# IntrinsicTime

The directional-change operator, the intrinsic-time scaling laws, and the Alpha
Engine coastline trader, implemented in MQL5.

Companion code for the MQL5 article: https://www.mql5.com/en/articles/23814

## What it does

Physical time is an arbitrary clock for a market. Intrinsic time replaces it:
the clock only ticks when price reverses by a fixed threshold, so quiet periods
compress and active ones stretch.

That reframing comes with published scaling laws, which are empirical
regularities relating threshold size to event counts and move lengths. The
article verifies them on live ticks rather than taking them on trust, which is
what `DcOS_ScalingLaws.mq5` is for. If your broker's feed does not reproduce
them, nothing built on top will behave as advertised.

The Alpha Engine is the trading side: coastline trading works the reversals,
scaling into positions as the coastline extends, with liquidity and inventory
management around it. `AlphaEngine.mq5` is the Expert Advisor.

## Layout

```
Include/IntrinsicTime/DcTypes.mqh          directional-change types
Include/IntrinsicTime/DcOperator.mqh       the DC operator
Include/IntrinsicTime/ScalingLaws.mqh      scaling-law measurement
Include/IntrinsicTime/AeTypes.mqh          Alpha Engine types
Include/IntrinsicTime/AeAlphaEngine.mqh    the engine
Include/IntrinsicTime/AeCoastlineTrader.mqh  coastline position logic
Include/IntrinsicTime/AeLimitOrder.mqh     order handling
Include/IntrinsicTime/AeLiquidity.mqh      liquidity model
Include/IntrinsicTime/AeLiveTrader.mqh     live execution layer
Include/IntrinsicTime/AeRunner.mqh         run harness
Experts/IntrinsicTime/AlphaEngine.mq5      the Expert Advisor
Scripts/IntrinsicTime/DcOS_SelfTest.mq5    DC operator checks
Scripts/IntrinsicTime/DcOS_ScalingLaws.mq5 scaling laws on live ticks
Scripts/IntrinsicTime/Ae_SelfTest.mq5      engine checks
Scripts/IntrinsicTime/Ae_RandomWalk.mq5    behaviour on a random walk
```

Run the two self-tests first, then the scaling-law script on your own feed.

## Disclaimer

Educational code. Past behaviour of any model or dataset says nothing about
future results. Test on your own data and broker conditions before drawing
conclusions.