1. Introduction
1.1 Executive Summary
Factor investing has become widely popular across a broad swathe of investment strategies in the last three decades. The focus has been on fundamental factor models which were designed for equities and other linear instruments. Until now, macroeconomic factor models and macro effects were largely ignored as computational power and techniques had to catch up to statistical requirements. In this paper, we introduce Quant Insight’s (Qi) cutting-edge macro factors as vital and unique tools in the efforts to identify, understand and control the macroeconomic risks whipsawing portfolios in the post COVID world.
A factor can be thought of as any characteristic relating to a group of stocks that is important in explaining their return and risk. Extensive academic research has shown the validity of the style factor approach, viz that certain factors, effectively intrinsic stock characteristics, have historically earned a long-term risk premium and represent exposure to systematic sources of risk. Common “equity risk premia” factors include Value, Low Size, Low Volatility, High Yield, Quality and Momentum.
Style Factors work over the long term but shorter term, the market is more and more driven by macroeconomic indicators that change at much shorter frequencies and drive prices. Qi gathers a broad range of macro factors and builds models that demonstrate their strong explanatory power over security prices. These factors include GDP growth, interest rates, FX, commodity prices, credit spreads, inflation rates and risk indicators.
Critically, Qi’s macro factors are not intrinsic to stocks. They are “environmental” factors that may be dynamic and shift over time. A stock may begin the year being positively related to GDP growth but by the end of the year that relationship could have gradually changed to a negative sensitivity, reflecting a change in the prevailing market regime. The dynamic nature of these macro factor relationships, the interrelatedness of macro factors themselves and the infrequent nature of data releases has stymied the development of solutions despite the dominance of macro in day-to-day market moves.
Qi presents a novel solution to control macro risk and improve portfolio risk adjusted returns. In this paper we will introduce Qi macro factors, discuss Qi’s modelling method to attribute returns and risk to macro factors and showcase practical applications.
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