Optimizing the shares of native tree species in forest plantations with biased financial parameters

Addressing uncertainty is a key requirement to follow the principle of precaution in sustainable ecosystem management. The maximization of worst-case outcomes according to the “maximin” decision rule, based on the two parameters mean and variance of a financial indicator, is a prominent approach to integrate uncertainty in decision-making. In forestry, the problem of selecting the optimum tree species combination for a forest plantation investment can be seen as a problem of optimal portfolio selection, to be solved according to the “maximin” decision rule. Yet, it is well known that portfolios computed from expected means and variances are highly sensitive to changes in the estimated parameters. The financial results may be poor if we rely too much on the historical data. This paper tests an extended worst-case model that considers a lower bound for the expected mean net present value (NPV) of a tree species portfolio and an upper bound for its variance. Biased expected mean NPVs, variances and correlations for the tree species Picea abies [L.] Karst. (Spruce) and Fagus sylvatica L. (Beech) were used to test the variability of the resulting tree species portfolios (27 scenarios). A comprehensive simulated data set, which was adopted from an existing study and defined as the independent reference, served to evaluate the financial performance of the tree species portfolios obtained from optimization with the biased data. Compared with the results of classical worst-case optimization instances, it was feasible to reduce the variability of tree species shares effectively when the optimization was carried out with the extended worst-case approach. Furthermore, the financial performance of this approach was better when tested with the independent data. The worst-case forest NPVs achieved with the extended approach were on average 10% (statistical confidence 0.95) or 147% (statistical confidence 0.99) greater in comparison to the results of the classical approach. The influence of the uncertainty parameter selection was tested and the results were discussed against the controversial viewpoints on the usefulness of the “information-gap decision theory”. Finally, the significance of our results for sustainable ecosystem management is pointed out.     

ACQUISITION OF INFORMATION TO DIVERSIFY CONTRACTUAL RISK*

Are hedging transactions that diversify a manager’s compensation risk detrimental to incentives, or can they improve contracting efficiency? If hedging provides efficiency benefits, should the manager or the firm undertake it? In our model, both the firm and the manager can trade financial portfolios to diversify the manager’s compensation risk. Prior to the portfolio selection, the parties need to acquire information on how different financial portfolios fit their diversification purposes. We illustrate that financial portfolios correlated with firm‐specific risk improve contracting efficiency. For equal information costs, it is optimal for the firm to undertake the hedging on the manager’s behalf.     

Hedge fund return higher moments over the business cycle

We investigate how macroeconomic and financial uncertainty impacts the behavior of hedge fund strategy higher moments—i.e., co-skewness and co-kurtosis—and their respective cross-sectional dispersions. Consistent with theoretical models, we find that strategy managers trade off these two higher moments when building optimal portfolios. Moreover, these trade-offs depend on the kind of strategy. Our experiments show that the VIX and its conditional variance are the most important factors affecting higher moment risk in the hedge fund industry. They also reveal that the behavior of hedge fund strategies is very asymmetric depending on the phase of the business cycle. In contrast to studies which rely on the mean-variance setting, we find that systemic risk—as measured by the cross-sectional dispersions of higher moments—tends to decrease in the low regime. The indicators of market volatility play a decisive role to explain this decline in systemic risk.     

Regional and copula estimation effects on EU and US energy equity portfolios

ABSTRACT

The aim of this paper is to investigate the regional interdependence structure of energy equities in the US and in the EU. Based on weekly stock prices of 28 big energy firms in the two regions from 2008 to 2019, we compare the efficiency of using bivariate or multivariate copulas to describe the dependence structure of energy equities. Furthermore, we investigate the impact of the choice between these two methods on the performance of energy equity portfolios. Our empirical results show that multivariate copulas, such as C-Vine, allow to better describe the dependence structure of energy equities. We also find that there is a stronger and more complex dependence structure among EU energy equities than among US energy equities. Our scenario analysis also shows that the dependence structure is stronger during the GFC while being weaker during the ESDC. More importantly, the correlation matrix obtained from the multivariate copula method allows to obtain optimal mean-CVaR portfolios with a higher performance than that from the bivariate copula method. More importantly, optimal portfolios constituted with multivariate copulas allow to reduce the portfolio’s sensitivity to oil prices.     

Endogenous Home Bias in Portfolio Diversification and Firms’ Entry

The home bias in portfolios is considered a main puzzle in international macroeconomics. This paper provides a new benchmark for its analysis in a tractable new open economy macroeconomic model, where the home‐biased position is an optimal allocation. An equilibrium model of perfect risk‐sharing is specified, with endogenous portfolios and firm entry. Unlike in previous work, the international portfolio diversification is driven by home bias in capital goods—independently of home bias in consumption when countries are of equal size. The model explains the recent patterns of portfolio allocations in developed economies. Most important, optimal portfolio shares are independent of market dynamics.     

