arXiv subjects

Jaime Ortiz

Publications and source records attributed to Jaime Ortiz.

4 recordsLinked to original sources

arXiv2026

Energy Market and Carbon Emission Spillovers in Critical Minerals Investment: A Dynamic Connectedness Approach

Design/methodology/approach A time-varying parameter vector autoregression (TVP-VAR) model is employed to quantify dynamic connectedness and directional volatility spillovers using daily data from May 1, 2013, to May 2, 2023. The study isolates the impact of extreme events by splitting the data into pre- and post-COVID-19 samples based on the February 2020 stock market crash. Purpose This paper examines the daily financial risk spillovers associated with investing in critical minerals. It examines the dynamic interconnectedness between seven critical mineral Exchange-Traded Fund (ETF) portfolios and key economic-wide variables, including the energy market, carbon emissions, market sentiment, and global infrastructure. Findings Portfolios with high Environmental, Social, and Governance (ESG) scores significantly contribute to shock spillovers. Net directional connectedness analysis reveals that West Texas Intermediate (WTI) crude oil and carbon emission futures consistently act as "net receivers," absorbing volatility from the system. Conversely, Cobalt and Aluminum ETFs primarily act as "net givers," transmitting volatility. The pandemic caused significant structural shifts in these transmission roles. Practical implications The identification of specific net givers and receivers provides actionable insights for investors, facilitating better hedging strategies against time-varying structural breaks and broader economic shocks. Originality This study uniquely utilizes financial ETF data rather than physical mineral prices to capture accessible investment risks. It is among the first to link ESG scores to the directional role (giver vs. receiver) of critical mineral assets within a broader macro-financial network.

econ.EM↗

arXiv2026

Dynamic Risk in the U.S. Banking System: An Analysis of Sentiment, Policy Shocks, and Spillover Effects

The 2023 U.S. banking crisis propagated not through direct financial linkages but through a high-frequency, information-based contagion channel. This paper moves beyond exploration analysis to test the "too-similar-to-fail" hypothesis, arguing that risk spillovers were driven by perceived similarities in bank business models under acute interest rate pressure. Employing a Time-Varying Parameter Vector Autoregression (TVP-VAR) model with 30-day rolling windows, a method uniquely suited for capturing the rapid network shifts inherent in a panic, we analyze daily stock returns for the four failed institutions and a systematically selected peer group of surviving banks vulnerable to the same risks from March 18, 2022, to March 15, 2023. Our results provide strong evidence for this contagion channel: total system connectedness surged dramatically during the crisis peak, and we identify SIVB, FRC, and WAL as primary net transmitters of risk while their perceived peers became significant net receivers, a key dynamic indicator of systemic vulnerability that cannot be captured by asset-by-asset analysis. We further demonstrate that these spillovers were significantly amplified by market sentiment (as measured by the VIX) and economic policy uncertainty (EPU). By providing a clear conceptual framework and robust empirical validation, our findings confirm the persistence of systemic risks within the banking network and highlight the importance of real-time monitoring in strengthening financial stability.

econ.EM↗

arXiv2024

Robust Optimal Contribution Selection

Optimal contribution selection (OCS) is a selective breeding method that manages the conversion of genetic variation into genetic gain to facilitate short-term competitiveness and long-term sustainability in breeding programmes. Traditional approaches to OCS do not account for uncertainty in input data, which is always present and challenges optimization and practical decision making. Here we use concepts from robust optimization to derive a robust OCS problem and develop two ways to solve the problem using either conic optimization or sequential quadratic programming. We have developed the open-source Python package 'robustocs' that leverages the Gurobi and HiGHS solvers to carry out these methods. Our testing shows favourable performance when solving the robust OCS problem using sequential quadratic programming and the HiGHS solver.

math.OC↗

arXiv2024

Will Southeast Asia be the next global manufacturing hub? A multiway cointegration, causality, and dynamic connectedness analyses on factors influencing offshore decisions

The COVID-19 pandemic has compelled multinational corporations to diversify their global supply chain risk and to relocate their factories to Southeast Asian countries beyond China. Such recent phenomena provide a good opportunity to understand the factors that influenced offshore decisions in the last two decades. We propose a new conceptual framework based on econometric approaches to examine the relationships between these factors. Firstly, the Vector Auto Regression (VAR) for multi-way cointegration analysis by a Johansen test as well as the embedding Granger causality analysis to examine offshore decisions--innovation, technology readiness, infrastructure, foreign direct investment (FDI), and intermediate imports. Secondly, a Quantile Vector Autoregressive (QVAR) model is used to assess the dynamic connectedness among Southeast Asian countries based on the offshore factors. This study explores a system-wide experiment to evaluate the spillover effects of offshore decisions. It reports a comprehensive analysis using time-series data collected from the World Bank. The results of the cointegration, causality, and dynamic connectedness analyses show that a subset of Southeast Asian countries have spillover effects on each other. These countries present a multi-way cointegration and dynamic connectedness relationship. The study contributes to policymaking by providing a data-driven innovative approach through a new conceptual framework.

econ.GN↗