This paper reviews and examines the method development aspects of Al Janabi (2012) theoretical foundations and optimization algorithms for the assessment of Liquidity-Adjusted Value at Risk (LVaR) technique under adverse market conditions. This paper focuses on the development of robust...

We develop measures of certain kinds of liquidity trading risk that is useful for completing the definition of market risk and for predicting liquidity-adjusted VaR (L-VaR) under illiquid market conditions. We argue that asset liquidity risk associated with the uncertainty of liquidating...

The attempt of this article is to fill a gap in the equity trading risk management literature and particularly from the perspective of emerging and illiquid financial markets, such as in the context of the Moroccan stock market. This paper provides real-world risk management techniques and...

Measuring risk is at the center of modern financial risk management. As the world economy is becoming more complex and standard modeling assumptions are violated, the advanced artificial intelligence solutions may provide the right tools to analyze the global market. In this paper, we provide a...

FRTB proposes Indirect Approach (IA) to address data challenges during period of stress for calculating stress Expected Shortfall (ES) under Internal Model Method (IMM). Unlike other topics like Non-Modellable Risk Factors (NMRF) and Profit and Loss Attribution Test (PLAT), Indirect Approach...

Risk decomposition is a standard tool for analyzing investment portfolio risk. The portfolio is divided into notional parts—e.g., individual securities, holdings by sector or region, factor exposures—whose contributions to net risk are estimated and reported. Convention regards the...

We study issues of robustness in the context of Quantitative Risk Management and Optimization. We develop a general methodology for determining whether a given risk measurement related optimization problem is robust, which we call "robustness against optimization". The new notion is studied for...

Interest rate data are an important element of macroeconomic forecasting. Projections of future interest rates are not only an important product themselves, but also typically matter for forecasting other macroeconomic and financial variables. A popular class of forecasting models is linear...

Quasi maximum likelihood estimation of Value at Risk (VaR) and Expected Shortfall (ES) is discussed. The reference likelihood is that of a location-scale asymmetric Laplace distribution, related to a family of loss functions that lead to strictly consistent scoring functions for joint estimation...

This paper analyzes the patterns of the World Air traffic flow and shows that at equilibrium, it always meets the Geometric Brownian Motion GBM criteria. The corresponding GBM model has been used to run Monte Carlo Simulations of the projected air traffic level at the end of the year 2021. Then...