Mixed forests and finance — Methodological approaches

Mixed forest ecosystems show effects of risk compensation similar to diversified portfolios of stocks. Other than portfolios of stocks, the composition of long-lived forests cannot be adjusted at short notice to current market developments. Thus, the financial robustness of tree-species portfolios is very important. However, it is still an open question, which financial approaches are appropriate to evaluate the financial robustness of mixed forests compared to single-species forests.This paper analysed various possibilities to assess portfolios of tree species, namely, the mean-variance (MV) approach applied for the selection of optimal portfolios, the second order stochastic dominance (SSD) criterion and the information-gap approach. For the numerical analysis existing financial data on Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.) were used which were generated by Monte-Carlo simulations (MCS) under risk.Regardless of the analysed approach, in all cases pure forests did not outperform mixed forests. The MV approach was restricted by the assumption of normally distributed financial returns. It had the tendency to favour larger proportions of the high-risk species Norway spruce. SSD was only able to distinguish between the efficient and the inefficient portfolios. It showed that forests with less than 20% (financial returns generated by MCS) or less than 30% (normally distributed financial returns) of Norway spruce were inefficient. Under information-gap modelling the advantages of risk compensation in mixed forests became clearest. Under the given assumptions, the financial robustness of a mixed forest (50% European beech and 50% Norway spruce) was between 4 and 18 times greater than that of pure Norway spruce.Modern information-gap modelling is very similar to the well known safety first rules and as such it is not that novel to financial optimisation as it seems at the first glance. Although the information-gap theory resulted in the same rankings as the minimisation of the estimated probability of failure, it nevertheless proved to be useful as a supplement to the other methods. Against the background of severe uncertainty inherent in long-term decision-making in forestry, information-gap modelling is based on appropriate assumptions. It favours a decision, which promises the greatest tolerance to possible errors in the available information, while still guaranteeing a minimal acceptable financial result. In principle, classical safety first rules do the same. However, the information-gap model is able to quantify the immunity of a decision against errors in the estimated financial data. From a theoretical point of view, this approach provides a supplementary and methodologically sound opportunity to incorporate severe uncertainty in decision-making.     

PORTFOLIO SELECTION BETWEEN A MATURE MARKET AND SELECTED EMERGING MARKETS INDICES IN THE PRESENCE OF STRUCTURAL BREAKS

The paper examines the influence of the structural breaks on the optimal weights, hedge ratios and hedge effectiveness index (HEI) of risk‐minimizing portfolios composed of S&P500 and selected emerging markets’ indices from East Europe, Asia and South America. We employ a bivariate DCC‐EGARCH models without and with structural breaks and we find better estimation features when structural breaks are included in the model. However, we do not find evidence that insertion of structural breaks increases portfolio hedging performances. The differences that exist between optimal weights, hedge ratios and HEI values are so small that tangible economic benefit for international investors do not exist.     

Investment horizon effect on asset allocation between value and growth strategies

How does the optimal risk exposure of assets change as their investment horizons increase? Does this impact investment portfolio decision-making, in particular, optimal asset allocation between value and growth strategies over various investment horizons? This paper adopts a new approach to address these questions by examining portfolio allocation between value and growth stocks over various investment horizons. This new approach is based on wavelet analysis, which decomposes the returns of a particular investment strategy across multiple investment horizons. The key empirical results show that the success of pursuing the value strategy (short-selling growth stocks and going long on value stocks) is impacted by the approach used to classify value and growth stock returns. We explore two common alternatives: Fama-French versus Standard & Poor's (S&P) 500/Barra portfolios. The results using Fama-French portfolios show that as the investment horizon increases, the optimal mean allocation of investors tilts heavily away from growth stocks, particularly for lower and moderate levels of risk aversion. Interestingly, for S&P 500/Barra portfolios the allocation weights between value and growth do not vary much.     

Managing portfolio risk in strategic technology management: evidence from a panel data-set of the world's largest R&D performers

In this article, we analyze the impact of firms’ technology bases on their financial performance. By taking a strategic perspective of technology, we argue that it is not sufficient to analyze only the size or novelty/quality of the technology base as technology bases can best be understood as portfolios of individual technologies. In such a framework, risk consideration should be taken into account. More specifically, we argue that increasing technological breadth can serve as a hedge against the inherent uncertainties of developing and commercializing technology, in particular when the technology base is very large or novel. We also propose that technology has higher impacts on financial performance for firms with broader technology portfolios. A similar argument proposes that technological breadth can offset the increased risks of addressing foreign markets. We test our hypotheses using an international panel data-set of large R&D-performing firms. Our results suggest that broad technology portfolios can indeed serve as a hedge against technological and commercialization risks.     

