Table 3.
Parameter estimates for univariate models.
| Asia | Europe | USA | |
|---|---|---|---|
| Model | 2S-MSIAH | 2S-MSIH | 2S-MSIAH |
| μ1 | 0.10* (0.06) | 0.18*** (0.04) | −0.03 (0.06) |
| μ2 | −0.72*** (0.26) | −0.17 (0.14) | 0.03 (0.15) |
| β1 | 0.58*** (0.07) | 0.10 (0.10) | |
| β2 | 0.12 (0.16) | 0.29*** (0.11) | |
| σ1 | 0.40*** (0.04) | 0.12*** (0.02) | 0.35*** (0.06) |
| σ2 | 1.48*** (0.33) | 1.80*** (0.26) | 1.78*** (0.32) |
| Duration 1 | 143.38 | 9.11 | 10.33 |
| Duration 2 | 32.69 | 2.72 | 7.68 |
This table reports the parameter estimates of the univariate 2-state Markov switching models for the daily flow of ETFs with exposure to Asia, Europe, and U.S. The model choice (MSIAH Vs. MSIH) is based on the lowest AIC and BIC score from Table 2. The general MSIAH model is specified as yt = mSt + bStyt−1 + et, where yt refers to a vector of individual location flows, mStrepresents the conditional mean in each state (1 and 2), and sStshows the conditional volatility of each state. bSt denotes the first-order autoregressive term and et shows the residuals. The MSIH model is a special form of MSIAH where bSt = 0. Duration shows the respective duration of being in one regime during the period of the study. The sample period is from January 2020 to October 2020. The parentheses contain the standard error. *, **, and ***, respectively, denote significance at the 10%, 5%, and 1% levels.