# Why I'm Continuing my "Failed" Volatility Trading Community 
Author: AlgoTest
Author URL: https://algotest.in/blog/author/algotest/
Published: 2025-11-14
Tags: trading edge, volatility trading, implied volatility, position sizing
Tag URLs: trading edge (https://algotest.in/blog/tag/trading-edge/), volatility trading (https://algotest.in/blog/tag/volatility-trading/), implied volatility (https://algotest.in/blog/tag/implied-volatility/), position sizing (https://algotest.in/blog/tag/position-sizing/)
URL: https://algotest.in/blog/why-im-continuing-my-failed-volatility-trading-community/

I’ve been interacting with retail option traders since late 2021, and here’s the thing I keep noticing:

**Almost nobody has an explicit opinion on volatility.**

Well, they _do_, but they don’t know that they do. You hear things like:

- “Sell at 9:20 AM to earn theta.”
- “I have low capital, so I’m an option buyer.”
- “I have large capital, so I’m an option seller.”
- “Theta is an edge.”

These are _all_ volatility opinions disguised as trading rules.

## **The Problem**

Most Indian retail traders come from a price-action background. They’re plotting option charts on TradingView, drawing lines, looking for breakouts - but they’re ultimately trading volatility instruments without thinking in volatility terms. And 90% retail traders are losing money (no correlation implied 😉)

To address this gap, I tried an experiment:

I started a small [volatility trading community](https://algotest.in/courses/raghav-vol-course?utm_source=blogs) \- not for money, but to give the average “desi price action trader” an entry point into vol thinking.

**The Reality Check - PAIN**

As expected, early feedback wasn’t great. I resonated with about 20% of people. The remaining 80% dropped off quickly.

If I measure the outcome purely on adoption or revenue, this has been a _failed experiment_.

The [community](https://algotest.in/courses/raghav-vol-course?utm_source=blogs) content isn’t free… but even behind a paywall it hasn’t been a profitable endeavour for AlgoTest.

And yet - **I want to keep this going.**

I also conduct a paid 2-hour webinar once a month that introduces the core concepts before the full course - the cost is usually ₹99 **,** enough to get you to feel like you have some skin in the game. Occasionally, I'll make this webinar [free](https://algotest.in/masterclass/volatility-trading-masterclass?utm_source=blogs) ​

![](https://prod.superblogcdn.com/site_cuid_cmbhlz3q0002sxzc513a62pj5/images/frame-19840813422-1763469311125-compressed.png)

## **Why Continue a “Failed” Project?** ​

Because of the people who stayed. The 20% who are hungry to learn. The ones who ask good questions, challenge assumptions, and force me to articulate things better.

Talking to those traders - especially those who come from the pure price-action world but _want_ to level up intellectually - genuinely makes me a better trader.

(Disclaimer: I barely trade these days - maybe 1–2 lots in NIFTY when time permits - but even those trades are guided by my read of relative volatility, IV vs IV of other strikes, and the IV/RV relationship.)

### **Building Tools to Teach Better** ​

To make the concepts more concrete, I built a few tools.

The first one is designed using option buying as an example - the segment that dominates Indian retail. It’s a simple yet powerful tool that follows a very simple trade prospecting funnel? First, the **Edge Calculator** will determine if the algo has edge, then the **Trade Simulator** will run some simulations for the algo, and finally the **Position Size Calculator** will help you size your trades based on risk, volatility, and your capital.

Check out the all-in-one [Edge Calculator, Trade Simulator, and Position Size Calculator here](https://algotest.in/edge-calculator).​

### The idea is simple:

You can use actual backtest data from AlgoTest - win%, loss%, average win, average loss - and show:

1. **Does the strategy have edge?** The first decision criterion. If there’s no edge, stop right there (Yes, sometimes it can make sense to continue trading even if the system is negative edge - diversification, but we'll treat that as out of syllabus for now)
2. **What does a simplified equity curve look like if history repeats?** Yes, oversimplified - but useful to illustrate how sizing impacts the journey.
3. **How to apply Kelly for position sizing**, given the margin required for long options. You will almost never be able to handle the variance that Kelly gives you, but it's a good theoretical starting point when looking at position sizing in isolation for a new trading strategy.

To learn more about the tool, check out the [documentation for the all-in-one Edge Calculator, Trade Simulator and Position Size Calculator.](https://docs.algotest.in/strategy-builder/edge-calculator/) ​

This tool forces traders to confront questions they rarely ask:

- Did this strategy _actually_ make money historically? (i.e. does it have edge?)
- If yes, and assuming the past repeats (BIG ASSUMPTION), _how should I size my trades?_(i.e. if the strategy has edge, what should my position sizing look like?)
- If not, why am I punting?

Most Indian option buyers are essentially playing slot machines. This tool backfills some missing basics.

PS: the tool sometimes shows how Kelly bet sizing, a formula that tells you how much to bet, gets too greedy and asks you to borrow money to trade (not usually a good idea unless you _**really**_ know what you're doing - see [Leverage in Trading: 2.25 Crores in 8 minutes?)](https://algotest.in/blog/leverage-in-trading-2-25-crores-in-8-minutes/?utm_source=blog)

​


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