Vertical alliance portfolios and the business performance of small technology-based firms

This paper discusses how small technology-based firms (STBFs) effectively manage vertical alliances by choosing proper alliance structures to both manage challenges and pursue higher performance. We consider the main challenges of STBFs’ vertical alliances as opportunistic risk and coordination concern between partners, and derive four types of vertical alliance portfolios with different extents of risk and return based on the relational perspective. We then examine the impact of each portfolio on performance and the moderating effect of STBFs’ age and technological capability. The results show the portfolio focusing on bilateral alliances is not helpful for STBFs, while the others are useful. The portfolio focusing on unilateral alliances promises young firms better performance, while hybrid portfolios of unilateral and bilateral alliances are more helpful for older STBFs. In hybrid portfolios, bilateral alliance in the upstream is beneficial to specific technology-focused firms, while bilateral alliance in the downstream is recommended to STBFs whose technology covers a wider range.     

An alternative approach for portfolio performance evaluation: enabling fund evaluation relative to peer group via Malkiel’s monkey

We propose an implementable portfolio performance evaluation procedure that compares a portfolio with respect to the portfolios constructed by an infinite number of Malkiel’s blindfolded monkeys, or equivalently the whole enumeration of all possible portfolios. We argue that this approach exhibits two main advantages. First, it does not require any benchmark portfolios because a portfolio is being compared to an infinite number of portfolios. Second, it is market condition invariant. Since the market conditions are already reflected in the portfolio performances of an infinite blindfolded monkeys, our measure of portfolio performances is invariant to volatile market conditions.     

Spatial distribution of species populations,relative economic values,and the optimal size and number of reserves

We examine the tradeoff between the number and average size of nature reserves. When the costs of enforcing reserve boundaries are negligible, we find analytically that the relative price of biodiversity has a positive impact on the optimal total reserved area but an ambiguous impact on the optimal number of reserves. Simulation modeling of floral diversity in a tropical timber concession reveals that the resolution of this ambiguity depends on spatial distributions of the populations of tree species: whether or not they are spatially aggregated (clumped). The impact of biodiversity price on optimal reserve number remains analytically ambiguous when enforcement costs are not negligible. Multiple reserves being economically superior to a single reserve now requires, in addition to aggregation, a biodiversity price that is sufficiently high to offset the effects of enforcement costs. Most of our simulation scenarios generate threshold biodiversity prices that do not exceed a leading estimate of the marginal value of a higher plant species in the bioprospecting literature. Several smaller reserves evidently can be economically superior to a single larger one even in the presence of enforcement costs.      

Tail dependence risk exposure and diversification potential of Islamic and conventional banks

This paper undertakes a rolling window comparative analysis of risks for portfolios consisting of GCC Islamic and conventional bank indices. We draw our empirical results by employing canonical, drawable and regular vine copula models, as well as by implementing a portfolio optimization method with a conditional Value-at-Risk constraint. We find evidence of higher riskiness in the group of Islamic banks relative to the group of conventional banks across each of the financial rolling window scenarios under consideration. Specifically, a greater negative (nonlinear) tail asymmetric dependence is observed in the pairs of Islamic banks’ relationships. The results also show that the optimal portfolio model supports a clear preference towards the group of conventional banks in regard to risk minimization and diversification benefits.     

Sustainable competitive advantage and stock performance: the case for wide moat stocks

‘In business, I look for economic castles protected by unbreachable “Moats”’. Warren Buffett Companies that have sustainable competitive advantages should be able to create a barrier (Moat) to prevent or lessen competition from other firms. The wider the Moat the greater the barrier and the more secure the company’s profitability. Using the Morningstar classification of ‘Wide Moat’ stocks, we construct annually rebalanced equal- and value-weighted portfolios to analyse their performance in order to determine if they deliver superior performance relative to standard benchmark portfolios. The period for our analysis extends from June 2002 through May 2014. We find that the ‘Wide Moat’ portfolios outperform both the S&P 500 and Russell 3000 indices generating higher average monthly and annualized returns, Sharpe Ratio, Sortino Ratio, Treynor Ratio, Omega Ratio, Upside Potential Ratio, M², M² Alpha, and cumulative returns. When we compute alpha using Carhart four-factor and Fama–French five-factor models, we find that ‘Wide Moat’ portfolios had significantly positive risk-adjusted alphas with both the models. ‘Wide Moat’ portfolios also lost less value during the 2007–2009 financial crisis compared to both S&P 500 and Russell 3000. In conclusion, we find that ‘Wide Moat’ stocks have created significant value for their investors over the course of our study.     

