- Email: [email protected]
Two centuries of global financial market integration: Equities, government bonds, treasury bills, and currencies
Economics Letters 182 (2019) 26–29
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Two centuries of global financial market integration: Equities, government bonds, treasury bills, and currencies✩ ∗
Adam Zaremba a,b , , George D. Kambouris b , Andreas Karathanasopoulos b a
Department of Investment and Capital Markets, Faculty of Management, Poznań University of Economics and Business, al. Niepodległości 10, 61-875, Poznań, Poland b Dubai Business School, University of Dubai, Academic City, Emirates Road, Dubai, P.O. Box: 14143, United Arab Emirates
highlights
graphical
abstract
• We perform the longest study of
•
• • •
global financial integration ever conducted. We examine returns on four asset classes in 83 countries through two centuries. The integration progresses in peaks and troughs instead of linearly. The post-2000 markets exhibit the strongest integration in history. However, certain asset classes in 1860 and 1930 recorded comparable levels.
article
info
Article history: Received 26 April 2019 Received in revised form 17 May 2019 Accepted 27 May 2019 Available online 29 May 2019 JEL classification: F15 F36 G15
a b s t r a c t We perform the longest and broadest study of time variation in global financial market integration ever conducted. Using a unique comprehensive dataset, we examine returns on equities, government bonds, treasury bills, and currencies in 83 countries through a period of almost two centuries. The study discloses that the integration progresses in peaks and troughs instead of linearly. Although the post-2000 markets exhibit the strongest integration in history, certain asset classes in 1860 and 1930 recorded comparable levels. The high degree of current integration is a result of the surge that commenced as recently as 1970, rather than a consequence of a multi-century gradual process. © 2019 Elsevier B.V. All rights reserved.
Keywords: Financial market integration Global markets Factor analysis Early asset data
1. Introduction
✩ Funding: This work was supported by the National Science Centre of Poland grant no.: 2015/19/B/HS4/00378). ∗ Corresponding author at: Department of Investment and Capital Markets, Faculty of Management, Poznań University of Economics and Business, al. Niepodległości 10, 61-875, Poznań, Poland. E-mail addresses: [email protected], [email protected] (A. Zaremba), [email protected] (G.D. Kambouris), [email protected] (A. Karathanasopoulos). https://doi.org/10.1016/j.econlet.2019.05.043 0165-1765/© 2019 Elsevier B.V. All rights reserved.
There are mounting studies in economics that debate the nature of global financial integration.1 They discuss questions such as: Is the integration a stable, long-run progression to ever-higher levels of global market co-movement? Or, does the integration move in waves, exhibiting hikes and reversals? Is the integration linear, J-shaped, U-shaped, or ‘‘swoosh’’-shaped? Since the 1 See, e.g., Bekaert and Mehl (2019), Billio et al. (2017), Dorodnykh (2014), or Sharma and Seth (2012) for a literature review.
A. Zaremba, G.D. Kambouris and A. Karathanasopoulos / Economics Letters 182 (2019) 26–29
27
Fig. 1. Number of countries covered in the sample. Note. Fig. 1 discloses the number of countries in the sample with data on equities, government bonds, treasury bills, and currencies available through time.
