Stock market reaction to US interest rate hike: evidence from an emerging market

Abstract

This paper investigates how a developing stock market responds to US interest rate increases, using Korean firm data. We find that the Fed's sharp rate hike causes the flight to quality of investors in the emerging market. Furthermore, firms with more export sales, higher foreign ownership, and larger market capitalization outperform during a US interest rate shock. We also find that financial flexibility is particularly valuable for small-cap firms when the US aggressively raises interest rates.

1. Introduction

Inflation, triggered by the 2019 coronavirus disease (COVID-19) pandemic and the Russia–Ukraine war, poses a challenge for the global economy. The Federal Reserve (Fed) has been implementing its fastest pace of rate increases since March 2022 to curb the soaring inflation, even at the time of writing this paper. On June 15, the Fed shocked the world by raising its benchmark rate by 75 basis points (bps), as well as by signaling another big move in the following month. The Fed's aggressive path has been strengthening the US dollar compared with other currencies, and it has negatively affected the Korean stock market (Fig. 1). The small, open Korean economy is very sensitive to global economic fluctuations because of its huge dependence on exports and foreign investors. In the aftermath of the US rate hikes, foreign investors continue to leave the Korean stock market (Fig. 2). Many emerging countries have also been suffering from capital outflow due to the super-strong dollar and are facing defaults because their external debt is at record levels [1].1 Thus, special attention should be paid to emerging countries because a crisis is contagious through the globally connected financial market.2

Fig. 1.

Strong US Dollar and Weak Korean Stock Market in 2022. This figure plots the trends in the US dollar and the Korea Composite Stock Price Index (KOSPI). The real broad dollar index (orange line) and the KOSPI (blue line) are retrieved from the Fed and Korea Exchange, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2.

Foreign Investors Leaving the Korean Stock Market. This figure shows the net inflows and outflows of Korea's foreign stock investment from January to June 2022.

The goal of this paper is to understand the effect of the Fed's drastic rate hikes on emerging market stock returns. We focus our analysis on the Fed's sharp rate increases during the period from January 3, 2022, to June 30, 2022. Specifically, we have two main objectives. First, we explore how the radical steps of the Fed's monetary tightening affect the emerging stock market overall. Second, we analyze which firms perform better during the periods of the Fed's fastest rate hikes in decades. A rate hike may affect individual stock returns heterogeneously. We explore this issue mainly by focusing on export exposure and foreign ownership, which are the two most important pillars of the Korean economy. Exporting firms made Korea the world's seventh largest exporter, even during the unprecedented COVID-19 crisis. Furthermore, foreign investors have a strong influence on the Korean stock market, exceeding 30% of the total KOSPI market capitalization [2]. Finally, we investigate whether a strong financial position matters for emerging market firms during US interest rate shocks. It is well known that financial flexibility, such as enough cash holdings and less debt, plays a vital role in corporate value during crises (e.g. Ref. [3]).

We organize our primary analysis along two periods in 2022, which we label Uncertainty (January 3–May 31) and Giant-step (June 1–June 30) as the features of the two periods are different. As shown in Fig. 1, the Korean stock market experienced a dramatic plunge in January and a sharp drop in June. During the Uncertainty period, the Fed increased its rates by 25 bps in March and then 50 bps in May. However, the next extent of the rate hike was still unpredictable, and the KOSPI did not plummet during this period. In contrast, during the Giant-step period, the stock market fell dramatically from the beginning of June as the possibility of the Fed's rate hike of 75 bps was on the rise. In fact, the average capital asset pricing model (CAPM) adjusted cumulative return of our sample for Uncertainty is positive (0.0628), while that for Giant-step is negative (−0.0330), as reported in Table 1. Furthermore, during the Giant-step period, we investigate market reactions in more detail by subdividing the period into a 5-day event window (June 14–June 20) and an 11-day event window (June 9–June 23), which shows the most negative stock returns around the Fed's giant-step announcement (see Table 1). Although the Fed enacted its second consecutive 75 bps rate increase in July, we focus on the rate hike in June because the giant step in July, signaled by the Fed in advance, did not surprise markets.

Table 1.

Overview of studies on US monetary policy, stock market returns, emerging stock markets, and firm characteristics.

Authors	Sample/Data	Approach	Period	Results
Thorbecke (1997)	Center for Research in Security Prices (CRSP) database	Event study	1967–1990	Expansionary monetary policies lead to greater stock returns.
		Vector autoregression (VAR)
Bernanke and Kuttner (2005)	CRSP value-weighted equity returns	Event study	1989–2002	An unexpected 25-basis-point rate cut of the Fed leads to a 1% increase in stock prices.
		VAR
Ehrmann and Fratzscher (2004)	S&P500 constituent stocks	Event study	1994–2003	Monetary policy affects individual stocks heterogeneously depending on firms' financial constraints and investment opportunities.
Chuliá, Martens, and van Dijk (2010)	S&P100 index constituents	Regression	1997–2006	Monetary policy announcements have heterogenous effects depending on firm characteristics.
Maio (2014)	CRSP (equity portfolios)	VAR	1963–2008	Changes in monetary policy have a greater impact on stock returns of more financially constrained stocks than on those of less constrained stocks.
Brusa, Savor, and Wilson (2020)	Stock markets in 38 countries	Event study	1973–2016	Federal Open Market Committee (FOMC) announcements have a unique impact on global equity prices, while those of non-US central banks do not affect global markets or their domestic stock markets.
		Regression
Conover, Jensen, and Johnson (1999)	16 countries (Including the US)	Regression	1956–1995	International stock markets respond both to the local policies as well as to changes in US monetary policy.
Maćkowiak (2007)	8 emerging markets from East Asia and Latin America	VAR	1986–2000	US monetary policy shocks quickly and strongly affect emerging markets.
Iacoviello and Navarro (2019)	50 advanced and emerging economies	Regression	1965–2016	Higher US policy rates lead to a larger decline of GDP in emerging economies than in advanced economies.
Ramelli and Wagner (2020)	Nonfinancial Russell 3000 constituents	Regression	2018–2020	Firms with greater foreign revenues had more negative stock returns while COVID-19 spread in China.
Yong and Laing (2021)	2836 nonfinancial US firms	Event study	2020 (WHO's announcement of a pandemic)	International exposure is negatively related to stock returns in the short run, whereas that relationship reverses in the long run.
		Regression
Baek, Kang, and Park (2004)	644 nonfinancial firms listed on the Korean Stock	Regression	1997–1998	Korean firms with higher foreign ownership experienced a smaller reduction in their stock prices during the 1997 Korean financial crisis.
	Exchange
Wei, Xie, and Zhang (2005)	5284 firm years of China's privatized firms	Regression	1991–2001	Foreign ownership is significantly positively related to Tobin's Q.
Mishra (2014)	Nonfinancial Australian firms	Regression	2001–2009	Foreign ownership has a positive and significant impact on Tobin's Q.
Fahlenbrach, Rageth, and Stulz (2020)	Nonfinancial and nonutility firms with available fiscal year 2019 data in Compustat	Regression	2020:2–2020:3 (COVID-19 pandemic)	A sudden and unanticipated revenue shortfall affects a firm's stock less if the firm is more financially flexible.
Ding, Levine, Lin, and Xie (2021)	6744 firms in 61 countries	Regression	2020:1–2020:5 (COVID-19 pandemic)	Firms with more cash, less debt, less short-term debt perform better during the COVID-19 pandemic
Lins, Servaes, and Tufano (2010)	2005 survey of chief financial officers (CFO) from 29 countries	Survey	2005	Firms tend to hold non-operational cash to hedge against negative cash flow shocks.
		Regression
Campello et al. (2011)	Survey of CFO from 31 countries	Survey	2008–2009	Cash holdings can be used as a buffer during a financial crisis.
		Regression
Crouzet and Mehrotra (2020)	US manufacturing firms	Regression	1977–2014	Large firms are less cyclically sensitive than small firms.

