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Bernales, A., Reus, L., & Valdenegro, V. (2022). Speculative bubbles under supply constraints, background risk and investment fraud in the art market. J. Corp. Financ., 77, 101746.
Abstract: We examine the unexplored effects on art markets of artist death (asset supply constraints), collectors' wealth (background risk) and forgery risk (risk of investment fraud), under short-sale constraints and risk aversion. Speculative bubbles emerge and have the form of an option strangle (a put option and a call option), in which strike prices are affected by art supply constraints and the association of the artworks' emotional value with both collectors' wealth and forgery, while the options' underlying asset is the stochastic heterogeneous beliefs of agents. We show that speculative bubbles increase with four elements: art supply constraints; a more negative correlation between collectors' wealth and the artworks' emotional value; a more positive relationship between forgery and the artworks' emotional value; and more heterogeneous beliefs. These four sources of speculation increase the expected turnover rate; however, they also augment the variance of speculative bubbles, which generates price discounts (i.e. risk premiums) for holding artworks. Consequently, the net impact of speculation is not necessarily increased art prices. This study not only contributes to the art market literature, but also to studies about speculative bubbles in other financial markets under heterogeneous beliefs, short-sale constraints and risk-averse investors, since we additionally consider the simultaneous effect of asset supply constraints, investors' background risk and the risk of investment fraud.
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Castaneda, P., & Reus, L. (2019). Suboptimal investment behavior and welfare costs: A simulation based approach. Financ. Res. Lett., 30, 170–180.
Abstract: We propose a representation of suboptimal investment behavior based on the stochastic discount factor (SDF) paradigm. Suboptimal investment behavior is rationalized as being the investor's optimal decision under a wrong SDF, while wealth trajectories and budget constraints are based on the true SDF. We develop a novel Monte Carlo simulation approach to compute the welfare costs for this suboptimal behavior. We study the suboptimal portfolio choice under CRRA preferences using two financial market models. The Monte Carlo simulation delivers comparable welfare losses to those computed in the original studies, which are based on partial differential equations (PDE) and – finite-difference schemes.
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Munoz, F. D., van der Weijde, A. H., Hobbs, B. F., & Watson, J. P. (2017). Does risk aversion affect transmission and generation planning? A Western North America case study. Energy Econ., 64, 213–225.
Abstract: We investigate the effects of risk aversion on optimal transmission and generation expansion planning in a competitive and complete market. To do so, we formulate a stochastic model that minimizes a weighted average of expected transmission and generation costs and their conditional value at risk (CVaR). We show that the solution of this optimization problem is equivalent to the solution of a perfectly competitive risk averse Stackelberg equilibrium, in which a risk-averse transmission planner maximizes welfare after which risk-averse generators maximize profits. This model is then applied to a 240-bus representation of the Western Electricity Coordinating Council, in which we examine the impact of risk aversion on levels and spatial patterns of generation and transmission investment. Although the impact of risk aversion remains small at an aggregate level, state-level impacts on generation and transmission investment can be significant, which emphasizes the importance of explicit consideration of risk aversion in planning models. (C) 2017 Elsevier B.V. All rights reserved.
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Ortega-Martinez, E., Toledo-Alarcon, J., Fernandez, E., Campos, J. L., Oyarzun, R., Etchebehere, C., et al. (2024). A review of autotrophic denitrification for groundwater remediation: A special focus on bioelectrochemical reactors. J. Environ. Chem. Eng., 12(1), 111552.
Abstract: Groundwater is an important resource that can help in climate change adaptation. However, the pollution of these aquifers with nitrate is a widespread problem of growing concern. Biological denitrification using inorganic electron donors shows significant advantages in treating nitrate-polluted groundwater where organic matter presence is negligible. However, mass transfer limitations and secondary contamination seem to be the major hinderance to spread the use of these technologies. This could be solved by the use of bioelectrochemical systems (BES), which emerge as an attractive technology to solve these problems due to the reported low energy demand and high denitrification rates. However, technical and operational issues must be considered to replicate these results at full-scale. This review summarizes the biological basis of autotrophic denitrification and the key aspects of its application in bioelectrochemical systems. In addition, an estimation of the capital costs required for the implementation of a BES considering different population sizes and initial nitrate concentration in the ground-water is made.
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Reus, L., & Mulvey, J. M. (2016). Dynamic allocations for currency futures under switching regimes signals. Eur. J. Oper. Res., 253(1), 85–93.
Abstract: Over the last decades, speculative investors in the FX market have profited in the well known currency carry trade strategy (CT). However, during currencies or global financial crashes, CT produces substantial losses. In this work we present a methodology that enhances CT performance significantly. For our final strategy, constructed backtests show that the mean-semivolatility ratio can be more than doubled with respect to benchmark CT. To do the latter, we first identify and classify CT returns according to their behavior in different regimes, using a Hidden Markov Model (HMM). The model helps to determine when to open and close positions, depending whether the regime is favorable to CT or not. Finally we employ a mean-semivariance allocation model to improve allocations when positions are opened. (C) 2016 Elsevier B.V. All rights reserved.
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Villena, M. J., & Reus, L. (2016). On the strategic behavior of large investors: A mean-variance portfolio approach. Eur. J. Oper. Res., 254(2), 679–688.
Abstract: One key assumption of Markowitz's model is that all traders act as price takers. In this paper, we extend this mean-variance approach in a setting where large investors can move prices. Instead of having an individual optimization problem, we find the investors' Nash equilibrium and redefine the efficient frontier in this new framework. We also develop a simplified application of the general model, with two assets and two investors to shed light on the potential strategic behavior of large and atomic investors. Our findings validate the claim that large investors enhance their portfolio performance in relation to perfect market conditions. Besides, we show under which conditions atomic investors can benefit in relation to the standard setting, even if they have not total influence on their eventual performance. The 'two investors-two assets' setting allows us to quantify performance and do sensitivity analysis regarding investors' market power, risk tolerance and price elasticity of demand. Finally, for a group of well known ETFs, we empirically show how price variations change depending on the volume traded. We also explain how to set up and use our model with real market data. (C) 2016 Elsevier B.V. All rights reserved.
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