There are two broad objectives of the research reported in this paper. First, we assess whether government-provided cyber threat intelligence (CTI) is helpful in preventing, or responding to, cyber-attacks among small...There are two broad objectives of the research reported in this paper. First, we assess whether government-provided cyber threat intelligence (CTI) is helpful in preventing, or responding to, cyber-attacks among small businesses within the U.S. Defense Industrial Base (DIB). Second, we identify ways of improving the effectiveness of government-provided CTI to small businesses within the DIB. Based on a questionnaire-based survey, our findings suggest that government-provided CTI helps businesses within the DIB in preventing, or responding to, cyber-attacks providing a firm is familiar with the CTI. Unfortunately, a large percentage of small firms are not familiar with the government-provided CTI feeds and consequently are not utilizing the CTI. This latter situation is largely due to financial constraints confronting small businesses that prevent firms from having the wherewithal necessary to effectively utilize the government-provided CTI. However, we found a significant positive association between a firm’s familiarity with the government-provided CTI and whether a firm is being periodically reviewed by the Defense Counterintelligence and Security Agency (DCSA) or is compliant with the Cybersecurity Maturity Model Certification (CMMC) program. The findings from our study also show that the participating firms believe that external cyber threats are more likely to be the cause of a future cybersecurity breach than internal cybersecurity threats. Finally, our study found that the portion of the IT budget that small businesses within the DIB spend on cybersecurity-related activities is dependent on the perception that a firm would be the target of an external cyber-attack.展开更多
Cyber security breaches inflict costs to consumers and businesses. The possibility also exists that a cyber security breach may shut down an entire critical infrastructure industry, putting a nation’s whole economy a...Cyber security breaches inflict costs to consumers and businesses. The possibility also exists that a cyber security breach may shut down an entire critical infrastructure industry, putting a nation’s whole economy and national defense at risk. Hence, the issue of cyber security investment has risen to the top of the agenda of business and government executives. This paper examines how the existence of well-recognized externalities changes the maximum a firm should, from a social welfare perspective, invest in cyber security activities. By extending the cyber security investment model of Gordon and Loeb [1] to incorporate externalities, we show that the firm’s social optimal investment in cyber security increases by no more than 37% of the expected externality loss.展开更多
Among the existing researches on brand value,few of them focused on the demands of the companies in the clothing industry to brand value. There were three innovation points as follows: first of all,two key demands of ...Among the existing researches on brand value,few of them focused on the demands of the companies in the clothing industry to brand value. There were three innovation points as follows: first of all,two key demands of apparel companies to existing brand value were summarized through investigation; then,the concept of rapid brand value evaluation and multi-dimensional factors( MDFs) was presented; finally,the relationship between apparel corporate brand value and the sales revenue in apparel market with the sales revenue was proven by empirical research.During the process of empirical study,the sales revenue data of 66 apparel enterprises domestic and abroad were collected,and the regression analysis has been done on the relationship between the corporate brand value and the apparel market sales revenue of apparel enterprise. The empirical research showed that they were positively correlated to each other. This conclusion presented a method of judging brand value development trend quickly by single indicator.展开更多
Investments in cybersecurity are critical to the national and economic security of a nation. There is, however, a strong tendency for firms in the private sector to underinvest in cybersecurity activities. This paper ...Investments in cybersecurity are critical to the national and economic security of a nation. There is, however, a strong tendency for firms in the private sector to underinvest in cybersecurity activities. This paper reports the results of a survey designed to empirically assess whether treating cybersecurity as an important component of a firm’s internal control system for financial reporting purposes serves as a driver for private sector firms to invest in cybersecurity activities. The findings, in this regard, are significantly positive. The study also shows that a firm’s concern over the risk of incurring a large loss due to a cybersecurity breach and the degree the firm treats cybersecurity investments as generating a competitive advantage are drivers of the level of private sector investment in cybersecurity activities. The implications of the empirical results for designing public policies to mitigate the tendency of private sector firms to underinvest in cybersecurity are also explored.展开更多
