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The purpose of this paper is to assess how much difference it makes for US firms to use the two‐factor ICAPM to estimate their cost of equity instead of a single‐factor CAPM.

For a large sample of US companies, the authors compare the empirical cost of equity estimates of a two‐factor international CAPM with those of the single‐factor domestic CAPM and the single‐factor global CAPM.

The authors find that the cost of equity estimates of the two‐factor ICAPM are reasonably close to those of either single‐factor model for US firms with low‐to‐moderate foreign exchange exposure; and second, perhaps surprisingly, for US firms with extreme foreign exchange exposure, that the cost of equity estimates of the two‐factor ICAPM tend to be very close to those of the domestic CAPM, and even closer than to those of the single‐factor global CAPM.

The paper's findings might prove useful to academic researchers wanting to resolve the seemingly contradictory empirical results on the pricing of FX risk.

The findings will hopefully help managers decide whether they should go to the trouble of estimating a US firm's cost of equity with the two‐factor international CAPM instead of a traditional single‐factor CAPM.

The paper extends the existing literature by focusing on the two‐factor ICAPM, and finds some new and surprising empirical results.

Finance theory such as Merton’s ICAPM suggests that there should be a positive relationship between the expected return and risk. Empirical evidence on this relationship, however, is far from conclusive. Building on the recent econometric research on this topic such as Lundblad (2007) and Hedegaard and Hodrick (2016), we estimate the risk-return relation implied in the ICAPM using a long sample (1962~2016) of daily, weekly, and monthly excess stock returns in Korea. More specifically, we estimate various volatility models including GARCH-M using the overlapping data inference (ODIN) method suggested by Hedegaard and Hodrick (2016), as well as the traditional maximum likelihood estimation methodology. For the full sample period, we fail to find a positive risk-return relationship that is significant and robust. For the subsample period from 1998 to 2016, however, we find a significantly positive risk-return relation for GARCH-M model regardless of return intervals and estimation methods. This result is also robust to using other specifications such as EGARCH-M which includes the leverage effect of the variance process and EGARCH-M-GED whose conditional distribution has fatter tails. Our findings suggest that there is indeed a positive relationship between the expected return and risk in the Korean stock market, at least for the period after 1998.

The purpose of this study is to investigate whether the surprise components of systematic risk, which are useful in forecasting future investment opportunities, help explain the cross-section of average returns associated with portfolios sorted on size, book-to-market and accruals. This study also aims to examine the mispricing attributes of the size, value and accrual effects by investigating the relative economic relevance of aggregate risk factors, which are related to exogenous shocks in state variables, in the cross-sectional returns of triple-sorted portfolios.

This study uses innovations of systematic risk, which affect the cash flows and risk-adjusted discount rates of all firms in an economy and determines the expected returns of portfolios based on firm characteristics. This study uses independent sorts based on size, book-to-market and total accruals – all of which are measured at the firm level – and construct three-dimensional test portfolios. For unobserved innovations, this study estimates a triangular structural vector autoregressive system and obtain the exogenous innovations in state variables. The author uses Fama-MacBeth two-pass cross-sectional regressions and examines whether the structural innovations explain a significant part of the cross-sectional variation in the average returns of the test portfolios.

This study finds that variations in expected returns of testing assets are determined by differences in the underlying assets’ exposure to systematic risk innovation. The empirical evidence also shows that exogenous innovation in Fama-French (FF) risk factors leaves out important cross-sectional information about expected returns, and additionally, the FF-factor betas have lower cross-sectional power than the proxy for innovation betas. The cross-sectional differences in the test portfolios’ sensitivity to instruments such as the short-term Treasury bill rate and term spread survive the presence of FF-factor betas.

In contrast to the existing literature, this study uses structural innovations that are uncorrelated and thus exogenous in nature. The author creates test portfolios that display a wide range of average returns and are unlikely to show spurious variability in risk exposures. Unlike the existing research, where size, value and accrual anomalies have been analyzed in isolation, this study examine these pricing patterns jointly, focusing on the possible contributing role of structural innovation in economy-wide predictor variables. To the best of the author’s knowledge, this paper is the first attempt to link the sensitivity of portfolios sorted on size, book-to-market and accruals to exogenous structural innovation.

This essay provides a non‐technical account of the development of thinking about the ways in which financial markets work. The account is organized by distinguishing between the “financial approach” and the “monetary approach” to the study of financial markets. The financial approach emphasizes the importance of arbitrage in determining financial asset prices. The monetary approach utilizes the more traditional tools of supply and demand, and places greater emphasis on the role of market imperfections. The essay evaluates the contribution of each approach to improving our understanding of financial markets. It concludes that the central problem in financial market research remains that of providing a satisfactory explanation of the determination of asset prices. In the emerging regime of liberalized, competitive financial markets both the financial approach and the monetary approach have a distinctive contribution to make in understanding how these markets work. This paper is based on research funded by the Economic and Social Research Council under grant No. B0023‐2151.

The purpose of this paper is to explore the consequences of appraisal smoothing in the estimation of the risks and returns of farm real estate. It examines the degree to which the risk and return characteristics of farm real estate are an artifact of the methods used to measure aggregate property values.

A multifactor asset pricing model is estimated using farm real estate returns in a manner consistent with prior research, as well as using farm real estate returns calculated using two synthetic unsmoothing procedures developed in the real estate finance literature.

The model suggests that unsmoothed farm real estate returns exhibit characteristics that differ from those suggested by prior research. The unsmoothed returns suggest a stronger correlation with economy wide investment risks.

