You're paying $48 for a SaaS plan someone else gets for $29.
Same plan. Same features. Just a better deal you didn't know existed.
So I built https://t.co/U4lqcCKdVZ: every SaaS deal worth grabbing, in one place. 🎟️
Launching now
Buying SaaS is easy. Finding the best deal isn’t.
Discounts, referral offers, coupons and affiliate deals are scattered across the web. I’m building a simple way to find the deal before you subscribe—and track savings across your SaaS stack.
@kirubaakaran This resonates — once a tool starts firing more trades, cost drag becomes the real risk, not just signal quality. Built a calculator to show exactly how much brokerage+STT+GST erode an account at scale:
https://t.co/oXPishJwxh
"Same price = no loss," a friend argued about scalping.
Wrong. Your sell price needs to be HIGHER than buy just to break even. Flat isn't neutral, it's already a loss.
771 trades wiped ₹50,000 — zero bad calls, just fees.
Built a calculator to prove it:
https://t.co/oXPishJwxh
@romanbuildsaas@marclou Wow, impressive! 🔥 Congratulations on the success.
TrustMRR is really useful — honestly, one of the best ways to showcase and show off your SaaS journey. 😄🚀
Wishing you even more success!
@marclou I’m new to the micro-SaaS world, and I genuinely love the way you’re building. It motivates me to start building too.
TrustMRR rocks! 🚀
Wishing you great health and continued success. 🙏
@SriniVega I have attended it. Still following it.But everyone can’t make money by following because MTM swing and long term option pyshco won’t set for everyone. Need different mindset
Final Thought:
Backtesting isn't about predicting the future.
It's about stress-testing your logic.
Your job isn't to build the best curve —
It's to build a strategy that survives reality.
Backtesting is a dopamine machine.
You write a script. Run it.
Chart goes up. Sharpe is 2.5+.
You think you're the next Renaissance Technologies.
Then you go live — boom.
Drawdowns. Slippage. Whiplash.
Here’s why:
✅ Before going live:
• Simulated slippage & fees?
• Validated across time periods?
• Used point-in-time data?
• Avoided perfect tuning?
• Used realistic capital/order sizes?