This paper extends the literature on the economics of sharing cybersecurity information by and among profit-seeking firms by modeling the case where a government agency or department publicly shares unclassified cyber...This paper extends the literature on the economics of sharing cybersecurity information by and among profit-seeking firms by modeling the case where a government agency or department publicly shares unclassified cyber threat information with all organizations. In prior cybersecurity information sharing models a common element was reciprocity—i.e., firms receiving shared information are also asked to share their private cybersecurity information with all other firms (via an information sharing arrangement). In contrast, sharing of unclassified cyber threat intelligence (CTI) by a government agency or department is not based on reciprocal sharing by the recipient organizations. After considering the government’s cost of preparing and disseminating CTI, as well as the benefits to the recipients of the CTI, we provide sufficient conditions for sharing of CTI to result in an increase in social welfare. Under a broad set of general conditions, sharing of CTI will increase social welfare gross of the costs to the government agency or department sharing the information. Thus, if the entity can keep the sharing costs low, sharing cybersecurity information will result in an increase in net social welfare.展开更多
Given the importance of cybersecurity to the survival of an organization, a fundamental economics-based question that must be addressed by all organizations is: How much should be invested in cybersecurity related act...Given the importance of cybersecurity to the survival of an organization, a fundamental economics-based question that must be addressed by all organizations is: How much should be invested in cybersecurity related activities? Gordon and Loeb [1] presented a model to address this question, and that model has received a significant amount of attention in the academic and practitioner literature. The primary objective of this paper is to discuss the Gordon-Loeb Model with a focus on gaining insights for the model’s use in a practical setting.展开更多
This paper provides an analysis of how the benefits of information segmentation can assist an organization to derive the appropriate amount to invest in cybersecurity from a cost-benefit perspective. An analytical mod...This paper provides an analysis of how the benefits of information segmentation can assist an organization to derive the appropriate amount to invest in cybersecurity from a cost-benefit perspective. An analytical model based on the framework of the Gordon-Loeb Model (<span><span><span style="font-family:Verdana;">[1]</span><span></span></span></span><span><span></span></span><span></span><span><span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">) is presented that provides a set of sufficient conditions for information segmentation to lower the total investments in cybersecurity and the expected loss from cybersecurity breaches. A numerical example illustrating the insights gained from the model is also presented.</span></span></span>展开更多
The spirit of now in nowcasting suggests expanding the current to include the near future.Decision theory is then developed by incorporating the consequences of actions into the present.With the future falling into th...The spirit of now in nowcasting suggests expanding the current to include the near future.Decision theory is then developed by incorporating the consequences of actions into the present.With the future falling into the present discounting it is no longer permitted.Value functions are then observed to be determinate only up to scale and shift that are then locked down by fixing values arbitrarily in two selected states,much like declaring water to freeze and boil at zero and a hundred degrees celsius.The locked down value functions associated policy functions are seen to exist in decision contexts in where the only time is now.Examples are studied in univariate and multivariate dimensions for the decision state space and the dimension of shocks delivering state transitions.The policy functions are expanded from realisitic training sets to the full state space using Gaussian Process Regression.They are implemented on real data with reported performances.展开更多
Risks embedded in asset price dynamics are taken to be accumulations of surprise jumps.A Markov pure jump model is formulated on making variance gamma parameters deterministic functions of the price level.Estimation i...Risks embedded in asset price dynamics are taken to be accumulations of surprise jumps.A Markov pure jump model is formulated on making variance gamma parameters deterministic functions of the price level.Estimation is done by matrix exponentiation of the transition rate matrix for a continuous time finite state Markov chain approximation.The motion is decomposed into a space dependent drift and a space dependent martingale component.Though there is some local mean reversion in the drift,space dependence of the martingale component renders the dynamics to be of the momentum type.Local risk is measured using market calibrated measure distortions that introduce risk charges into the lower and upper prices of two price economies.These risks are compensated by the exponential variation of space dependent arrival rates.Estimations are conducted for the S&P 500 index(SPX),the exchange traded fund for the financial sector(XLF),J.P.Morgan stock prices(JPM),the ratio of JPM to XLF,and the ratio of XLF to SPX.展开更多
