International evidence on the relative importance of the determinants of earnings forecast accuracy

We analyze earnings forecasting errors made by financial analysts for 18 developed countries over the 1990–2006 period. We use the Heston–Rouwenhorst approach to unravel country-, industry-, and firm-specific effects as a source of variation in financial analysts’ earnings forecast errors. We first estimate each effect with a dummy variable regression, and then decompose the variance of forecast errors into different effects. We provide evidence that the differences between countries, industrial sectors, and analyst-following offer a weak explanation for differences in forecast errors. Country effects however largely dominate industry and analyst-following effects. By contrast, the type of earnings (profits or losses)—and variations in earnings (increases or decreases) play a significant role in the forecast accuracy of financial analysts.     

Emerging markets,downside risk and the asset allocation decision

This study examines the use of downside risk measures in the construction of an optimal international portfolio, with particular reference to the estimated allocations in emerging markets and the out-of-sample performance of the optimal portfolios. The use of downside risk measures is assessed due to the problems of using a conventional mean-variance analysis approach in the presence of the non-normality often found to be present in emerging market data. The data set used consists of the MSCI indices for developed equity markets and the IFC data set on emerging markets. The primary component of the paper consists of the construction of optimal portfolios under both mean-variance and downside risk frameworks. In addition, the use of Bayes–Stein estimators is also assessed, in an attempt to reduce estimation error. The resulting estimated allocations are then used to assess the out-of-sample performance of the optimal portfolios. The results indicate that for risk-averse investors the use of downside risk measures can result in significant improvements in performance.     

Is the profitability of Indian stocks compensation for risks?

This paper examines the profitability of the Indian stock market using an extensive new data set that includes 1,515 stocks and covers a time-period spanning 1992 to 2014. Using both the popular Jegadeesh-Titman and the 52-week momentum trading strategies, we discover that portfolios of all stocks and various portfolios of industry stocks are profitable. These profits, we find, disappear once we account for a range of market and macroeconomic factors, suggesting that market and industry profits are compensation for risks. Our results survive a battery of robustness tests.     

Aggregate Volatility and Market Jump Risk: An Option‐Based Explanation to Size and Value Premia

It is well documented that stock returns have different sensitivities to changes in aggregate volatility, however less is known about their sensitivity to market jump risk. By using S&P 500 crash‐neutral at‐the‐money straddle and out‐of‐money put returns as proxies for aggregate volatility and market jump risk, I document significant differences between volatility and jump loadings of value versus growth, and small versus big portfolios. In particular, small (big) and value (growth) portfolios exhibit negative (positive) and significant volatility and jump betas. I also provide further evidence that both volatility and jump risk factors are priced and negative. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:34–55, 2014     

A market index futures contract and portfolio selection

This paper shows that if security returns are generated according to the market model and there is a futures market in the market index, then optimal portfolios can be selected in three steps: 1) select the optimal combination of firm unique characteristics; 2) select the optimal investment in the market; and 3) select the optimal investment in the risk-free asset. The futures market contract separates the choice of firm and market exposure and thus both simplifies the mathematics involved and increases the mean/variance efficiency of the optimal portfolio.     

Portfolio Optimization and Martingale Measures

The paper studies connections between risk aversion and martingale measures in a discrete-time incomplete financial market. An investor is considered whose attitude toward risk is specified in terms of the index b of constant proportional risk aversion. Then dynamic portfolios are admissible if the terminal wealth is positive. It is assumed that the return (risk) processes are bounded. Sufficient (and nearly necessary) conditions are given for the existence of an optimal dynamic portfolio which chooses portfolios from the interior of the set of admissible portfolios. This property leads to an equivalent martingale measure defined through the optimal dynamic portfolio and the index 0 < b ≤ 1. Moreover, the option pricing formula of Davis is given by this martingale measure. In the case of b = 1; that is, in the case of the log-utility, the optimal dynamic portfolio defines the numéraire portfolio.     

Non-convex optimal portfolio sets and constant relative risk aversion

This paper shows by example that, under constant relative risk aversion (CRRA), the set of optimal portfolios can be non-convex even in the presence of a complete set of Arrow-Debreu securities. This implies that, with exclusively CRRA investors, market models without a strong distributional assumption such as that of the capital asset pricing model cannot be tested by testing the optimality of the market portfolio, or by assuming a representative investor. This demonstration extends the key result of Dybvig and Ross [Dybvig, P. H., & Ross S. A. (1982). Portfolio efficient sets. Econometrica, 50, 1525–1546], who showed an example of non-convexity with less restrictive utility assumptions but which could not apply to the case of a complete set of Arrow-Debreu securities.     

