Implementing efficient conservation portfolio design

Modern tools for cost-effective conservation reserve site planning require the planner to have information about spatial distributions of conservation costs and benefits. Climate change creates unprecedented uncertainty about future land values and species habitat ranges, such that conservation scientists cannot map costs and benefits with certainty anymore. This paper contributes to the literature on the economics of conservation in the face of climate change uncertainty. It advances a new method for using modern portfolio theory to choose lands to protect that yield total conservation returns with less uncertainty. It explores the implications for portfolio recommendations of variation in the correlations between ecological and land-value responses to climate change. It also tests the robustness of the method to shortcuts that might be taken to simplify analysis, identifying problems that arise if conservation costs are ignored in portfolio analysis and demonstrating when portfolio recommendations are sensitive to how ecological benefits are quantified.     

Stochastic growth: a duality approach

We re-examine the representative agent's optimal consumption and savings under uncertainty in the presence of investment constraints using martingale representation and convex analysis techniques. This framework allows us to explicitly quantify precautionary savings which induces a higher average growth rate than in a certainty setup. We provide a closed form solution for a Cobb-Douglas economy. The effect of uncertainty on portfolio selection is analyzed. Consumption growth rate and risk free interest rate exhibit a U-shaped relationship. Uncertainty negatively affects expected consumption growth rate; such a result seems to be supported by empirical evidence.     

RISKY PRODUCTION WITH EX-ANTE PRICES UNDER MONOPOLY ANALYTICAL AND SIMULATION RESULTS

This paper concerns the case of a monopolist facing multiplicative uncertainty in demand. Karlin and Carr (1962), henceforth KC, show that, when price and production are both chosen ex ante , the uncertainty price exceeds the certainty price. They also give a sufficient condition under which the firm locates above the certainty demand curve, but they do not consider the effect on the output level. In this note we replicate the KC results and then go further. In the special case that the price elasticity of certainty demand is constant, and the probability distribution for the uncertainty parameter in the demand function is uniform, output is unambiguously lower under uncertainty, and KC's condition for the firm to locate above the certainty demand curve can be strengthened to one that is both necessary and sufficient. The robustness of these results is tested under less stringent assumptions on demand, abandoning symmetry for a lognormal distribution of the uncertainty parameter. Simulation confirms that the results hold up, and also determines the effects upon the firm's decisions of an increase in demand uncertainty.     

Fuzzy possibilistic portfolio selection model with VaR constraint and risk-free investment

We propose a possibilistic portfolio model with VaR constraint and risk-free investment based on the possibilistic mean and variance, while assuming that the expected rate of returns is a fuzzy number. The model shows more clearly that, in the financial market affected by several non-probabilistic factors, risk-averse investors wish not only to reach the expected rate of returns in their actual investment, but also to assure that the maximum of their possible future risk is lower than an expected loss. Under the condition that the expected rate of returns is a normal distribution fuzzy variable, we proposed a theorem as the solution, and derive a crisp equivalent form of the possibilistic portfolio under constraints of VaR and risk-free investment. This model is an expansion of the fuzzy possibilistic mean–variance model by Zhang (2007). Finally, an empirical study is carried out using the data concerning some stocks of various industries listed at the Shanghai Stock Exchange. A conclusion is reached that the investors are able to choose a portfolio more suitable to them under the VaR constraint.     

Portfolio Choice and Liquidity Constraints*

We study the infinite‐horizon model of household portfolio choice under liquidity constraints and revisit the portfolio specialization puzzle. We show why the puzzle is robust to several model variations, and argue that positive correlation between earnings shocks and stock returns is unlikely to provide an empirically plausible resolution. We find that relatively small fixed costs for stock market entry are sufficient to deter stockholding because, for a plausible range of parameter values, households can achieve desired consumption smoothing with small or zero holdings of stocks. Such costs could arise from informational considerations, sign‐up fees, and investor inertia.     

