Predicting the Stock Price using Historical Price, Volatility and Downside Risks

This is the authors' abstract. We don't add key points for this paper.

This study examines and analyses the influence of historical stock prices, volatility risk, and downside risk on stock prices in the rapidly growing Infrastructure sector on the Indonesian Stock Exchange (IDX) from 2014 to 2022. Using a nine-year dataset, we integrated standard deviation and Ulcer Index as volatility and downside risk measures, respectively, employing Structural Equation Modeling (SEM). Results show a significant positive effect of historical stock prices on future prices in this dynamic market. However, this positive trend is counteracted by the negative effect of volatility risk on stock prices, emphasising the importance of risk management strategies in the Infrastructure sector. We have also identified a positive effect for historical volatility risk (t) on future volatility risk (t+1), indicating a potential connection between past and future market volatility. Also, downside risk is established as a negative effect on stock prices, emphasising risk mitigation in historical stock performance. In addition to indirect effects, we found that historical stock price (t) plays a mediating role, affirming the influence of downside risk (t) on future stock price (t+1). This research provides valuable insights into predicting future stock prices, offering a comprehensive understanding of the interplay among historical performance, volatility, and downside risk. These findings contribute to developing effective strategies for investors and policymakers to navigate the complexities of the stock market.