You can develop auto-trading models with 10th grade math. The less complex your systems, the better off you'll be.
Learning quant trading takes an enormous amount of time if you do not have a substantial math background. Furthermore most of the quant finance books assume the readers atleast understands basic linear algebra, advanced calculus, real analysis, calc. based probability, ect. Learning the language of mathematics and then also learning programming is a very time consuming endevour. Most people learn these skills at the University and then venture out into the quant world because that is what they are most familiar with. If you are not mathematically inclined already, odds are you are going to give up before you learn the necessary knowledge to become competent at being a quant, or atleast building profitable quantitative trading models. Your time would most likely be better spend perfecting the strategies your already familiar with. Many people believe quant strategies are superior because they appear on the surface to be very rigorous. They're not. In order to apply mathematics to markets (and by extension people) you have to assume things about people's behavior in the future. Mathematics is developed in the universe of certainty. People, however, are uncertain. They are uncertain about what they are going to wear to work, what they are going to eat for dinner, where they are going to go to vacation, ect. As a result, at best mathematics can provide its users in the world of trading a very good estimatio of what might occur, but it is never going to be an absolute. At worst though, mathematics can use its rigour to fool its user into believing that he/she is onto something big when in fact they are not in the right ball park. So how is this different from any other form of trading? Its not. Quant strategies are just another form of trading. It ultimately comes down to the ability of the person using the strategy.
Thank you for your thoughtful replies. I apologize for my slow response as I had to think about what I'm actually trying to accomplish. What I'm trying to do is move from feeling and eyeballing, which is what I do with discretionary trading, to trying to build models for algorithmic trading, as I can't model the instinct that drives my manual trading. For example, I want to build a Market Making model. I know conceptually how I want to go about doing this, but I don't have the mathematical tools to describe or investigate what I'm trying to exploit. I want to keep a running average of how many steps it takes a certain security to move from one price to another within each minute of the trading session, then post my bids and asks depending on how today's trading is going compared to this average. I have no idea how to begin quantifying this.
"This is your last chance. After this, there is no turning back. You take the blue pill -- the story ends, you wake up in your bed and believe whatever you want to believe. You take the red pill -- you stay in Wonderland and I show you how deep the rabbit-hole goes." - welcome!
When you talk about "steps" keep in mind that you are dealing with lots of things that change: size of the price changes and frequency of trades etc. I would try to generalize things into the standard volatility measurements used in option pricing, like you find on Yahoo Finance under the statistics for a stock. I think there are some things you can learn using excel that are very quant-like. Excel is something of an equalizer because, once you take some stochastic process, discretize it, generate appropriate random stuff to feed it, monte carlo it, "calibrate" it, you will start to see those sexy looking formulas laid bare and naked in sequences of cells.