We start by providing evidence on stock market responses to the Fed's giant step, examining daily abnormal returns around the announcement date from the perspective of export exposure and foreign ownership. We find that low-exporting firms and low-foreign-ownership firms experience more negative abnormal returns from the Fed's aggressive monetary tightening. Next, we conduct cross-sectional regressions to investigate the impact of firm characteristics on individual stock returns. We consider the following two aspects: 1) periods, as discussed above, and 2) corporate size because firm characteristics vary across sizes. We find that export sales, foreign equity ownership, and market capitalization are positively correlated with stock returns during the Giant-step period, whereas there are no significant results for these variables during the Uncertainty period. These results imply that exports and foreign investors play essential roles in corporate value during a US interest rate shock. Finally, we investigate whether financial flexibility is valuable for firms when US interest rates skyrocket. We find that small-cap firms with more (net) short-term debt underperform during the shocks. Taken together, our results suggest that the Fed's sharp rate hikes cause the flight to quality of investors in the emerging market.

Our study contributes to the literature in several ways. First, it provides early evidence on the economic impacts of US rate increases due to COVID-19 and the Russia–Ukraine war from the perspective of emerging markets. The literature in this regard is now expanding (e.g. Ref. [4]) because the US took the first rate hike just several months ago. Second, Korea could be a predictor of the future direction of the global economy because it rapidly reflects global economic fluctuations, as Korea has a relatively liquid stock market and export-led economy. Finally, to the best of our knowledge, this is the first study to find that export exposure and foreign ownership are significant factors for the value of emerging market firms when the US sharply raises interest rates. Previous literature demonstrates that foreign ownership is significantly positively related to firm value ([5,6]). In addition to existing studies, we find that the impact of foreign ownership on corporate value in an emerging market varies depending on US monetary policy.

The remainder of this paper is organized as follows. Section 2 reviews the existing literature. Section 3 describes the data and methodology, Section 4 presents the results, Section 5 tests the robustness of our results, Section 6 provides discussion, and Section 7 concludes the paper.

2. Related literature

This paper builds on several branches of literature. This study is related to the impact of US monetary policy on stock market returns, which has been studied extensively. Both researchers and policymakers have long been interested in this issue with the goal of understanding the monetary policy transmission mechanism. This is because the stock market is directly and immediately affected by changes in the federal funds rate. Further, the stock market influences the real economy through changes in firms’ cost of capital as well as the wealth effect on consumption and investment. Thorbecke [7] found that positive monetary shocks lead to greater stock returns and have larger impacts on small firms, which are more likely to be credit constrained, than on large firms. Bernanke and Kuttner [8] reported that an unexpected 25-basis-point rate cut in the federal funds target rate is related to a 1% increase in stock prices. In addition, changes in monetary policy have heterogenous effects depending on firm characteristics [9,10]. Maio [11] showed that changes in the federal funds rate have a greater impact on stock returns of more financially constrained stocks (e.g., small and value stocks) than on those of less constrained stocks (e.g., large and growth stocks).

Recently, Brusa, Savor, and Wilson [12] examined stock markets in 38 countries from 1973 to 2016, finding that, whereas their stock markets are strongly affected by the Fed's policy announcements, there is no comparable result for other central banks either internationally or domestically. Their results are consistent with previous studies showing that US monetary policy exerts substantial influence in the global financial system via changes in international asset prices, capital flows, and credit growth (e.g. Refs. [[13], [14], [15]]). Conover, Jensen, and Johnson [16] found that stock markets respond both to the local policies as well as to changes in US monetary policy, using data from 16 countries over the period of 1956–1995. Maćkowiak [17] showed that US monetary policy shocks quickly and strongly affect emerging markets by examining eight emerging markets from East Asia (including Korea) and Latin America. Iacoviello and Navarro [18] reported that higher US policy rates lead to a larger decline of gross domestic product (GDP) in emerging economies than in developed economies.

Although extensive research has been conducted on the impact of the Fed's rate policy on the stock market and other countries, sharp interest hikes by the Fed have received little attention. This is because, the recent interest rate increases by the Fed are sharper than they have been in decades. This drastic US monetary policy will significantly affect both the US and the global economy. Therefore, studies regarding the effect of this radical US monetary policy on various economies will be needed in the future. This study provides early evidence on this issue in terms of immediate stock market reactions.

Flight to quality refers to the phenomenon in which investors tend to suddenly shift their portfolio toward safer assets in times of increased market uncertainty or crisis [19,20]. In Korea, investors consider firms that rely more heavily on exports and foreign investors to be safer assets because Korea is a small export-driven open economy. In this regard, our work is also related to the literature exploring the effects of export exposure and foreign ownership on firm-level stock returns. In fact, little attention has been paid to the impact of export exposure on firm value, but COVID-19 shed light on the importance of exports on corporate value due to sudden plunges in international trade. Ramelli and Wagner [21] showed that more export-oriented US firms had more negative stock returns as COVID-19 was spreading in China. Yong and Laing [22] examined the US stock market reaction to the World Health Organization (WHO)'s announcement declaring COVID-19 a pandemic and found that international exposure is negatively related to stock returns in the short run, whereas that relationship reverses in the long run.

