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The variance risk premium defined as the difference between risk neutral variance and physical variance is one of the most crucial information recovered from option prices. It does not, however, reflect the asymmetry in upside and downside movements of underlying asset returns, and also has limitation in reflecting asymmetric preference of investors over gains and losses. In this sense, this paper decomposes variance risk premium into downside - and upside-variance risk premium, and then derives the skewness risk premium and examines its effectiveness in predicting future underlying asset returns. Using KOSPI200 option prices, we obtained the following results. First, we found out that the estimated skewness risk premium has meaningful forecasting power for future stock returns, while the estimated variance risk premium has little forecasting power. Second, by utilizing our results of skewness risk premium, we developed a profitable investment strategy, which verifies the effectiveness of skewness risk premium in predicting future stock returns. In conclusion, the empirical results of this paper can contribute to the literature in that it helps us understand why variance risk premium, in most global markets except the US market, has not been successful in forecasting future stock returns. In addition, our results showing the profitability of investment strategies based on skewness risk premium can also give important implications to practitioners.

More studies have investigated the relation between option measures and stock returns during scheduled corporate events. This study adds to the literature and investigates the informational role of options concerning stock returns following unscheduled corporate news events. The authors focus on individual analysts' recommendation changes rather than consensus revisions, as the recommendation consensus might discard a large amount of potentially valuable information in the aggregation process.

Based on the econometric model, the authors follow Bakshi et al. (2003) to construct the model-free option implied measures. The authors further decompose the implied option variance into upside and downside components. In such a way, the different informational roles of call and put options can be distinguished. A variety of regression analyses are conducted to examine the predictive power of option implied measures, and the ordered probit model is used to test the tipping hypothesis of analyst recommendations.

This study’s results show that the option market impounds the “valuable” firm-specific news; thus, the pre-event option market is strongly related to stock returns around recommendations even though recommendation changes are largely “unscheduled”. At the same time, these results suggest that upside (good) and downside (bad) implied volatilities contain distinctive information on subsequent stock returns.

This study provides new evidence that an increase in upside (downside) volatility around analyst recommendation changes would increase the probability that analysts upgrade (downgrade) the stock. The findings provide implications for investors and risk managers in making investment decisions.

This study aims to investigate the existence of herding in the Athens Stock Exchange over the 1995-2010 period and examine its effects on market volatility.

Herding is examined over portfolios formed on beta and size of the selected stocks. The detection of herding has been done using the state space model of Hwang and Salmon (2004). Four volatility measures are employed.

The findings depict the presence of herding over two different periods of time. Large differences are observed among the portfolios regarding the herding periods. The results confirm a linear effect of herding on all volatility measures considered. Stocks exhibiting higher levels of herding or adverse herding will also present higher volatility, and from this point of view, herding can be regarded as an additional risk factor.

The fact that herding is considered to be an additional risk factor, can lead market participants and investors to a better understanding of market risk, asset pricing and asset allocation.

Many studies have shown that from a theoretical and empirical point of view, downside risk-based measures of risk are better than the traditional ones. Despite academic appeal and practical implications, downside risk has not been thoroughly examined in markets outside developed country markets. Using downside beta as a measure of downside risk, this study examines the relationship between downside beta and stock returns in Indian equity market, an emerging market with unique investor, asset and market characteristics.

This is an empirical study done by using ranked portfolio return analysis and regression analysis methodologies.

The study results show that downside risk, as measured by downside beta, is distinctly priced in the Indian equity market. There is a direct positive relationship between downside beta and contemporaneous realized returns, indicating a premium for downside risk. Downside risk carries a higher weightage than upside potential in the aggregate return of the stock portfolios. Downside beta is a better measure of systematic risk than conventional market beta and downside coskewness.

The empirical results support the adoption of downside beta in practice and provide a case for replacing traditional beta with downside beta in asset pricing applications, trading and investment strategies, and capital allocation decision-making.

This is one of the first in-depth studies examining downside beta in Indian equity markets using a broad sample of individual stock returns covering a wide time range of 22 years. To the best of our knowledge, this study is the first one to compare downside beta and downside coskewness using individual stock data from the Indian equity market.

The purpose of this paper is to examine whether superior risk-adjusted returns can be generated using monthly covered call option strategies in large capitalized Australian equity portfolios and across varying market volatility conditions.

The authors construct monthly in-the-money (ITM) and out-of-the-money (OTM) S&P/ASX 20 covered call portfolios from 2010 to 2015 and use standard and alternative performance measures. An assessment of variable levels of market volatility on risk-adjusted return performance is also carried out using the spread between implied and realized volatility indexes.