Interval portfolio selection models within the framework of uncertainty theory

The expected returns for securities are traditionally estimated as crisp values. Since the improper values may bring on an unsuccessful investment decision, portfolio experts generally prefer offering interval estimations for expected returns rather than crisp ones. The portfolio selection problem with interval expected returns is widely studied recently. In this paper, by considering the security returns with interval expected returns as uncertain variables, a mean-semiabsolute deviation model is proposed within the framework of uncertainty theory, which is a crisp nonlinear programming model and can be well solved by the classical optimization algorithms. In order to illustrate the method, some numerical experiments are given and solved.     

A large CVaR-based portfolio selection model with weight constraints

Although the traditional CVaR-based portfolio methods are successfully used in practice, the size of a portfolio with thousands of assets makes optimizing them difficult, if not impossible to solve. In this article we introduce a large CVaR-based portfolio selection method by imposing weight constraints on the standard CVaR-based portfolio selection model, which effectively avoids extreme positions often emerging in traditional methods. We propose to solve the large CVaR-based portfolio model with weight constraints using penalized quantile regression techniques, which overcomes the difficulties of large scale optimization in traditional methods. We illustrate the method via empirical analysis of optimal portfolios on Shanghai and Shenzhen 300 (HS300) index and Shanghai Stock Exchange Composite (SSEC) index of China. The empirical results show that our method is efficient to solve a large portfolio selection and performs well in dispersing tail risk of a portfolio by only using a small amount of financial assets.     

Dynamic asset allocation with ambiguous return predictability

We study an investor's optimal consumption and portfolio choice problem when he is confronted with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investor's aversion to model uncertainty. The investor deals with specification doubts by slanting his beliefs about submodels of returns pessimistically, causing his investment strategy to be more conservative than the Bayesian strategy. Unlike in the Bayesian framework, the hedging demand against model uncertainty may cause the investor's stock allocation to decrease sharply given a small doubt of return predictability, even though the expected return according to the VAR model is large. Over much of the parameter space, the robust strategy is very close to the Bayesian strategy with Epstein–Zin preferences and risk aversion chosen to match the same average portfolio holdings. This is true in particular when the IID model is unlikely and the dividend yield is low, as in recent years. However, differences in strategies can be substantial if the IID model is unlikely and the dividend yield is high.     

Portfolio style: Return-based attribution using quantile regression

Return-based classification identifies a portfolio's style signature in the time series of its returns. Detection is based on a regression of portfolio returns on returns of factor mimicking indices. The method is easy to apply and does not require information about portfolio composition. Classification using least squares means that style is determined by the way factor exposure influences expected returns. We introduce regression quantiles as a complement to the standard analysis. The regression quantiles extract additional information from the time series of returns by identifying the way style affects returns at places other than the expected value. This allows discrimination among portfolios that would be otherwise judged equivalent based on conditional expectations. It also provides direct information about the impact of style on the tails of the conditional return distribution. Simple examples are presented to illustrate regression quantile classification.     

Interviews with Institutional Investors: The How and Why of Active Investing

We interview professional institutional investors to learn how they choose between active and passive management, select active equity managers and construct multi-manager portfolios. We find that many of the aspects emphasized in the fund management literature, such as returns generated by the average manager and emphasis on past performance, play a relatively minor role in decisions. In contrast, judgment is found to play a central role, particularly the evaluation of people when selecting managers, the role of confidence in retaining managers, and self-perceptions about capability to identify skilled managers. Past performance is not taken at face value, but analyzed to understand underlying sources of returns. Stated reasons for preferring active management relate to whether a handful of skilled active managers can be identified and combined to generate a better expected portfolio outcome; and are only vaguely associated with the performance of the average manager.     

Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations

This paper discusses a portfolio adjusting problem with additional risk assets and a riskless asset in the situation where security returns are given by experts' evaluations rather than historical data. Uncertain variables are employed to describe the security returns. Using expected value and risk index as measurements of portfolio return and risk respectively, we propose two portfolio optimization models for an existing portfolio in two cases, taking minimum transaction lot, transaction cost, and lower and upper bound constraints into account. In one case the riskless asset can be both borrowed and lent freely, and in another case the riskless asset can only be lent and the borrowing of riskless asset is not allowed. The adjusting models are converted into their crisp equivalents, enabling the users to solve them with currently available programming solvers. For the sake of illustration, numerical examples in two cases are also provided. The results show that under the same predetermined maximum tolerable risk level the expected return of the optimal portfolio is smaller when the riskless asset can only be lent than when the riskless asset can be both borrowed and lent freely.     