From the perspective of foreign ownership, previous research generally reports that the stock market positively evaluates the presence of foreign investors. Baek, Kang, and Park [23] found that Korean firms with higher foreign ownership experienced a smaller reduction in their stock prices during the 1997 Korean financial crisis. Wei, Xie, and Zhang [6] showed that foreign ownership of privatized firms in China is significantly positively associated with Tobin's Q over the period of 1991–2001. Mishra [5] found that foreign ownership has a positive and significant impact on Tobin's Q by examining Australian firms over the period of 2001–2009.

This study is also related to the literature exploring the effects of financial flexibility on firm-level stock returns. Financial flexibility refers to a firm's ability to access and restructure its financing at a low cost [3,24]. In general, financially flexible firms are those with sufficient cash holdings and low short-term debt. For instance, Ding et al. [25] showed that firms with more cash reserves, less debt, and greater total assets performed better than other firms during the COVID-19 pandemic. Most prior work focuses on the role of cash reserves as a liquidity buffer during a crisis (e.g. Refs. [[26], [27], [28]]). Campello et al. [26] emphasized the value of cash in managing corporate liquidity during market distress. However, cash holdings can also be harmful for firm value because they are vulnerable to agency problems such as managers' discretion and incentives to pursue private benefits (e.g. Ref. [29]). Financial flexibility is particularly important for Korean firms—especially for small firms—because they are more likely to rely heavily on short-term debt (see Table 2). Furthermore, small firms are generally more susceptible to shocks than are large ones because they tend to have fewer resources and greater credit constraints [30,31].

Table 2.

Descriptive Statistics. This table reports the summary statistics. Panels A–D provide statistics for the entire sample and large-cap, mid-cap, and small-cap firms, respectively. CAPM-adjusted cumulative returns June09–June23 (11-day window) and June14–June20 (5-day window) are cumulative returns [-5, +5] and [-2, +2] around the Fed's 75 bps hike on June 16 (day 0), respectively. Note that we set June 16 as the event day instead of June 15 because of the time difference between Korea and the US. Appendix A defines all the variables.

	Panel A: All firms
	N	Mean	SD	Min	Median	Max
Dependent Variables
CAPM-adjusted cumulative returns
January03–May31 (Uncertainty)	727	0.0628	0.2030	−0.5592	0.0563	0.7139
June01–June30 (Giant-step)	727	−0.0330	0.0735	−0.2725	−0.0375	0.2010
June09–June23 (11-day window)	727	−0.0415	0.0599	−0.2107	−0.0446	0.1626
June14–June20 (5-day window)	727	−0.0256	0.0403	−0.1474	−0.0264	0.1179
Independent Variables
Export Exposure	727	0.2079	0.2932	0.0000	0.0344	1.0006
Foreign Ownership	727	0.0945	0.1172	0.0024	0.0477	0.5955
Size	727	26.7008	1.4871	24.4103	26.4088	31.4018
Cash Holdings	727	0.0694	0.0723	0.0002	0.0461	0.3876
Leverage	727	0.3971	0.2056	0.0112	0.3986	0.9020
ST Debt	727	0.2703	0.1620	0.0019	0.2573	0.7214
LT Debt	727	0.1264	0.1172	0.0010	0.0959	0.5969
Net ST Debt	727	0.2609	0.1652	−0.0159	0.2466	0.7214
ROA	727	0.0240	0.0740	−0.2819	0.0301	0.2319
Dividends	727	0.0091	0.0109	0.0000	0.0059	0.0589
R&D	727	0.0072	0.0153	0.0000	0.0001	0.0812
B/M	727	2.0161	1.5123	0.1426	1.7022	8.2836
Momentum	727	0.0943	0.3627	−0.8702	0.0675	1.3730

	Panel B: LargeCap [N = 242]		Panel C: MidCap [N = 242]		Panel D: SmallCap [N = 243]
	Mean	SD		Mean	SD	Mean	SD
Dependent Variables
CAPM-adjusted cumulative returns
January03–May31 (Uncertainty)	0.0394	0.1809		0.0542	0.1970	0.0946	0.2251
June01–June30 (Giant-step)	−0.0171	0.0688		−0.0428	0.0707	−0.0390	0.0784
June09–June23 (11-day window)	−0.0239	0.0533		−0.0464	0.0592	−0.0541	0.0628
June14–June20 (5-day window)	−0.0167	0.0368		−0.0280	0.0418	−0.0321	0.0406
Independent Variables
Export Exposure	0.2379	0.3295		0.2077	0.2801	0.1781	0.2644
Foreign Ownership	0.1625	0.1284		0.0709	0.0943	0.0501	0.0937
Size	28.4279	1.1112		26.4244	0.3179	25.2561	0.3857
Cash Holdings	0.0673	0.0702		0.0630	0.0631	0.0777	0.0818
Leverage	0.3956	0.1979		0.3853	0.2022	0.4103	0.2164
ST Debt	0.2395	0.1369		0.2645	0.1539	0.3067	0.1848
LT Debt	0.1556	0.1225		0.1211	0.1267	0.1025	0.0939
Net ST Debt	0.2266	0.1391		0.2547	0.1569	0.3014	0.1878
ROA	0.0430	0.0695		0.0307	0.0639	−0.0016	0.0805
Dividends	0.0127	0.0129		0.0095	0.0098	0.0053	0.0081
R&D	0.0113	0.0204		0.0050	0.0111	0.0053	0.0119
B/M	1.5954	1.4303		2.1049	1.5328	2.3467	1.4798
Momentum	0.0976	0.3687		0.1277	0.3726	0.0578	0.3444

An overview of these studies is given in Table 1.

3. Data and methodology

We retrieve financial data for non-financial firms listed on the KOSPI market from the KISVALUE database. We delete observations with missing information on daily stock returns, foreign ownership, and export sales. Stock returns and market capitalization are shown as daily values while other financial statements variables are given as annual values. Accounting data for firms’ characteristic variables are calculated using values at the end of 2021. Our final sample consists of 727 firms.