Incorporating time-varying jump intensities in the mean-variance portfolio decisions

This paper examines the role of time-varying jump intensities in forming mean-variance portfolios. We find that compared with the no-jump or constant-jump models, the model which incorporates time-varying jump intensities better fits the dynamics of the assets returns, and yields mean-variance portfolios with higher Sharpe ratios. Our research suggests that using a better econometric model that captures non-normal features in the data has benefits for portfolio allocation even for a mean-variance investor.     

Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market

We investigate the use of machine learning (ML) to forecast stock returns in the Brazilian market using a rich proprietary dataset. While ML portfolios can easily outperform the local market, the performance of long-short strategies using ML is hampered by the high volatility of the short portfolios. We show that an Equal Risk Contribution (ERC) approach significantly improves risk-adjusted returns. We further develop an ERC approach that combines multiple long-short strategies obtained with ML models, equalizing risk contributions across ML models, which outperforms, on a risk-adjusted basis, all individual ML long-short strategies, as well as alternative combinations of ML strategies.     

Book Reviews

In a world of limited resources, marketing managers tasked to deliver shareholder value face decisions about how to maximise the returns on their marketing portfolio. Risk is less often considered. In finance the picture is very different; financial portfolio management is concerned with both risk and returns. The central innovation in this paper is the application of modern portfolio theory (MPT) to the management of marketing portfolios in food retailing and in drinks manufacturing. The authors develop a model that calculates an efficient frontier of marketing portfolios that maximise overall return within certain risk constraints, first for a simple two-segment marketing world and then for a more realistic multi-segment portfolio. However, marketing portfolios differ from financial ones in the sense that the allocation of marketing spend affects the returns from the portfolio. Therefore, a second innovation, an extension of MPT to take account of marketing spend allocation decisions, has been developed. Using this model, marketers can determine the risk and the returns of marketing investments, helping them select an optimal portfolio. This would go some way to ensuring that marketing contributes to shareholder value creation, currently one of its major challenges.     

COMMENT ON “SKEWNESS‐AWARE ASSET ALLOCATION”

This paper discusses risk measures proposed by Low et al. One of their new risk measures is skewness‐aware deviation, which is closely related to constant absolute risk aversion utility functions. This measure captures downside risk more effectively than traditional variance does. The authors also propose a second measure, skewness‐aware variance, which is derived from skewness‐aware deviation. This measure simplifies asset allocation problems and empirical results indicate that it captures risk better than traditional variance. However, this measure is also found to be inconsistent due to factor selection. Additionally, in the aspect of skewness‐aware deviation, optimal portfolios based upon skewness‐aware variance are sometimes less efficient than optimal portfolios that base themselves on traditional variance.     

Corporate venture capital (CVC) investments and technological performance: Geographic diversity and the interplay with technology alliances

Firms are increasingly operating portfolios of geographically dispersed CVC investments for accessing a variety of location-specific knowledge, often alongside traditional external knowledge-sourcing strategies such as technology alliances. We examine the conditions under which geographic diversity in corporate venture capital (CVC) investments has positive consequences for firms' technological performance in the context of simultaneously pursued technology alliance strategies. We find that geographic diversity in CVC portfolios enhances performance as long as firms avoid knowledge redundancy in knowledge-sourcing arising from geographic overlaps with technology alliances, and the managerial complexity, coordination costs, and resource constraints stemming from the simultaneous pursuit of diversity in both technology alliances and CVC investments. Our inferences draw on a panel data set on the patents, CVC investments, and technology alliances of 55 CVC-active firms in a variety of industries.     

A Markowitz Optimization of Commodity Futures Portfolios

We examine the diversification benefits of using individual futures contracts instead of simply a commodity index. We determine the ex‐ante, ex‐post, and stability results for optimal Markowitz portfolios, investigate the instability between the ex‐ante and ex‐post results, and compare our results to traditional and naïve portfolios. The ex‐ante complete futures portfolio dominates the traditional and naive portfolios and the ex‐post portfolio outperforms the naïve portfolio. The instability between the ex‐ante and ex‐post results is primarily driven by the time‐varying returns of the individual assets rather than by risk. Finally, the Sharpe portfolio results are essentially identical to the Markowitz results. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 33:343‐368, 2013     

Flexible covariance dynamics,high-frequency data,and optimal futures hedging

This paper investigates the out-of-sample performance of hedged portfolios constructed using a novel rotated ARCH (RARCH) model class, which enables flexible covariance dynamics for spot and futures returns. The model's empirical fit can be significantly improved when it incorporates rotated realized covariance matrix measures. The empirical results suggest that a highly risk-averse hedger implementing the restricted RARCH model would be willing to pay substantial switching fees to capture the incremental gains generated by the flexible and informative alternative; this thus supports the economic importance of incorporating high-frequency data into flexible RARCH modeling processes for the construction of optimal hedged portfolios.     