Diversification across ASEAN-wide sectoral and national equity returns

This paper examines the effects of local and global shocks on the sector indices and national returns of the Association of Southeast Asian Nations (ASEAN) by using the univariate AR-GARCH model. We find that regional and global shocks have different influences on the ASEAN-wide sector and national equity indices. There is evidence that the ASEAN-wide sectoral returns are mostly driven by local shocks, except for the insurance and technology sectors. The volatility of Singapore's and Vietnam's national returns mostly results from their own shocks rather than local and global shocks. Applying the trend spillover model, this paper also shows that the effects of regional and global shocks on return volatility have been decreasing for almost all ASEAN-wide sectors' equity indices, while the trend for the volatility spillover effects of those shocks are positive and significant for the production and industries group sectors, as well as the food and beverage sector. Comparing the variance ratios of ASEAN sectoral and national returns, it is evident that the percentage of national equity returns belonging to their own shocks is higher than that of sectoral returns, indicating that investors might be better off diversifying their assets across countries rather than sectors in ASEAN area. This finding is consistent with the results of the mean–variance frontiers, as the portfolio composed purely of ASEAN national returns has a stronger efficiency frontier than a portfolio of all ASEAN-wide sector equity returns. By using the spanning and intersection tests, the paper also indicates that adding ASEAN national equity returns might improve the efficiency frontiers of investors' holding portfolios.     

The relation between asset growth and the cross-section of stock returns: Evidence from the Chinese stock market

This study examines the effect of firm investment on stock returns by using data on the Chinese stock market. We find that stocks with higher investment experience lower future returns and there is an obvious investment effect in the Chinese stock market. The investment effect is stronger for firms that have higher cash flows, lower debt or for state-owned firms. We further explore the relation between investment and returns over the 3 years around portfolio formation. The results show that the high investment firms earn higher returns than low investment firms before portfolio formation; however the high investment firms earn lower returns than low investment firms after portfolio formation, such evidence is supportive of investor's overreaction explanation. Additionally, the stock returns don't necessarily decrease after investment, and the stock returns don't significantly positively correlate with firm profitability or book-to-market, so the result don't support risk-based explanation. Overall, both our portfolio sort and two-stage cross-sectional regression analysis show that behavioral finance theories are better than risk-based theories in explaining the investment anomaly. Evidence from the Chinese stock market provides a useful perspective to understand the debate on the investment anomaly.     

A possibilistic portfolio adjusting model with new added assets

In order to fit changes in financial markets, portfolio managers often need to revise an existing portfolio. This article analyzes the portfolio adjusting problem with new added assets. We propose a possibilistic portfolio adjusting model with transaction costs and bounded constraints on holdings of assets, which can be transformed into a linear programming problem. Both the lower bounds on holdings and the total investment constraints influence the optimal portfolio adjusting strategies. Furthermore, a numerical example of a portfolio adjusting problem is given to illustrate our proposed effective approaches. The numerical results show the case that investors do not need to invest total capital and to hold all assets in the portfolio for some required return levels.     

An experimental study of the impact of competition for Other People’s Money: the portfolio manager market

In this paper we experimentally investigate the impact that competing for funds has on the risk-taking behavior of laboratory portfolio managers compensated through an option-like scheme according to which the manager receives (most of) the compensation only for returns in excess of pre-specified strike price. We find that such a competitive environment and contractual arrangement lead, both in theory and in the lab, to inefficient risk taking behavior on the part of portfolio managers. We then study various policy interventions, obtained by manipulating various aspects of the competitive environment and the contractual arrangement, e.g., the Transparency of the contracts offered, the Risk Sharing component in the contract linking portfolio managers to investors, etc. While all these interventions would induce portfolio managers, at equilibrium, to efficiently invest funds in safe assets, we find that, in the lab, Transparency is most effective in incentivising managers to do so. Finally, we document a behavioral “Other People’s Money” effect in the lab, where portfolio managers tend to invest the funds of their investors in a more risky manner than their Own Money, even when it is not in either the investors’ or the managers’ interest to do so.     

