I need your opinions, people. Is 10 lac enough capital. Can you suggest to me some good videos to learn options selling strategies.

I’ve been trying to automate small parts of my Nifty/Bank Nifty option selling setup and realised the hard part is not always the strategy.

The strategy can look clean on paper, but live execution brings weird problems.

For example:

• order shows pending for longer than expected

• hedge leg fills late

• WebSocket reconnects at the worst time

• margin updates are not clear after one leg executes

• position state takes a few seconds to reflect properly

• retry logic becomes dangerous during fast moves

• option chain data feels slightly stale during expiry

Earlier I mostly cared about brokerage, margin, app speed, charts and option chain layout.

Now I’m more interested in boring things like order status consistency, reconnect behaviour, rate limits, sandbox quality, error messages and support that can actually explain edge cases.

I’ve been looking at Nubra trading app for this kind of workflow because it seems more focused on API-based trading setups, but I’m still treating it as something to benchmark properly before trusting it live.

For people here who sell options manually or semi-automate adjustments, what would you check first before letting a script touch real orders?

Order accuracy, WebSocket stability, margin behaviour, Greeks/data quality, or support?

📊 Daily Summary

Metric	Value
Date	18/05/2026
Instrument	Nifty 50 Options (26 May Expiry)
Strategy	Bear Call Spread
Total P&L	-₹1,807.00 (Red)
Capital Used	₹2,50,000
ROI %	-0.72%

📝 Trade Breakdown

Trade #1: 24100 CE (The Short Leg)

• Entry: 10:21 AM @ ₹51.50
• Exit: 11:24 AM @ ₹65.40
• Result: -₹1,807.00 (-13.90 pts)
• Note: Deployed a Bear Call Spread based on the clear morning bearish momentum. However, right after the entry window, the market found a bottom and staged a strong bullish reversal, triggering my mechanical stop-loss.

Hedge Management (24900 CE)

• Entry: 10:17 AM @ ₹5.75
• Exit: 11:25 AM @ ₹5.75
• Result: ₹0.00 (Flat)
• Note: Far OTM protection leg for margin optimization. Closed out perfectly at cost when the short leg was stopped out.

🧠 Analysis & Psychology

• The Setup: The market exhibited strong bearish price action during early trade. I waited out the initial morning chop and positioned a Bear Call Spread using the 26 May monthly expiry for lower volatility sensitivity.
• The Reality: The market pulled a classic morning trap. It looked decidedly weak up until 10:15 AM, but then completely flipped its intraday trajectory and marched upward. The 26 May expiry slowed down the premium spike, but the directional move was strong enough to hit my risk threshold.
• Execution & Discipline: Today marks a major evolution in my trading psychology. I have officially implemented a strict rule: Maximum 1 trade per day. When my SL was hit at 11:24 AM, I didn't look for a recovery trade or double down. I accepted the loss, closed the terminal, and walked away.
• Psychology: Accepting a loss on your single trade of the day takes an immense amount of discipline. The old urge to "get it back" was there, but implementing the one-trade constraint completely eliminates emotional decision-making. A drawdown of just -0.72% is incredibly easy to manage.

📉 Visuals

https://preview.redd.it/wkecrmjyfu1h1.jpg?width=1272&format=pjpg&auto=webp&s=4ec7bfd3b02d0c27aaab548c6af4548e1cd50b09

💡 Key Takeaways

1. The Power of One: Limiting your day to a single trade changes your relationship with losses. It stops a bad morning from spiraling into a catastrophic week.
2. Far Expiry Security: Using the 26 May contracts ensured that even during a sharp 100+ point upside reversal, the premium expansion was steady and mechanical, not violent.
3. Live to Fight Tomorrow: The system worked flawlessly. The risk was contained, the terminal was shut down on time, and my mental capital is completely preserved for tomorrow's setup.

Disclaimer: This is my personal trading journal for educational purposes. Also, the entire post is formatted via Gemini AI, but the trades and psychology are 100% real.

