A new behavioral finance mean variance framework

PurposeThe author proposes an update to the mean variance (MV) framework that replaces a constant risk aversion parameter using a dynamic risk aversion indicator. The contribution to the literature is made through making the static risk aversion parameter operational using an indicator of market sentiment. Results suggest that Sharpe ratios improve when the author replaces the traditional risk aversion parameter with a dynamic sentiment indicator from the behavioral finance literature when allocating between a risky portfolio and a risk-free asset. However, results are mixed when using the behavioral framework to allocate between two risky assets.Design/methodology/approachThe author includes a dynamic risk aversion parameter in the mean variance framework and back test using the traditional and updated behavioral mean variance (BMV) framework to see which framework leads to better performance.FindingsThe author finds that the behavioral framework provides superior performance when allocating between a risky and risk-free asset; however, it under performs when allocating between risky assets.Research limitations/implicationsThe research is based on back testing; therefore, it cannot be concluded that this strategy will perform well in real-time circumstances.Practical implicationsPortfolio managers may use this strategy to optimize the allocation between a risky portfolio and a risk-free asset.Social implicationsAn improved allocation between risk-free and risky assets that could lead to less leverage in the market.Originality/valueThe study is the first to use such a sentiment indicator in the traditional MV framework and show the math.

An Adaptive, Situation-Based Risk Assessment and Security Enforcement Framework for the Maritime Sector

Maritime processes involve actors and systems that continuously change their underlying environment, location and threat exposure. Thus, risk mitigation requires a dynamic risk assessment process, coupled with an adaptive, event driven security enforcement mechanism, to efficiently deal with dynamically evolving risks in a cost efficient manner. In this paper, we propose an adaptive security framework that covers both situational risk assessment and situational driven security policy deployment. We extend MITIGATE, a maritime-specific risk assessment methodology, to capture situations in the risk assessment process and thus produce fine-grained and situation-specific, dynamic risk estimations. Then, we integrate DynSMAUG, a situation-driven security management system, to enforce adaptive security policies that dynamically implement security controls specific to each situation. To validate the proposed framework, we test it based on maritime cargo transfer service. We utilize various maritime specific and generic systems employed during cargo transfer, to produce dynamic risks for various situations. Our results show that the proposed framework can effectively assess dynamic risks per situation and automate the enforcement of adaptive security controls per situation. This is an important improvement in contrast to static and situation-agnostic risk assessment frameworks, where security controls always default to worst-case risks, with a consequent impact on the cost and the applicability of proper security controls.

Predictive validity of Stable-2007 in incarcerated samples

Some are unclear whether risk assessment instruments, specifically dynamic risk instruments, have demonstrated utility in the risk estimation, treatment recommendations, and monitoring change over time in men at risk for or under sentence of Indeterminate Detention (ID) for sexual offenses. We compare two datasets, the first consisting of individuals representing a routine sample of persons convicted of a sexual offense and the second of men representative of a high risk/needs sample. These two distinct samples (n = 442, mean Static-99R score = 2.4; n = 168, mean Static-99R score 4.5) were then also scored on the Stable-2007. For both groups this scoring occurred in an institutional setting. The Stable-2007 predicted sexual recidivism in Sample 1 independently and in conjunction with the Static-99R. In the high-risk sample the results were the same. In both samples a compound outcome variable (Sexual + Violent reoffense) was also calculated with the Stable-2007 predicting the compound outcome variable in Sample 1 but not Sample 2. This is interesting in that it suggests that the Stable-2007 assesses constructs specific to sexual re-offense in higher risk offenders and not general traits of violence or common anti-social behaviour. Limitations and directions for further research are discussed.

Stable-2007 and indeterminate detention

Public safety is the primary reason to assess future risk in men with a history of sexual offending. Over the last twenty-five years our knowledge of, and ability to assess, dynamic risk factors in men with a history of sexual offending has meaningfully improved, but understanding, adoption, utilization, and reasonable implementation of the fruits of this new knowledge is not universal. This article presents a brief overview of the development of dynamic risk assessment for men with a history of sexual offending, primarily following the work of R. Karl Hanson and his associates. This is followed by a review of a meta-analysis on the reliability and validity of STABLE-2007 and two other independent studies that provide useful ancillary information. Utilizing STABLE-2007 with men faced with, or under sanction of indeterminate detention is the focus of this paper and we will review how mental health diagnoses affect recidivism assessment, some concerns about implicit assessment biases, how to employ stable dynamic assessment in secure facilities, address treatment implications resulting from dynamic assessment, and present ideas for future research. I will close by presenting nine (9) arguments why using STABLE-2007 is recommended practice with indeterminate detention populations.