financial market integration is a long-term multidimensional phenomenon, providing a proper answer requires examining the comprehensive data through a truly long period of time. In this study, by using a unique dataset of returns on multiple asset classes from more than 80 countries and covering a period of more than 170 years, we aim to shed some light on these questions. The major aim of this article is to explore the time variation of returns in global financial integration across different asset classes through the long run. Hence, using the most comprehensive sample ever examined in this regard, we investigate returns on equities, government bonds, treasury bills, and currencies in 83 countries for the period 1848–2019. We apply a principal components-based method of Pukthuanthong and Roll (2009), designed to track changes in the market integration through time. We demonstrate that the increase in financial integration is not a linear process. Although the levels of integration during the recent decades are generally the highest in history, the integration moves in peaks and troughs. Many asset classes, such as equities and currencies, elevated the levels of integration in the years preceding World War II, but also even further in the past, particularly in the 1860s. The contemporary surge in integration is a consequence of the most recent peaks and troughs that commenced in the 1970s, rather than a consequence of the multi-century linear process. The remainder of the article proceeds as follows: Section 2 discloses our dataset; Section 3 discusses the methods used; Section 4 presents the results; and finally, Section 5 concludes the study. 2. Data Our analyses focus on four major asset classes: equities, government bonds, treasury bills, and currencies, as well as on a pooled sample of all of them. For equities and government bonds, we follow to achieve better coverage, and merge the data from different sources. For equities, in particular, we use single country DS Global Indices calculated and obtained from Thomson Reuters Datastream (TRD). If not available, we rely on GFD Global Equity total return indices obtained from Global Financial Data (GFD). Both types of indices represent value-weighted portfolios covering the majority of the investable universe in different countries. The government bonds are represented by the returns on 10-year benchmark government bonds. To reiterate, our primary data source for government bonds is TRD, which we splice before its inception with GFD. The treasury bill returns are proxied by the GFD USD Bill Return indices. Finally, for currencies, we utilize spot rates versus the U.S. dollar obtained from GFD. We convert all the
foreign exchange (FX) rates to direct quotations, i.e., the amount of U.S. currency required to buy one unit of foreign currency. Our sample comprises 83 countries, although not all the data is available in each country. Specifically, the coverage for equities, government bonds, treasury bills, and currencies includes 71, 57, 62, and 83 countries, respectively. To avoid any small sample bias, we begin our examination in July 1848, at the period when at least 10 countries are covered for each asset class. The number of all the assets available increase gradually from 65 in 1848, the first year of our examination, to 266 in January 2019, when our study period ends (see Fig. 1 for details). For all the asset classes, we use monthly total returns and the frequency is dictated by the availability of early data. To assure comparability of asset returns across different countries, we express all the returns in U.S. dollars. To enable replication, the statistical properties of our sample along with the source tickers are reported in Tables A1–A4 in the Online Appendix. 3. Methods We examine our dataset with the multiple R2 analysis originating from Pukthuanthong and Roll (2009) and employed also by Berger et al. (2011) and Zaremba and Maydybura (2019), which provides an overview of time-series changes in the integration of financial markets. Following the approach of Pukthuanthong and Roll (2009), in the first step, for each month t, we use fiveyear data lagged by five years; i.e., we use the months t-119 to t-60 to derive the first three components of the asset returns. Next, we use these components to calculate the returns on the three major factors through the last five years, i.e., through the months t-59 to t. Finally, we regress the individual asset returns on the global principal components in the period t-59 to t. The multiple R2 obtained by this method forms a measure of stock market integration. We apply the above-described procedure to each of the asset classes separately (equities, government bonds, treasury bills, and currencies), as well as to the pooled sample of all the assets. Finally, closely following Pukthuanthong and Roll (2009), each month we compute cross-sectional average multiple R2 coefficients to provide a snapshot of the evolution of market integration through time. In addition, we regress R2 coefficients on the time (month) variable to formally examine the time trend in the integration. Our approach departs from Pukthuanthong and Roll (2009) in two essential ways: first, these authors used daily returns from year t-1 to derive the components and, subsequently, roll to daily data in year t to compute the factor returns. Due to our data limitations, we rely on two consecutive 60-month component and
28
A. Zaremba, G.D. Kambouris and A. Karathanasopoulos / Economics Letters 182 (2019) 26–29
Fig. 2. Integration of global financial markets through time. Note. Fig. 2 displays average multiple R2 coefficients from the Pukthuanthong and Roll’s (2009) test of integration. The coefficients are calculated from the regression of all the single country indices on the first three principal components of the global equity market. Panels A, B, C, D, and E present the results for the pooled sample of all the assets, as well as for the equities, government bonds, treasury bills, and currencies, respectively. The 1848, 1900, and 1950 cohorts demonstrate the results-based sample of all the assets available as of March 1948, January 1900, and January 1950. The full sample cohort results are based on all the assets available.
