Shane's advice is good. I think it's worth adding the following two techniques not already mentioned:
Self-Organizing Maps (SOMs)
Seriation (pdf pertaining to R package
seriation, but great intro to the topic).
They are not explicit visualize techniques, per se. Instead, they are algos that transform underlying data in ways that aim to lead to greater/new insight on the underlying data. Thus, in my mind, the above approaches share the common objective with xy plots, contour plots, scatter-plot matrices, heat maps, etc.
For strict quantitative visualization, Tufte, as mentioned above, a great place to start. Personally, I've gotten more out of Wong's, "The Wall Street Journal Guide to Information Graphics" and Janert's "Data Analysis with Open Source Tools". However, keep in mind that each have different audiences and objectives in mind.
I also believe Processing (mentioned by Shane) has a very bright future in finance - it's been used heavily by multimedia artists primarily because of its relative ease and great flexibility.