Portfolio Optimization Across Risk, Returns, and Climate

Use MATLAB and the Computational Finance Suite of tools to model climate effects on portfolio risks and returns. Related products: Climate Data Toolbox for MATLAB: https://bit.ly/3sJdEvC MATLAB Computational Finance Suite: https://bit.ly/3lqgHF4 MATLAB: https://bit.ly/3LCwY4i Learn how to leverage portfolio optimization models in conjunction with climate data while balancing the demands of transparency, scalability, and model risk management. Climate data and optimization can impact the bottom line of organizations by tilting portfolios in a targeted way. Building advanced analytics and machine learning models on top of these factor repositories of climate data can improve business decisions. Some tasks that stand to gain the most from such improvements include risk mitigation, trading opportunity identification, customer goal-based investing, and forecasting risk across complex multibillion-dollar instrument portfolios. However, implementation at scale and with compliance is daunting to most financial institutions at all levels of Assets Under Management (AUM).