Modeling of uncertainty by probability errs by ignoring the uncertainty in probability.When financial valuation recognizes the uncertainty of probability,the best the market may offer is a two price framework of a low...Modeling of uncertainty by probability errs by ignoring the uncertainty in probability.When financial valuation recognizes the uncertainty of probability,the best the market may offer is a two price framework of a lower and upper valuation.The martingale theory of asset prices is then replaced by the theory of nonlinear martingales.When dealing with pure jump compensators describing probability,the uncertainty in probability is captured by introducing parametric measure distortions.The two price framework then alters asset pricing theory by requiring two required return equations,one each for the lower upper valuation.Proxying lower and upper valuations by daily lows and highs,the paper delivers the first empirical study of nonlinear martingales via the modeling and simultaneous estimation of the two required return equations.展开更多
Asset returns are modeled by locally bilateral gamma processes with zero covariations.Covariances are then observed to be consequences of randomness in variations.Support vector machine regressions on prices are emplo...Asset returns are modeled by locally bilateral gamma processes with zero covariations.Covariances are then observed to be consequences of randomness in variations.Support vector machine regressions on prices are employed to model the implied randomness.The contributions of support vector machine regressions are evaluated using reductions in the economic cost of exposure to prediction residu-als.Both local and global mean reversion and momentum are represented by drift dependence on price levels.Optimal portfolios maximize conservative portfolio val-ues calculated as distorted expectations of portfolio returns observed on simulated path spaces.They are also shown to outperform classical alternatives.展开更多
Joint densities for a sequential pair of returns with weak autocorrelation and strong correlation in squared returns are formulated.The marginal return densities are either variance gamma or bilateral gamma.Two-dimens...Joint densities for a sequential pair of returns with weak autocorrelation and strong correlation in squared returns are formulated.The marginal return densities are either variance gamma or bilateral gamma.Two-dimensional matching of empirical characteristic functions to its theoretical counterpart is employed for dependency parameter estimation.Estimations are reported for 3920 daily return sequences of one thousand days.Path simulation is done using conditional distribution functions.The paths display levels of squared return correlation and decay rates for the squared return autocorrelation function that are comparable to these magnitudes in daily return data.Regressions of log characteristic functions at different time points are used to estimate time scaling coefficients.Regressions of these time scaling coefficients on squared return correlations support the view that autocorrelation in squared returns slows the rate of passage of economic time.An analysis of financial markets for 2020 in comparison with 2019 displays a post-COVID slowdown in financial markets.展开更多
文摘There are two broad objectives of the research reported in this paper. First, we assess whether government-provided cyber threat intelligence (CTI) is helpful in preventing, or responding to, cyber-attacks among small businesses within the U.S. Defense Industrial Base (DIB). Second, we identify ways of improving the effectiveness of government-provided CTI to small businesses within the DIB. Based on a questionnaire-based survey, our findings suggest that government-provided CTI helps businesses within the DIB in preventing, or responding to, cyber-attacks providing a firm is familiar with the CTI. Unfortunately, a large percentage of small firms are not familiar with the government-provided CTI feeds and consequently are not utilizing the CTI. This latter situation is largely due to financial constraints confronting small businesses that prevent firms from having the wherewithal necessary to effectively utilize the government-provided CTI. However, we found a significant positive association between a firm’s familiarity with the government-provided CTI and whether a firm is being periodically reviewed by the Defense Counterintelligence and Security Agency (DCSA) or is compliant with the Cybersecurity Maturity Model Certification (CMMC) program. The findings from our study also show that the participating firms believe that external cyber threats are more likely to be the cause of a future cybersecurity breach than internal cybersecurity threats. Finally, our study found that the portion of the IT budget that small businesses within the DIB spend on cybersecurity-related activities is dependent on the perception that a firm would be the target of an external cyber-attack.
