The Case for Designing Custom Entry Signals
Designing your own entry signal begins with a clear concept. Rather than adopting a popular indicator wholesale, the process involves identifying an underlying idea—often borrowed from another field—and translating it into market terms. The source notes describe this as starting from a widely accepted notion among traders and investors, then extending it into a more general framework. The example used throughout is a physics-based model of motion, which is explicitly presented as an illustration rather than a validated system. The author notes the idea is untested but serves to demonstrate how a concept can be built. A custom entry signal is not simply a random combination of indicators. It should rest on a logical premise about why prices move in a certain way. For instance, the physics analogy assumes that objects in motion tend to stay in motion unless acted upon by an external force. In markets, this translates to the idea that a market moving quickly in one direction is more likely to continue in that direction than to reverse abruptly. The value of the exercise lies in articulating the premise, identifying measurable variables, and then defining the conditions under which an entry might be considered. This approach encourages traders to think in terms of probabilities and risk, rather than certainties. The goal is not to predict the future with precision but to find repeatable situations where the odds may favor a particular outcome. The source emphasizes that the specific example is just a starting point; the real work is in refining the concept and testing it rigorously.
The Physics Analogy: Direction, Speed, and Acceleration
The analogy begins with a car in a very large parking lot. You do not know where the car is going, but you can observe where it has been. You can measure its direction, its speed (or rate), its change in speed (acceleration or deceleration), and its momentum. With this information, under certain conditions, you can form a reasonable expectation about the car's near-term behavior. The objective is to identify when the car is likely to continue moving quickly in the same direction for as long as possible. A key insight is that a car moving in a particular direction is more likely to continue in that direction than to change direction. It may turn, but continuation is the more probable outcome. The more you know about its speed, the rate of change of speed, and its momentum, the better you can assess when continuation is most likely. To change direction, a car generally must slow down. Therefore, if a car is moving fast, it is more likely to keep moving fast in the same direction than to reverse. Speed and acceleration provide probabilistic clues. The analogy is not perfect, but it offers a structured way to think about market movement. It suggests that the rate of price change and changes in that rate could contain information about future price movement. The source uses this analogy to propose that similar principles might apply to financial markets, while acknowledging that the translation is not exact.