A. Zaremba, G.D. Kambouris and A. Karathanasopoulos / Economics Letters 182 (2019) 26–29
factor calculation periods. Second, whereas Pukthuanthong and Roll (2009) utilize ten (10) principal components, we examine only three (3). This is aimed at avoiding spurious correlations in a small asset sample. Finally, we assure the validity of our results by conducting the following robustness checks. First, similar to Pukthuanthong and Roll (2009), we base the analysis not only on the full sample of countries, but also to cohorts available at certain moments in time. We pick three arbitrary dates: July 1848 (the beginning of our sample), January 1900, and January 1950. Notably, each of these cohorts comprises an identical number of assets through time, so the results are not influenced by the time-varying size of the asset universe. Second, we replicate the analysis based on five different principal components. The outcomes of this exercise, reported in Figures A1 and Table A5 in the Online Appendix, are qualitatively consistent with our baseline results. Finally, we check different estimation periods for principal components and factors, spanning from 36 to 120 months. As this analysis leads to no major difference, for the sake of brevity, we do not report them in the paper. 4. Results Fig. 2 presents the average multiple R2 coefficients through time. Starting with the broad overview, Panel A reports the results based on the pooled sample of all assets. Consistently with the earlier studies (e.g., Bekaert and Mehl, 2019; Billio et al., 2017), from the 1970s we observe a systematic rise in integration. It reaches its peak following the Global Financial Crisis, and subsequently moderately decreases. Importantly, before 1970, the integration was not linear, J-shaped, or U-shaped, but moved in peaks and troughs. The first big surge happened around 1860 and the second in 1930 and in the years preceding World War II. The integration levels during that period were only moderately lower than in recent years, indicating that the global market integration is not a completely new phenomenon—it happened at least twice in the past with an almost comparable degree. The peaks and troughs of global financial integration are also likewise evident for individual asset classes. The equities (Panel B) with the levels of integration among the major stock markets in the 1860s are approximately similar to today and exhibit a Ushape. The government bonds (Panel C) also display an increase of integration in the 19th century and before World War II, but in this case, the markets have been incomparably more correlated in recent years. The results for the treasury bills (Panel D) are very volatile and display episodes of elevated integration in the past. Finally, the currency markets (Panel E)—similarly as in equities— reveal an elevated level of integration in the 1860s and 1930s and are comparable to the current levels. Clearly, the global market integration does not appear to be a linear process, but rather moves in peaks and troughs. The estimation of the slope coefficients on the time (month) variable—reported in Table 1—confirm the intuition from Fig. 2. When we consider the examination of the full study period, based on the full sample of the 1848 cohort, we can hardly see a significant linear increase in the integration. However, when we take into account a more recent period, including the 1950 cohort in particular, the time trend is clear and significant across all the
29
Table 1 Time trend in the multiple R2 ratios. 1848 cohort 1900 cohort 1950 cohort Full sample cohort
Equities
Bonds
Bills
Currencies
All assets
0.007 (0.169) 0.030** (2.206) 0.086** (2.512) −0.005 (−0.189)
0.023 (1.297) 0.044*** (4.542) 0.096* (1.910) 0.011 (1.482)
0.004 (0.381) 0.048*** (4.268) 0.085*** (4.652) −0.003 (−0.172)
0.018 (1.101) 0.029* (1.959) 0.073*** (7.057) 0.004 (0.279)
0.021 (0.764) 0.039*** (2.848) 0.087* (1.857) 0.010 (0.663)
Note. The table reports the slope coefficients (multiplied by 100) of the regression of the Pukthuanthong and Roll (2009)-style multiple R2 coefficients on the time (month) variable. The numbers in brackets areNewey and West (1987) adjusted t-statistics. The analysis is performed separately for equities, government bonds, treasury bills, currencies, and the merged sample of all the assets. The 1848, 1900, and 1950 cohorts indicate the examination of countries available in July 1848, January 1900, and January 1950, respectively. The full sample cohort refers to the examination of all the countries available in the sample.