文摘Cyber security breaches inflict costs to consumers and businesses. The possibility also exists that a cyber security breach may shut down an entire critical infrastructure industry, putting a nation’s whole economy and national defense at risk. Hence, the issue of cyber security investment has risen to the top of the agenda of business and government executives. This paper examines how the existence of well-recognized externalities changes the maximum a firm should, from a social welfare perspective, invest in cyber security activities. By extending the cyber security investment model of Gordon and Loeb [1] to incorporate externalities, we show that the firm’s social optimal investment in cyber security increases by no more than 37% of the expected externality loss.
基金Shanghai Style Fashion Design&Value Creation Knowledge Service Center,China(No.ZX201311000031)Shanghai Style Fashion Trend Research Based on Knowledge Management of the Fundamental Research Funds for the Central Universities,China(No.15D110719)Shanghai Style Fashion Trend Research Based on Cloud Computing of the Fundamental Research Funds for the Central Universities,China(No.15D11073)
文摘Among the existing researches on brand value,few of them focused on the demands of the companies in the clothing industry to brand value. There were three innovation points as follows: first of all,two key demands of apparel companies to existing brand value were summarized through investigation; then,the concept of rapid brand value evaluation and multi-dimensional factors( MDFs) was presented; finally,the relationship between apparel corporate brand value and the sales revenue in apparel market with the sales revenue was proven by empirical research.During the process of empirical study,the sales revenue data of 66 apparel enterprises domestic and abroad were collected,and the regression analysis has been done on the relationship between the corporate brand value and the apparel market sales revenue of apparel enterprise. The empirical research showed that they were positively correlated to each other. This conclusion presented a method of judging brand value development trend quickly by single indicator.
文摘Investments in cybersecurity are critical to the national and economic security of a nation. There is, however, a strong tendency for firms in the private sector to underinvest in cybersecurity activities. This paper reports the results of a survey designed to empirically assess whether treating cybersecurity as an important component of a firm’s internal control system for financial reporting purposes serves as a driver for private sector firms to invest in cybersecurity activities. The findings, in this regard, are significantly positive. The study also shows that a firm’s concern over the risk of incurring a large loss due to a cybersecurity breach and the degree the firm treats cybersecurity investments as generating a competitive advantage are drivers of the level of private sector investment in cybersecurity activities. The implications of the empirical results for designing public policies to mitigate the tendency of private sector firms to underinvest in cybersecurity are also explored.
文摘This paper extends the literature on the economics of sharing cybersecurity information by and among profit-seeking firms by modeling the case where a government agency or department publicly shares unclassified cyber threat information with all organizations. In prior cybersecurity information sharing models a common element was reciprocity—i.e., firms receiving shared information are also asked to share their private cybersecurity information with all other firms (via an information sharing arrangement). In contrast, sharing of unclassified cyber threat intelligence (CTI) by a government agency or department is not based on reciprocal sharing by the recipient organizations. After considering the government’s cost of preparing and disseminating CTI, as well as the benefits to the recipients of the CTI, we provide sufficient conditions for sharing of CTI to result in an increase in social welfare. Under a broad set of general conditions, sharing of CTI will increase social welfare gross of the costs to the government agency or department sharing the information. Thus, if the entity can keep the sharing costs low, sharing cybersecurity information will result in an increase in net social welfare.
文摘Given the importance of cybersecurity to the survival of an organization, a fundamental economics-based question that must be addressed by all organizations is: How much should be invested in cybersecurity related activities? Gordon and Loeb [1] presented a model to address this question, and that model has received a significant amount of attention in the academic and practitioner literature. The primary objective of this paper is to discuss the Gordon-Loeb Model with a focus on gaining insights for the model’s use in a practical setting.
