Value at Risk(VaR).Extending the conditional autoregressive VaR model proposed by Engle and Manganelli(2004),I examine 30 potential drivers of Bitcoin’s 5%and 1%VaR.For the 5%VaR,quantity variables,such as Bitcoin trading volume and monetary policy rate,were positively significant,but these effects were attenuated when new samples were added.The 5%VaR responds positively to the Internet search index and negatively to the fluctuation of returns on commodity variables and the Chinese stock market index.For the 1%VaR,variables related to the macroeconomy play a key role.The consumer sentiment index exerts a strong positive effect on the 1%VaR.I also find that the 1%VaR has positive relationships with the US economic policy uncertainty index and the fluctuation of returns on the corporate bond index.展开更多
With the application of phasor measurement units(PMU)in the distribution system,it is expected that the performance of the distribution system state estimation can be improved obviously with the PMU measurements into ...With the application of phasor measurement units(PMU)in the distribution system,it is expected that the performance of the distribution system state estimation can be improved obviously with the PMU measurements into consideration.How to appropriately place the PMUs in the distribution is therefore become an important issue due to the economical consideration.According to the concept of efficient frontier,a value-at-risk based approach is proposed to make optimal placement of PMU taking account of the uncertainty of measure errors,statistical characteristics of the pseudo measurements,and reliability of the measurement instrument.The reasonability and feasibility of the proposed model is illustrated with 12-node system and IEEE-33 node system.Simulation results indicated that uncertainties of measurement error and instrument fault result in more PMU to be installed,and measurement uncertainty is the main affect factor unless the fault rate of PMU is quite high.展开更多
This paper clarifies the distinctions between loan loss reserves （LLR）, expected loss （EL）, and loan loss provisions （LLP）. The paper also includes information on individual and collective impairment assessment ...This paper clarifies the distinctions between loan loss reserves （LLR）, expected loss （EL）, and loan loss provisions （LLP）. The paper also includes information on individual and collective impairment assessment of local commercial banks in Malaysia collected from their annual reports. Most banks have maintained collective assessment （CA） allowance ratio of lower than 1.2% of gross total loans.展开更多
This paper analyzes the relationship between the risk factor of each stock and the portfolio’s risk based on a small portfolio with four U.S.stocks,and the reason why these risk factors can be regarded as a market in...This paper analyzes the relationship between the risk factor of each stock and the portfolio’s risk based on a small portfolio with four U.S.stocks,and the reason why these risk factors can be regarded as a market invariant.Then,it evaluates the properties of the convex and coherent risk indicators of the capital requirement index composed of VaR and ES,and use three methods(the historical estimation method,boudoukh’s mixed method and Monte Carlo method)to estimate the risk measurement indicators VaR and ES respectively based on the assumption of multivariate normal distribution’risk factors and multivariate student t-copula distribution’s one,finally it figures out that these three calculation results are very close.展开更多
This study introduces the dynamic Gerber model(DGC)and evaluates its performance in the prediction of Value at Risk(VaR)and Expected Shortfall(ES)compared to alternative parametric,non-parametric and semi-parametric m...This study introduces the dynamic Gerber model(DGC)and evaluates its performance in the prediction of Value at Risk(VaR)and Expected Shortfall(ES)compared to alternative parametric,non-parametric and semi-parametric methods for estimating the covariance matrix of returns.Based on ES backtests,the DGC method produces,overall,accurate ES forecasts.Furthermore,we use the Model Confidence Set procedure to identify the superior set of models(SSM).For all the portfolios and VaR/ES confidence levels we consider,the DGC is found to belong to the SSM.展开更多
Efficient flight path design for unmanned aerial vehicles(UAVs)in urban environmental event monitoring remains a critical challenge,particularly in prioritizing high-risk zones within complex urban landscapes.Current ...Efficient flight path design for unmanned aerial vehicles(UAVs)in urban environmental event monitoring remains a critical challenge,particularly in prioritizing high-risk zones within complex urban landscapes.Current UAV path planning methodologies often inadequately account for environmental risk factors and exhibit limitations in balancing global and local optimization efficiency.To address these gaps,this study proposes a hybrid path planning framework integrating an improved Ant Colony Optimization(ACO)algorithm with an Orthogonal Jump Point Search(OJPS)algorithm.Firstly,a two-dimensional grid model is constructed to simulate urban environments,with key monitoring nodes selected based on grid-specific environmental risk values.Subsequently,the improved ACO algorithm is used for global path planning,and the OJPS algorithm is integrated to optimize the local path.The improved ACO algorithm introduces the risk value of environmental events,which is