Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to ...Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to finish, there is a need for revolution in archaic monetary management institutes. By not being in tune with the contemporary trends and times, banks are losing on an opportunity to transform some of their business models and relieve humans of repetitive work, prevent frauds, make better decisions and consequently gain losses. Banks can engage in implementation of new Virtual Assistants and Artificial Intelligence (A.I.) machine learning technologies, just as the other industries have engaged in modernizing <i>i.e. </i> medical checks, medical reports and evaluations, and this research paper will elaborate and emphasize the impact of artificial intelligence implementation on the banking sector processes. This research is based on both quantitative and model-based proofs of system performance by using several analytical tools, such as SPSS. The automation process helps institutions to enhance profitability, performance and to reduce human dependency. In a nutshell, Virtual Assistants powered with Artificial Intelligence improve the business process performance in every sector of business, especially the banking sector making it fast, reliable and not human dependent.展开更多
Compared to OFDM systems with cyclic prefi x, fi lterbank multicarrier with offset quadrature amplitude modulation(FBMC/OQAM) system is considered as an alternative technology for next generation wireless communicatio...Compared to OFDM systems with cyclic prefi x, fi lterbank multicarrier with offset quadrature amplitude modulation(FBMC/OQAM) system is considered as an alternative technology for next generation wireless communication systems. However, FBMC systems suffer from intrinsic imaginary interference caused by the real-fi eld orthogonality destruction when passing through complex-valued fading channels. By analyzing the transmultiplexer's response of FBMC/OQAM systems, in this paper, a simple conjugated transmission scheme is proposed for FBMC/OQAM systems. Following the specific conjugation design, the intrinsic imaginary interference including the intrinsic inter-symbol and the inter-carrier interference can be eliminated at the receiver side through linear signal processing operation. Meanwhile, the proposed conjugated transmission scheme is able to obtain extra linear combination diversity gains for improving the systematic performance of FBMC/OQAM. Simulation results show that the proposed scheme is more efficient than conventional methods, especially in practical application scenarios with large Doppler spread caused by high-speed movement.展开更多
Analyzing the interdependencies among financial institutions is critical for designing systemic risk monitoring mechanisms;however,most existing research focuses on the first moment of the return distribution,which fa...Analyzing the interdependencies among financial institutions is critical for designing systemic risk monitoring mechanisms;however,most existing research focuses on the first moment of the return distribution,which falls into the conventional models of choice under risk.Previous literature has observed the scarcity of investors’attention and processing power,which makes the traditional theory of choice under risk more vulnerable and brings the salience theory that accommodates investors’cognitive limitations to our attention.Motivated by evidence of salience theory value(STV)containing unique information not captured by traditional higher-order moments,we employ a quantile connectedness approach to examine the STV interconnectedness of China’s systemically important banks(C-SIBs).The quantile approach allows us to uncover the dynamic STV interconnectedness of C-SIBs under normal,bearish,and bullish market conditions and is well-suited to extreme risk problems.Our results show that the C-SIBs system is asymmetrically interconnected across quantiles and at higher levels under bullish than bearish market conditions.Principally,a bank’s performance in the C-SIBs system depends on its systemic importance and market conditions.Furthermore,the comparative analysis indicates that STV could provide more information than higher-order moments in capturing the dynamic change in the C-SIBs system and detecting some market events more precisely.These results have important implications for policymakers and market participants to formulate regulatory policy and design risk management strategies.展开更多
A time domain designing method is proposed for discrete Fourier transform （DFT） modulated filter banks （DFT-FBs） for application in multi-carrier transceiver systems. Instead of using the time-reversed pair limita...A time domain designing method is proposed for discrete Fourier transform （DFT） modulated filter banks （DFT-FBs） for application in multi-carrier transceiver systems. Instead of using the time-reversed pair limitation between the transmitting /receiving filter pair, the receiving filters in the proposed filter banks are derived from transmitting filters in accordance with the Moore-Penrose generalized inverse matrix. It can be freely obtained to design the transmitting prototype filter, which mainly affects the level of spectral containment. Furthermore, the symbol error rate （SER） performance of the proposed filter bank based trans-multiplexer with one tap equalizer is investigated in ideal channel and multi-path channel environments respectively. Simulation shows that the proposed approach can achieve significant SER reductions when square root raised cosine （RRC） prototype filter is used for comparing with the orthogonal frequency division multiplexing （OFDM） and the general DFT-FBs based applications.展开更多
The systemic importance of a bank is usually measured by its effect on the banking system,conditional on the insolvency of the bank and solvency of other banks.However,banks encounter different kinds of shocks simulta...The systemic importance of a bank is usually measured by its effect on the banking system,conditional on the insolvency of the bank and solvency of other banks.However,banks encounter different kinds of shocks simultaneously in reality.So that,the conditional re-sults give biased estimates of banks'systemic importance when potential risks are ignored.Researchers like Tarashev et al.proposed the Shapley value method to deal with risk in-teractions,but it suffers heavy computational costs.This paper proposes an ANOVA-like decomposition method to measure the systemic importance of banks in more compli-cated and realistic environments,which considers both interactions and individual effects of multiple shocks and provides a more exact estimation of systemic importance.It is found that the method proposed in this paper fits well in the network models.And meanwhile,a discussion between the method proposed in this paper and the Shapley value method is made based on the numerical example,which aims to demonstrate it's the advantages.The Shapley value method requires 2n subsystems,while the ANOVA-like decomposition method requires only n+1 model runs.In the application part,the pro-posed method is adopted to measure the systemic importance of 16 Chinese listed banks.With low computational costs,the model outputs the individual effect,interaction,and total effect of each bank.The results confirm that interactions of different shocks play a significant role in the systemic importance of a bank;thus,the total effect considering interactions should be adopted.展开更多
文摘Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to finish, there is a need for revolution in archaic monetary management institutes. By not being in tune with the contemporary trends and times, banks are losing on an opportunity to transform some of their business models and relieve humans of repetitive work, prevent frauds, make better decisions and consequently gain losses. Banks can engage in implementation of new Virtual Assistants and Artificial Intelligence (A.I.) machine learning technologies, just as the other industries have engaged in modernizing <i>i.e. </i> medical checks, medical reports and evaluations, and this research paper will elaborate and emphasize the impact of artificial intelligence implementation on the banking sector processes. This research is based on both quantitative and model-based proofs of system performance by using several analytical tools, such as SPSS. The automation process helps institutions to enhance profitability, performance and to reduce human dependency. In a nutshell, Virtual Assistants powered with Artificial Intelligence improve the business process performance in every sector of business, especially the banking sector making it fast, reliable and not human dependent.
