Balazs Vajda helps develop and extend independent model-validation tools used to ensure the accuracy and granularity in backtesting practices. Prior to joining MSCI, Balazs served as a risk management intern at Morgan Stanley, while earning his master’s degree in economics at Central European University.
Research and Insights
Articles by Balazs Vajda
Backtesting Private Asset ModelsReport | Jun 19, 2020 |
MSCI’s Barra Private Real Estate Model (PRE2), Barra Private Equity Model (PEQ2) and MSCI Private Infrastructure Model (PIN1) have advanced the understanding of investments in global private assets. Private assets were once considered low-risk investments uncorrelated with most public assets due to the smoothness in private asset valuations. With innovative statistical methodology, the MSCI private asset models reveal the intrinsic risk in private assets, show large exposures to systematic...
MSCI Multi-Asset Class (MAC) Factor Model ValidationReport | May 27, 2020 |
The MSCI Multi-Asset Class (MAC) Factor Model introduces several major advances in risk modeling, including systematic MAC strategy factors, a next-generation fixed income model, and improved equity models. This document demonstrates the value of the MSCI MAC Factor Model in forecasting risk, based on (1) visual inspection of the risk forecasts and realized returns, and (2) statistical tests. The MSCI MAC Factor Model is evaluated on an absolute (stand-alone) basis, and is also compared with...
Backtesting Year in Review: A Look at 2017Report | Feb 19, 2018 |
Measures employed by risk managers and portfolio managers, such as Expected Shortfall and Value at Risk, are designed to calculate the risk level of a portfolio. But some risk models may work better than others for different asset classes and for different market conditions. Besides backtesting Value-at-Risk and Expected Shortfall, we ranked four types of simulations models available in RiskMetrics RiskManager using the MSCI Model Scorecard, an innovative tool that measures how well a model...