Random State Machine Strategy

📌 Random State Machine Strategy (Educational)
This strategy showcases a randomized entry model driven by a finite state machine, integrated with user-defined exit controls and a full-featured moving average filter.

🧠 Trade Entry Logic
Entries occur only when:

A random trigger occurs (~5% probability per bar)

The state machine accepts a new transition (sm.step())

Price is:

Above the selected MA for long entries

Below the selected MA for short entries

This ensures that entries are both stochastically driven and trend-aligned, avoiding frequent or arbitrary trades.

⚙️ How It Works
Randomized Triggers
A pseudo-random generator (seeded with time and volume) attempts to trigger state transitions.

Finite State Machine
Transitions are managed using the StateMachine from robbatt/lib_statemachine — credit to robbatt for the modular FSM design.

Controlled Reset
The state machine resets every N bars (default: 100) if at least two transitions have occurred. This prevents stale or locked states.

Backtest Range
Define a specific test window using Start and End Date inputs.

Risk & Exits
Specify risk in points and a target risk/reward ratio. TP is auto-computed. Timed and MA-based exits can be toggled.

🧪 How to Use
Enable Long or Short trades

Choose your Moving Average type and length

Set Risk per trade and R/R ratio

Toggle TP/SL, timed exit, or MA cross exit

Adjust the State Reset Interval to suit your signal frequency

📘 Notes
Educational use only — not financial advice

Random logic is used to model structure, not predict movement

Thanks to robbatt for the lib_statemachine integration