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This study aims to organise and present the development of asset pricing models in the international environment. The stock market integration and cross-listing lead us to another objective of bibliometric analysis for “International Asset Pricing” to provide a complete overview and give scope and directions for future research.

Web of Science database is used to search with “International Asset Pricing.” Of 3,438 articles, 2,487 articles are selected for the final bibliometric analysis. Various research such as citation analysis, keyword analysis, author’s and corresponding author's analysis have been conducted.

The bibliometric analysis finds that the USA comes out to be the country where the maximum research was conducted on the topic. The keyword analysis was also analysed to evaluate the significant areas of the research. Risk, return and international asset pricing are the most frequently used keywords. The year 2020 has the maximum number of published research articles and citations due to the change in the market structure worldwide and the effect of Covid-19 across the world.

The present paper provides the collection, classification and comprehensive analysis of “International Asset pricing,” which may help the academicians, researchers and practitioners for future research for the relevant subject area.

This study aims to provide a comprehensive overview of asset pricing research and identifies the general research trends in the area. The study also aims to provide future direction to the researchers in the area of asset pricing.

The study uses bibliometric analysis techniques to achieve the stated purpose. The study covers 3,007 articles published in the top 50 finance and economics journals, accessed from the Scopus database for a period of 47 years (1973–2020). After initial searching for “asset pricing” as the main keyword in “title, abstract, keywords”, the database yields 6,583 articles. This number further reduces to 3,007 articles when the search is restricted to research and review articles published in the top 50 peer-reviewed journals.

The tabular and pictorial representation obtained from the analysis exhibit that asset pricing is an extensively researched area; however, a sudden rise in the number of publications (242) observed for 2019 demonstrates a growing interest amongst researchers. Further, affiliation statistics indicate that the volume of research is mainly concentrated in the USA and other developed nations; hence it opens vistas for the exploration of risk-return dynamics in the context of emerging markets.

The work presents an exhaustive and comprehensive review along with potential research implications. The present study reconciles various contradictory views of the prior studies under asset pricing such as risk-return trade-off, low-risk anomaly and provides the researchers with potential research gaps.

The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets.

The general methodology to test asset pricing models involves regressing test asset returns (left-hand side assets) on pricing factors (right-hand side assets). Then the performance of different models is evaluated based on how well they price multiple test assets together. The parameters used to compare relative performance of different models are their pricing errors (GRS statistic and average absolute intercepts) and explained variation (average adjusted R²).

The Fama-French five-factor model improves the pricing performance for stocks in Australia, Canada, China and the USA. The pricing in these countries appears to be more integrated. However, the superior performance in these four countries is not consistent across a variety of test assets and the magnitude of reduction in pricing errors vis-à-vis three- or four-factor models is often economically insignificant. For other markets, the parsimonious three-factor model or its four-factor variants appear to be more suitable.

Unlike most asset pricing studies that use test assets based on variables that are already used to construct RHS factors, this study uses test assets that are generally different from RHS sorts. This makes the tests more robust and less biased to be in favour of any multifactor model. Also, most international studies of asset pricing tests use data for different markets and combine them into regions. This study provides the evidence from ten countries separately because prior research has shown that locally constructed factors are more suitable to explain asset prices. Further, this study also tests for the usefulness of adding a quality factor in the existing asset pricing models.

The purpose of this paper is to examine whether the conditionally expected return on size-based portfolios in an emerging market (EM) is determined by the country’s world risk exposure. The authors analyze the degree of financial integration of 23 emerging equity markets grouped into five size portfolios using the conditional international asset pricing model with both world and domestic market risks. The authors also compare the model’s fitness on the predictability of portfolio returns by using world and EM indices.

This study investigates whether large-cap stocks are priced globally and whether mid- and small-cap stocks are strongly influenced by domestic risk factors. The authors first examine the predictability of large-, mid-, and small-cap stock portfolio returns by using global and local variables, and next compare the model fitness by using world and EM indices on the prediction of size-based stock returns. Finally, the authors test whether the world price of covariance risk is the same for different portfolios.

