Electricity price forecasting is a mature research area, with various techniques already developed in recent years to help both generators and retailers hedge against price and load associated risks. This paper aims to add on to the forecasting literature, with emphasis on the importance of making such forecasts transparent to facilitate countries' transitions towards more liberalised retail electricity markets. We conduct univariate forecasting of Singapore's weekly wholesale electricity prices with the Autoregressive Integrated Moving Average (ARIMA) models, complimented with the use of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models and their variants to account for volatility. Results show that our models reasonably emulate the price trends based on out of sample forecasts. The magnitude of expected future weekly price spikes may be estimated to a reasonable extent based on historical price outages, determined exogenously in the model. These forecasts can thus serve as possible references to retail players in a competitive market for all parties to make more informed decisions before participating in the open market. This is especially important for smaller consumers of electricity who are typically last to be exposed to retail choices. Adequate knowledge of prices will be necessary to increase desired switching rates.