— IAm#Mansis r/IndiaOptionSelling - Join this community.

Hello

Can you please help in reviewing my nifty strangle. I understand upside and downside risk and have a mental adjustment to be made at key levels to this.

Trade

30July sell: 22500CE and 26000PE entered on 5-May-2026

Mechanics

• Manage at 21DTE
• Book 50% profit(~7-7.5K)
• Mental stop loss of max 3x gain(~40K)

As you can see from the picture I have rolled untested side once to 25300 to collect more premium.

Can someone please review this and help me get better at this.

I was able to see 3.8K profit on this within couple of days and didnt booked. Now thinking should there be rule to book 25% profit within 1 week on entering ?

https://preview.redd.it/3babg3u0is1h1.png?width=1514&format=png&auto=webp&s=14c36c9e8aac8a269480469c00825a30e55038e3

One thing I noticed over the years:
A lot of traders can handle losses.
What really affects them is seeing profit vanish.
You’re up nicely.
Everything is fine.
Then market pulls back.
And suddenly:
you exit early
tighten stops too much
keep checking P&L
stop following the original plan
Not because the trade became bad.
Because the mind already started treating that profit as “owned”.
That shift changes behaviour fast.
Took me years to recognise how much open profit affects decision making.

I’ve started judging broker APIs very differently after trying to automate parts of my options-selling setup. What used to matter most for me, low brokerage, big margins and a snappy mobile app, became secondary once I moved a few workflows to a Python script for Nifty/Bank Nifty option selling. Small infra issues quickly compound: a late hedge, a websocket hiccup, or confusing order states turn a neat plan into a messy session.

What I used to prioritise:

- brokerage

- margin

- app speed

- option chain and charts

- basic order placement

What actually matters for semi-automated option selling:

- order status consistency (no divergent views between API and exchange)

- WebSocket stability and reconnect behaviour

- rate-limit clarity and predictable throttling

- historical tick and OHLC coverage for backtests

- sandbox/UAT quality so you can test without real capital

- clear, actionable error messages from the API

- reliable order modification and cancellation behaviour

- responsive, knowledgeable support for edge cases

- Greeks and options analytics in the stream (reduces local computation and delay)

One API I’m evaluating is the Nubra trading app, it feels more API-first than many retail brokers and seems focused on the workflow reliability pieces above. Not claiming it’s the automatic winner; you still need to bench-test your own strategy and order flow.

Checklist I’d run before trusting an options-selling algo:

- uptime / SLA history

- WebSocket 99th-percentile latency and reconnect tests

- end-to-end order accuracy (simulated and live)

- margin behaviour under rapid price moves

- data coverage (intraday ticks, historical options chain snapshots)

- quality of docs and code examples

- sandbox parity with live environment

- support SLAs and technical depth

- Greeks/options data availability in streams

If you’ve done this shift from manual to API-based option selling, what one infra issue caused the biggest P\&L or operational headache for you?

​

Not a success story post.

This is an honest breakdown of the mistakes that cost me the most money in Nifty options — and what the data

showed me after backtesting 157 weeks.

Sharing because I see these same mistakes in almost every retail trader I talk to.

---

MISTAKE 1 — Buying same week expiry

Looked cheap. Was actually expensive.

Same week expiry options lose 50-70% of value on one small adverse move. Theta decay was eating 30-40% of my premium before the move even happened.Even on winning trades I barely profited because decay ran faster

than price moved.

Fix — Next week expiry for all Monday and Tuesday entries. Give the trade room to breathe.

---

MISTAKE 2 — Placing stops at

obvious levels Previous day Low. Round numbers. Visible support that everyone sees.These are exactly the levels that get swept before reversal in approximately 53% of Nifty weeks from my backtesting data.My stop would get hit. Then Nifty would go exactly where I expected.

Without me in the trade.

Fix — Structure based stops only.

Stop goes at the level that actually invalidates the trade thesis — not where it hurts least.

---

MISTAKE 3 — Entering mid-week

I used to wait for "confirmation" before entering. That confirmation usually came on Tuesday or Wednesday.