The authors find that the conditional expected returns of large-cap stocks should be priced by global variables. Mid- and small-cap stocks are influenced by domestic variables rather than global variables, and their returns are priced by local residual risks. The test of the conditional asset pricing model shows that the largest stocks have the smallest mean absolute pricing errors (MAE), and their pricing errors are lower in large markets than in small markets. Third, the EM index offers more predictability for the excess returns of mid- and small-cap stocks than the world market index, but the explanatory power of this index does not increase for large-cap stocks.

EMs in the past were known as segment markets, with local risk factors more important than global risk factors, suggesting significant benefits from adding EMs to global portfolios. It would be interesting to examine whether financial integration differs for various firm sizes in the markets.

This study explores the nature of the spot foreign exchange risk premium. Employing Ross's Arbitrage Pricing Theory (APT) as a vehicle, it tests the hypothesis that cross‐sectional differences in pure currency returns depend on measures of systematic (covariance) risk. These tests have greater power, in the sense of an enhanced ability to reject the hypothesis, since they explicitly allow for the possibility that idiosyncratic risk is priced. A battery of tests is unable to reject the hypothesis that expected exchange returns can be explained by a single‐factor APT. One implication of these results is that official intervention in exchange markets is unnecessary and undesirable.

The purpose of this paper is to investigate the pricing of European real estate equities. The study examines the main drivers of real estate equity returns and determines whether loadings on systematic risk factors – the excess market return, small minus big (SMB), HIGH minus low (HML) – can explain cross‐sectional return differences in unconditional as well as in conditional asset pricing tests.

The paper draws upon time‐series regressions to investigate determinants of real estate equity returns. Rolling Fama‐French regressions are applied to estimate time‐varying loadings on systematic risk factors. Unconditional as well as conditional monthly Fama‐MacBeth regressions are employed to explain cross‐sectional return variations.

Systematic risk factors are important drivers of European real estate equity returns. Returns are positively related to the excess market return and to a value factor. A size factor impacts predominantly negatively on real estate returns. The results indicate increasing market integration after the introduction of the Euro. Loadings on systematic risk factors have weak explanatory power in unconditional cross‐section regressions but can explain returns in a conditional framework. Beta – and to a lesser extent the loading on HML – is positively related to returns in up‐markets and negatively in down markets. Equities which load positively on SMB outperform in down markets.

The implementation of a liquidity or a momentum factor could provide further evidence on the pricing of European real estate equities.

The findings could help investors to manage the risk exposure more effectively. Investors should furthermore be able to estimate their cost of equity more precisely and might better be able to pick stocks for time varying investment strategies.

This is the first paper to examine the pricing of real estate equity returns in a pan‐European setting.

The purpose of this paper is, to study macroeconomic risk factors driving the expected stock returns of listed private equity (LPE). The authors use LPE indices divided into different styles and regions from January 2004 to December 2016 and a set of country stock indices to estimate the macroeconomic risk profiles and corresponding risk premiums. Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market βs that are greater than 1. A one-factor asset pricing model using world stock market returns as the only possible risk factor is rejected on the basis of generalized method of moments (GMM) orthogonality conditions. In contrast, using the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of economic policy uncertainty as additional risk factors, this multifactor model is able to price a cross-section of expected LPE returns. The risk-return profile of LPE differs from country equity indices. Consequently, LPE should be treated as a separate asset class.

Following Ferson and Harvey (1994), the authors use an unconditional asset pricing model to capture the structure of returns across LPE. The authors use 11 LPE indices divided into different styles and regions from January 2004 to December 2016, and a set of country stock indices as spanning assets to estimate the macroeconomic risk profiles and corresponding risk premiums.

Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market ßs that are greater than 1. The authors estimate a one-factor asset pricing model using world stock market returns as the only possible risk factor by GMM. This model is rejected on the basis of the GMM orthogonality conditions. By contrast, a multifactor model built on the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of global economic policy uncertainty as additional risk factors is able to price a cross-section of expected LPE returns.

Given data availability, the authors’ sample is strongly influenced by the financial crisis and its aftermath.

Information about the risk profile of LPE is important for asset allocation decisions. In particular, it may help to optimally react to contemporaneous changes in economy-wide risk factors.

To the best of authors’ knowledge, this is the first LPE study which investigates whether a set of macroeconomic factors is actually priced and, therefore, associated with a non-zero risk premium in the cross-section of returns.

