Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a field of mathematics that explicitly and quantitatively analyzes multiple conflicting criteria in decision-making.
Often in both our daily lives and options trading, we experience multiple conflicting criteria that need to be balanced in order to make informed, logical decisions.
From an options trading point of view, the most classic examples are risk vs. reward. However, these criteria are conflicting, as the trader is rewarded for the risk they take on. Finding the optimal trade-off between these two criteria is one of the most important factors in determining the trader's success.
Another example in options trading is the tradeoff between high theta decay vs. gamma risk on the position. A premium seller would be interested in maximizing the daily theta decay but experience increased gamma risk as theta decay increases.
MCDM can be applied more broadly, beyond the field of finance. For example, purchasing a car also has conflicting criteria. Cost, comfort, safety, and fuel economy may be some of the main criteria for evaluation. It would be very unusual that the cheapest car is the most comfortable and the safest one.
While we weigh multiple criteria implicitly in our daily life, we are often comfortable with the consequences of such decisions that are made based solely on intuition (an emotional decision at the core). On the other hand, when stakes are high, such as managing a large personal investment portfolio, a more structured approach is warranted.
Structuring complex problems well and considering multiple criteria explicitly leads to optimized decisions with the best blend of conflicting criteria.
The field has been around since the early 1960s with a myriad of approaches and methods. Machine learning in recent years has improved the accuracy and scope of what can be calculated. OptionAutomator applies a proprietary method to the Brutus Option Ranker, vetted by options traders, Ph.D. in Mathematics, and Data Scientists. Combined with visual tools to systematically set up a personalized options strategy, MCDM and machine learning can finally be applied to the options trading world to deliver ranked traded vs. an unsorted list of trades found in conventional options screeners.