We conduct both the event study and cross-sectional ordinary least squares (OLS) regression because more detailed and enriched results can be obtained through the combination of both methodologies. Through the event study, we can examine stock market reactions to the announcement of the Fed's giant-step. Furthermore, through the cross-sectional regression, we can investigate firms' heterogeneous exposures to the US interest rate shock. We first perform event studies by calculating daily abnormal returns surrounding the Fed's giant-step. The abnormal return is defined as the difference between the actual return and the normal return due to the market-wide movement. Following Brown and Warner [32,33], we employ the market-adjusted model to calculate daily abnormal returns. Note that we set June 16 as the event day instead of June 15 because of the time difference between Korea and the US. Therefore, event windows span from May 31, 2022, through June 30, 2022. The abnormal return is measured as

$${AR}_{it}=R_{it}-R_{mt}$$ (1)

where ${AR}_{it}$ represents the abnormal return of stock i on day t. $R_{it}$ is the actual return of stock i on day t. $R_{mt}$ is the market return on day t. The KOSPI index is used as a proxy for the market return.

Then, we perform the following cross-sectional regressions to examine the heterogeneous effects of the Fed's rate policy on firm-level stock returns.

$${{cumulativereturns}_i(t}_1,t_2)={\beta }_0+{\beta }_1{ExportExposure}_i+{\beta }_2{ForeignOwnership}_i+{\beta }_3{Size}_i+{\beta }_4^{\prime }{FirmControls}_i+{\phi }_j+{\epsilon }_i$$ (2)

where $cumulativereturns$ denote CAPM-adjusted cumulative returns of stock i during the Uncertainty and Giant-step periods. Specifically, the cumulative returns are calculated using equation (5) below. ${\beta }_0$ is a constant, ${\beta }_4^{\prime }$ is a vector of parameters. $ExportExposure$ is calculated as export sales over total sales at the end of 2021. $ForeignOwnership$ is the ratio of the average annual ratio of the number of shares held by foreign investors to the total number of shares outstanding in 2021. $Size$ is measured as the natural logarithm of market capitalization at the end of 2021. $FirmControls$ include Cash Holdings, Leverage, ST Debt, LT Debt, Net ST debt, ROA, Dividends, R&D, B/M, and Momentum. 2-Digit Korean Standard Industrial Classification (KSIC) industry fixed effects (${\phi }_j$) are included in all regressions. ${\epsilon }_i$ is the error term. t-statistics are calculated based on robust standard errors. All continuous variables are winsorized at the 1st and 99th percentiles to mitigate the impact of outliers.

Following the asset pricing literature, we construct CAPM-adjusted returns (CAPM alphas) for the dependent variable ($cumulativereturns$). We estimate the following CAPM to obtain each stock's beta for the period between January 4, 2021, and December 30, 2021.

$$R_{it}-R_{ft}=a_i+b_i\left(R_{mt}-R_{ft}\right)+e_{it}$$ (3)

where $R_{ft}$ indicates the risk-free rate on day t. We use the yields of the 91-day monetary stabilization bond retrieved from the Bank of Korea (BOK), as a proxy for the risk-free rate. $e_{it}$ is the error term.

The model to compute CAPM-adjusted returns for the Uncertainty and Giant-step periods is given by:

$$C{APMAR}_{it}=R_{it}-R_{ft}-{\hat{b}}_i\left(R_{mt}-R_{ft}\right)$$ (4)

where $C{APMAR}_{it}$ denotes the CAPM-adjusted return for stock i on day t. $\hat{b}$ is the OLS parameter estimates from equation (3).

The CAPM-adjusted cumulative return is calculated as the sum of the CAPM-adjusted returns from equation (4) for each period $\left(t_1,t_2\right)$ of the Uncertainty and the Giant-step, as follows:

$${cumulativereturns}_i\left(t_1,t_2\right)=\sum _{t=t_1}^{t_2}{CAPMAR}_{it}$$ (5)

Our main independent variables of interest are export exposure, foreign ownership, and financial flexibility. Financial flexibility is the ease with which a firm responds to and restructures its financing to unexpected shocks. In general, firms with more cash and less debt are considered more financially flexible and thus less affected by shocks [21,24,34]. We also consider net short-term debt (Net ST debt), a measure of short-term liquidity.

Other control variables are firm characteristics that correspond to risk factors from the asset-pricing literature [[35], [36], [37]], including book-to-market, momentum, and profitability. We also consider research and development (R&D) and dividends because innovative or dividend-paying firms are expected to be more resilient to market turbulence [38,39]. Appendix A defines all the variables in detail.

Table 2 presents the summary statistics. Panel A shows the statistics for the entire sample. Through cumulative abnormal returns, we can see the features of each period. As mentioned above, the average CAPM-adjusted cumulative return from January 3 through May 31 (Uncertainty period) is 0.0628, while that from June 1 through June 30 (Giant-step period) is −0.0330. The results suggest that the stock market has been seriously negatively affected by rising interest rates since June. The average cumulative return (−0.0415) for the 11-day window is more negative than that (−0.0256) for the 5-day window. Firm leverage averages 0.3971, and firms are more dependent on short-term debt (0.2703) than on long-term debt (0.1264).

In Panels B–D, we split the sample into terciles, depending on firm size, to examine the differences in every independent variable instead of employing the small-cap dummy or interacting Size with other explanatory variables. As expected, larger firms have stronger fundamentals than smaller firms. They are more export-oriented, attractive to foreign investors, profitable, and pay more dividends than smaller firms. Furthermore, they are more financially sound. Large-cap firms have less debt, especially short-term debt (0.2395), than small-cap firms (0.3067). Interestingly, however, large-cap firms have the lowest stock returns (0.0394), whereas small-cap firms have the highest stock returns (0.0946) during the Uncertainty period. This might be because foreign shareholders kept selling Korean stocks from the beginning of 2022 in that they usually invest in large firms (see Fig. 2). However, this pattern was reversed during the Giant-step period. Small-cap firms show poorer performance in stock returns (−0.0390) than large-cap firms (−0.0171). Stock returns of the 5-day and 11-day windows show similar results to those of the Giant-step period. This seems to be partly because foreign investors change their behavior. As shown in Fig. 3, the foreign ownership of larger firms continues to drop during the Uncertainty period and then suddenly starts to increase during the Giant-step period, while that of small-cap firms continues to decrease during the Giant-step period.

Fig. 3.