The purpose of this paper is to provide empirical evidence on how 1999–2001 dot-com crisis and 2007–2009 subprime crisis affect the gains from international diversification from the perspective of US investors.

A conditional international CAPM with asymmetric multivariate GARCH-M specification is used to estimate international diversification gains.

The authors find that over the entire sample period, the average gains from international diversification is statistically significant and about 1.253 percent per year. During the subprime crisis period, the average gains decreases to about 0.567 percent per year, but it increases to 2.829 percent per year during the dot-com crisis.

These research findings although confirm the conjectures that international financial turmoil tends to increase the co-movements among global financial markets, are in contrast to the conjectures that international diversification does not work during the financial crisis as evidence from the dot-com crisis. Therefore, future research on international diversification should not just focus on the correlation among international financial markets and should adopt a fully parameterized asset pricing model to study this research topic.

Given the empirical results found in this paper that international diversification gains may be decreasing or increasing during the financial crisis, as long as investors are not able to predict international financial crises, it is the average gains from international diversification over the longer periods that should encourage investors to diversify, regardless of potentially lower benefits over the shorter periods of time.

The major value of this paper is that although the increase in the conditional correlation during the financial turmoil is consistent with previous studies, the empirical results clearly show that the impact of a financial crisis on the gains from international diversification cannot be solely determined by the correlation between domestic and world stock market returns since the gains also depend on the unsystematic risk from the domestic stock market. Consequently, it is premature for previous studies to conclude that the gain from international diversification is diminishing due to an increasing correlation among international stock markets during the financial crisis.

Whether stock returns are linked to exchange rate changes and whether foreign exchange risk is priced in a domestic context are less conclusive and thus still subject to a great debate. The purpose of this paper is to provide new empirical evidence on these two inter‐related issues, which are critical to investors and corporate risk management.

This paper applies two different econometric approaches: Nonlinear Seemingly Unrelated Regression (NLSUR) via Hansen's Generalized Method of Moment (GMM) and multivariate GARCH in mean (MGARCH‐M) to examine the exchange rate exposure and its pricing.

Using industry data for Japan, similar to previous studies, foreign exchange risk is not priced based on the test of an unconditional two‐factor asset pricing model. However, strong evidence of time‐varying foreign exchange risk premium and significant exchange rate betas are obtained based on the tests of conditional asset pricing models using MGARCH‐M approach where both conditional first and second moments of industry returns and risk factors are estimated simultaneously.

The strong empirical evidence found in this study implies that corporate currency hedging not only results in more stable cash flows for a firm, but also reduces its cost of capital, and hence is justifiable.

This paper conducts an in‐depth investigation regarding the exchange rate exposure and its pricing by utilizing two different econometric approaches: NLSUR via Hansen's GMM and MGARCH‐M. In doing so, a more reliable conclusion about the exchange rate exposure and its pricing can be drawn.

The purpose of this paper is to examine financial integration across North American stock markets from January 1984 to December 2003.

The paper uses an arbitrage pricing theory framework. The risk factors considered are the three Fama and French factors augmented with momentum for both countries as well as their international counterparts. Both the domestic and international four factor models in cross section and test for partial, mild, and strong financial integration are estimated. The domestic and international model are estimated on domestic portfolios and on a subset of Canadian cross listings matched with American stocks.

Results can be summarized as follows: first, results show stronger evidence of mild rather than partial or strong integration in both domestic portfolios and interlisted stocks. Second, interlisted stocks appear at first glance to be more integrated than the domestic portfolios, but this result can be attributed to the poor explanatory power of the models applied to interlisted stocks. Once the authors rule out the case where the model does not generate statistically important risk premiums for both countries, the evidence of integration is similar in both domestic and interlisted stocks. Third, the domestic and international models have similar explanatory power, although the domestic model performs better with the Canadian interlisted stocks are found.

The results suggest that, in an international context, a portfolio manager is better off using the four factor model as a benchmark in cross sections rather than the single market. Furthermore, if the agency problem described in Karolyi is ignored, Canadian interlisted stocks and Canadian domestic portfolios have the same diversification potential.