Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions

To enhance environmental sustainability, many countries will electrify their transportation systems in their future smart city plans. So the number of electric vehicles (EVs) running in a city will grow significantly. There are many ways to re-charge EVs' batteries and charging stations will be considered as the main source of energy. The locations of charging stations are critical; they should not only be pervasive enough such that an EV anywhere can easily access a charging station within its driving range, but also widely spread so that EVs can cruise around the whole city upon being re-charged. Based on these new perspectives, we formulate the Electric Vehicle Charging Station Placement Problem (EVCSPP) in this paper. We prove that the problem is non-deterministic polynomial-time hard. We also propose four solution methods to tackle EVCSPP and evaluate their performance on various artificial and practical cases. As verified by the simulation results, the methods have their own characteristics and they are suitable for different situations depending on the requirements for solution quality, algorithmic efficiency, problem size, nature of the algorithm, and existence of system prerequisite.Comment: Submitted to IEEE Transactions on Smart Grid, revise

Direction-of-Change Forecasts for Asian Equity Markets Based on Conditional Variance, Skewness and Kurtosis Dynamics: Evidence from Hong Kong and Singapore

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-ofchange forecasts useful for market timing. We attempt to do so in the context of two key Asian equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management.

Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of-change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management

Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics: International Evidence

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management

Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management

Convex Fairness Measures: Theory and Optimization

We propose a new parameterized class of fairness measures, convex fairness measures, suitable for optimization contexts. This class includes our new proposed order-based fairness measure and several popular measures (e.g., deviation-based measures, Gini deviation). We provide theoretical analyses and derive a dual representation of these measures. Importantly, this dual representation renders a unified mathematical expression and a geometric characterization for convex fairness measures through their dual sets. Moreover, we propose a generic framework for optimization problems with a convex fairness measure objective, including reformulations and solution methods. Finally, we provide a stability analysis on the choice of convex fairness measures in the objective of optimization models

A systematic review and meta-analysis of psychosocial interventions aiming to reduce risks of suicide and self-harm in psychiatric inpatients

Psychosocial interventions, such as Cognitive Behavioural Therapy (CBT), are often recommended in UK clinical guidelines to reduce suicidality and self-harm in service users with serious mental health problems, but the effectiveness of these interventions in acute mental health inpatient settings is not established. The aim of this study is to examine the types, and effectiveness of psychosocial interventions in inpatients settings in reducing the risk of self-harm and suicidality. A systematic review and meta-analysis was conducted of randomised controlled trials (RCTs) examining the efficacy of suicide and self-harm focused inpatient psychosocial interventions on suicidality (primary outcome), depression, hopelessness and suicide attempts (secondary outcomes). A total of ten studies met eligibility criteria were included in this review. All had low to moderate risk of bias for majority of the indicators, except for blinding of participants where all studies had high risk of bias. All studies examined psychosocial interventions for suicide reduction and none examined a psychosocial intervention for self-harm. The majority of the psychosocial interventions were CBT and Dialectical Behavioural Therapy (DBT). The interventions were no more effective than control treatments in reducing suicidality, depression, hopelessness or suicide attempts post-therapy and at follow-up. However, the majority were small pilot or feasibility RCTs. In conclusion, the findings from this review suggests that psychosocial interventions are not any more effective in reducing suicidality in acute mental health inpatient settings than control interventions. However, a large-scale RCT examining a psychosocial intervention for suicide is needed to provide conclusive findings. There were also no identified RCTs examining self-harm interventions indicating a need to conduct research in this area