# @mehul8797 on Instagram

- **Type:** Image
- **Original URL:** https://www.instagram.com/p/DeW7m3CFlc_
- **Gondola URL:** https://gondola.cc/posts/71685558-mehul8797-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/ac683b0ba3.jpg
- **Posted:** 2026-10-11T15:00:06.000+00:00
- **Account Owner:** Mehul Patel (@mehul8797) — https://gondola.cc/mehul8797

## Caption

Most traders journal every trade. Almost none of them interrogate the journal.

Your last 100 trades already hold the answer to why you’re not consistent. The problem is that most traders read their journal for feelings (“I was impatient today”) instead of measuring patterns.

Here’s the shift: stop looking at P&L in dollars and win rate. Look at expectancy in R, meaning your average result per trade measured in units of risk. A 40% win-rate trader can be very profitable. A 75% win-rate trader can be slowly bleeding out. Win rate alone tells you almost nothing.

This carousel gives you 6 questions to make Claude audit your trades like a quant would:
→ Do you actually have an edge, or is it 3 lucky trades?
→ Which times of day cost you money?
→ What happens to your trading after a loss?
→ Where does your edge decay during the day?
→ Which setups should you stop trading?
→ How do you turn the findings into testable rules?

One important nuance: 100 trades is a starting sample, not proof. Treat every finding as a hypothesis, test new rules forward, and spot-check the AI’s math by hand. The goal isn’t a perfect answer. It’s a testable one.

Save this for your weekend review, and send it to the trader who keeps saying “I just need more discipline.”

Once you know your rules, the next step is taking emotion out of execution. I built my own rules into an algorithm. If you want to see how it works, comment “ALGO” and I’ll send you the details.

#futurestrading #daytrading #algotrading #quanttrading #tradingjournal

## Stats

- **Views:** 0
- **Likes:** 15
- **Shares:** 0
- **Comments:** 0

## Tags

futurestrading, quanttrading, tradingjournal, daytrading, algotrading

---
Copyright (c) Gondola