asset classes. In other words, the current high levels of integration are a result of the increase in the several most recent decades, rather than a consequence of the long-run trend. 5. Concluding remarks Using a unique and most comprehensive sample of data from 83 countries for the years 1848–2019, we explore the time changes in global integration of equities, government bonds, treasury bills, and currency markets and we demonstrate that the integration does not increase linearly over the long run, but rather moves in peaks and troughs. Although the current levels of market co-movements are particularly high, comparable levels were recorded in the 19th century and in the years preceding World War II. Future studies may focus on exploring the sources of this time variation in global financial market integration. Appendix A. Supplementary data Supplementary material related to this article can be found online at https://doi.org/10.1016/j.econlet.2019.05.043. References Bekaert, G., Mehl, A., 2019. On the global financial market integration swoosh and the trilemma. J. Int. Money Financ. 94, 227–245. Berger, D., Pukthuanthong, J.J., Yang, K., 2011. International diversification with frontier markets. J. Financ. Econ. 101 (1), 227–242. Billio, M., Donadelli, M., Paradiso, A., Riedel, M., 2017. Which market integration measure?. J. Bank. Financ. 76, 150–174. Dorodnykh, E., 2014. A Literature Review of the Stock Market Integration. in: Stock Market Integration: An International Perspective. Palgrave Pivot, London. Newey, W.K., West, K.D., 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55 (3), 703–708. Pukthuanthong, K., Roll, R., 2009. Global market integration: An alternative measure and its application. J. Financ. Econ. 94, 214–232. Sharma, A., Seth, N., 2012. International financial integration in the aftermath of the global financial crisis. Qualit. Res. Financ. Markets 4 (1), 84–122. Zaremba, A., Maydybura, A., 2019. The cross-section of returns in frontier equity markets: Integrated or segmented pricing?. Emerg. Mark. Rev 38, 219–238.
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Two centuries of global financial market integration: Equities, government bonds, treasury bills, and currencies✩ ∗
Adam Zaremba a,b , , George D. Kambouris b , Andreas Karathanasopoulos b a
Department of Investment and Capital Markets, Faculty of Management, Poznań University of Economics and Business, al. Niepodległości 10, 61-875, Poznań, Poland b Dubai Business School, University of Dubai, Academic City, Emirates Road, Dubai, P.O. Box: 14143, United Arab Emirates
highlights
graphical
abstract
• We perform the longest study of
•
• • •
global financial integration ever conducted. We examine returns on four asset classes in 83 countries through two centuries. The integration progresses in peaks and troughs instead of linearly. The post-2000 markets exhibit the strongest integration in history. However, certain asset classes in 1860 and 1930 recorded comparable levels.
article
info
Article history: Received 26 April 2019 Received in revised form 17 May 2019 Accepted 27 May 2019 Available online 29 May 2019 JEL classification: F15 F36 G15
a b s t r a c t We perform the longest and broadest study of time variation in global financial market integration ever conducted. Using a unique comprehensive dataset, we examine returns on equities, government bonds, treasury bills, and currencies in 83 countries through a period of almost two centuries. The study discloses that the integration progresses in peaks and troughs instead of linearly. Although the post-2000 markets exhibit the strongest integration in history, certain asset classes in 1860 and 1930 recorded comparable levels. The high degree of current integration is a result of the surge that commenced as recently as 1970, rather than a consequence of a multi-century gradual process. © 2019 Elsevier B.V. All rights reserved.