Oil shocks,US economic uncertainty,and emerging stock markets

This paper investigates the impacts of oil price shocks and US economic uncertainty on emerging equity markets within a structural VAR model. I find that both precautionary oil demand and US economic uncertainty shocks have significant negative effects on emerging stock returns, whereas aggregate demand shocks cause a sustained rise of the returns. In particular, the direct effects of oil shocks on emerging stock returns are amplified by the endogenous response of US economic uncertainty. Variance decomposition analysis shows that oil market fundamentals and US economic uncertainty are an important determinant of emerging equity returns, accounting for 35% and 24% of their long-term variations, respectively. The heterogeneous impacts of structural shocks on individual emerging markets, however, suggest that a well-diversified portfolio can be obtainable.     

Individual Decision Making and Investor Welfare

This article analyses and quantifies the costs of suboptimal decision making for an investor with a multi-period horizon. In light of the empirical evidence that investors are too conservative and hold portfolios that are insufficiently diversified, we evaluate the costs of suboptimal equity participation both analytically and using simulation, and also estimate the costs of suboptimal diversification using simulation. We find that suboptimal leverage imposes only modest costs on the investor for reasonable parameter values. While the costs of inadequate diversification can be very high, we find that, because of the higher returns on small firms, an equally weighted portfolio of as few as five randomly chosen firms can provide the same level of expected utility as the value weighted market portfolio.
(J.E.L.: G11, G18, G23).     

Portfolio choice with high frequency data: CRRA preferences and the liquidity effect

This paper suggests a new approach for portfolio choice. In this framework, the investor, with CRRA preferences, has two objectives: the maximization of the expected utility and the minimization of the portfolio expected illiquidity. The CRRA utility is measured using the portfolio realized volatility, realized skewness and realized kurtosis, while the portfolio illiquidity is measured using the well-known Amihud illiquidity ratio. Therefore, the investor is able to make her choices directly in the expected utility/liquidity (EU/L) bi-dimensional space. We conduct an empirical analysis in a set of fourteen stocks of the CAC 40 stock market index, using high frequency data for the time span from January 1999 to December 2005 (seven years). The robustness of the proposed model is checked according to the out-of-sample performance of different EU/L portfolios relative to the minimum variance and equally weighted portfolios. For different risk aversion levels, the EU/L portfolios are quite competitive and in several cases consistently outperform those benchmarks, in terms of utility, liquidity and certainty equivalent.     

不确定性条件下资本市场投资预期收益模型探析

在现实经济活动中特别是在资本市场投资中,人们对将来的情况很难准确地预测到,他们所知道的最多只不过是在未来各种各样的收益状况下所可能产生的结果.也就是说,未来经济活动特别是资本市场投资活动具有不确定性.由于不确定性的预期的作用和影响,在不确定性条件下的资本市场投资预期收益模型与在确定性条件下的收益模型存在着一定的偏差.只有减少人们对经济不确定性的预期,才能使资本市场投资需求旺盛.     

Stock return predictability: the role of inflation and threshold dynamics

This paper argues that the nature of stock return predictability varies with the level of inflation. We contend that the nature of relations between economic variables and returns differs according to the level of inflation, due to different economic risk implications. An increase in low level inflation may signal improving economic conditions and lower expected returns, while the opposite is true with an equal rise in high level inflation. Linear estimation provides contradictory coefficient values, which we argue arises from mixing coefficient values across regimes. We test for and estimate threshold models with inflation and the term structure as the threshold variable. These models reveal a change in either the sign or magnitude of the parameter values across the regimes such that the relation between stock returns and economic variables is not constant. Measures of in-sample fit and a forecast exercise support the threshold models. They produce a higher adjusted R², lower MAE and RMSE and higher trading related measures. These results help explain the lack of consistent empirical evidence in favour of stock return predictability and should be of interest to those engaged in stock market modelling as well as trading and portfolio management.