基金supported by the MOST Program of International S&T Cooperation(Grant No.2016YFE0123200)National Natural Science Foundation of China(Grant No.61471100/61101090/61571082)+1 种基金Science and Technology on Electronic Information Control Laboratory(Grant No.6142105040103)Fundamental Research Funds for the Central Universities(Grant No.ZYGX2015J012/ZYGX2014Z005)
文摘Compared to OFDM systems with cyclic prefi x, fi lterbank multicarrier with offset quadrature amplitude modulation(FBMC/OQAM) system is considered as an alternative technology for next generation wireless communication systems. However, FBMC systems suffer from intrinsic imaginary interference caused by the real-fi eld orthogonality destruction when passing through complex-valued fading channels. By analyzing the transmultiplexer's response of FBMC/OQAM systems, in this paper, a simple conjugated transmission scheme is proposed for FBMC/OQAM systems. Following the specific conjugation design, the intrinsic imaginary interference including the intrinsic inter-symbol and the inter-carrier interference can be eliminated at the receiver side through linear signal processing operation. Meanwhile, the proposed conjugated transmission scheme is able to obtain extra linear combination diversity gains for improving the systematic performance of FBMC/OQAM. Simulation results show that the proposed scheme is more efficient than conventional methods, especially in practical application scenarios with large Doppler spread caused by high-speed movement.
文摘Analyzing the interdependencies among financial institutions is critical for designing systemic risk monitoring mechanisms;however,most existing research focuses on the first moment of the return distribution,which falls into the conventional models of choice under risk.Previous literature has observed the scarcity of investors’attention and processing power,which makes the traditional theory of choice under risk more vulnerable and brings the salience theory that accommodates investors’cognitive limitations to our attention.Motivated by evidence of salience theory value(STV)containing unique information not captured by traditional higher-order moments,we employ a quantile connectedness approach to examine the STV interconnectedness of China’s systemically important banks(C-SIBs).The quantile approach allows us to uncover the dynamic STV interconnectedness of C-SIBs under normal,bearish,and bullish market conditions and is well-suited to extreme risk problems.Our results show that the C-SIBs system is asymmetrically interconnected across quantiles and at higher levels under bullish than bearish market conditions.Principally,a bank’s performance in the C-SIBs system depends on its systemic importance and market conditions.Furthermore,the comparative analysis indicates that STV could provide more information than higher-order moments in capturing the dynamic change in the C-SIBs system and detecting some market events more precisely.These results have important implications for policymakers and market participants to formulate regulatory policy and design risk management strategies.
基金supported by Young Scientists Fund of Chongqing University of Posts and Telecommunications(A2013-32)
文摘A time domain designing method is proposed for discrete Fourier transform （DFT） modulated filter banks （DFT-FBs） for application in multi-carrier transceiver systems. Instead of using the time-reversed pair limitation between the transmitting /receiving filter pair, the receiving filters in the proposed filter banks are derived from transmitting filters in accordance with the Moore-Penrose generalized inverse matrix. It can be freely obtained to design the transmitting prototype filter, which mainly affects the level of spectral containment. Furthermore, the symbol error rate （SER） performance of the proposed filter bank based trans-multiplexer with one tap equalizer is investigated in ideal channel and multi-path channel environments respectively. Simulation shows that the proposed approach can achieve significant SER reductions when square root raised cosine （RRC） prototype filter is used for comparing with the orthogonal frequency division multiplexing （OFDM） and the general DFT-FBs based applications.
基金This research was supported by the National Natural Science Foundation of China under Grants 71425002,71571179
文摘The systemic importance of a bank is usually measured by its effect on the banking system,conditional on the insolvency of the bank and solvency of other banks.However,banks encounter different kinds of shocks simultaneously in reality.So that,the conditional re-sults give biased estimates of banks'systemic importance when potential risks are ignored.Researchers like Tarashev et al.proposed the Shapley value method to deal with risk in-teractions,but it suffers heavy computational costs.This paper proposes an ANOVA-like decomposition method to measure the systemic importance of banks in more compli-cated and realistic environments,which considers both interactions and individual effects of multiple shocks and provides a more exact estimation of systemic importance.It is found that the method proposed in this paper fits well in the network models.And meanwhile,a discussion between the method proposed in this paper and the Shapley value method is made based on the numerical example,which aims to demonstrate it's the advantages.The Shapley value method requires 2n subsystems,while the ANOVA-like decomposition method requires only n+1 model runs.In the application part,the pro-posed method is adopted to measure the systemic importance of 16 Chinese listed banks.With low computational costs,the model outputs the individual effect,interaction,and total effect of each bank.The results confirm that interactions of different shocks play a significant role in the systemic importance of a bank;thus,the total effect considering interactions should be adopted.