used to direct the UAV to the area with higher risk.In the OJPS algorithm,the path search direction is restricted to the orthogonal direction,which improves the computational efficiency of local path optimization.In order to evaluate the performance of the model,this paper utilizes the metrics of the average risk value of the path,the flight time,and the number of turns.The experimental results demonstrate that the proposed improved ACO algorithm performs well in the average risk value of the paths traveled within the first 5 min,within the first 8 min,and within the first 10 min,with improvements of 48.33%,26.10%,and 6.746%,respectively,over the Particle Swarm Optimization(PSO)algorithm and 70.33%,19.08%,and 10.246%,respectively,over theArtificial Rabbits Optimization(ARO)algorithm.TheOJPS algorithmdemonstrates superior performance in terms of flight time and number of turns,exhibiting a reduction of 40%,40%and 57.1%in flight time compared to the other three algorithms,and a reduction of 11.1%,11.1%and 33.8%in the number of turns compared to the other three algorithms.These results highlight the effectiveness of the proposed method in improving the UAV’s ability to respond efficiently to urban environmental events,offering significant implications for the future of UAV path planning in complex urban settings.展开更多
Considering participators' risk bias,which is measured by the method of value at risk,the risk constraints in a two-echelon supply chain coordination under buy-back contract is equal to giving the order of an uppe...Considering participators' risk bias,which is measured by the method of value at risk,the risk constraints in a two-echelon supply chain coordination under buy-back contract is equal to giving the order of an upper bound.With a risk-averse dominant enterprise(M)and a risk-neutral non-dominant one(R),the coordination which optimizes the supply chain under the risk constraints is achieved by a penalty mechanism L to reduce R's order.With risk-neutral M and risk-averse R,M can motivate R to increase his order by providing a risk subsidy K,and two cases are discussed.If the risk constraints of R cannot satisfy M's participation constraint to offer K,M will prefer to accept R's order to obtain a sub-optimization solution of the supply chain.Or else,with M's K,R's optimal order just coordinates the supply chain,which is equal to the case without risk bias,and in this situation R's risk bias only affects the profit distribution between the participators.展开更多
This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its gene...This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its generalization error bound is established through the lens of uniform convergence analysis.The CVaR-based MRO can achieve the polynomial decay rate on the excess risk,which extends the generalization analysis associated with the expected risk to the risk-averse case.展开更多
In this paper, the expressions of tail value of risk （TVaR） and exponential tail value of risk （EVaR） for the total risk portfolio are given, which are splitted into two cases： the bivariate case and the multivar...In this paper, the expressions of tail value of risk （TVaR） and exponential tail value of risk （EVaR） for the total risk portfolio are given, which are splitted into two cases： the bivariate case and the multivariate case according to the number of the insurances. Then the risk contributions of the insurances portfolio and the credit portfolio are also obtained. Further more, for clarifying the above results, a numerical example is given.展开更多
Operational risk events have severely impacted the development of third-party payment(TPP)platforms,and have even led to a discussion on the operational risk capital charge settlement by relevant international regulat...Operational risk events have severely impacted the development of third-party payment(TPP)platforms,and have even led to a discussion on the operational risk capital charge settlement by relevant international regulators.However,prior studies have mostly focused on qualitative mechanism analysis,and have rarely examined quantitative risk assessment based on actual operational risk events.Therefore,this study attempts to assess the operational risk on TPP platforms in China by constructing a systematic framework incorporating database construction and risk modeling.First,the operational risk database that covers 202 events between Q1,2014,and Q2,2020 is constructed.Then,specific causes are clarified,and the characteristics are analyzed from both the trend and loss severity perspectives.Finally,the piecewise-defined severity distribution based-Loss Distribution Approach(PSD-LDA)with double truncation is utilized to assess the operational risk.Two main conclusions are drawn from the empirical analysis.First,legal risk and external fraud risk are the two main causes of operational risk.Second,the yearly Value at Risk and Expected Shortfall are 724.46 million yuan and 1081.98 million yuan under the 99.9%significance level,respectively.Our results are beneficial for both TPP platform operators and regulators in managing and controlling operational risk.展开更多