Changes in Foreign Ownership by Firm Size. This figure shows the trends in average daily foreign ownership by month for large-cap, mid-cap, and small-cap firms from January 2022 to June 2022.

4. Empirical results

4.1. Which firms perform better when the US sharply raises the interest rate?

In Fig. 4, we first investigate the stock market reactions to the Fed's announcement of 75 bps hike on June 16 using the market-adjusted model of equation (1). We focus on export exposure (Fig. 4) and foreign ownership (Fig. 4), which are the most important pillars of the Korean economy. We find that less export-oriented firms and low foreign ownership firms not only become more volatile, experience more negative returns in the aftermath of the Fed's giant step.

Fig. 4.

Daily Abnormal Returns for the Fed's Giant-step. This figure reports daily abnormal returns [-10, +10] around the Fed's announcement on June 16 (day 0) for subsamples depending on exports and foreign ownership. Event windows span from May 31, 2022, through June 30, 2022. (4.1) Presents the daily abnormal returns for high- (gray bars) and low-exporting firms (blue bars). Among exporting firms, the sample is divided into quartiles depending on the ratio of export sales to total sales. The number of high- and low-exporting firms is 112 (highest) and 113 (lowest), respectively. (4.2) Displays the daily abnormal returns for high- (gray bars) and low-foreign-ownership firms (blue bars). The sample is divided into quartiles depending on the market capitalization. The number of high- and low-foreign-ownership firms is 181 (highest) and 182 (lowest), respectively. Abnormal returns are computed using the market-adjusted model. (4.1) High-Exporting Firms vs. Low-Exporting Firms. (4.2) High Foreign Ownership Firms vs. Low Foreign Ownership Firms. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Next, we conduct cross-sectional regressions of stock returns on firm characteristics described in equation (2). Table 3 shows the results consistent with those in Fig. 4. During the Giant-step period, firms relying more on exports and foreign investments earn greater stock returns (Columns 5, 6, and 8). In addition, larger firms perform better than smaller firms during the same period (Columns 7 and 8). However, we obtain different results for the Uncertainly period because Export Exposure, Foreign Ownership, and Size do not have statistically significant coefficients (Columns 1, 2, and 4). Furthermore, Column 3 reports that Size is negatively associated with stock returns during the Uncertainty period, consistent with Panels B–D in Table 2. Turning to the other control variables, Cash Holdings have a negative and significant coefficient (Column 8), implying that more cash-abundant firms earn lower stock returns. This unexpected result is attributable to large-cap firms, as Panel B of Table 4 shows. Investors seem to worry about the agency problem (e.g. Ref. [29]) of large-cap firms, which usually accumulate a substantial amount of cash. Moreover, firms that pay more dividends outperform during the entire period.

Table 3.

Changes in the Relation Between Stock Returns and Firm Characteristics. This table shows the results of cross-sectional regressions of individual stock returns on firm characteristics. Appendix A defines all the variables. t-statistics based on robust standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.

Dependent Variable: CAPM-adjusted cumulative returns
	Panel A: Uncertainty [January03–May31]					Panel B: Giant-step [June01–June30]
	(1)	(2)	(3)	(4)		(5)	(6)	(7)	(8)
Export Exposure	−0.0168			−0.0007		0.0251***			0.0222**
	(-0.66)			(-0.03)		(2.76)			(2.43)
Foreign Ownership		−0.0622		−0.0639			0.0917***		0.0396*
		(-1.09)		(-1.10)			(3.91)		(1.69)
Size			−0.0102**	−0.0032				0.0074***	0.0048**
			(-2.14)	(-0.62)				(3.95)	(2.09)
Cash Holdings				−0.0543					−0.1154**
				(-0.47)					(-2.51)
Leverage				−0.0180					−0.0009
				(-0.44)					(-0.06)
ROA				0.1401					−0.0090
				(1.08)					(-0.20)
Dividends				1.3213**					0.6700**
				(2.02)					(2.27)
R&D				−0.7822					0.1627
				(-1.44)					(0.88)
B/M				0.0378***					0.0059***
				(6.24)					(2.64)
Momentum				−0.0315					−0.0113
				(-1.20)					(-1.27)
Constant	0.2008***	0.2044***	0.4785***	0.0785		0.0036	−0.0017	−0.1964***	−0.1611**
	(3.16)	(3.18)	(3.23)	(0.46)		(0.16)	(-0.08)	(-3.50)	(-2.30)
Industry Fixed Effects	Yes	Yes	Yes	Yes		Yes	Yes	Yes	Yes
R-squared	0.0596	0.0603	0.0644	0.1374		0.0434	0.0540	0.0551	0.0996
Observations	727	727	727	727		727	727	727	727

Table 4.

Changes in the Relation Between Stock Returns and Corporate Characteristics by Firm Size This table shows the results from regressions of stock returns on firm characteristics by dividing the sample into large-, mid-, and small-cap stocks. Appendix A defines all the variables. t-statistics based on robust standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.

Dependent Variable: CAPM-adjusted cumulative returns
	Panel A: Uncertainty [January03–May31]				Panel B: Giant-step [June01–June30]
	LargeCap	MidCap	SmallCap		LargeCap	MidCap	SmallCap
	(1)	(2)	(3)		(4)	(5)	(6)
Export Exposure	0.0574	0.0205	−0.0757		0.0439***	0.0415**	−0.0215
	(1.53)	(0.47)	(-1.52)		(3.21)	(2.18)	(-1.41)
Foreign Ownership	−0.0811	−0.0689	−0.0785		0.0001	0.0776**	0.0149
	(-0.80)	(-0.64)	(-1.03)		(0.00)	(2.01)	(0.28)
Size	0.0183	−0.0161	0.0008		0.0112**	0.0027	−0.0267*
	(1.62)	(-0.36)	(0.02)		(2.26)	(0.18)	(-1.86)
Cash Holdings	0.1005	−0.1436	−0.3120		−0.1073*	−0.1068	−0.1358
	(0.68)	(-0.70)	(-1.60)		(-1.68)	(-1.29)	(-1.48)
Leverage	0.1830**	0.0107	−0.1585**		0.0012	0.0042	−0.0062
	(2.53)	(0.17)	(-2.28)		(0.04)	(0.16)	(-0.23)
ROA	0.0618	0.0143	0.3828*		0.0101	0.1039	−0.0594
	(0.32)	(0.06)	(1.79)		(0.14)	(1.00)	(-0.91)
Dividends	1.3018	2.5141*	2.3875*		0.2447	1.0250**	1.7471***
	(1.45)	(1.76)	(1.66)		(0.58)	(2.03)	(2.77)
R&D	−0.9107	−2.4701	−0.5962		0.1973	0.3653	−0.0582
	(-1.15)	(-1.54)	(-0.81)		(0.78)	(0.74)	(-0.19)
B/M	0.0056	0.0401***	0.0559***		0.0111**	0.0066*	0.0001
	(0.55)	(3.37)	(5.76)		(2.59)	(1.92)	(0.02)
Momentum	0.0038	−0.0141	−0.1054**		−0.0154	−0.0282*	0.0105
	(0.08)	(-0.33)	(-2.03)		(-0.93)	(-1.79)	(0.67)
Constant	−0.4972	0.4140	−0.0695		−0.3302**	−0.1637	0.6601*
	(-1.47)	(0.35)	(-0.08)		(-2.20)	(-0.40)	(1.80)
Industry Fixed Effects	Yes	Yes	Yes		Yes	Yes	Yes
R-squared	0.1634	0.1427	0.3017		0.2026	0.1368	0.1384
Observations	242	242	243		242	242	243

