Reference-dependent preferences and the risk–return trade-off

This paper studies the cross-sectional risk–return trade-off in the stock market. A fundamental principle in finance is the positive relation between risk and expected return. However, recent empirical evidence suggests the opposite. Using several intuitive risk measures, we show that the negative risk–return relation is much more pronounced among firms in which investors face prior losses, but the risk–return relation is positive among firms in which investors face prior gains. We consider a number of possible explanations for this new empirical finding and conclude that reference-dependent preference is the most promising explanation.     

Re-examining the risk–return relationship in Europe: Linear or non-linear trade-off?

This paper analyzes the risk–return trade-off in Europe using recent data from 11 European stock markets. After relaxing the linear assumptions in the risk–return relationship by introducing a new approach that considers the current state of the market, we obtain significant evidence for a positive risk–return trade-off for low volatility states. However, this finding is reduced or even non-significant during periods of high volatility. Maintaining the linear assumption over the risk–return trade-off leads to non-significant estimations for all cases. These results are robust across countries despite the conditional volatility model used. These results also demonstrate that the inconclusive results in previous studies may be due to strong linear assumptions when modeling the risk–return trade-off. This previous research fails to uncover the global behavior of the relationship between return and risk.     

The risk–return relations in the Singapore stock market

This paper examines the risk–return relations in the Singapore stock market for the period April 1986 to December 1998. Though beta is significantly related to realized returns, the explanatory power is low. Adding other stock characteristics such as skewness and kurtosis provides limited incremental benefits. However, when a conditional framework based on up and down markets is introduced, the explanatory power increases more than 100 times and there is a significant positive (negative) relation between beta and returns when the market excess returns are positive (negative). The same relation applies when unsystematic risk, total risk and kurtosis are added separately to the beta–return relation during up and down markets with increased explanatory power. Our results indicate that other stock characteristics in addition to beta are also important in pricing risky assets and investors do not hold diversified portfolios. Our results are also checked and compared with another conditional model with time-varying betas conditional on a set of economic variables.     

The role of jump dynamics in the risk–return relationship

Surprisingly, a positive risk–return relationship has not been consistently observed for the traditional GARCH in the mean model in other studies. In this paper, we employ a combination of the jump diffusion and GARCH model in the mean equation to test the risk–return relationship for U.S. stock returns. The results suggest a statistically significant relationship between risk and return if the risk measure includes components of smoothly changing variance and jump events.     

Revisiting the ICAPM under the distortion of risk–return tradeoff in short-horizon stock returns

We suggest that the distortion of the positive risk–return relation in the ICAPM is a consequence of trading by informed investors to exploit mispricing. We hypothesize and demonstrate that a non-positive (strongly positive) risk–return relation following positive (negative) market returns is attributed to short-selling (purchasing) of overpriced (underpriced) stocks along with optimistic (pessimistic) expectations conditional on good (bad) market news. We verify this asymmetry in the risk–return relation through the indirect risk–return relation conditional on good (bad) market news. We also find that the attenuation (reinforcement) of the positive risk–return relation is more profound in high- (low-) sentiment periods.     

Conditional risk–return relationship in a time-varying beta model

We investigate the asymmetric risk–return relationship in a time-varying beta CAPM. A state space model is established and estimated by the Adaptive Least Squares with Kalman foundations proposed by McCulloch. Using S&P 500 daily data from 1987:11–2003:12, we find a positive risk–return relationship in the up market (positive market excess returns) and a negative relationship in the down market (negative market excess returns). This supports the argument of Pettengill et al., who use a constant beta model. However, our model outperforms theirs by eliminating the unexplained returns and improving the accuracy of the estimated risk price.     

