TY - JOUR T1 - Price Change, Volatility, and Accurate VaR: <em>Evidence from the NSW and QLD Power Markets</em> JF - The Journal of Alternative Investments SP - 82 LP - 95 DO - 10.3905/jai.2018.20.4.082 VL - 20 IS - 4 AU - Rangga Handika AU - Yusuf Khudri Y1 - 2018/03/31 UR - https://pm-research.com/content/20/4/82.abstract N2 - This article investigates the relationship among price changes, volatility forecasts, and accurate Value-at-Risk (VaR) estimates in power markets. The authors use various GARCH(p,q) methods to model daily volatility and estimate VaR in New South Wales (NSW) and Queensland (QLD) regions. Then, they explore the relationship among price changes, and volatility forecasts and accurate VaRs for both generator and retailer sides, at 99 percent, 95 percent and 90 percent VaR confidence levels in six different out-of-sample periods. They find that forecasted volatility and accurate VaR variables tend to be statistically significant in explaining variations in power price changes. They also find that the coefficients of forecasted volatility tend to be negative. This indicates that higher forecasted volatility predicts negative price changes. Therefore, market participants in power markets, either generator or retailer, should expect a negative price change when their volatility forecast is high. Furthermore, the authors find that accurate VaR tends to lead to a decrease in price changes. This implies that well-functioning market risk management explains an unfavorable price change for the generator, but a favorable price change for the retailer in the Australian power markets.TOPICS: Commodities, developed, VAR and use of alternative risk measures of trading risk, statistical methods ER -