In Table 4, we explore our results in more detail by dividing the sample by firm size. Columns 1–3 of Panel A show no statistically significant impacts of Export Exposure, Foreign Ownership, or Size on stock returns for all stocks during the Uncertainty period. However, Columns 4 and 5 of Panel B report that Export Exposure is positively related to stock returns for large- and mid-cap stocks during the Giant-step period. Furthermore, Foreign Ownership of mid-cap stocks also has a positive and significant coefficient. Although Cash Holdings do not have significant results, Leverage has a negative coefficient for small-cap stocks during the Uncertainty period (Column 3). As for Dividends, mid- and small-cap stocks have positive and significant coefficients during the entire sample period.

Table 5 repeats the previous tests of Table 4 for the periods before and after the Fed's giant-step announcement. As mentioned above, we subdivide the Giant-step period into 5-day and 11-day event windows to examine how individual stocks respond to the Fed's rate hike in more detail. Results for exports and foreign investors remain unchanged around the event. Different from Table 4, Leverage of small-cap stocks in Columns 3 and 6 has significantly negative coefficients in both event windows.

Table 5.

Stock Returns and Firm Characteristics around the Fed's Giant-step. This table presents the results of regressions of stock returns on firm characteristics by firm size for the 5-day and 11-day event windows around June 16 (day 0). Appendix A defines all the variables. t-statistics based on robust standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.

	Panel A: CAPM-adj cumulative returns June14–June20 (5-day window)
	LargeCap	MidCap	SmallCap
	(1)	(2)	(3)
Export Exposure	0.0160**	0.0271**	−0.0014
	(2.12)	(2.07)	(-0.16)
Foreign Ownership	−0.0037	0.0224*	−0.0114
	(-0.18)	(1.81)	(-0.39)
Size	0.0061**	0.0174*	−0.0179**
	(2.28)	(1.86)	(-2.36)
Cash Holdings	−0.0436	−0.0651	−0.0157
	(-1.39)	(-1.19)	(-0.34)
Leverage	0.0021	−0.0009	−0.0313**
	(0.13)	(-0.06)	(-1.97)
ROA	0.0016	−0.0358	−0.0161
	(0.03)	(-0.68)	(-0.41)
Dividends	0.3186*	0.5916*	0.8197***
	(1.66)	(1.73)	(2.80)
R&D	0.0298	0.0282	0.0103
	(0.16)	(0.09)	(0.06)
B/M	0.0036**	0.0012	0.0015
	(1.99)	(0.46)	(0.73)
Momentum	0.0075	−0.0025	−0.0012
	(0.68)	(-0.28)	(-0.14)
Constant	−0.2038***	−0.5074**	0.4327**
	(-2.67)	(-2.00)	(2.21)
Industry Fixed Effects	Yes	Yes	Yes
R-squared	0.1426	0.0894	0.1453
Observations	242	242	243

4.2. The value of financial flexibility during the period of rising interest rates

To further support the results of Leverage in Table 5, we test whether there are differences in the effect of financial flexibility on stock returns between large- and small-cap stocks, subdividing by the maturity of debt: long-, short-, and net-short-term debt, as shown in Table 6. In Panel A of the large-cap stocks, we find no significant results. However, in Panel B, we find that financially flexible small-cap stocks are more resilient to the Fed's sharp rate hike. Specifically, small firms relying more on short-term debt underperform (Column 5), while long-term debt does not significantly affect small-cap firms' stock returns (Column 6). We conduct regressions separately for short- and long-term debt in Columns 5 and 6 because these variables are highly correlated. However, the results in Column 7, which contain the two variables, continue to hold. The net short-term debt in Column 8 presents consistent results, with a negative coefficient (−0.0314).

Table 6.

Effects of Financial Flexibility on Stock Returns around the Fed's 75 bps Increase. This table reports the results of regressions of stock returns on financial flexibility for large- and small-cap stocks around the Fed's giant step. Appendix A defines all the variables. t-statistics based on robust standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.