Reinsurance decisions in life insurance: An empirical test of the risk–return criterion

Recent studies have analyzed optimal reinsurance contracts within the framework of profit maximization and/or risk minimization. This type of framework, however, does not consider reinsurance as a tool for capital management and financing. In the present paper, we consider different proportional reinsurance contracts used in life insurance (viz., quota-share, surplus, and combinations of quota-share and surplus) while taking into account the insurer's capital constraints. The objective is to determine how different reinsurance transactions affect the risk/reward profile of the insurer and whether factors, such as claims severity, premiums, and insurer's risk appetite, influence the choice of a proportional reinsurance coverage. We compare each reinsurance structure based on actual insurance company data, using the risk–return criterion. This criterion determines the type of reinsurance that enables insurer to retain the largest underwriting profits and/or minimize the risk of the retained claims while keeping the insurer's risk appetite constant, assuming a given capital constraint. The results of this study confirm that the choice of reinsurance arrangement depends on many factors, including risk retention levels, premiums, and the variance of the sum insured values (and therefore claims). As such, under heterogeneous insurance portfolio single type of reinsurance arrangement cannot maximize insurer's returns and/or minimize the risk, therefore a combination of different reinsurance coverages should be employed. Hence, future research on optimal risk management choices should consider heterogeneous portfolios while determining the effects of different financial and risk management tools on companies' risk–return profiles.     

Investor sentiment and the risk–return relation: A two-in-one approach

Traditional finance theory posits a positive risk–return relation, but empirical evidence is inconclusive. Retail investor sentiment has long been viewed as a distorting factor, while more recently institutional investor sentiment is thought to play a role. We examine the separate and joint impacts of retail and institutional investor sentiments on the risk-return relation. We find, at both market and firm levels, the risk-return relation is more likely to be distorted by the two investor-type sentiments jointly, rather than separately. We further find a cross-sectional pattern, with the risk-return relation being more sensitive to investor sentiment for stocks with specific characteristics.     

Time-varying betas and the cross-sectional return–risk relation: evidence from the UK

The seminal study by Fama and MacBeth in 1973 initiated a stream of papers testing for the cross-sectional relation between return and risk. The debate as to whether beta is a valid measure of risk was reanimated by Fama and French and subsequent studies. Rather than focusing on exogenous variables that have a larger explanatory power than an asset's beta in cross-sectional tests, the matrix of variances-covariances is assumed to follow a time varying ARCH process. Using monthly data from the UK market from February 1975 to December 1996, the cross-sectional return–risk relations obtained with an unconditional specification for assets’ betas are compared to those obtained when the estimated betas are based on an ARCH model. The approach taken by Pettengill, Sundaram and Mathur, which allows a negative cross sectional return–risk relation in periods in which the market portfolio yields a negative return relative to the risk free rate, was also investigated. These tests are also carried out on samples pertaining to a specific month and on samples from which a particular month is removed. Results suggest that the CAPM holds better in downward moving markets than in upward moving markets hence beta is a more appropriate measure of risk in bear markets.     

Differences in the strengths of evidence matters in risk–risk trade-offs

Making decisions between alternatives are challenging when there is weak or unreliable knowledge about the risks and benefits of the alternatives. This requires a trade-off between risks (and benefits). Here, we comment on a recent paper on risk–risk trade-offs and highlight the difficulties of making such trade-offs when the available evidence is of different strength. One current example of a risk–risk trade-off under weak evidence is the restriction and reevaluation of the risks of neonicotinoid insecticides to bees conducted by the European Food Safety Authority (EFSA). We argue that a risk–risk trade-off is essential in this context. Although considerable research efforts have been focused at determining the risks of neonicotinoids to bees, the evidence base is still limited. However, focus on strengthening evidence on impacts of one substance may lead policy-makers and public to believe that its substitutes are less harmful, when in fact evidence is weak on the impacts of these substitutes as well. We argue that a broader management of uncertainty is needed and that the difference in uncertainty underlying evidence of risk for different alternatives needs to be communicated to policy-makers. We suggest that this can be done, for example, using measures of uncertainty, which take into account strength in evidence, and combine these with principles to guide decision-making.     

