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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.

Extensive studies have investigated the relation between risk and return in the stock and major asset markets, whereas little studies have been done for housing, particularly the Australian housing market. This study aims to determine the relationship between housing risk and housing return in Australia.

The analysis of this study involves two stages. The first stage is to estimate the presence of volatility clustering effects. Thereafter, the relation between risk and return in the Australian housing market is assessed by using a component generalised autoregressive conditional heteroscedasticity-in-mean (C-CARCH-M) model.

The empirical results show that there is a strong positive risk-return relationship in all Australian housing markets. Specifically, comparable results are also evident in all housing markets in various Australian capital cities, reflecting that Australian home buyers, in general, are risk reverse and require a premium for higher risk level. This could be attributed the unique characteristics of the Australian housing market. In addition, there is evidence to suggest that a stronger volatility clustering effect than previously documented in the daily case.

The findings enable more informed and practical investment decision-making regarding the relation between housing return and housing risk.

This paper is the first study to offer empirical evidence of the risk-return relationship in the Australian housing market. Besides, this is the first housing price volatility study that utilizes daily data.

This paper aims to investigate the effect of global financial market uncertainty on the relation between risk and return in G7 stock markets.

Market uncertainty is quantified using a probability-based measure derived from a regime-switching model in which the state transition probabilities are time-varying in response to leading economic indicators. Time variation in the risk return relation is estimated using a GARCH-M model.

While the regime-switching model successfully distinguishes between crisis and normal states, there remains substantial variability through time in the level of uncertainty about which state prevails. Results show that a strong negative relation exists between this uncertainty and the reward-to-variability ratio across all G7 stock markets. This finding is qualitatively consistent at both monthly and weekly horizons.

Extant evidence on the risk-return relation is conflicting. Most papers assume the relation is time constant. Allowing the reward-to-variability ratio to vary through time in response to return regime uncertainty increases the understanding of asset pricing. It also has important implications for asset allocation decisions by investors.

The risk-return relationship is one of the most widely investigated topics in finance, yet this relationship remains one of the most controversial topics. The purpose of this paper is to investigate the asymmetric volatility and the risk-return tradeoff at the sector level in the emerging stock market of Jordan.

Data consist of daily prices for 22 sub-sectors spanning from August 1, 2006, to September 30, 2015, covering the periods of pre, during, and after the global financial crisis. The EGARCH-M model is used to document the patterns of asymmetric volatility of sub-sector returns and the risk-return tradeoff during the non-overlapping three sub-sample periods.

The major findings of this study are as follows. In the pre-crisis period, the results suggest some evidence of a positive relationship between risk and return. The results also reveal that good news has more effect than bad news during the same period. In the crisis period, there is a negative but insignificant risk-return relationship and negative shocks have more impact than positive ones. In the post-crisis period, the authors find positive but insignificant risk-return tradeoff with weak evidence of volatility asymmetry.

The results have major implications for investors willing to engage their investment decisions in the Amman Stock Exchange (ASE) and for policymakers who seek to attract and retain regional and international investors. Since the empirical investigation is conducted at the sector level, the study may aid investors to target specific sub-sectors with positive and significant risk-return tradeoff. In addition, investors need to monitor the asymmetric patterns which make the level of risk-aversion more susceptible to coming news. For policymakers, the latest infrastructure reforms are crucial to achieving the potential for growth but the ASE market authority needs to undergo further reforms and provide various promotional incentives.

Although there are numerous studies on asymmetric volatility and risk-return tradeoff, there is a lack of parallel studies at the sector level for both developed and emerging stock markets. Such assessment at the sector level is crucial for international investors after their choice of countries or markets for better choice of portfolio diversification and allocation of financial resources.

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.

To date, the validity of the empirical tests that employ the mean‐variance approach for testing the risk‐return relationship in the research stream named Bowman’s paradox is inherently unverifiable, and the results cannot be generalized. However, this problem can be solved by developing an econometric model with two fundamental characteristics: first, the use of a time‐series model for each firm, avoiding the traditional cross‐sectional analysis; and, second, the estimation of a model with a single variable (firm’s rate of return), whose expectation and variance are mathematically related according to behavioral theories, forming a heteroskedastic model similar to GARCH (generalized autoregressive conditional heteroskedasticity). The application of this methodology for Bowman’s paradox is new, and its main advantage is that it solves the previous criticism of the lack of identification. With this model, we achieve results that agree with behavioral theories and show that these theories can also be carried out with market measures.