Keywords: Financial market integration Global markets Factor analysis Early asset data
1. Introduction
✩ Funding: This work was supported by the National Science Centre of Poland grant no.: 2015/19/B/HS4/00378). ∗ Corresponding author at: Department of Investment and Capital Markets, Faculty of Management, Poznań University of Economics and Business, al. Niepodległości 10, 61-875, Poznań, Poland. E-mail addresses: [email protected], [email protected] (A. Zaremba), [email protected] (G.D. Kambouris), [email protected] (A. Karathanasopoulos). https://doi.org/10.1016/j.econlet.2019.05.043 0165-1765/© 2019 Elsevier B.V. All rights reserved.
There are mounting studies in economics that debate the nature of global financial integration.1 They discuss questions such as: Is the integration a stable, long-run progression to ever-higher levels of global market co-movement? Or, does the integration move in waves, exhibiting hikes and reversals? Is the integration linear, J-shaped, U-shaped, or ‘‘swoosh’’-shaped? Since the 1 See, e.g., Bekaert and Mehl (2019), Billio et al. (2017), Dorodnykh (2014), or Sharma and Seth (2012) for a literature review.
A. Zaremba, G.D. Kambouris and A. Karathanasopoulos / Economics Letters 182 (2019) 26–29
27
Fig. 1. Number of countries covered in the sample. Note. Fig. 1 discloses the number of countries in the sample with data on equities, government bonds, treasury bills, and currencies available through time.
financial market integration is a long-term multidimensional phenomenon, providing a proper answer requires examining the comprehensive data through a truly long period of time. In this study, by using a unique dataset of returns on multiple asset classes from more than 80 countries and covering a period of more than 170 years, we aim to shed some light on these questions. The major aim of this article is to explore the time variation of returns in global financial integration across different asset classes through the long run. Hence, using the most comprehensive sample ever examined in this regard, we investigate returns on equities, government bonds, treasury bills, and currencies in 83 countries for the period 1848–2019. We apply a principal components-based method of Pukthuanthong and Roll (2009), designed to track changes in the market integration through time. We demonstrate that the increase in financial integration is not a linear process. Although the levels of integration during the recent decades are generally the highest in history, the integration moves in peaks and troughs. Many asset classes, such as equities and currencies, elevated the levels of integration in the years preceding World War II, but also even further in the past, particularly in the 1860s. The contemporary surge in integration is a consequence of the most recent peaks and troughs that commenced in the 1970s, rather than a consequence of the multi-century linear process. The remainder of the article proceeds as follows: Section 2 discloses our dataset; Section 3 discusses the methods used; Section 4 presents the results; and finally, Section 5 concludes the study. 2. Data Our analyses focus on four major asset classes: equities, government bonds, treasury bills, and currencies, as well as on a pooled sample of all of them. For equities and government bonds, we follow to achieve better coverage, and merge the data from different sources. For equities, in particular, we use single country DS Global Indices calculated and obtained from Thomson Reuters Datastream (TRD). If not available, we rely on GFD Global Equity total return indices obtained from Global Financial Data (GFD). Both types of indices represent value-weighted portfolios covering the majority of the investable universe in different countries. The government bonds are represented by the returns on 10-year benchmark government bonds. To reiterate, our primary data source for government bonds is TRD, which we splice before its inception with GFD. The treasury bill returns are proxied by the GFD USD Bill Return indices. Finally, for currencies, we utilize spot rates versus the U.S. dollar obtained from GFD. We convert all the
