GOLD PRICESFORECASTING USING TRIPLE EXPONENTIAL METHOD

Governments, organizations, and citizens have taken an interest in gold price fluctuations. Gold price forecasting that is accurate may effectively capture price shift tendencies and reduce the effects of gold market volatility. However, due to the multi-factor and nonlinear nature of the gold market. The triple exponential smoothing strategy is used in this study to predict the rise in a value over time since it can replicate trends and seasonal patterns. according to the gold price swings pattern and seasonal components at the same time To calculate system accuracy, the Mean Absolute Percentage Error is employed (MAPE). With alpha 0.15 and beta 0.85 as parameter values, the triple exponential smoothing (TES) approach achieves an accuracy rate of 86.93 percent and a MAPE of 12.49 percent in this study.

Impact persistence of stock market risks in commodity markets: Evidence from China

The risk spillover among financial markets has been noticeably investigated in a burgeoning number of literature. Given those doctrines, we scrutinize the impact persistence of volatility spillover and illiquidity spillover of Chinese commodity markets in this paper. Based on the sample from 2010 to 2020, we reveal that there is a cross-market spillover of volatility and illiquidity in China and also, interactions between volatility and illiquidity in different financial markets are pronounced. More importantly, we demonstrate that different commodity markets have different responsiveness to stock market shocks, which embeds their market characteristics. Specifically, we discover that the majority of the traders in gold market might be hedger and therefore gold market is more sensitive to stock market illiquidity shock and thus the shock impact in persistent. On the other hand, agricultural markets like corn and soybean markets might be dominated by investors and thus those markets respond to the stock market volatility shocks and the shock impact in persistent over 10 periods given the first period of risk shock happening. In fact, different Chinese commodity markets’ responsiveness towards Chinese stock market risk shocks indicates the stock market risk impact persistence in Chinese commodity markets. This result can help policymakers to understand the policy propagation effect according to this risk spillover channel and risk impact persistence mechanism in China.

Stock market flexibility during COVID-19 pandemic: evidence from Pakistan

PurposeThe authors examine the impact of coronavirus disease 2019 (COVID-19) pandemic on the stock market, forex market and gold market of Pakistan.Design/methodology/approachBy using the daily data of COVID-19 confirmed cases, stock index, foreign currency rates and gold prices for the period 10 March 2020 to 16 October 2020, the authors explore that the stock index negatively responds to the corona pandemic.FindingsAdditionally, the authors observe the price hikes in gold and foreign currency corresponding to the number of COVID-19 positive cases.Practical implicationsThe study analysis unveils that the stock market adversely responds to a pandemic, whereas, forex and gold markets serve as a safe haven for investors at the time of financial distress.Originality/valueThis study complements the literature and provides empirical evidence of the stock market, the gold market and foreign currency market, in the perspective of Pakistan.

Market Backwardation and The Theory of Storage: An Empirical Investigation of Indian Gold Futures Markets

The backwardation and contango in the futures markets are explained by two popular theories, namely the theory of storage and the theory of risk premium. The investment assets tend to follow the theory of risk premium, whereas the consumption assets are likely to follow the theory of storage. As India is the largest importer of gold, and gold is used for consumption purposes (mostly by jewellers, who store gold as a consumption commodity), we empirically test whether backwardation in the gold market is explained by the theory of storage. We use the indirect test of the theory of storage developed by Fama and French (1988 , Journal of Finance, Vol. 4, p. 1075), calculate the interest adjusted basis (IAB) and test the implications of the theory of storage. We also use two asymmetric models of the Generalized Autoregressive Conditional Heteroscedastic (GARCH) family to understand the asymmetric volatility of IAB. We find that the Indian gold futures markets partially follow the theory of storage; however, we do not find any support of asymmetric behaviour of IAB in the contango and backwardation markets. Our results suggest that in the context of the Indian gold market, keeping inventory has minimal benefits, and gold behaves more like an investment asset.

The Comparison between ARIMA and ARFIMA Model to Forecast Kijang Emas (Gold) Prices in Malaysia using MAE, RMSE and MAPE

Gold is known as the most valuable commodity in the world because it is a universal currency recognized by every single bank across the globe. Thus, many people were interested in investing gold since gold market was always steadier compared to other investment (Khamis and Awang, 2020). However, the credibility of gold was questionable due to the changes in gold prices caused by a variety of circumstances (Henriksen, 2018). Hence, information on the inflation of gold prices were needed to understand the trend in order to plan for the future in accordance with international gold price standards. The aim of this study was to identify the trend of Kijang Emas monthly average prices in Malaysia from the year 2010 to 2021, to determine the best fit time series model for Kijang Emas prices in Malaysia and using univariate time series models to forecast Kijang Emas prices in Malaysia. The ARIMA and ARFIMA models were used in this study to model and forecast the prices of gold (Kijang Emas) in Malaysia. Each of the actual monthly Kijang Emas prices for 2021 were found to be within the 95% predicted intervals for both the ARIMA and ARFIMA models. The performances for each model were checked by considering the values of MAE, RMSE and MAPE. From the findings, all the MAE, RMSE and MAPE values showed that the ARFIMA model emerged as the better model in forecasting the Kijang Emas prices in Malaysia compared to the ARIMA model.