In order to study the effect of different risk measures on the efficient portfolios （fron- tier） while properly describing the characteristic of return distributions in the stock market, it is assumed in this paper ...In order to study the effect of different risk measures on the efficient portfolios （fron- tier） while properly describing the characteristic of return distributions in the stock market, it is assumed in this paper that the joint return distribution of risky assets obeys the multivariate t-distribution. Under the mean-risk analysis framework, the interrelationship of efficient portfolios （frontier） based on risk measures such as variance, value at risk （VaR）, and expected shortfall （ES） is analyzed and compared. It is proved that, when there is no riskless asset in the market, the efficient frontier under VaR or ES is a subset of the mean-variance （MV） efficient frontier, and the efficient portfolios under VaR or ES are also MV efficient; when there exists a riskless asset in the market, a portfolio is MV efficient if and only if it is a VaR or ES efficient portfolio. The obtained results generalize relevant conclusions about investment theory, and can better guide investors to make their investment decision.展开更多
A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC...A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.展开更多
The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or schedu...The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or scheduling,and integer partitions.An accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical computers.To effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk.The proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum resources.The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era.We investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the model.Moreover,we also discuss the performance of the model under different conditional values at risk.Through computer simulation,the scale can reach more than nine qubits.By selecting the noise type,we construct simulators with different QVs and study the performance of the model with them.In addition,we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem.This model provides a new perspective for solving the subset sum problem.展开更多
Value at risk(VaR)and expected shortfall(ES)have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions,external regulations,and risk capital al...Value at risk(VaR)and expected shortfall(ES)have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions,external regulations,and risk capital allocation.However,existing VaR estimation approaches fail to accurately reflect downside risks,and the ES estimation technique is quite limited owing to its challenging implementation.This causes financial institutions to overestimate or underestimate investment risk and finally leads to the inefficient allocation of financial resources.The main purpose of this study is to use machine learning to improve the accuracy of VaR estimation and provide an effective tool for ES estimation.Specifically,this study proposes a VaR estimator by combining quantile regression with“Mogrifier”recurrent neural networks to capture the“long memory”and“clustering”properties of financial assets;while for estimating ES,this study directly models the quantile of assets and employs generative adversarial networks to generate future tail risk scenarios.In addition to the typical properties of financial assets,the model design is also consistent with heterogeneous market theory.An empirical application to four major global stock indices shows that our model is superior to other existing models.展开更多
This article proposes an innovative method for modeling financial markets using multifractional Brownian motion(mBm).Unlike traditional fractional Brownian motion,mBm offers variable local memory,providing a more accu...This article proposes an innovative method for modeling financial markets using multifractional Brownian motion(mBm).Unlike traditional fractional Brownian motion,mBm offers variable local memory,providing a more accurate representation of the multifractal volatility and long-range dependencies found in financial time series.We present a precise mathematical formulation of mBm,sophisticated techniques for estimating the Hurst function,efficient numerical simulation algorithms,and a detailed empirical study covering several major stock indices.The results indicate that mBm more accurately reflects price dynamics,significantly improves risk analysis,and provides more precise pricing of exotic options compared to traditional models.展开更多
基金The National Social Science Foundation of China (No.07AJL005)the Foundation of City University of Hong Kong (No.9610058)
文摘Value at risk (VaR) is adopted to measure the risk level in the electricity market. To estimate VaR at higher accuracy and reliability, the wavelet variance decomposed approach for value at risk estimates (WVDVaR) is proposed. Empirical studies conduct in five Australian electricity markets, which evaluate the performances of both the proposed approach and the traditional ARMA-GARCH approach using the Kupiec backtesting procedure. Experimental results suggest that the proposed approach measures electricity market risks at higher accuracy and reliability than the bench mark ARMA-GARCH approach, as indicated by the higher p values during the Kupiec backtesting procedure. In addition, the new approach also provides more insight into the risk evolution process over time and helps in adjusting VaR estimates to the time horizons that best suit investor interests. The distribution of risk according to investor preferences is shown by decomposing VaR across different time horizons. This also provides important information for the appropriate aggregation of risk measures based on investor investment preferences.