Revisiting the intertemporal risk–return relation: asymmetrical effect of unexpected volatility shocks

We suggest that an unexpected volatility shock is an important risk factor to induce the intertemporal relation, and the conflicting findings on the relation could be attributable to an omitting variable bias resulting from ignoring the effect of an unexpected volatility shock on the relation. With the effect of an unexpected volatility shock incorporated in estimation, we find a strong positive intertemporal relation for the US monthly excess returns for 1926:12–2008:12. We also find a significant link between the asymmetric mean-reversion and the intertemporal relation in that the quicker reversion of negative returns is attributed to the negative intertemporal relation under a prior negative return shock.     

Flight-to-quality in the stock–bond return relation: a regime-switching copula approach

Financial Markets and Portfolio Management - This paper examines the existence, intensity and international dependence of flight-to-quality from stocks to government bonds. To this end, we develop...     

Dodd–Frank and risk in the financial services industry

We present evidence that discretionary risk taking by financial institutions has declined following the passage of Dodd–Frank. The largest institutions experience the greatest reduction in risk consistent with the legislation’s objective of reducing systemic risk and an ultimate goal of ending the too-big-to-fail doctrine. Analysis of a sample of banks, the most highly regulated financial institutions, reveals that banks exhibiting characteristics consistent with riskier business strategies prior to Dodd–Frank experience the greatest risk reduction. Further, banks that alter their business practices by increasing their capital ratios and reducing their level of non-performing loans following the law’s passage are shown to experience the greatest reduction in risk. Our results point to the efficacy of Dodd–Frank in reducing risk in the financial system.     

On dividends in the phase–type dual risk model

The dual risk model assumes that the surplus of a company decreases at a constant rate over time, and grows by means of upward jumps which occur at random times with random sizes. In the present work, we study the dual risk renewal model when the waiting times are phase-type distributed. Using the roots of the fundamental and the generalized Lundberg’s equations, we get expressions for the ruin probability and the Laplace transform of the time of ruin for an arbitrary single gain distribution. Then, we address the calculation of expected discounted future dividends particularly when the individual common gains follow a phase-type distribution. We further show that the optimal dividend barrier does not depend on the initial reserve. As far as the roots of the Lundberg equations and the time of ruin are concerned, we address the existing formulae in the corresponding Sparre-Andersen insurance risk model for the first hitting time, and we generalize them to cover also the situations where we have multiple roots. We do that working a new approach and technique, approach we also use for working the dividends, unlike others, it can be also applied for every situation.     

Causality in quantiles and dynamic stock return–volume relations

This paper investigates the causal relations between stock return and volume based on quantile regressions. We first define Granger non-causality in all quantiles and propose testing non-causality by a sup-Wald test. Such a test is consistent against any deviation from non-causality in distribution, as opposed to the existing tests that check only non-causality in certain moment. This test is readily extended to test non-causality in different quantile ranges. In the empirical studies of three major stock market indices, we find that the causal effects of volume on return are usually heterogeneous across quantiles and those of return on volume are more stable. In particular, the quantile causal effects of volume on return exhibit a spectrum of (symmetric) V-shape relations so that the dispersion of return distribution increases with lagged volume. This is an alternative evidence that volume has a positive effect on return volatility. Moreover, the inclusion of the squares of lagged returns in the model may weaken the quantile causal effects of volume on return but does not affect the causality per se.     

Estimating the risk–return profile of new venture investments using a risk-neutral framework and ‘thick’ models

This study proposes cascade neural networks to estimate the model parameters of the Cox–Ross–Rubinstein risk-neutral approach, which, in turn, explain the risk–return profile of firms at venture capital and initial public offering (IPO)financing rounds. Combining the two methods provides better estimation accuracy than risk-adjusted valuation approaches, conventional neural networks, and linear benchmark models. The findings are persistent across in-sample and out-of-sample tests using 3926 venture capital and 1360 US IPO financing rounds between January 1989 and December 2008. More accurate estimates of the risk–return profile are due to less heterogeneous risk-free rates of return from the risk-neutral framework. Cascade neural networks nest both the linear and nonlinear functional estimation form in addition to taking account of variable interaction effects. Better estimation accuracy of the risk–return profile is desirable for investors so they can make a more informed judgement before committing capital at different stages of development and various financing rounds.     

