I was working on a quantitative skills lesson for our decision-making course for Army officers.
Here are 10 decision rules and how they can apply to the development and operation of a trading system:
Regret Theory: A trading system could use regret theory to evaluate the performance of different investment strategies based on the difference between the actual returns and the best possible returns. This could help identify which strategies are most effective and which should be avoided.
Bounded Rationality: A trading system could use bounded rationality to develop a set of criteria for selecting investments that take into account the available information, time, and cognitive resources. This could help ensure that the system is making rational decisions within its limitations.
Weighted Average: A trading system could use a weighted average to evaluate the potential returns and risks of different investments based on their relative importance. This could help prioritize investments that are most likely to generate the desired returns.
Randomized: A trading system could use a randomized approach to select investments based on a probability distribution. This could help ensure that the system is not overly biased towards certain types of investments.
Sunk Cost Fallacy: A trading system could avoid the sunk cost fallacy by making investment decisions based on current market conditions rather than past investments. This could help prevent the system from continuing to invest in a course of action that is no longer rational.
Availability Heuristic: A trading system could avoid the availability heuristic by basing investment decisions on objective data rather than relying on what is most easily recalled from memory. This could help prevent the system from making biased or irrational decisions.
Anchoring and Adjustment Heuristic: A trading system could use the anchoring and adjustment heuristic to adjust investment decisions based on a reference point, such as a benchmark index. This could help ensure that the system is making decisions that are consistent with its goals and objectives.
Prospect Theory: A trading system could use prospect theory to evaluate investments based on the perceived gains and losses relative to a reference point, rather than the absolute value. This could help the system avoid making overly risky or conservative investments.
Intuition: A trading system could use intuition to make investment decisions based on the experience and expertise of its designers and operators. This could help the system identify opportunities and risks that may not be immediately apparent from quantitative analysis.
Inertia: A trading system could use inertia to maintain a stable portfolio of investments over time, rather than constantly changing positions based on short-term market fluctuations. This could help the system maintain a long-term perspective and avoid making impulsive decisions based on market noise or emotional reactions. However, the system should also be periodically reviewed and adjusted as needed to ensure that it remains aligned with the overall investment goals and objectives.
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