Table 2.

The effect of exchange rate on Japanese stock returns. This table reports predictability test results based on the following time-series regression model:

$S{R}_t=\alpha +\beta E{R}_t+\delta V_t+{\epsilon }_t$

Where $S{R}_t$ is the Japanese stock market returns proxied using the Nikkei stock price index (log percentage returns are computed), $E{R}_t$ is the Yen–US dollar exchange rate such that an increase denotes a depreciation of the Japanese Yen, $V_t$ is the conditional variance and the model’s innovations, ${\epsilon }_t$, follow a Student t distribution, and ${\epsilon }_t=V_t{u}_t$. Following Bollerslev (1986), the conditional volatility is obtained as $V_t={\rho }_0+{\rho }_1{\epsilon }_{t-1}^2+{\rho }_2{V}_{t-1}$, where ${\rho }_s$ (s $=$ 0,1,2) are parameters to be estimated and the sum of non-intercept terms are less than one. To obtain robust estimates of the standard errors we estimate the model using the quasi maximum likelihood function (QMLF) of Bollerslev and Wooldridge (1992). We only report the main slope coefficient relating to $\beta$$=$ 0 for three sample periods: COVID-19 sample (31/12/2019 to 17/8/2020); pre-COVID-19 Sample A (04/1/2010 to 30/12/2019); and pre-COVID-19 Sample B (31/12/2018 to 16/8/2019). Here, DOW is day-of-the-week and GOIL is oil price growth. Standard errors are reported in parenthesis.

	Panel A: QMLF			Panel B: QMLF with control for endogeneity
Sample periods	No controls	DOW controls	DOW$+$GOIL controls	No controls	DOW controls	DOW$+$GOIL controls
COVID-19 sample	1.5510⁎⁎⁎ (0.1309)	1.5216⁎⁎⁎ (0.1615)	1.4624⁎⁎⁎ (0.1631)	1.6836⁎⁎⁎ (0.2295)	1.7052⁎⁎⁎ (0.2358)	1.7408⁎⁎⁎ (0.2514)
		$R^2=7.80\text{\%}$				$R^2=7.94\text{\%}$
Pre-COVID-19 Sample A	1.1621⁎⁎⁎ (0.0283)	1.1655⁎⁎⁎ (0.0284)	1.1740⁎⁎⁎ (0.0285)	1.2766⁎⁎⁎ (0.030)	1.2819⁎⁎⁎ (0.0425)	1.3216⁎⁎⁎ (0.0438)
		$R^2=30.67\text{\%}$				$R^2=31.06\text{\%}$
Pre-COVID-19 Sample B	1.0887⁎⁎⁎ (0.1219)	1.1175⁎⁎⁎ (0.1218)	1.1703⁎⁎⁎ (0.1264)	1.2611⁎⁎⁎ (0.1853)	1.3310⁎⁎⁎ (0.1773)	1.3796⁎⁎⁎ (0.1982)
		$R^2=36.16\text{\%}$				$R^2=36.12\text{\%}$

^***Denotes statistical significance at the 1% level.