The dark side of Bitcoin: Do Emerging Asian Islamic markets help subdue the ethical risk?

Continuous financing of illicit activities (drug and human trafficking, child abuse, cybercrimes) through Bitcoin nurtures the ethical risk of investors. Building on this argument, the current study investigates the extreme tail dependence between Bitcoin and Emerging Asian Islamic (EAI) markets. We report multiple tail-dependent copulas differing across turmoil periods for the whole sample period. Under the ethical-risk hypothesis and modern portfolio theory, our findings demonstrated stronger safe-haven properties of EAIs for Bitcoin to mitigate ethical risk, and higher diversification benefits are documented for both equally adjusted and optimal portfolios. We formulated useful implications for policymakers, governments, regulation authorities, ethical investors, and portfolio managers for policymaking and strategizing their investment portfolios.     

ROBUST PORTFOLIOS AND WEAK INCENTIVES IN LONG‐RUN INVESTMENTS

When the planning horizon is long, and the safe asset grows indefinitely, isoelastic portfolios are nearly optimal for investors who are close to isoelastic for high wealth, and not too risk averse for low wealth. We prove this result in a general arbitrage‐free, frictionless, semimartingale model. As a consequence, optimal portfolios are robust to the perturbations in preferences induced by common option compensation schemes, and such incentives are weaker when their horizon is longer. Robust option incentives are possible, but require several, arbitrarily large exercise prices, and are not always convex.     

MODELING LIQUIDITY EFFECTS IN DISCRETE TIME

We study optimal portfolio choices for an agent with the aim of maximizing utility from terminal wealth within a market with liquidity costs. Under some mild conditions, we show the existence of optimal portfolios and that the marginal utility of the optimal terminal wealth serves as a change of measure to turn the marginal price process of the optimal strategy into a martingale. Finally, we illustrate our results numerically in a Cox–Ross–Rubinstein binomial model with liquidity costs and find the reservation ask prices for simple European put options.     

Should retailers adjust their micro-marketing strategies to type of outlet? An application to location-based store space allocation in limited and full-service grocery stores

Many retailers today operate strategically different types of sites: ‘limited-service’ stores—that offer all core products/services but only a shallow assortment of non-core services—and ‘full-service’ sites with deep lines of both core and non-core services. An important question for these retailers is whether and how to adopt a micro-marketing strategy in each of these formats. In a micro-marketing strategy, retailers tailor their marketing mix to the characteristics of the local market in which each store outlet operates—a central issue being whether the allocation of store space across product categories should be location-specific. This paper (i) examines the conditions for such micro-marketing to be beneficial, and (ii) in particular—how these benefits depend on store format. It also (iii) indicates how the pattern of space adjustments to local conditions should differ between formats. The propositions are tested in a grocery retail setting, for a retail chain operating limited-service supermarkets and full-service hypermarkets. Our results suggest that micro-marketing is beneficial in both types of format. Yet, the appropriate way of localizing space allocation patterns is format-specific. While supermarkets should primarily adjust the space shares of food (core) categories, hypermarkets should primarily adapt the space shares of non-food (non-core) categories to local market conditions. The outcomes of the study have conceptual as well as managerial relevance and may prove useful for multi-format retailers in a wide range of settings.     

Optimal partial hedging of options with small transaction costs

This study uses asymptotic analysis to derive optimal hedging strategies for option portfolios hedged using an imperfectly correlated hedging asset with small fixed and/or proportional transaction costs, obtaining explicit formulae in special cases. This is of use when it is impractical to hedge using the underlying asset itself. The hedging strategy holds a position in the hedging asset whose value lies between two bounds, which are independent of the hedging asset's current value. For low absolute correlation between hedging and hedged assets, highly risk‐averse investors and large portfolios, hedging strategies and option values differ significantly from their perfect market equivalents. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark 31:855–897, 2011