foreign exchange (FX) rates to direct quotations, i.e., the amount of U.S. currency required to buy one unit of foreign currency. Our sample comprises 83 countries, although not all the data is available in each country. Specifically, the coverage for equities, government bonds, treasury bills, and currencies includes 71, 57, 62, and 83 countries, respectively. To avoid any small sample bias, we begin our examination in July 1848, at the period when at least 10 countries are covered for each asset class. The number of all the assets available increase gradually from 65 in 1848, the first year of our examination, to 266 in January 2019, when our study period ends (see Fig. 1 for details). For all the asset classes, we use monthly total returns and the frequency is dictated by the availability of early data. To assure comparability of asset returns across different countries, we express all the returns in U.S. dollars. To enable replication, the statistical properties of our sample along with the source tickers are reported in Tables A1–A4 in the Online Appendix. 3. Methods We examine our dataset with the multiple R2 analysis originating from Pukthuanthong and Roll (2009) and employed also by Berger et al. (2011) and Zaremba and Maydybura (2019), which provides an overview of time-series changes in the integration of financial markets. Following the approach of Pukthuanthong and Roll (2009), in the first step, for each month t, we use fiveyear data lagged by five years; i.e., we use the months t-119 to t-60 to derive the first three components of the asset returns. Next, we use these components to calculate the returns on the three major factors through the last five years, i.e., through the months t-59 to t. Finally, we regress the individual asset returns on the global principal components in the period t-59 to t. The multiple R2 obtained by this method forms a measure of stock market integration. We apply the above-described procedure to each of the asset classes separately (equities, government bonds, treasury bills, and currencies), as well as to the pooled sample of all the assets. Finally, closely following Pukthuanthong and Roll (2009), each month we compute cross-sectional average multiple R2 coefficients to provide a snapshot of the evolution of market integration through time. In addition, we regress R2 coefficients on the time (month) variable to formally examine the time trend in the integration. Our approach departs from Pukthuanthong and Roll (2009) in two essential ways: first, these authors used daily returns from year t-1 to derive the components and, subsequently, roll to daily data in year t to compute the factor returns. Due to our data limitations, we rely on two consecutive 60-month component and
28
A. Zaremba, G.D. Kambouris and A. Karathanasopoulos / Economics Letters 182 (2019) 26–29
Fig. 2. Integration of global financial markets through time. Note. Fig. 2 displays average multiple R2 coefficients from the Pukthuanthong and Roll’s (2009) test of integration. The coefficients are calculated from the regression of all the single country indices on the first three principal components of the global equity market. Panels A, B, C, D, and E present the results for the pooled sample of all the assets, as well as for the equities, government bonds, treasury bills, and currencies, respectively. The 1848, 1900, and 1950 cohorts demonstrate the results-based sample of all the assets available as of March 1948, January 1900, and January 1950. The full sample cohort results are based on all the assets available.
A. Zaremba, G.D. Kambouris and A. Karathanasopoulos / Economics Letters 182 (2019) 26–29
factor calculation periods. Second, whereas Pukthuanthong and Roll (2009) utilize ten (10) principal components, we examine only three (3). This is aimed at avoiding spurious correlations in a small asset sample. Finally, we assure the validity of our results by conducting the following robustness checks. First, similar to Pukthuanthong and Roll (2009), we base the analysis not only on the full sample of countries, but also to cohorts available at certain moments in time. We pick three arbitrary dates: July 1848 (the beginning of our sample), January 1900, and January 1950. Notably, each of these cohorts comprises an identical number of assets through time, so the results are not influenced by the time-varying size of the asset universe. Second, we replicate the analysis based on five different principal components. The outcomes of this exercise, reported in Figures A1 and Table A5 in the Online Appendix, are qualitatively consistent with our baseline results. Finally, we check different estimation periods for principal components and factors, spanning from 36 to 120 months. As this analysis leads to no major difference, for the sake of brevity, we do not report them in the paper. 