The results of this paper show that covered call writing produces similar nominal returns at lower risk when compared against the standalone buy-and-hold portfolio. Both standard and alternative performance measures (with the exception of the upside potential ratio) demonstrate that covered call portfolios produce superior risk-adjusted returns, particularly when written deeper OTM. The 36-month rolling regressions also reveal that deeper OTM portfolios deliver greater risk-adjusted returns in the majority of the sub-periods investigated. This paper also establishes that volatility spread variation may be a driver of performance for covered call writing in Australia.

The authors suggest that deeper OTM covered call strategies based on large capitalized portfolios create value for investors/fund managers in the Australian stock market and can be executed in volatile market conditions. Such strategies are particularly useful for those seeking market neutral asset allocation and less risk exposure in volatile market environments.

The purpose of this paper is to empirically analyze volatility properties of the house price returns of Turkey and Istanbul, Ankara and Izmir provinces over the period of July 2007-June 2014.

The paper uses conditional variance models, namely, ARCH, GARCH and E-GARCH. As the supportive approach for the discussions, we also use correlation analysis and qualitative inputs.

Empirical findings suggest several points. First, city/country-level house price return volatility series display volatility clustering pattern and therefore volatilities in house price returns are time varying. Second, it seems that there were high (excess) and stable volatility periods during observation term. Third, a significant economic event may change country/city-level volatilities. In this context, the biggest and relatively persistent shock was the lagged negative shocks of global financial crisis. More importantly, short-lived political/economic shocks have not significant impacts on house price return volatilities in Turkey, Istanbul, Ankara and Izmir. Fourth, however, house price return volatilities differ across geographic areas, volatility series may show some co-movement pattern. Fifth, volatility comparison across cities reveal that Izmir shows more excess volatility cases, Ankara recorded the highest volatility point and Istanbul and national series show lower and insignificant volatilities.

The study uses maximum available data and focuses on some house price return volatility patterns. The first implication of the findings is that micro/macro dimensions of house price return volatilities should be carefully analyzed to forecast upside/downside risks of house price returns. Second, defined volatility clustering pattern implies that rate of return of housing investment may show specific patterns in some periods and volatile periods may result in some large losses in the returns. Third, model results generally suggest that however data constraint is a major problem, market participants should analyze regional idiosyncrasies during their decision-making in housing portfolio management. Fourth, because house prices are not sensitive to relatively less structural shocks, housing may represent long-term investment instrument if it provides satisfactory hedging from inflation.

The evidences and implications would be useful for housing market participants aiming to manage/use externalities of housing price movements. From a practical contribution perspective, the study provides a tool that will allow measuring first time of the return volatility patterns of house prices in Turkey and her three biggest provinces. Local level analysis for Istanbul, Ankara and Izmir provinces, as the globally fastest growing cities, would be found specifically interesting by international researchers and practitioner.

The purpose of this paper is to compare the risk and return characteristics as well as the allocation of mean‐variance (MV) and downside risk (DR) optimized portfolios of international real estate stock markets and to discuss implications for portfolio management.

The analysis focuses on real estate markets only and examines the appropriateness of the Markowitz approach based on MV optimization in comparison to the DR framework suggested by Estrada. Therefore, the two frameworks are presented before the properties of the return distributions are analyzed. Afterwards, the risk and return characteristics as well as the allocation of the efficient portfolios in both frameworks and the divergences are analyzed.

Because of non‐normally distributed returns, negative skewness, and probably non‐quadratic utility functions of investors, MV optimization is not appropriate and the alternative approach by Estrada has its merit compared with other DR frameworks. Furthermore, MV‐efficient and DR‐efficient portfolio allocation differ, as shown by a similarity index. Summarizing, MV optimization is inherent with misleading results and DR optimization shows stronger out‐of‐sample performance – at least during time periods characterized by high market volatility and financial market turmoil.

This study provides some interesting and valuable insights into the DR of international securitized real estate portfolios and the limitations for portfolio management based on MV optimization.

The paper aims to explore the optimal strategies of inventory financing when the risk-averse retailer has different objectives, in the presence of multi-risk, i.e. demand risk, non-operational risk and retailer's strategic default risk.

This paper develops an inventory financing model consisting of a bank and a risk-averse retailer with strategic default. This paper considers two scenarios, i.e. the capital-constrained retailer cares about its profit or firm value. In the first scenario, the bank acts as a Stackelberg leader determining its interest rate, and the retailer acts as a follower determining its pledged quantity. In the second one, the bank capital market is perfectly competitive. Lagrange multiplier method is adopted to solve the optimization.

The optimal strategies in inventory financing scheme in two scenarios are derived. Only when the initial stock is relatively high, the retailer pledges part of the initial stock. Retailer's risk aversion reduces its pledged quantity and performance. The strategic default reduces its profit. When it is relatively high, the bank refuses to offer the loan.

Analytical inventory and financing strategies are specified to help retailers and banks to better understand the interaction of finance and operations management and to better respond to multi-risk.

New results and managerial insights are derived by incorporating partially endogenous strategic default and risk aversion into inventory financing, which enriches the interfaces of operations management and finance.

