Empirical Analysis Impact of Inflation Dynamics on Financial Market Performance

The paper investigates how inflation affects financial market performance in the United States. Motivated by pronounced market volatility in 2023 following rapid Federal Reserve rate hikes, the study emphasizes the enduring importance and complexity of inflation for economic stability and financial markets. It frames inflation as a central factor influencing stock indices and investor behavior, noting historical shocks such as the 2008 financial crisis and COVID-19. The purpose is to quantify the relationship between inflation (proxied by CPI) and market indices (NASDAQ and S&P 500) over 2000–2023, and to evaluate how this relationship changes around major events.

The review highlights theoretical and empirical links between inflation and financial markets. Huybens and Smith (1999) show positive correlations between real activity, bank lending, and trading volume, alongside long-run negative relationships between inflation, financial activity, and real equity returns. Boyd, Levine, and Smith (2001) find a negative, nonlinear link between inflation and banking/stock market development. Bryan and Cecchetti (1993) stress careful construction of CPI measures and dynamic factor models for common inflation components. Dunbar and Owusu-Amoako (2023) address forecasting short-term inflation via adjustments to the HNKPC with hedging considerations. Bundick and Smith (2018) document improved U.S. inflation expectations post numeric target communication, contrasting with Japan. Thiel (2001) notes the financial sector’s role in growth. Cochrane (2017) discusses macro-finance mechanisms beyond interest rate movements, and Bodie (1979) analyzes inflation risk, portfolio behavior, and interest rates. The paper aims to contribute via regression analysis, heterogeneity assessment over two decades, and policy implications for markets.

Study scope: United States, 2000–2023. Data source: Federal Reserve Economic Data (FRED). Variables: Explanatory variable is inflation proxied by CPI (with a robustness alternative using the Median CPI). Dependent variables are financial market performance indicators: NASDAQ Index and S&P 500 Index. Descriptive statistics (sample sizes vary by series) indicate broad increases over time with notable volatility around major crises. Model: Linear regression of market index levels on inflation: Y_i = b0 + b1 X_i + ε_i, where Y_i is a market index (NASDAQ or S&P 500) and X_i is CPI (or Median CPI in robustness). Analyses include: (1) correlation analysis between CPI and stock indices to visualize direction/strength of association and identify deviations during shock events; (2) benchmark regression estimating the effect of CPI on NASDAQ; (3) robustness tests replacing CPI with Median CPI and NASDAQ with S&P 500; (4) temporal heterogeneity analysis splitting the sample around major events (pre–Aug 2007 financial crisis, post-2007 to pre–Jan 2020 COVID-19, and post–Jan 2020) to assess changes in CPI’s impact on market indices.

- Correlation analysis: CPI and stock indices (especially NASDAQ) show a predominantly positive co-movement over 2000–2023, with notable deviations during “black swan” events such as the 2008 crisis and COVID-19. - Benchmark regression (Table 2): CPI has a positive and statistically significant association with the NASDAQ Index. Coefficient ≈ 221.5956 (SE 26.4428), R^2 ≈ 0.7141, N = 282. - Robustness tests (Table 2): - Replacing CPI with Median CPI yields a significant positive coefficient ≈ 1424.7323 (SE 10.9177), R^2 ≈ 0.2986, N = 282. - Using S&P 500 as the dependent variable yields a significant positive coefficient ≈ 66.1847 (SE 31.9382), R^2 ≈ 0.7895, N = 118. These results support the robustness of a positive inflation–market relationship. - Temporal heterogeneity (Table 3): - Pre–Aug 2007: Negative and significant coefficient ≈ −34.1385 (t ≈ −2.1093), R^2 ≈ 0.0476, N = 91, indicating CPI negatively related to NASDAQ. - Aug 2007 to Jan 2020: Positive and highly significant coefficient ≈ 329.8423 (t ≈ 37.7718), R^2 ≈ 0.9066, N = 149, indicating strong positive relationship. - Post–Jan 2020 (COVID-19 period): Coefficient ≈ 53.5506 (t ≈ 1.2619), not statistically significant; R^2 ≈ 0.0383, N = 42, indicating no substantial correlation.

The findings address the core question by showing that inflation, proxied by CPI, generally correlates positively with U.S. equity market performance, particularly after the 2007–2008 financial crisis and before COVID-19. This suggests periods when inflation co-moves with broader economic strength and market valuations. However, the relationship is not stable across time: it was negative before August 2007 and became statistically insignificant during the COVID-19 era, reflecting regime changes and the influence of extraordinary shocks and policy interventions. The robustness checks across alternative inflation measures (Median CPI) and indices (S&P 500) reinforce that the positive link is not an artifact of a specific series. These results are relevant for policymakers and investors, implying that the impact of inflation on markets depends on macro-financial regimes and crisis periods, and that policy communications and expectations management may shape market responses to inflation dynamics.

The study concludes that CPI is generally positively associated with U.S. financial market performance, as evidenced by significant benchmark regressions and corroborated through robustness tests using Median CPI and the S&P 500. Temporal heterogeneity analysis reveals that this relationship shifts across regimes: negative before the 2007 crisis, strongly positive from the 2007 crisis until just before COVID-19, and not significant after COVID-19’s onset. The paper underscores that the inflation–market nexus is dynamic rather than uniformly positive. Future research directions include expanding macro- and micro-level analyses (households and firms), incorporating additional factors such as currency, savings rates, and labor markets, and improving predictive models for market behavior under inflation/deflation. The authors also propose using mathematical and statistical simulations on historical data to isolate inflation’s effects, evaluating anti-inflationary policy effectiveness, and assessing governmental countermeasures using derivatives and firm-level financial data to inform policy and investment strategies.