Political–security risk in the oil and gas industry: the impact of terrorism on risk management and mitigation

Oil and gas companies are experiencing an increase in terrorist attacks. The industry became a legitimate target for terrorist groups in the 1990s and the number of attacks have increased yearly, with a spike after the 9/11 attacks. In today’s interconnected world, political risk is not only about the relationship between the host government and the company. Oil and gas companies may experience risks on a transnational, national and human security level. The success of new investments often depends on the successful utilization of risk management strategies. This study focuses on the importance of political–security risk in the oil and gas industry. In January 2013, the oil and gas industry experienced one of its deadliest attacks at the In Amenas gas facility in Algeria, forcing firms to reconsider its focus on security management. Statoil undertook a thorough analysis of security at the site as well as of the company′s corporate security risk management. The report revealed a lack of focus on political–security risk. This study argues that political–security risk has not been used to its full potential in the oil and gas industry. The oil and gas industry has always focused on site security, but a broader more holistic approach to risk management has been lacking. As a result of the In Amenas incident, the industry has become more willing to have a new discussion on security and this has resulted in changes in the way companies operate.     

The roles of contextual moderation and personality in relation to the knowledge–risk link in the workplace

While hypothesized, a consistent association between knowledge about a hazard and the estimation of risk associated with that hazard has not been found. Risk communication is premised on the fact that knowledge about a hazard (information) will change people's perceptions of risk and behaviour. In this review methodological and theoretical factors that might account for this lack of consistent association are explored. In this context issues to do with the measurement and assessment of hazard knowledge, knowledge calibration, and the role of context as a moderator are explored. It is argued that contextual factors moderate the knowledge–risk link, with this link being stronger in less controllable, ambiguous contexts. Further this review asks: How can messages be framed (using prospect theory) so as to be more effective in the work place? It is argued that messages framed as gains should be more useful for prevention behaviours (e.g. wearing ear guards) and messages framed as losses should be more effective for detection behaviours (using radiation meters). Finally, the role of personality (e.g. need for cognition, typical intellectual engagement, and self-esteem) in relation to knowledge about a hazard, message framing and risk perception is discussed.     

Systemic risk: A new trade-off for monetary policy?

We introduce time-varying systemic risk (à la He and Krishnamurthy, 2014) in an otherwise standard New-Keynesian model to study whether simple leaning-against-the-wind interest rate rules can reduce systemic risk and improve welfare. We find that while financial sector leverage contains additional information about the state of the economy that is not captured in inflation and output leaning against financial variables can only marginally improve welfare because rules are detrimental in the presence of falling asset prices. An optimal macroprudential policy, similar to a counter cyclical capital requirement, can eliminate systemic risk raising welfare by about 1.5%. Also, a surprise monetary policy tightening does not necessarily reduce systemic risk, especially during bad times. Finally, a volatility paradox a la Brunnermeier and Sannikov (2014) arises when monetary policy tries to excessively stabilize output.     

A behavioral explanation for the negative asymmetric return–volatility relation

We examine the short-term dynamic relation between the S&P 500 (Nasdaq 100) index return and changes in implied volatility at both the daily and intraday level. Neither the leverage hypothesis nor the volatility feedback hypothesis adequately explains the results. Alternatively, we propose that the behavior of traders (from the representativeness, affect, and extrapolation bias concepts of behavioral finance) is consistent with our empirical results of a strong daily and intraday negative return–implied volatility relation. Moreover, both the presence and magnitude of the negative relation and the asymmetry between return and implied volatility are most closely associated with extreme changes in the index returns. We also show that the strength of the relation is consistent with the implied volatility skew.