文摘This study investigates the factors of Bitcoin’s tail risk,quantified by Value at Risk(VaR).Extending the conditional autoregressive VaR model proposed by Engle and Manganelli(2004),I examine 30 potential drivers of Bitcoin’s 5%and 1%VaR.For the 5%VaR,quantity variables,such as Bitcoin trading volume and monetary policy rate,were positively significant,but these effects were attenuated when new samples were added.The 5%VaR responds positively to the Internet search index and negatively to the fluctuation of returns on commodity variables and the Chinese stock market index.For the 1%VaR,variables related to the macroeconomy play a key role.The consumer sentiment index exerts a strong positive effect on the 1%VaR.I also find that the 1%VaR has positive relationships with the US economic policy uncertainty index and the fluctuation of returns on the corporate bond index.
基金The author Min Liu received the grant of the National Natural Science Foundation of China(http://www.nsfc.gov.cn/)(51967004).
文摘With the application of phasor measurement units(PMU)in the distribution system,it is expected that the performance of the distribution system state estimation can be improved obviously with the PMU measurements into consideration.How to appropriately place the PMUs in the distribution is therefore become an important issue due to the economical consideration.According to the concept of efficient frontier,a value-at-risk based approach is proposed to make optimal placement of PMU taking account of the uncertainty of measure errors,statistical characteristics of the pseudo measurements,and reliability of the measurement instrument.The reasonability and feasibility of the proposed model is illustrated with 12-node system and IEEE-33 node system.Simulation results indicated that uncertainties of measurement error and instrument fault result in more PMU to be installed,and measurement uncertainty is the main affect factor unless the fault rate of PMU is quite high.
文摘This paper clarifies the distinctions between loan loss reserves （LLR）, expected loss （EL）, and loan loss provisions （LLP）. The paper also includes information on individual and collective impairment assessment of local commercial banks in Malaysia collected from their annual reports. Most banks have maintained collective assessment （CA） allowance ratio of lower than 1.2% of gross total loans.
文摘This paper analyzes the relationship between the risk factor of each stock and the portfolio’s risk based on a small portfolio with four U.S.stocks,and the reason why these risk factors can be regarded as a market invariant.Then,it evaluates the properties of the convex and coherent risk indicators of the capital requirement index composed of VaR and ES,and use three methods(the historical estimation method,boudoukh’s mixed method and Monte Carlo method)to estimate the risk measurement indicators VaR and ES respectively based on the assumption of multivariate normal distribution’risk factors and multivariate student t-copula distribution’s one,finally it figures out that these three calculation results are very close.
文摘This study introduces the dynamic Gerber model(DGC)and evaluates its performance in the prediction of Value at Risk(VaR)and Expected Shortfall(ES)compared to alternative parametric,non-parametric and semi-parametric methods for estimating the covariance matrix of returns.Based on ES backtests,the DGC method produces,overall,accurate ES forecasts.Furthermore,we use the Model Confidence Set procedure to identify the superior set of models(SSM).For all the portfolios and VaR/ES confidence levels we consider,the DGC is found to belong to the SSM.
基金supported by the Special Project forKey Fields of Ordinary Universities in Guangdong Province(Number:2023ZDZX1076).
