Aktiemarkedets reaktioner under inflation og deflation: En analyse af værdiansættelse (P/E), afkast samt adfærdsbaserede signaler (målt ved Google Trends)

Abstract

Purpose
This thesis investigates how inflation and deflation affect stock market valuation and returns. While prior research has primarily focused on actual and expected inflation, this study introduces a more comprehensive framework by analyzing four distinct inflation measures: actual, expected, unexpected, and implicit, and explores whether investor attention, proxied by Google Trends data, can enhance the understanding of market dynamics. The objective is to assess how different inflation and deflation environments influence forward price-to-earnings (P/E) ratios and stock returns in the U.S. stock market, based solely on data from the S&P 500.
Methodology
Following a positivist and deductive research paradigm, the analysis employs a quantitative approach. Polynomial regression is used to capture non-linear relationships between inflation measures and valuation. Inflation regimes and quartile splits based on different inflation measures are used to analyze return distributions, employing descriptive statistics such as means, standard deviations, and boxplots. In the final part of the analysis, Google Trends data are incorporated through visual time series comparisons and return pattern analysis to assess how changes in search intensity reflect collective attention and relate to shifts in market valuation and stock performance. The robustness of findings is tested through alternative model specifications and historical period splits.
Major Findings
The results indicate a general pattern in which stock market valuation (forward P/E) is highest at inflation levels close to zero, while both high inflation and deep deflation are linked to lower valuations. Expected inflation has the strongest explanatory power among the four inflation types. Stock returns are also highest under low to moderate inflation. Higher inflation is generally linked to lower returns, except for implicit inflation, which peaks around 2%. Google Trends data show that spikes in search interest for “inflation” and “deflation” often coincide with falling valuations and returns. The effect varies with context and narrative, and differs across stock types.
Academic Contribution
This thesis contributes to behavioral finance by integrating traditional macroeconomic analysis with behavior-based signals. By incorporating Google Trends data, the study explores how collective attention to inflation and deflation relates to shifts in stock valuation and returns. The approach complements existing literature by combining long-term historical data with real-time behavioral indicators.