Obligatory First Post

I'm Jason Victor. I recently graduated from my alma mater in '09  (hence the handle "Jason Victor Dartmouth") where I studied computer science. I am generally enthused by mathematics and work in or around the financial markets.

But let me start a little farther back. I started programming when I was six. By about sixteen, I had figured out the craft of programming, as it were, and began searching for a more specific interest. I found it in what was then called "artificial intelligence." Now, I call it "machine learning." But no matter. More on that later.

Anyway, I was poor, since I was a kid, and I needed free data. And one source I found was financial data -- it's abundant, it's confusing, and it provides an interesting way to test statistical techniques. Little did I know that would lead me down a much more interesting path than even I had anticipated.

To my more academic readers, please don't immediately disregard my thoughts regarding finance. It's really a fascinating field. I find a lot of similarities between finance and physics -- in practice, both involve stretching current computational and mathematical boundaries, and in theory, there's so much conflict and argument that it's abundantly clear it really hasn't been figured out yet. Just as physicists come up with theories for different pieces of physics that inherently conflict with others, grappling tirelessly for the elusive Theory of Everything, the theory of finance is equally wrought with disturbing half-truths, unrealistic assumptions, and conflicting ideologies. It's poorly understood, at best. For those with a quantitative inclination and a trailblazing ideology, the financial markets are a literal paradise.

In the following pages, I plan to record my thoughts about these wonderfully interesting subjects. And I want to accomplish a couple different things.

For one, as someone that started programming at a young age and had to teach myself for most of my life, I feel for those in the same situation. I want to document everything I wish I had access to when I was learning; I want to chart a clearer course for those looking to learn how to hack beautifully.

I want to create something similar for those looking to understand quantitative finance. That is a particularly difficult thing to get your head around. Most start with either an ill-conceived plan to make millions or a meek interest in building a career around it -- and frankly, I don't hold it against either group. But, the world around us, for some reason, does make it a pain to learn.

Here's why. There are two parts to what I will from now on call "quantness":

1. The parts that have to do with making money
2. The parts that don't have to do with making money

The second category of concepts is obviously much easier to learn, because people are willing to teach you. But it's less clear to the unsuspecting novice why in the world these concepts are useful. What are they used for? Why are they writing this? Do I really need to know this?

Really, it would be easier to start off by learning about quantitative investment strategies. But, alas, those are a whole lot harder to get anyone to explain to you. If a strategy works, the last thing anyone is going to do would be tell you about it.

So, I will try to make what little order I can of the madness that is computer science, math and quant finance. I'm no professor, and I'm certainly not an expert in anything -- but, I have managed to get my head around these concepts just enough to truly fall in love with them, and I want to help others to do the same.

All the best,

Jason Victor