This is the first study to evaluate the impacts of appraisal smoothing in a farm real estate context. It provides a simple framework for addressing many of the pricing anomalies associated with farmland.

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.

The purpose of this paper is to investigate the mechanism of transmitting economic policy uncertainty (EPU) shocks to capital structure.

The authors adopt a novel approach that bridges the asset pricing implications of EPU and the debt-financing decisions of Chinese firms by introducing a variable “policy-risk-induced equity return” (PRER). PRER is the product of the EPU beta and the EPU shock. Differentiating firms as per the signs of the EPU beta helps to shed light on the deep questions of whether their respective leverage targets and speeds of adjustment are different and how the targets and speeds are determined.

The empirical evidence shows that it is the equity market that channels EPU shocks to capital structure through PRER in China. Firms with positive (negative) EPU betas have PRER impact negatively (positively) the leverage target, conforming to the market-timing theory. EPU and non-policy uncertainty shocks cause the speed of adjustment to change over time. Overall, the intertemporal relation between EPU and leverage is negative. These results are robust to alternative leverage measures and after controlling for non-policy uncertainty shocks and conventional firm characteristics and have implications for academic research, policymaking, market stability, and corporate financing.

This study is the first to probe for, and provide insights into, the underlying reason why EPU impacts capital structure by connecting asset pricing to corporate financing for a large sample of Chinese publicly traded firms.

The purpose of this paper is to pay more attention to four different research questions at least. One is that this study intends to explore the changes of the risk-return relationship over time, because the institutions and environment have changed a lot and might tend to influence the risk-return regime in the Chinese stock markets. The second question is whether there is any difference for the risk-return relationship between Shanghai and Shenzhen stock markets. The third question is to compare the similarities and dissimilarities of the risk-return tradeoff for different frequency data. The fourth question is to compare the explanation power of different GARCH-M type models which are all widely used in exploring the risk-return tradeoff.

This paper investigates the risk-return tradeoff in the Chinese emerging stock markets with a sample including daily, weekly and monthly market return series. A group of variant specifications of GARCH-M type models are used to test the risk-return tradeoff. Additionally, some diagnostic checks proposed by Engle and Ng (1993) are used in this paper, and this will help to assess the robustness of different models.

The empirical results show that the dynamic risk-return relationship is quite different between Shanghai and Shenzhen stock markets. A positive and statistically significant risk-return relationship is found for the daily returns in Shenzhen Stock Exchange, while the conditional mean of the stock returns is negatively related to the conditional variance in Shanghai Stock Exchange. The risk-return relationship usually becomes much weaker for the lower frequency returns in both markets. A further study with the sub-samples finds a positive and significant risk-return trade-off for both markets in the second stage after July 1, 1999.

This paper extends the existing related researches about the Chinese stock markets in several ways. First, this study uses a longer sample to investigate the relationship between stock returns and volatility. Second, this study estimates the returns and volatility relationship with different frequency sample data together. Third, a group of variant specifications of GARCH-M type models are used to test the risk-return tradeoff. In particular, the author employs the Component GARCH-M model which is relatively new in this line of research. Fourth, this study investigates if there is any structural break affecting the risk-return relationship in the Chinese stock markets over time.

The study investigates the inter-linkages between geopolitical risk (GPR) and food price (FP).

By employing the bootstrap full- and sub-sample rolling-window Granger causality tests.

The empirical results show that there is a time-varying bidirectional causality between GPR and FP. High GPR leads to a rise in FP, suggesting that geopolitical events usually may disrupt supply and demand conditions in food markets, and even trigger global food crises. However, the negative effect of GPR on FP does not support this view in certain periods. This is mainly because GPR is also related to the global economic situation and oil price, which together have impacts on the food market. These results cannot always be supported by the inter-temporal capital asset pricing model, which states that GPR affects FP in a positive manner. Conversely, there is a positive impact of FP on GPR, indicating that the food market is an effective tool that can reflect global geopolitical environment.

In the context of the Russia–Ukraine conflict, these analyses can assist investors and policymakers to understand the sensitivity of FP to GPR. Also, it will provide significant revelations for governments to attach importance to the role of food price information in predicting geopolitical events, thus contributing to a more stable international environment.

The purpose of the study is to examine the dynamics in the troika of asset pricing, volatility, and the business cycle in the US and Japan.

The study uses a six-factor asset pricing model to derive the realized volatility measure for the GARCH-type models.

The comprehensive empirical investigation led to the following conclusion. First, the results infer that the market portfolio and human capital are the primary discounting factors in asset return predictability during various phases of the subprime crisis phenomenon for the US and Japan. Second, the empirical estimates neither show any significant impact of past conditional volatility on the current conditional volatility nor any significant effect of subprime crisis episodes on the current conditional volatility in the US and Japan. Third, there is no asymmetric volatility effect during the subprime crisis phenomenon in the US and Japan except the asymmetric volatility effect during the post-subprime crisis period in the US and full period in Japan. Fourth, the volatility persistence is relatively higher during the subprime crisis period in the US, whereas during the subprime crisis transition period in Japan than the rest of the phases of the subprime crisis phenomenon.

The study argues that the empirical investigations that employed the autoregressive method to derive the realized volatility measure for the parameter estimation of GARCH-type models may result in incurring spurious estimates. Further, the empirical results of the study show that using the six-factor asset pricing model in an intertemporal framework to derive the realized volatility measure yields better estimation results while estimating the parameters of GARCH-type models.