Using Japan REITs stock data, this paper examines the risk‐return relations conditional on up and down markets periods. The results show that beta is significantly and positively (negatively) related to realized returns in up (down) markets before and after controlling for extra risk factors. The same conditional results are found for unsystematic risk and total risk, providing evidence that investors do not hold well‐diversified portfolios. Though skewness is significantly priced, the coefficients are unexpectedly positive (negative) in up (down) markets, indicating that investors dislike positively skewed portfolios and would ask for compensation if they are required to hold them during up markets. One possible reason is that the investors have a poor concept of skewness and/or they are too aggressive during bullish markets and so they ignore the benefit of positive skewness. Subsidiary results highlight that there is no seasonal effect in the conditional relation between beta/unsystematic risk/total risk/skewness and returns. This study is the first comprehensive study of the risk‐return relations in Japan REITs market, which provides out‐of‐sample evidence relative to earlier tests on Asian and international stock markets. The findings give important insights and provide useful guidance on investing in Japan REITs market.

The purpose of this paper is to investigate if Bowman’s Paradox (negative association between risk and return) is caused by managerial myopia. It also attempts to disentangle whether results are more consistent with one or more potential explanations.

The paper uses univariate statistics and OLS regressions. Empirically examines the relationship between four risk and return proxies, across a wide ranging time period and utilizing a number of model specifications. Results hold after using three-way clustered errors and using a more robust rolling five year, fixed regression methodology measure.

Confirms the existence of the Paradox. Also documents that the association between risk and return is positive in “winner” firms and negative in “loser” firms. Upon further analysis, the earlier negative risk-return relationship is found to entirely be due to the volatility of the (short term) income statement component of the performance terms. Results imply that executives of winner (loser) firms are less (more) likely to manage earnings or engage in other value destroying activities.

The study is confined by the typical archival study limitations; including potential endogeneity, selection biases and generalizability of the results.

Anecdotal evidence indicates that the business community makes extensive use of these performance measures. These performance measures are also pervasive in academic research. Given the importance of controlling for both managerial and firm performance, a good performance proxy is quintessential.

Although over 30 years have passed since Bowman (1980) first observed the negative correlation, to date, no consensus explanation exists. Findings suggest that Bowman’s Paradox, is potentially a manifestation of managerial myopia. Thus, this result contributes to several existing research streams.

This paper aims to attempt to capture the intertemporal/time-varying risk–return relationship in the Brazil, Russia, India and China (BRIC) equity markets after the global financial crisis (2007-2009), i.e. during a relative calm period. There has been a significant increase in advanced economies’ equity allocations to the emerging markets ever since the financial crisis. So, the present study is an attempt to account for the said relationship, thereby justifying investments made by the international investors.

The study uses non-linear models comprising asymmetric component generalised autoregressive conditional heteroskedastic model in mean (CGARCH-M) (1,1) model, generalised impulse response functions under vector autoregressive framework and Markov regime switching in mean and standard deviation model. The span of data ranges from 1 July 2009 to 31 December 2014.

The ACGARCH-M (1,1) model reports a positive and significant risk-return relationship in the Russian and Chinese equity markets only. There is leverage and volatility feedback effect in the Russian market because falling returns further increase conditional variance making the investors to expect a risk premium in the expected returns. The impulse responses indicate that for all of the BRIC markets, the ex-ante returns respond positively to a shock in the long-term risk component, whereas the response is negative to a shock in the short-term risk component. Finally, the Markov regime switching model confirms the existence of two regimes in all of the BRIC markets, namely, Bull and Bear regimes. Both the regimes exhibit negative relationship between risk and return.

It is an imperative task to comprehend the relationship shared between risk and returns for an investor. The investors in the emerging economies should understand the risk-return dynamics well ahead of time so that the returns justify the investments made under riskier environment.

The present study contributes to the literature in three senses. First, the data relate to a period especially after the global financial crisis (2007-2009). Second, the study has used a relatively newer version of GARCH based model [ACGARCH-M (1,1) model], generalised impulse response functions and Markov regime switching model to account for the relationship between risk and return. Finally, the study provides an insightful understanding of the risk–return relationship in the most promising emerging markets group “BRIC nations”, making the study first of its kind in all the perspectives.

In a study of catalog and mail‐order houses, both perceptual and objective measures of risk supported the U‐shaped risk‐return association proposed by Fiegenbaum and Thomas. Results also supported prospect theorists contention that there is a steeper slope for firms below the target performance. Unlike the prediction by prospect theory that steeper slopes exist around the referent point, steeper slopes were found in the outermost tertiles.