In January 2020, prior to the onset of the global coronavirus (COVID-19) pandemic, three of the seven largest economies by GDP had negative yields for two-year government bonds (Japan, Germany and France). With the onset of the pandemic, two-year bond yields in these countries actually rose slightly - in contrast to the other major economies, where yields fell over this period. As of December 2024, yields for two-year government bonds exhibited fluctuations across all countries. Notably, Japan showed a slight upward trend, while China experienced a modest decline.Negative yields assume that investors lack confidence in economic growth, meaning many investments (such as stocks) may lose value. Therefore, it is preferable to take a small loss on government debt that carries almost no risk to the investor, than risk a larger loss on other investments. As both the yen and euro are considered very safe assets, Japanese, German and French bonds were already being held by many investors prior to the pandemic as a hedge against economic downturn. Therefore, with the announcement of fiscal responses to the pandemic by many governments around March 2020, the value of these assets rose as confidence increased (slightly) that the worst case may be avoided. At the same time, yields on bonds with a higher return fell, as investors sought out investments with a higher return that were still considered safe.

As of December 2024, the countries with the highest 10-year yields are the United Kingdom, the United States and Australia with 4.68, 4.38 and 4.21 percent, respectively. Of the largest economies by GDP, the United States saw the sharpest fall in absolute terms for 10-year government bond yields due to the coronavirus (COVID-19) pandemic. From a level of 1.51 percent in January 2020, yields on 10-year government bonds fell to 0.65 percent by April 2020, and had further fallen to 0.53 percent by July 2020 before starting to recover towards the end of the year. Conversely, countries that went into 2020 with already low bond yields like Japan, Germany and France actually saw a small increase in March 2020 - although these already low yields mean that these small changes are significant in relative terms.

In 2024, China’s level of total investment reached around 40.4 percent of the gross domestic product (GDP). This value is expected to remain stable in 2025 and increase slightly in the following years. Final consumption accounted for 55.7 percent in 2023. International comparison of total investments The GDP of a country can be calculated by the expenditure approach, which sums up final consumption (private and public), total investment, and net exports. The ratio of consumption to investment may vary greatly between different countries.Matured economies normally consume a larger share of their economic output. In the U.S. and many European countries, total investment ranges roughly at only 20 to 25 percent of the GDP. In comparison, some emerging economies reached levels of 30 to 40 percent of investment during times of rapid economic development. Level of total investment in China China is among the countries that spend the highest share of their GDP on investments. Between 1980 and 2000, 30 to 40 percent of its economic output were invested, roughly on par with South Korea or Japan. While the latter’s investment spending ratio decreased in later years, China’s even grew, especially after the global financial crisis, peaking at staggering 47 percent of GDP in 2011.However, returns on those investments declined year by year, indicated by lower GDP growth rates. This resulted in a quickly growing debt burden, which reached nearly 285 percent of the GDP in 2023, up from only 135 percent in 2008. The Chinese government defined the goal to shift to consumption driven growth, but the transformation takes longer than expected.

Using all stocks listed in the Tokyo Stock Exchange and macroeconomic data for Japan, the dataset comprises the following series:

1. Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
2. Monthly returns for 20 momentum portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
3. Monthly returns for 25 price-to-cash flow-dividend yield portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
4. Fama and French three-factors (RM, SMB and HML), following the Fama and French (1993) methodology. (Raw data source: Datastream database)
5. Fama and French five-factors (RM, SMB, HML, RMW, and CMA), following the Fama and French (2015) methodology for all factors, except for RMW, which is determined using the return on assets as sorting variable, as in Hou, Xue and Zhang (2014). (Raw data source: Datastream database)
6. Private final consumption expenditure, in national currency and constant prices, non-seasonally adjusted, for Japan. (Raw data source: OECD)
7. Consumer Confidence Index (CCI) for Japan. (Raw data source: OECD)
8. Three-month interest rate of the Treasury Bill for Japan. (Raw data source: OECD)
9. Gross Domestic Product (GDP) for Japan. (Raw data source: OECD)
10. Consumer Price Index (CPI) growth rate for Japan. (Raw data source: OECD)

We have produced all return series using the following data from Datastream: (i) total return index (RI series), (ii) market value (MV series), (iii) market-to-book equity (PTBV series), (iv) total assets (WC02999 series), (v) return on equity (WC08301 series), (vi) price-to-cash flow ratio (PC series), and (vii) dividend yield (DY series). We have used the generic rules suggested by Griffin, Kelly, & Nardari (2010) for excluding non-common equity securities from Datastream data. We also exclude stocks with less than twelve observations in the period from July 1992 to June 2018. Accordingly, our sample comprises a total number of 5,312 stocks.

REFERENCES:

Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56. Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116, 1–22. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do market efficiency measures yield correct inferences? A comparison of developed and emerging markets. Review of Financial Studies, 23, 3225–3277. Hou K, Xue C, Zhang L. (2014). Digesting anomalies: An investment approach. Review of Financial Studies, 28, 650-705.