Traffic models play an important role in network simulation and performance analysis. This paper presents a frame-level hybrid framework for modeling variable bitrate (VBR) video traffic. To accurately capture long-range dependent (LRD) and short-range dependent (SRD) properties of video traffic, we incorporate elements of wavelet-domain analysis into classical time-domain modeling found in prior work. However, unlike previous studies, we analyze and successfully model both inter-GOP and intra-GOP correlation. Through the use of QQ plots and leaky-bucket simulations, we evaluate the accuracy of our approach and demonstrate that the autocorrelation function and the frame-size distribution of synthetic traffic match those of the original traffic very well. The leaky-bucket simulation also demonstrates that our model effectively preserves the temporal burstiness of the original video and can be used to predict buffer overflow probabilities and network packet loss.