文摘Efficient flight path design for unmanned aerial vehicles(UAVs)in urban environmental event monitoring remains a critical challenge,particularly in prioritizing high-risk zones within complex urban landscapes.Current UAV path planning methodologies often inadequately account for environmental risk factors and exhibit limitations in balancing global and local optimization efficiency.To address these gaps,this study proposes a hybrid path planning framework integrating an improved Ant Colony Optimization(ACO)algorithm with an Orthogonal Jump Point Search(OJPS)algorithm.Firstly,a two-dimensional grid model is constructed to simulate urban environments,with key monitoring nodes selected based on grid-specific environmental risk values.Subsequently,the improved ACO algorithm is used for global path planning,and the OJPS algorithm is integrated to optimize the local path.The improved ACO algorithm introduces the risk value of environmental events,which is used to direct the UAV to the area with higher risk.In the OJPS algorithm,the path search direction is restricted to the orthogonal direction,which improves the computational efficiency of local path optimization.In order to evaluate the performance of the model,this paper utilizes the metrics of the average risk value of the path,the flight time,and the number of turns.The experimental results demonstrate that the proposed improved ACO algorithm performs well in the average risk value of the paths traveled within the first 5 min,within the first 8 min,and within the first 10 min,with improvements of 48.33%,26.10%,and 6.746%,respectively,over the Particle Swarm Optimization(PSO)algorithm and 70.33%,19.08%,and 10.246%,respectively,over theArtificial Rabbits Optimization(ARO)algorithm.TheOJPS algorithmdemonstrates superior performance in terms of flight time and number of turns,exhibiting a reduction of 40%,40%and 57.1%in flight time compared to the other three algorithms,and a reduction of 11.1%,11.1%and 33.8%in the number of turns compared to the other three algorithms.These results highlight the effectiveness of the proposed method in improving the UAV’s ability to respond efficiently to urban environmental events,offering significant implications for the future of UAV path planning in complex urban settings.
基金The National Natural Science Foundation of China(No.70671025)the National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘Considering participators' risk bias,which is measured by the method of value at risk,the risk constraints in a two-echelon supply chain coordination under buy-back contract is equal to giving the order of an upper bound.With a risk-averse dominant enterprise(M)and a risk-neutral non-dominant one(R),the coordination which optimizes the supply chain under the risk constraints is achieved by a penalty mechanism L to reduce R's order.With risk-neutral M and risk-averse R,M can motivate R to increase his order by providing a risk subsidy K,and two cases are discussed.If the risk constraints of R cannot satisfy M's participation constraint to offer K,M will prefer to accept R's order to obtain a sub-optimization solution of the supply chain.Or else,with M's K,R's optimal order just coordinates the supply chain,which is equal to the case without risk bias,and in this situation R's risk bias only affects the profit distribution between the participators.
基金Supported by Education Science Planning Project of Hubei Province(2020GB198)Natural Science Foundation of Hubei Province(2023AFB523).
文摘This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its generalization error bound is established through the lens of uniform convergence analysis.The CVaR-based MRO can achieve the polynomial decay rate on the excess risk,which extends the generalization analysis associated with the expected risk to the risk-averse case.
基金Supported by the National Natural Sciences Foundation of China(Grant No.61175041)the Funds of Doctoral Programme of China(Grant No.2010041110036)+3 种基金the Fundamental Research Funds for the Central Universities(Grant Nos.DUT12LK16DUT12LK29)the Funds for Frontier Interdisciplines of DUT(GrantNos.DUT12JS05DUT10JS06)
文摘In this paper, the expressions of tail value of risk （TVaR） and exponential tail value of risk （EVaR） for the total risk portfolio are given, which are splitted into two cases： the bivariate case and the multivariate case according to the number of the insurances. Then the risk contributions of the insurances portfolio and the credit portfolio are also obtained. Further more, for clarifying the above results, a numerical example is given.
基金supported by grants from the National Natural Science Foundation of China(71425002,72101166)the Capital University of Economics and Business for the Fundamental Research Funds for Universities affiliated to Beijing(XRZ2021066).
