By: Freddy Guime
Developing a trading application brings challenges in the realm of usability. Traders are very interested in extracting useful information from their trading application; even so, traders will claim to want to see everything at the same time. How do we fix this usability conundrum - where there is a limit on the amount of information that can be understood by the human brain, yet there is a demand to display that and more?
On this particular entry, we explore, á la Jane Goodall style (with apologies to the traders), how options traders behave in their environment and pay attention to how they digest their information and interact (and this is where the analogy diverges) with their trading software.
Giving context to the problem, a small operations (a million dollar fund manager) options trader can in practice manage a portfolio of two to three products, each product may trade up to two years ahead (resulting in 12 to 24 tradeable months), and each month can have between 20 to 100 strike prices. This brings approximately 480 to 7200 possible options instruments; In addition, each option can contain a theoretical price, market price, risk indicators (collectively known as greeks), and position information.
That is a lot of information to handle.
So how does an options trader get their day job done? It mostly consists consists of identifying “market opportunities” and actingon them. The issue here is that the art of identifying these market opportunities is a personal experience, and as such, there are as many ways of identifying opportunities (aforementioned as trading strategies) as there are stars in the sky.
In the basic principle the trading strategy has at least three, not necessarily easy, steps. First is to define what theoretical model to use, which encompasses: volatility curve, mathematical model (black scholes, whaley, binomial tree w/dividends), and assumptions of the underlying future/equity/option, interest rates, carry cost, and others.
Second is to look at the risk tolerance. This is not necessarily a seven point Likert scale, but it encompasses multidimensional risk vectors; so some traders will tend to be more adverse to theta (passing of time) risk, whereas others are more concerned to their delta/directional (market movement) risk. In addition there are other factors such as how much exposure the exchange would allow you to have and what the hedge fund mandate is. All in all, fluctuating risk will change the trading strategies that each trader uses.
The third strategy involves the “crystal ball” predictions and relations between products. Traders will formulate their self-validating theories on how markets behave and will then create a set of rules they follow fairly consistently. Questions like “Are we in a Bear/Bull market?” are assumed, and others like product relationships (how does Gold relate to Oil prices) are expressed in mathematical (for the mathematically inclined trader) or at least biased (for the gut-feeling trader) strategies.
Evolution of Indicators
In the beginning, trading was an activity that involved human interaction and was easy to grasp. Like an auction, a farmer will stand in a podium, offer his product, and see who the highest bidder was. Sold! Next!
Then came new ways to buy and sell products (using papers that allow the claim of ownership or contracts). This made trading more efficient (a farmer didn’t have to stand at the podium with his herd). And it brought opportunity for volume (now there could be many contracts) and for speculation in derivative instruments (I’ll buy it only if the cattle price rises above this threshold).
Not waiting for an invitation academia descended into the trading pit, and started establishing fair value formulas. This ignited the next generation of traders, who don’t own (or want to own) cattle, but instead buy and sell the contracts depending on their view of the market. These are known as speculators.
Trading suddenly got both very abstract and mathematical, and as more people started participating and the exchanges grew to accommodate capacity, trading became “fast”. Because of this, a trader has to be aware and understand all of the risk greeks that are presentedand then make a mental decision on how to execute his trading strategy. Part 2…