Dependent Variable: CAPM-adjusted cumulative returns [June14–June20, 5-day window]
	Panel A: LargeCap Firms					Panel B: SmallCap Firms
	(1)	(2)	(3)	(4)		(5)	(6)	(7)	(8)
Cash Holdings	−0.0447	−0.0435	−0.0448			−0.0156	−0.0064	−0.0159
	(-1.42)	(-1.40)	(-1.42)			(-0.33)	(-0.14)	(-0.34)
ST Debt	0.0102		0.0101			−0.0325*		−0.0329*
	(0.49)		(0.48)			(-1.82)		(-1.84)
LT Debt		−0.0044	−0.0041				−0.0217	−0.0235
		(-0.17)	(-0.16)				(-0.75)	(-0.81)
Net ST debt				0.0084					−0.0314*
				(0.40)					(-1.79)
Export Exposure	0.0156**	0.0156**	0.0153*	0.0145**		−0.0018	−0.0021	−0.0014	−0.0013
	(2.11)	(1.99)	(1.95)	(1.98)		(-0.20)	(-0.24)	(-0.16)	(-0.15)
Foreign Ownership	−0.0044	−0.0045	−0.0050	−0.0037		−0.0070	−0.0008	−0.0106	−0.0075
	(-0.21)	(-0.22)	(-0.24)	(-0.18)		(-0.24)	(-0.03)	(-0.36)	(-0.26)
Size	0.0062**	0.0062**	0.0063**	0.0067**		−0.0177**	−0.0175**	−0.0179**	−0.0178**
	(2.35)	(2.30)	(2.35)	(2.58)		(-2.33)	(-2.29)	(-2.35)	(-2.34)
ROA	0.0030	−0.0014	0.0015	0.0027		−0.0090	−0.0021	−0.0144	−0.0104
	(0.06)	(-0.03)	(0.03)	(0.06)		(-0.24)	(-0.06)	(-0.37)	(-0.27)
Dividends	0.3161*	0.3138	0.3130	0.3174		0.8044***	0.9645***	0.8099***	0.7747**
	(1.67)	(1.62)	(1.62)	(1.65)		(2.64)	(3.32)	(2.75)	(2.50)
R&D	0.0205	0.0316	0.0203	0.0252		0.0299	0.0056	0.0169	0.0285
	(0.11)	(0.18)	(0.11)	(0.14)		(0.18)	(0.04)	(0.10)	(0.17)
B/M	0.0035**	0.0038**	0.0036*	0.0038**		0.0010	0.0004	0.0014	0.0011
	(2.01)	(2.06)	(1.94)	(2.24)		(0.50)	(0.20)	(0.69)	(0.54)
Momentum	0.0072	0.0078	0.0073	0.0079		−0.0013	−0.0011	−0.0012	−0.0008
	(0.67)	(0.73)	(0.67)	(0.74)		(-0.15)	(-0.12)	(-0.14)	(-0.09)
Constant	−0.2069***	−0.2048***	−0.2079***	−0.2239***		0.4224**	0.4134**	0.4313**	0.4239**
	(-2.74)	(-2.67)	(-2.74)	(-3.01)		(2.16)	(2.10)	(2.20)	(2.16)
Industry Fixed Effects	Yes	Yes	Yes	Yes		Yes	Yes	Yes	Yes
R-squared	0.1436	0.1427	0.1437	0.1377		0.1421	0.1292	0.1446	0.1413
Observations	242	242	242	242		243	243	243	243

5. Robustness tests

5.1. Endogeneity

This study focuses on the US interest rate shock in the aftermath of the COVID-19 crisis, which continues to significantly affect the global economy. In fact, corporate value is likely to be affected by both interest rate and COVID-19 shocks. Furthermore, exports and foreign investments can also be influenced by the COVID-19 pandemic. If these are the cases, there can be omitted variable bias in our cross-sectional regressions. To mitigate the potential endogeneity, we employ the instrumental variables-generalized method of moments (IV-GMM) estimation technique because the GMM estimator is more efficient than the two-stage least squares (2SLS) estimator in the presence of heteroskedasticity of unknown form. Regarding the IV-GMM method, an instrumental variable must satisfy two conditions. First, the instrument must be uncorrelated with the structural error term (exogeneity). Second, the instrument must be partially correlated with the endogenous explanatory variable (relevance) [40]. We use the lagged values of the two endogenous variables (Export Exposure and Foreign Ownership) as instrumental variables. This is because, for instance, whereas the lagged values of export exposure are likely to be correlated with the current export exposure, they are not correlated with the current error term.

Panels A and B of Table 7 report the first- and second-stage regression results of IV-GMM estimations. If we define K as 2021, 2020 and 2019 are defined as K-1 and K-2, respectively, because we calculate export exposure and foreign ownership as the value of 2021 in our cross-sectional regressions. We test the relevance of our instrumental variables by using the fist-stage F-tests. We report the Sanderson-Windmeijer (SW) F-statistics for each first-stage regression of Export Exposure and Foreign Ownership. We also present the Cragg-Donald Wald (CDW) F-statistics for the second-stage regression results of Columns 3 and 4 because we have two endogenous explanatory variables. If the F-statistic exceeds than the rule-of-thumb value of 10, we can reject the null hypothesis that the instruments are weak. As shown in Table 7, SW F-statistics and CDW F-statistics are greater than 10, indicating that our instruments are relevant. In addition, we perform the Hansen's J test for overidentifying restrictions to check for the exogeneity of our instruments. Columns 3 and 4 of Panel B show that Hansen J test statistics are insignificant, suggesting that our instruments are valid. Overall, Table 7 confirms our findings that the significant and positive impacts of export exposure and foreign ownership on stock returns are only observed in the Giant-step period. Therefore, our results remain unchanged even after controlling for the potential endogeneity.

Table 7.

Changes in the Relation Between Stock Returns and Firm Characteristics: IV-GMM This table shows the results of IV-GMM estimations for the relationship between firm-level stock returns and firm characteristics. Appendix A defines all the variables. t-statistics based on robust standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.

	Panel A: First-stage regressions		Panel B: Second-stage regressions
			(CAPM-adj cumulative returns)
	Export Exposure	Foreign Ownership	Uncertainty	Giant-step
	(1)	(2)	(3)	(4)
Export Exposure			0.0045	0.0214**
			(0.17)	(2.12)
Foreign Ownership			−0.0705	0.0417*
			(-1.14)	(1.77)
EXP: Export ExposureK-1	0.6752***	0.0052
	(5.89)	(0.67)
EXP: Export ExposureK-2	0.2529**	−0.0057
	(2.26)	(-0.72)
FOR: Foreign OwnershipK-1	0.0452	1.2203***
	(0.31)	(19.86)
FOR: Foreign OwnershipK-2	−0.0560	−0.2738***
	(-0.37)	(-4.30)
Size	0.0005	0.0014	−0.0029	0.0068***
	(0.12)	(1.55)	(-0.56)	(3.28)
Cash Holdings	0.0291	0.0009	−0.0598	−0.0955**
	(0.56)	(0.06)	(-0.52)	(-2.11)
Leverage	0.0141	−0.0032	−0.0120	−0.0103
	(0.54)	(-0.68)	(-0.29)	(-0.66)
ROA	0.0587	−0.0151	0.1440	−0.0147
	(0.64)	(-1.08)	(1.11)	(-0.33)
Dividends	0.3954	0.1921	1.4249**	0.6960**
	(0.56)	(1.46)	(2.17)	(2.36)
R&D	0.0332	−0.0894	−0.8097	0.0463
	(0.11)	(-1.21)	(-1.50)	(0.27)
B/M	−0.0019	0.0015**	0.0391***	0.0071***
	(-0.60)	(2.08)	(6.62)	(3.67)
Momentum	0.0151	0.0023	−0.0336	−0.0063
	(0.83)	(0.80)	(-1.33)	(-0.73)
Constant	0.0125	−0.0391*	0.0419	−0.2304***
	(0.12)	(-1.72)	(0.29)	(-4.06)
Industry Fixed Effects	Yes	Yes	Yes	Yes
SW F-statistic	495.01	2299.13
CDW F-statistic			701.58	701.58
Hansen J test (p-value)			0.4730	0.6017
R-squared	0.8074	0.9594	0.1375	0.0969
Observations	700	700	700	700