文摘Operational risk events have severely impacted the development of third-party payment(TPP)platforms,and have even led to a discussion on the operational risk capital charge settlement by relevant international regulators.However,prior studies have mostly focused on qualitative mechanism analysis,and have rarely examined quantitative risk assessment based on actual operational risk events.Therefore,this study attempts to assess the operational risk on TPP platforms in China by constructing a systematic framework incorporating database construction and risk modeling.First,the operational risk database that covers 202 events between Q1,2014,and Q2,2020 is constructed.Then,specific causes are clarified,and the characteristics are analyzed from both the trend and loss severity perspectives.Finally,the piecewise-defined severity distribution based-Loss Distribution Approach(PSD-LDA)with double truncation is utilized to assess the operational risk.Two main conclusions are drawn from the empirical analysis.First,legal risk and external fraud risk are the two main causes of operational risk.Second,the yearly Value at Risk and Expected Shortfall are 724.46 million yuan and 1081.98 million yuan under the 99.9%significance level,respectively.Our results are beneficial for both TPP platform operators and regulators in managing and controlling operational risk.
基金Supported by the NNSF of China (10571141) the Key Project of the NNSF of China (70531030).
文摘In order to study the effect of different risk measures on the efficient portfolios （fron- tier） while properly describing the characteristic of return distributions in the stock market, it is assumed in this paper that the joint return distribution of risky assets obeys the multivariate t-distribution. Under the mean-risk analysis framework, the interrelationship of efficient portfolios （frontier） based on risk measures such as variance, value at risk （VaR）, and expected shortfall （ES） is analyzed and compared. It is proved that, when there is no riskless asset in the market, the efficient frontier under VaR or ES is a subset of the mean-variance （MV） efficient frontier, and the efficient portfolios under VaR or ES are also MV efficient; when there exists a riskless asset in the market, a portfolio is MV efficient if and only if it is a VaR or ES efficient portfolio. The obtained results generalize relevant conclusions about investment theory, and can better guide investors to make their investment decision.
基金Sponsored by the National Natural Science Foundation of China(70571010)
文摘A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.
基金supported by the National Key R&D Program of China(Grant No.2019YFA0308700)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301500)。
文摘The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or scheduling,and integer partitions.An accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical computers.To effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk.The proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum resources.The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era.We investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the model.Moreover,we also discuss the performance of the model under different conditional values at risk.Through computer simulation,the scale can reach more than nine qubits.By selecting the noise type,we construct simulators with different QVs and study the performance of the model with them.In addition,we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem.This model provides a new perspective for solving the subset sum problem.
基金supported by the Jiangxi Provincial Natural Science Foundation(20212ACB211003)the National Natural Science Foundation of China(No.71671029).
文摘Value at risk(VaR)and expected shortfall(ES)have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions,external regulations,and risk capital allocation.However,existing VaR estimation approaches fail to accurately reflect downside risks,and the ES estimation technique is quite limited owing to its challenging implementation.This causes financial institutions to overestimate or underestimate investment risk and finally leads to the inefficient allocation of financial resources.The main purpose of this study is to use machine learning to improve the accuracy of VaR estimation and provide an effective tool for ES estimation.Specifically,this study proposes a VaR estimator by combining quantile regression with“Mogrifier”recurrent neural networks to capture the“long memory”and“clustering”properties of financial assets;while for estimating ES,this study directly models the quantile of assets and employs generative adversarial networks to generate future tail risk scenarios.In addition to the typical properties of financial assets,the model design is also consistent with heterogeneous market theory.An empirical application to four major global stock indices shows that our model is superior to other existing models.
文摘This article proposes an innovative method for modeling financial markets using multifractional Brownian motion(mBm).Unlike traditional fractional Brownian motion,mBm offers variable local memory,providing a more accurate representation of the multifractal volatility and long-range dependencies found in financial time series.We present a precise mathematical formulation of mBm,sophisticated techniques for estimating the Hurst function,efficient numerical simulation algorithms,and a detailed empirical study covering several major stock indices.The results indicate that mBm more accurately reflects price dynamics,significantly improves risk analysis,and provides more precise pricing of exotic options compared to traditional models.
