The relationship between agricultural commodities and stock market in case of Thailand: safe-haven, hedge, or diversifier?: cross-quantilogram analysis

This paper proposes to identify Agricultural futures’ roles (Safe-haven, Hedge, and Diversifier) in the Thai stock market during 2000-2020 by applying a bivariate Cross-Quantilogram (CQ) approach. The CQ approach can examine the cross-quantile correlation between assets, while the traditional approaches (such as GARCH, DCC, and MSV) examine only mean-to-mean dependency structures. The CQ methodology can estimate the tail dependencies and directional predictability between financial assets with greater accuracy than traditional methods since financial assets typically have a skewed and asymmetric distribution. The correlation between assets during the extreme market condition (tail dependencies) is important to classify a financial asset as a Safe-haven role. The agricultural commodities considered in this study are the most active asset categories in the markets (cereals, oilseeds, other soft commodities, and miscellaneous commodities). The results show that the agricultural assets are shown to be more explicitly correlated with the Thai stock market in crisis periods such as a negative result in canola during COVID-19. Agricultural commodities including wheat, oats, and canola can play a strong safe-haven role in the Thai stock market, according to the lowest cross-quantiles (bearish market) data. According to the results of overall quantiles (normal situations), wheat, corn, canola, soybean, and sugar can all be used as hedges. The rolling windows for directional predictability, which show the time-varying Cross-quantilogram, confirm the findings that these agricultural commodities can be served as Safe-havens throughout the periods of study. Therefore, including these specific agricultural commodities (Safe-haven or Hedge) in a portfolio of Thai stocks will help lower risk and boost performance both under normal and extreme downturn situations.

本文采用双变量交叉分位数图（Cross-Quantilogram，CQ）方法，旨在识别2000-2020年期间农业期货在泰国股票市场中的三类角色：避险资产、对冲工具与分散投资标的。交叉分位数图方法可检验不同资产间的跨分位数相关性，而传统计量方法（如GARCH、DCC及MSV）仅能考察均值-均值的相依结构。由于金融资产通常呈现偏态与非对称分布，相较于传统方法，交叉分位数图方法论能够更精准地估计金融资产间的尾部相依性与方向可预测性。在极端市场环境下的资产相关性（即尾部相依性），是将金融资产归类为避险角色的核心依据。本研究纳入的农业大宗商品均为市场交易最为活跃的品类，包括谷物、油籽、其他软商品及杂项大宗商品。研究结果表明，在危机时期（如新冠肺炎疫情期间），农业资产与泰国股票市场的相关性更为显著，例如油菜籽在疫情期间呈现负相关表现。基于最低跨分位数对应的熊市行情数据，小麦、燕麦及油菜籽可在泰国股票市场中发挥强劲的避险资产作用。基于总体分位数对应的正常市场环境结果，小麦、玉米、油菜籽、大豆及白糖均可作为对冲工具。用于检验方向可预测性的滚动窗口分析（可展示时变交叉分位数图）验证了上述结论：在本研究的样本期内，这些农业大宗商品均可作为避险资产。因此，在泰国股票投资组合中纳入这些具备避险或对冲属性的特定农业大宗商品，将有助于在正常市场及极端下行行情中降低组合风险、提升投资绩效。

搜集汇总

背景与挑战

背景概述

该数据集是一篇2021年发布的学术论文，研究泰国农业期货与股票市场的关系。它使用交叉分位数图方法，分析2000-2020年期间农产品（如小麦、燕麦和油菜籽）在泰国股市中的角色，发现部分农产品可作为安全港或对冲工具，以降低投资组合风险。