Modeling a system for managing options

By Raul Tortima on

There is no doubt about the importance of technology in the world of finance. In some cases, the lack of automated controls makes it impossible to implement the operation, such as the setting up of strategies with options, in particular those that every investor should at least know: covered calls and the sale of puts. Both are used as a hedge or to increase the overall return of the stock portfolio and, despite the aforementioned control, these are operations which are easy to understand.

As the saying goes “without control and measurement, there is no management”, it is paramount to monitor constantly, through measurements of some of the indicators involved in the mentioned operations. From some information (strike, option price, underlying asset price), it is possible to extract the necessary indicators for these measurements: Moneyness, Yield.

In some cases, whether due to lack of liquidity, to approaching maturity or by distancing moneyness, the option price does not present a reference. These situations can be disastrous for the investor who wants to clear a position, whether long or short.

A possible solution, less professional, is the presentation of orders according to some parameter of step over strikes with known prices. Another solution is to use the Black & Scholes model, which calculates a “fair” call or put price, based on data parameters (maturity, interest, underlying asset price, option volatility). This functionality should therefore be part of the options management system, being able to receive a given volatility, or to calculate it.

Considering that the use of covered calls is for optimizing and improving the return of the stock portfolio, it is assumed that there is no interest in getting rid of the asset. In this sense, monitoring the moneyness is essential to avoid an unwanted position exercise. On the opposite side, the sale of puts, moneyness represents the distancing of a possible unwanted purchase.

One way or another, moneyness is centerpiece from the beginning until clearing the whole position. In parallel, the maximum drop indicates the limit for the break-even, considering the premium paid / received, as of when the open operation starts to have a nominal loss. Last, but not least, the yield indicates the potential gain in case of exercise of the option. Some models could also consider the non-exercise situation, showing the yield as the return over the required margin to open the position.

A fundamental monitoring for these types of operations is a discovery system, based on the parameters mentioned above (strike, yield, moneyness, among others), whether isolated or in combination. Such subsystem would display all opportunities for entering a long or short position, ordered by a selected filter.

A parameter which could be added is volatility (vol), as a way of inferring the actual chance of having the current price to reach the strike. Although historical vol can be used, ideally it should be filtered and shown the implicit vol, derived from the same model of Black & Scholes quoted above, since it is inferred from what the market judges as the level of current volatility from the market prices.

Simulated scenarios should be covered in case of exercise, repurchase and rollover (up / down and forward), as well as the situation of non-exercise. For the exercise case, it is interesting to detail the gain / loss on the zeroing of the underlying, separate from the gain / loss obtained with the option. The repurchase and rollover can be shown in a separate section, taking into account all the “up / down” rollover scenarios, respectively, and “forward”. For estimated gain / loss situations, an opportunity cost analysis could be aggregated by comparing it with benchmarks, over the same period as to the life of the option.

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