The purpose of this paper is to analyze the mean-variance capital asset pricing model (CAPM) and downside risk-based CAPM (DR-CAPM) developed by Bawa and Lindenberg (1977), Harlow and Rao (1989), and Estrada (2002) to assess which downside beta better explains expected stock returns. The paper also explores whether investors respond differently to stocks that co-vary with declining market than to those of co-vary with rising market.

The paper uses monthly data of closing prices of stocks listed at the Karachi Stock Exchange (KSE). The data cover the period from January 2000 to December 2012. The standard, downside, and upside betas are estimated for different sub-periods,and then,their validity to quantify the risk premium is tested for subsequent sub-periods in a cross sectional regression framework. Though our empirical methodology is similar to that of Fama and MacBeth (1973) for testing the CAPM and the DR-CAPM, our approach to estimate the downside beta is different from earlier studies. In particular, we follow Estrada ' s (2002) suggestions and obtain the correct and unbiased estimation of the downside beta by running the time series regression through origin. The authors carry out the two-pass regression analysis using the generalized method of moment (GMM) in the first pass and the generalized least squares (GLS) estimation method in the second pass.

The results indicate that the mean-variance CAPM shows a negative risk premium for monthly returns of selected stocks. However, the results for the DR-CAPM of Bawa and Lindenberg (1977) and Harlow and Rao (1989) provide evidence of a positive risk premium for the downside beta. In contrast, the DR-CAPM of Estrada (2002) shows a negative risk premium in some sub-periods while the positive premium in the others. By comparing the risk premium for both downside and upside risks in a single-equation framework, the authors show that the stocks that co-vary with a declining market are compensated with a positive premium for bearing the downside risk. Yet, the risk premium for stocks that are negatively correlated with declining market returns is negative for all the three-downside betas in all the examined sub-periods.

The empirical findings of the paper are of great significance for investors for designing effective investment strategies. Specifically, the results help investors to identify an appropriate measure of risk and to construct well-diversified portfolio. The results are also useful for firm managers in capital budgeting decision-making process as they enable them to cost equities appropriately. The results also suggest that the risk-return relationship implied by mean-variance CAPM is negative and therefore this model is not suitable for gauging the risk associated with stocks traded in KSE. Yet, the authors show that DR-CAPM out performs in quantifying the risk premium.

Unlike prior empirical studies, the authors follow Estrada’s (2002) suggestions where downside beta is calculated using regression through origin to find correct and unbiased beta. Departing from the existing literature the authors estimate three different versions of DR-CAPM along with the standard CAPM for comparison purpose. Finally, the authors apply sophisticated econometrics methods that help in lessening the problem of non-synchronous trading and the issue of non-normality of returns distribution.

This study seeks to evaluate, in a global context, the impact of Sarbanes Oxley Act on a particular risk measure of importance to investors (risk‐adjusted returns), and two measures of risk due to asymmetry (upside and downside risk). A unique dataset permits a dual evaluation of the law's impact on such measures in leading non‐US economies as well (i.e. “ripple effects”).

Hypotheses are empirically evaluated on a sample (n=712) of the largest US and European firms (control) using daily return data from 1993 through 2009 – one of the most extensive data sets employed in the literature on this topic to date. The reliability of the risk measures is carefully evaluated using multiple approaches, including Fama‐MacBeth regressions. A series of difference‐in‐difference analyses is then employed to empirically assess Sarbanes Oxley's impact on equity risk.

The findings suggest Sarbanes Oxley decreased both risk‐adjusted returns and upside risk, whereas downside risk fails to explain the cross section of returns for the largest US firms. From a global perspective, it is suggested that the enactment of Sarbanes Oxley's in the USA motivated leading non‐US economies to adopt similar regulatory measures, which caused “ripple effects” – e.g. effects similar to those documented in this paper – in leading non‐US economies.

The findings suggest that comprehensive financial regulations, such as Sarbanes Oxley Act, are properly envisaged at the global level, as their impact is not confined to the home country. In an increasingly globalized economy, investor welfare is likely to be influenced – directly as well as indirectly – by economic and financial regulation(s) enacted in foreign economies. Arguably, this suggests the pivotal importance of effective mechanisms of global governance, such that a purely domestic approach to regulation may be short‐sighted. In either case, the findings of this study are entirely relevant if regulators are to consider the broader, global impact of regulation on investor welfare.

This is the first study to empirically analyze, within a global framework, Sarbanes Oxley's risk implications without relying on a series of simple mean variance analyses. Substantive research documents that the methodological approach employed is more precise, reliable as well as “investor relevant”. Furthermore, the authors seek to assess the law's impact on leading non‐US equity markets, a first for the literature. Consequently, this study provides a robust evaluation of the law's (international) impact on firm (equity) risk, making an important contribution to the literature.