Financial Risk Analysis of top semi-conductor industries using OGARCH model - Closeread Prize

Financial Risk Analysis of top semi-conductor industries using OGARCH model

Authors: Erika Oghenemaro Atoma


Read the closeread article: https://erica-prog.github.io/
Reproducible repo: GitHub - erica-prog/erica-prog.github.io: Scrollytelling with Quarto- Financial Risk Analysis of Semi-conductor industries


Abstract

This article attempts a concise financial risk analysis of top semiconductor industry stocks, leveraging unique models such as the multivariate OGARCH model, Value-at-Risk (VaR) and volatility metrics, powered by Yahoo finance data. The article also explores critical factors influencing investment decisions, emphasizing the importance of accounting for unseen volatility events. This article provides readers with an understanding of how these fluctuations impact stock performance and understand that volatility is essential for making informed investment choices in this sector.

Full Description

The following stocks are examined in a stock portfolio: Qualcomm (QCOM), Broadcom Inc. (AVGO), Micron Technology, Inc. (MU), Texas Instruments Incorporated (TXN), Advanced Micro Devices, Inc. (AMD), and NVIDIA Corporation (NVDA). The historical daily returns are log-transformed for each stock and analyzed to identify periods of varying volatility sizes during the sampled period (January 1, 2014, to December 31, 2023). The multivariate orthogonal GARCH (O-GARCH) model is applied using principal component factors to identify key drivers affecting these components and compute a conditional variance matrix for each period.

Additionally, a 1% value-at-risk model (VaR) model is calculated to examine the long position of $1 million on the stock portfolio for the next trading day. The reliability of the VaR model is further assessed using a backtesting framework to validate its effectiveness in forecasting risks.