Ph.D. Mellado-Cid, Cristhian

Agricultural product prices are subject to various uncertainties, including unpredictable weather conditions, pest infestations, and market fluctuations, which can significantly impact agricultural yields and productivity. Accurately assessing and understanding price is crucial for farmers, policymakers, and stakeholders in the agricultural sector to make informed decisions and implement appropriate risk management strategies. This study used the ordered weighted average (OWA) operator and its extensions as mathematical aggregation techniques incorporating ordered weights to capture and evaluate the factors influencing price variation. By generating different vectors related to different inputs to the traditional formulation, it is possible to aggregate information to calculate and provide a new view of the outcomes. The results of this research can help enhance risk management practices in agriculture and support decision-making processes to mitigate the adverse effects of price.

The main practical problems that are faced by portfolio optimisation under the Markowitz model are (i) its lower out-of-sample performance than the naive 1=n rule, (ii) the resulting asset weights with extreme values, and (iii) the high sensitivity of those asset weights to small changes in the data. In this study, we aim to overcome these problems by using a computation method that shifts the smaller eigenvalues of the covariance matrix to the space that houses the eigenvalue spectrum of a random matrix. We evaluate this new method using a rolling sample approach. We obtain portfolios that show both more stable asset weights and better performance than the 1=n rule. We expect that this new computation method will be extended to several problems in portfolio management, thereby improving their consistency and performance.

We examine real activities manipulation by firms prior to their debt issuances and how such manipulation activities affect bond yield spreads. We find that bond-issuing firms increase their real activities manipulation in the five quarters leading to a bond issuance. We document an inverse association between yield spread and pre-issue real activities manipulation,i.e., firms engaged in abnormally high levels of real activities manipulation are associated with subsequent lower cost of debt.

This article analyses the impact of ownership structure features and institutional settings on real activities manipulation. The analysis is based on a sample of listed companies in the underexplored Latin American market for the period of 2004–2016. Panel-data-based G.M.M. System Estimation is used in the empirical analysis. The results confirm that the monitoring role of the majority owner is crucial in mitigating managerial opportunistic behaviour. Here, opportunistic behaviour refers to engaging in real activities manipulation that reduces the informative content of financial statements. However, analysis of insider ownership revealed that managers had a negative impact on transparency. We observed that as insider ownership increases, managers engage more actively in real earnings management. We also find that the institutional ownership and the quality of the regulatory system proved to be effective mechanisms in reducing real activities manipulation.