5.2. Other robustness checks

To ensure the validity of our results, we conduct additional robustness checks. First, we recalculate the daily abnormal returns of Fig. 4 by employing the market model and find equivalent results. Second, we re-estimate our regressions using a small-cap dummy or interacting Size with other explanatory variables of interest. The results remain qualitatively unchanged. Third, we repeat our estimations using foreign ownership at the end of the year instead of the annual ratio and find similar results. Finally, we re-estimate our models using the Fama–French adjusted returns or raw returns, which include the stock's beta directly in the estimations, as dependent variables. Our results continue to hold.

6. Discussion

In the first half of 2022, the Fed implemented several sharp rate hikes at an unprecedented speed over a short-term period to tackle severe inflation. This radical monetary contraction of the US has greatly affected the global economy in various fields. In particular, the US monetary policy has had a greater impact on emerging economies than on advanced economies [18,41]. Under these circumstances, our work provides early evidence on the impact of the Fed's drastic monetary tightening on the emerging stock market. Furthermore, the stock market is a useful tool for studying the impact of monetary policy on the economy because it immediately reacts to changes in policy and further affects the real economy via changes in consumption and investment.

Our findings indicate that the Fed's sharp rate hike has caused a flight to quality by investors in the emerging stock market. Furthermore, firms with more export sales, higher foreign ownership, and larger market capitalization are more resilient to a US interest rate shock. We also find that financial flexibility is particularly valuable for small-cap firms when the US aggressively raises interest rates. Our results are consistent with previous literature showing that emerging stock markets are susceptible to US monetary shocks. In particular, to the best of our knowledge, this is the first study to propose the level of export exposure and foreign ownership as proxies for the flight to quality of investors in a small, open, and export-led economy. Furthermore, based on these proxies, we show that the impact of US monetary policy on emerging stock markets can differ depending on the level of the Fed's rate increases: relatively small increases (<75bps) versus big ($\ge$ 75bps) increases.

Another issue to consider is how the BOK base rate affects the Korean stock market. It is noteworthy that we can separate the effects of US and Korean monetary policy announcements on stock prices because Korea and the US have different interest rate decision dates. Therefore, our results remain robust, even after considering the BOK rate. Specifically, Korea raised its rates by only 25 bps in January (from 1% to 1.25%), April (from 1.25% to 1.5%), and May (from 1.5% to 1.75%), owing to concerns regarding serious household debt problems. In contrast, the US widened the magnitude of interest rate hikes in March (25 bps increase, from 0.25% to 0.5%), May (50 bps increase, from 0.5% to 1%), and June (75 bps increase, from 1% to 1.75%). In particular, the Fed's sudden aggressive stance in June shocked the global market, including Korea, because Chair Jerome Powell indicated in May that the Fed was unlikely to hike 75 bps in June [42]. Therefore, dividing the period into Uncertainty (January–May) and Giant-step (June) still holds, even after considering the BOK rate. All increases in the BOK rates belong to the uncertainty period in which Koreans paid much more attention to the Fed's decisions than to those of the BOK. The results for June are only affected by the Fed's announcements because Korea did not conduct any meeting for interest rate decisions in June. In addition, as mentioned above, Brusa, Savor, and Wilson [12] showed that FOMC announcements have a unique impact on global equity prices, while those of non-US central banks do not affect global markets or their domestic stock markets.

7. Conclusion

The Fed's sharp rate hikes pose greater challenges for emerging countries. This study investigates how investors in an emerging stock market evaluate the consequences of the Fed's interest rate increases for individual firms. We find strong evidence of the role of exports and foreign investors in corporate value during a US interest rate shock. Firms with more export sales and higher foreign ownership earn greater stock returns when the US benchmark rate skyrockets. Firm size also matters because investors prefer stocks with larger market capitalization during a shock. These results suggest that the Fed's aggressive rate increase causes the flight to quality of investors in the emerging market. Furthermore, small-cap firms relying more on short-term debt underperform, implying that a strong financial position is particularly important for small-cap firms during the period of rising interest rates.

This study has limitations and thus, suggests some interesting extensions. Until June (the Fed's first giant step), Korea did not aggressively increase its interest rates. However, after the Fed changed its stance, its rates skyrocketed by 75 bps four times in a row (June, July, September, and November 2022). Korea also had to rapidly increase its rates in July (50 bps increase, from 1.75% to 2.25%), August (25 bps increase, from 2.25% to 2.5%), and October (50 bps increase, from 2.5% to 3%). The BOK's 50 bps hike in July surprised the market and thus might have affected Korean stocks; many Koreans hoped the BOK would not raise the interest rate much due to heavy household debt. However, this is beyond our scope, and we leave further exploration of this issue to future research.

Author contribution statement

Jeongsim Kim: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Data availability statement

Data will be made available on request.

Declaration of interest's statement

The author declares no competing interests.

Appendix A.

Variable Definitions.

Variable	Definition
Dependent Variable
CAPM-adjusted cumulative returns	Sum of daily CAPM-adjusted returns over a certain period
Independent Variables
Export Exposure	Export sales over total sales
Foreign Ownership	Average annual ratio of the number of shares held by foreign investors to the total number of shares outstanding
Size	Natural logarithm of market capitalization at year-end 2021
Cash Holdings	Cash and cash equivalents over total assets
Leverage	Total debt divided by total assets
ST debt	Current liabilities over total assets
LT debt	Noncurrent liabilities over total assets
Net ST debt	Current liabilities minus cash scaled by total assets
ROA	Net income scaled by total assets
Dividends	Cash dividends over total assets
R&D	Research and development expense over total assets
B/M	Book value of equity over market value of equity at year-end 2021
Momentum	Sum of daily log excess returns on the stock from January 4, 2021, through December 30, 2021.