Volatility and Dependence Dynamics between Money Market Funds and Kenyan Treasury Bills: An Integrated Egarch–Copula–Dcc-Garch Analysis

Abstract

Purpose: Money Market Funds (MMFs) and Treasury Bills occupy an important position in Kenya’s short-term investment market, yet their risk characteristics and interaction are not adequately described by measures that consider volatility or dependence in isolation. This study examines the volatility dynamics and dependence structure between an anonymized Kenyan MMF and 91-day, 182-day and 364-day Treasury Bills using an integrated EGARCH–copula–DCC-GARCH framework.

Methodology: The analysis uses 140 matched monthly observations covering November 2014 to July 2026.Preliminary diagnostics were conducted to asses distributional characteristics, stationarity and conditional heteroskedasticity. Competing GARCH family models were established and compared using Akaike Information Criterion, with student-t innovations used to accommodate heavy tailed distributions. Copula models were then applied to standardized residuals transformed using Probability Integral Transform, followed by DCC-GARCH models to examine time varying conditional correlations across the three Treasury Bill maturities.

Findings: Preliminary results indicate non-normal return distributions, excess kurtosis and significant ARCH effects across all four series. Among the competing symmetric and asymmetric GARCH specifications, EGARCH provides the lowest Akaike Information Criterion for each series. Student-t innovations are used to accommodate the heavy-tailed distributions. Significant asymmetric volatility effects are found for the MMF, 91-day and 364-day Treasury Bill series, while the evidence for asymmetry in the 182-day series is weaker. After filtering the marginal dynamics and applying the Probability Integral Transform, the copula analysis indicates weak residual dependence, with the independence copula providing the final representation and Kendall’s tau of approximately 0.072. No meaningful lower- or upper-tail dependence is identified after accounting for the marginal volatility processes. The DCC-GARCH results add an important dynamic dimension: conditional correlations remain generally weak but vary over time and across maturities. The 364-day Treasury Bill has the largest short-run DCC adjustment coefficient (0.188), indicating greater responsiveness of its relationship with MMFs to new information.

Unique Contribution to Theory, Practice and Policy: The findings suggest that MMFs and Treasury Bills can provide diversification opportunities, but the strength of diversification is not fixed and should be assessed with regard to maturity and market conditions. The study contributes evidence from an emerging-market setting and demonstrates the value of combining marginal volatility, residual dependence and dynamic correlation models when analyzing short-term Kenyan financial assets.