Portfolio choice of financial investors and European business cycle convergence: a panel analysis for EU countries

We investigate the linkage between business cycle convergence and financial portfolio choice for a panel of 18 EU countries. We construct an index of similarity of financial portfolios which we then put into context with the view that “the financial world” has an impact on business cycles and contributes to business cycle convergence via the consumption-wealth linkage. The model which guides our analysis is the International Asset Pricing Model (IAPM). Portfolios of the 18 EU countries investigated by us turn out to become more similar over time. According to our fixed effects GMM TSLS estimations, similar portfolios contribute to a convergence of business cycles—via a convergence of consumption cycles. This turns out to be especially true for country-pairs that include euro area non-member countries and, thus, have quite different income and wealth structures.     

Revealed preferences for portfolio selection – does skewness matter?

In this article, we consider the portfolio selection problem as a Bayesian decision problem. We compare the traditional mean–variance and mean–variance–skewness efficient portfolios. We develop bi-level programming problem to investigate the market’s preference for risk by using observed (market) weights. Numerical experiments are conducted on a portfolio formed by the 30 stocks in the Dow Jones Industrial Average. Numerical results show that the market’s preferences are better explained when skewness is included.     

Self-fulfilling crises with default and devaluation

We characterize optimal debt policy in a dynamic stochastic general equilibrium model of defaults and devaluations in which self-fulfilling crises can arise. When the government cannot commit to repay its debt and cannot commit to maintain the exchange rate, consumers’ expectations of devaluation make the safe level of government debt very low. We show that, when the debt is in the crises zone—where self-fulfilling crisis can occur—the government finds it optimal to reduce the debt to exit the zone. The lower the probability that consumers assign to devaluation, however, the greater is the number of periods that the government will choose to take to exit the crisis zone. We argue that our model can help understand events in Argentina in 2001–2002 and throw light on some aspects of the current EMU sovereign debt crisis.     

Between a Rock and a Hard Place: A Trade-Theory Analysis of Leakage Under Production- and Consumption-Based Policies

Without a comprehensive global climate agreement, carbon leakage remains a contentious issue. Consumption-based pricing of emissions—which could in practice be implemented with a full border tax adjustment (BTA)—has been forwarded as an option to increase the effectiveness of unilateral climate policy. This paper questions the economic rationale behind this approach, using a theoretical $2 \times 2$ trade model in which leakage occurs through terms-of-trade effects. We show analytically, first, that consumption-based pricing of emissions does not necessarily result in less leakage than production-based policies. Second, the sign of the optimal unilateral carbon tariff depends on the carbon-intensity differential between the foreign country’s exporting and non-exporting sectors, and not on the differential between home’s and foreign’s exporting sectors, as implied by the full BTA approach. Third, based on empirical data for the year 2004, our model implies that full BTA applied by the European Union on e.g. imports from and exports to China would—by shifting China’s production from the export sector with a relatively low carbon-intensity towards the more carbon-intensive non-export sector—actually increase leakage.     

The dynamics of efficient asset trading with heterogeneous beliefs

This paper analyzes the dynamic properties of portfolios that sustain dynamically complete markets equilibrium when agents have heterogeneous priors. We argue that the conventional wisdom that belief heterogeneity generates continuous trade and significant fluctuations in individual portfolios may be correct but it needs some qualifications. We consider an infinite horizon stochastic endowment economy populated by many Bayesian agents with heterogeneous priors over the stochastic process of the states of nature. Our approach hinges on studying the portfolios that decentralize Pareto optimal allocations. Since these allocations are typically history dependent, we propose a methodology to provide a complete recursive characterization when agents believe that the process of states of nature is i.i.d. but disagree about the probability of the states. We show that even though heterogeneous priors within that class can indeed generate genuine changes in the portfolios of any dynamically complete markets equilibrium, these changes vanish with probability one if the true process consists of i.i.d. draws from a common distribution and the support of some agent's prior belief contains the true distribution. Finally, we provide examples in which asset trading does not vanish because either (i) no agent learns the true conditional probability of the states or (ii) some agent does not know the true process generating the data is i.i.d.     

Lead-lag effects in the mean and variance of returns of size-sorted UK equity portfolios

We test for lead-lag effects in the mean and variance among size-sorted portfolios for the UK stock market. We construct three sets of portfolios, namely a set of size-sorted equally-weighted portfolios of different capitalization size, a set of size-sorted value-weighted portfolios of different capitalization size, and a third set of portfolios of the same capitalization size. The recently proposed Cross Correlation Function test is employed. For both sets of portfolios with different capitalization size, we find evidence of a lead effect in both the mean and the variance from large-firm portfolios to small-firm portfolios. This result does not depend on the weighting scheme used to construct portfolios, and indicates that contrarian trading strategies on large-firm portfolios are profitable. For portfolios of equal capitalization size, there is hardly any evidence of a lead-lag effect in either the mean or the variance. This suggests that the lead-lag effect is due to the difference in the capitalization size among portfolios.I wish to thank two anonymous referees for helpful comments on a previous draft of this paper. The usual disclaimer applies.ing scheme.First version received: February 2002/Final version received: May 2003