文摘This paper provides an analysis of how the benefits of information segmentation can assist an organization to derive the appropriate amount to invest in cybersecurity from a cost-benefit perspective. An analytical model based on the framework of the Gordon-Loeb Model (<span><span><span style="font-family:Verdana;">[1]</span><span></span></span></span><span><span></span></span><span></span><span><span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">) is presented that provides a set of sufficient conditions for information segmentation to lower the total investments in cybersecurity and the expected loss from cybersecurity breaches. A numerical example illustrating the insights gained from the model is also presented.</span></span></span>
文摘The spirit of now in nowcasting suggests expanding the current to include the near future.Decision theory is then developed by incorporating the consequences of actions into the present.With the future falling into the present discounting it is no longer permitted.Value functions are then observed to be determinate only up to scale and shift that are then locked down by fixing values arbitrarily in two selected states,much like declaring water to freeze and boil at zero and a hundred degrees celsius.The locked down value functions associated policy functions are seen to exist in decision contexts in where the only time is now.Examples are studied in univariate and multivariate dimensions for the decision state space and the dimension of shocks delivering state transitions.The policy functions are expanded from realisitic training sets to the full state space using Gaussian Process Regression.They are implemented on real data with reported performances.
文摘Risks embedded in asset price dynamics are taken to be accumulations of surprise jumps.A Markov pure jump model is formulated on making variance gamma parameters deterministic functions of the price level.Estimation is done by matrix exponentiation of the transition rate matrix for a continuous time finite state Markov chain approximation.The motion is decomposed into a space dependent drift and a space dependent martingale component.Though there is some local mean reversion in the drift,space dependence of the martingale component renders the dynamics to be of the momentum type.Local risk is measured using market calibrated measure distortions that introduce risk charges into the lower and upper prices of two price economies.These risks are compensated by the exponential variation of space dependent arrival rates.Estimations are conducted for the S&P 500 index(SPX),the exchange traded fund for the financial sector(XLF),J.P.Morgan stock prices(JPM),the ratio of JPM to XLF,and the ratio of XLF to SPX.
基金Received 15 October 2021Accepted 16 March 2022Early access 25 March 2022。
文摘Modeling of uncertainty by probability errs by ignoring the uncertainty in probability.When financial valuation recognizes the uncertainty of probability,the best the market may offer is a two price framework of a lower and upper valuation.The martingale theory of asset prices is then replaced by the theory of nonlinear martingales.When dealing with pure jump compensators describing probability,the uncertainty in probability is captured by introducing parametric measure distortions.The two price framework then alters asset pricing theory by requiring two required return equations,one each for the lower upper valuation.Proxying lower and upper valuations by daily lows and highs,the paper delivers the first empirical study of nonlinear martingales via the modeling and simultaneous estimation of the two required return equations.
文摘Asset returns are modeled by locally bilateral gamma processes with zero covariations.Covariances are then observed to be consequences of randomness in variations.Support vector machine regressions on prices are employed to model the implied randomness.The contributions of support vector machine regressions are evaluated using reductions in the economic cost of exposure to prediction residu-als.Both local and global mean reversion and momentum are represented by drift dependence on price levels.Optimal portfolios maximize conservative portfolio val-ues calculated as distorted expectations of portfolio returns observed on simulated path spaces.They are also shown to outperform classical alternatives.
文摘Joint densities for a sequential pair of returns with weak autocorrelation and strong correlation in squared returns are formulated.The marginal return densities are either variance gamma or bilateral gamma.Two-dimensional matching of empirical characteristic functions to its theoretical counterpart is employed for dependency parameter estimation.Estimations are reported for 3920 daily return sequences of one thousand days.Path simulation is done using conditional distribution functions.The paths display levels of squared return correlation and decay rates for the squared return autocorrelation function that are comparable to these magnitudes in daily return data.Regressions of log characteristic functions at different time points are used to estimate time scaling coefficients.Regressions of these time scaling coefficients on squared return correlations support the view that autocorrelation in squared returns slows the rate of passage of economic time.An analysis of financial markets for 2020 in comparison with 2019 displays a post-COVID slowdown in financial markets.
