Abstract/Summary

This thesis explores the relationship between (a) the performance of the sub-sector indices of the US Information Technology sector and (b) a set of macroeconomic variables. More specifically, the study analyses the relationships between, on the one hand, the indices of US Software & Services, US Hardware & Equipment, and US Semiconductors & Semiconductor Equipment and, on the other, the US money supply, US manufacturing activity, US long-term real interest rates and US inflation. Monthly index and macroeconomic data were collected for the timeframe studied: 31 December 1998–31 January 2022. The Johansen cointegration analysis and the Vector Error Correction Model (VECM) are used to determine long-term relationships. Given the dramatic change in Software, Hardware and Semiconductor companies’ business models following the Global Financial Crisis (GFC), the analysis is split into pre- and post-GFC periods. The approach used is a differentiating one in which the design of an econometric model is determined both by a bottom-up, fundamental analysis and by the author’s practitioner experience. Results suggest a stable, long-term relationship between sub-sector indices and macroeconomic variables. All sub-sector indices show a positive relationship with money supply both pre- and post-GFC. The Semiconductors index exhibits a positive relationship with manufacturing activity pre-GFC yet a negative one post-GFC: attributable to structural changes in the Semiconductors sub-sector. The Software index shows a positive cointegration coefficient with long-term real interest rates both pre- and post-GFC, a particularly surprising finding of this study. While the relationship between the Hardware index and inflation is not statistically significant pre-GFC, the index shows a positive relationship with inflation post-GFC. This is an expected outcome which is driven by an increased dependence of Hardware firms on consumer spending after the launch of the first iPhone in 2007. This study closes a gap in the academic literature by analysing sub-sector indices and thereby expanding the discussion – by going beyond composite and sector indices – on the impact of macroeconomic variables on stock market indices. This is also one of only a handful of papers to analyse in detail the macroeconomic performance drivers of the Information Technology sector. The research will assist asset managers in better understanding the impact of macroeconomic factors on the performance of Software, Hardware and Semiconductor stocks. For investors, an appreciation of the findings of this thesis will benefit their investment frameworks, allowing them to take more informed decisions and consequently generate better risk-adjusted returns.