4. Results Fig. 2 presents the average multiple R2 coefficients through time. Starting with the broad overview, Panel A reports the results based on the pooled sample of all assets. Consistently with the earlier studies (e.g., Bekaert and Mehl, 2019; Billio et al., 2017), from the 1970s we observe a systematic rise in integration. It reaches its peak following the Global Financial Crisis, and subsequently moderately decreases. Importantly, before 1970, the integration was not linear, J-shaped, or U-shaped, but moved in peaks and troughs. The first big surge happened around 1860 and the second in 1930 and in the years preceding World War II. The integration levels during that period were only moderately lower than in recent years, indicating that the global market integration is not a completely new phenomenon—it happened at least twice in the past with an almost comparable degree. The peaks and troughs of global financial integration are also likewise evident for individual asset classes. The equities (Panel B) with the levels of integration among the major stock markets in the 1860s are approximately similar to today and exhibit a Ushape. The government bonds (Panel C) also display an increase of integration in the 19th century and before World War II, but in this case, the markets have been incomparably more correlated in recent years. The results for the treasury bills (Panel D) are very volatile and display episodes of elevated integration in the past. Finally, the currency markets (Panel E)—similarly as in equities— reveal an elevated level of integration in the 1860s and 1930s and are comparable to the current levels. Clearly, the global market integration does not appear to be a linear process, but rather moves in peaks and troughs. The estimation of the slope coefficients on the time (month) variable—reported in Table 1—confirm the intuition from Fig. 2. When we consider the examination of the full study period, based on the full sample of the 1848 cohort, we can hardly see a significant linear increase in the integration. However, when we take into account a more recent period, including the 1950 cohort in particular, the time trend is clear and significant across all the
29
Table 1 Time trend in the multiple R2 ratios. 1848 cohort 1900 cohort 1950 cohort Full sample cohort
Equities
Bonds
Bills
Currencies
All assets
0.007 (0.169) 0.030** (2.206) 0.086** (2.512) −0.005 (−0.189)
0.023 (1.297) 0.044*** (4.542) 0.096* (1.910) 0.011 (1.482)
0.004 (0.381) 0.048*** (4.268) 0.085*** (4.652) −0.003 (−0.172)
0.018 (1.101) 0.029* (1.959) 0.073*** (7.057) 0.004 (0.279)
0.021 (0.764) 0.039*** (2.848) 0.087* (1.857) 0.010 (0.663)
Note. The table reports the slope coefficients (multiplied by 100) of the regression of the Pukthuanthong and Roll (2009)-style multiple R2 coefficients on the time (month) variable. The numbers in brackets areNewey and West (1987) adjusted t-statistics. The analysis is performed separately for equities, government bonds, treasury bills, currencies, and the merged sample of all the assets. The 1848, 1900, and 1950 cohorts indicate the examination of countries available in July 1848, January 1900, and January 1950, respectively. The full sample cohort refers to the examination of all the countries available in the sample.
asset classes. In other words, the current high levels of integration are a result of the increase in the several most recent decades, rather than a consequence of the long-run trend. 5. Concluding remarks Using a unique and most comprehensive sample of data from 83 countries for the years 1848–2019, we explore the time changes in global integration of equities, government bonds, treasury bills, and currency markets and we demonstrate that the integration does not increase linearly over the long run, but rather moves in peaks and troughs. Although the current levels of market co-movements are particularly high, comparable levels were recorded in the 19th century and in the years preceding World War II. Future studies may focus on exploring the sources of this time variation in global financial market integration. Appendix A. Supplementary data Supplementary material related to this article can be found online at https://doi.org/10.1016/j.econlet.2019.05.043. References Bekaert, G., Mehl, A., 2019. On the global financial market integration swoosh and the trilemma. J. Int. Money Financ. 94, 227–245. Berger, D., Pukthuanthong, J.J., Yang, K., 2011. International diversification with frontier markets. J. Financ. Econ. 101 (1), 227–242. Billio, M., Donadelli, M., Paradiso, A., Riedel, M., 2017. Which market integration measure?. J. Bank. Financ. 76, 150–174. Dorodnykh, E., 2014. A Literature Review of the Stock Market Integration. in: Stock Market Integration: An International Perspective. Palgrave Pivot, London. Newey, W.K., West, K.D., 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55 (3), 703–708. Pukthuanthong, K., Roll, R., 2009. Global market integration: An alternative measure and its application. J. Financ. Econ. 94, 214–232. Sharma, A., Seth, N., 2012. International financial integration in the aftermath of the global financial crisis. Qualit. Res. Financ. Markets 4 (1), 84–122. Zaremba, A., Maydybura, A., 2019. The cross-section of returns in frontier equity markets: Integrated or segmented pricing?. Emerg. Mark. Rev 38, 219–238.