The data showed that Monday's price action predicted the weekly direction in over 70% of cases.

By the time I entered mid-week — the easy money was already made. I was buying tops and selling bottoms

without realizing it.

Fix — Monday is the setup day. If I miss Monday's entry —

I wait for next week. No chasing.

---

MISTAKE 4 — Revenge trading after a stop out Got stopped out. Immediately entered another trade to recover. That trade almost always lost too. Not because the market was against me. Because I was entering from emotion not from analysis. The setup wasn't there — I just needed to feel like I was doing something.

Fix — Hard rule. Minimum 30 minute

break after any loss before looking

at the chart again. Non-negotiable.

---

MISTAKE 5 — Judging the system on 3 trades

Had 3 losing trades in a row. Convinced the entire approach was broken. Changed everything. Then watched the original approach work perfectly for the next 6 weeks without me in it.3 trades is statistically meaningless. Even a 70% win rate system loses 3 in a row regularly.

Fix — Minimum 20-30 trades before

drawing any conclusions about

system performance. Zoom out.

---

The common thread across all 5? None of them were about predicting Nifty's direction correctly.They were all about process — how I entered, how I sized, how I managed risk, and how I responded to losses.

Fix the process. The direction calls take care of themselves.Happy to discuss any of these in the comments — which one have you experienced the most?

Indexes are too volatile now, one day up +1%, next day -1%.
Iron condors/strangles are getting SL on both sides.
How are you guys managing it?

Just have bought options and its not turning profitable just ups and downs and stuck in break even from months wanna start option selling using hedging whats the minimum capital needed to start

I’ve started judging broker APIs very differently after trying to automate parts of my option selling setup.

Earlier I mostly cared about the obvious stuff:

• brokerage
• margin
• app speed
• option chain
• charts
• basic order placement

But once you start running even a small Python script for Nifty/Bank Nifty option selling, the checklist changes completely.

Now I care more about boring infra things like:

• order status consistency
• WebSocket reconnect behaviour
• rate-limit clarity
• historical data coverage
• sandbox/UAT quality
• clean error messages
• order modification reliability
• how quickly support can explain weird edge cases

For option selling, these small things matter a lot. If your short strangle adjustment fires late, or your hedge leg gets delayed, or the API says pending while the position is already live, the whole strategy can become messy very quickly.

One API I’ve been looking at in this bucket is the Nubra trading app. It feels more API-first than the usual retail broker setup, especially if you are thinking about option selling workflows, WebSockets, Greeks, and order state reliability.

Not saying Nubra trading app is automatically the answer. I’d still benchmark any API against your own strategy and order flow. But I like evaluating it from the lens of workflow reliability instead of just features.

For people here selling options or running semi-automated strategies, what would you put at the top of the checklist?

• uptime
• WebSocket stability
• order accuracy
• margin behaviour
• data coverage
• docs
• sandbox quality
• support
• Greeks/options data

Curious what actually matters most once you go from manual option selling to API-based execution.

The idea is simple, let's say market is at 24000, so I sell 23000PE@200 and 25000CE@200 strangle, so collecting 400 premium. I let it run till expiry. Suppose, market ended at 22000, so I ended with 600 pts loss. Next month, I sell the same thing again, this time 23000PE would be easily 1200 and 25000CE would be 50. But, if market closed at 22500, I made 750 pts and covered last month loss also. Repeat it again, at least one time it will close between 23000-25000 and I get full premium and a huge profit. It should be done with max 10-20% of capital as positional long dated trade.

Will it work? Anyone explored this type of strategy?

Edit: Thanks for all the inputs, I reached to the conclusion as:

1. It's a bad idea because of being Naked, if want to do then go with hedge i.e. Iron Condor.

2. Without hedge it will become sleepless nights incase of any event.

3. Rather than sticking to the strike, it's best to move them as per market moves for better control.

Thanks to everyone who commented and provided valuable inputs.

need an option selling community.