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AlgoTest’s Edge – The 45% Advantage

The AlgoTest Edge

AlgoTest’s Edge – The 45% Advantage

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At AlgoTest, we proudly claim that 45% of our customers were profitable for the fiscal year 2023-24, a stark contrast to SEBI’s report indicating that only 11% of traders were profitable the year before.** 

While this may sound like we’re patting our own backs, we’re genuinely thrilled with the outcome—though not surprised. Our confidence stems from our unwavering belief in a systematic approach to trading.

Alpha is the amount by which you’re better than the average. 

If the average retail trader has an 11% chance of being profitable, the AlgoTest trader’s success probability is 4x that! 

– Raghav, co-founder at AlgoTest

While this can change over time, BUT this is what the data shows so far.

Our Vision

AlgoTest aims to correct the informational and knowledge asymmetry in the Indian financial markets and help the retail trader achieve their financial goals.  

The question worth asking is – Why do hedge funds and high frequency trading firms succeed? 

  1. They have the right knowledge.
  2. They have money to build or access the best tools.

Our question is – Why can’t retail traders have access to the same? 

The most advanced tools are useless unless you know how to use them. The most successful traders don’t make money in the long run because they have fancy dashboards, ultra fast price feeds, ultra low-latency execution engines. They make money because they follow a process.

Like Dhoni (Thala for us true believers), we believe in process over outcomes. We believe that to lose less (and subsequently win more) one needs to have a step-by-step plan in place. 

Loosely speaking, here’s our process : 

Idea -> Strategy -> Backtest -> Forward Test -> Live Trade

Your strategy begins with an idea.

That idea is then translated into a strategy. 

To verify if this idea and strategy is viable, backtesting is important.

To further ensure viability, you can forward test your strategy.

Once the strategy has been verified and you have some degree of confidence about its viability, you can go and trade it in the market. 

AlgoTest has built powerful tools to not only facilitate each stage of this process, but also to keep you honest in case the process breaks in any way.

Idea

Express your trading idea into a strategy using our extremely flexible and ready to use ‘920Straddle’ template (more templates on the way!).

Or go back in history and visualise your idea on the historical option chain using the simulator.

Strategy and Backtest

The Backtester, and the Simulator double up as places where you can ideate – backtester for testing your strategies that can be automated and simulator for discretionary/manual trades.

Forward Test

We have a Forward tester that you can use to test your strategies in the current markets without risking your capital.

Start trading!

Once your strategy has passed the above litmus test, you can then fully automate your algo with our algo trading execution engine (live trading terminal), or manually place orders in an optimal manner using our strategy builder.

Each of these tools forms an integral part of the process we defined above. And building each one of them from scratch requires coding and other technical expertise.

Our vision is to provide these tools at an affordable price so the retail trader can focus on getting their strategy just right and achieving their financial goals. 

A small warning

No process is foolproof and we have tools like Monte Carlo Drawdown, Curve Fitting analysis, etc for just such a scenario. 

Bear in mind that you may do everything right w.r.t the process to have the odds in your favour, but the market can still punch you in the face. Here’s my favourite meme that expresses this:

Funny Animation showing mismatch between backtest, paper trading and live trading

But what is our mission driving us towards this? 

AlgoTest is on a mission to democratise information and technology for the Indian retail trader . And we believe it starts with fixing informational and knowledge asymmetry in the financial world. 

There’s a reason why this is our mission. 

We are constantly approached by retail traders and this is how the conversation goes. 

Retail traders: “Aap strategy de do jo <insert percentage> return degi and jismein 0% drawdown hoga.”

AlgoTest – That’s illegal…but also how about we give you the tools and help you figure them out? 

It’s not just the tool that makes a successful trader but also the knowledge of how to them correctly. 

Our philosophy is : 

Give a trader a strategy, and they might profit temporarily (though it’s unlikely).

Teach them our process and the tools to execute it, and their chances of success improve (no guarantees, but their odds are better).

That’s what we do at AlgoTest. 

When someone gives you a strategy, it may or may not make money. Most likely you’ll get some crap logic and you’ll lose money.

We showcased this with Baap of Charts

Have you heard of Baap of Charts? The fin-fluencer who was heavily penalised by SEBI?

He gave out a strategy on twitter that we backtested. It turned out that strategy was a loss making one and when we published our results. Baap of Charts deleted his tweet.

Unlikely as it may be, even if somehow the strategy made money initially, eventually because of the dynamic nature of the markets, that strategy will stop making money. Then what?

There’s a SEBI’s statistic which said that only 11% retail traders made money in the 2022-2023 fiscal year. Assuming this number stays similar in the next year – i.e. 2023-2024, 45% of traders trading on AlgoTest were profitable before including brokerage and other costs. 

Here’s the monthly breakdown and the quarterly breakdown. 

In the best month, 62% of our traders made money, in the worst month, still 38% traders made money!

Monthly Breakdown

MonthProfitability (in %)
M_vanna62.16%
M_delta61.19%
M_charm60.88%
M_gamma57.45%
M_speed55.76%
M_vomma55.37%
M_color49.65%
M_theta49.05%
M_zomma48.50%
M_vega48.17%
M_rho43.46%
M_veta37.79%

Quarterly Breakdown

QuarterProfitability ( in %)
Q_delta54.05%
Q_vega52.05%
Q_gamma48.97%
Q_theta43.28%

While we are happy with this statistic…we are not surprised. Why? 

Because AlgoTest’s tools and processes are its alpha!

In finance, there’s this concept of alpha and beta. 

  • Beta is the average return you get from investing in the market as a whole. 
  • Alpha is any excess return you can get over that return. 

So if NIFTY returned 10% last year, and you were able to make 15%? 

The beta would be 10%.

Your alpha would be 5%.

People who have followed the process on our platform have outperformed the average retail trader by a whopping 4x

That’s alpha for the AlgoTest team, and it motivates us to keep building!!

So let’s summarise

“At AlgoTest, we don’t just provide strategies; we teach the process and provide the tools to execute that process. 

This approach helps traders lose less and win more over time.”

– Raghav, co-founder at AlgoTest

When someone hands you a strategy, it may or may not be profitable. However, if you understand and follow a process, you can adapt and thrive in dynamic market conditions. This philosophy has driven our development and is reflected in the success of our users.

SEBI’s statistics showed that only 11% of retail traders made money in the 2022-2023 fiscal year. In contrast, 45% of traders on AlgoTest were profitable. This significant difference is our alpha—our measure of success and motivation to continue building and improving our platform.

While the average retail trader has an 11% chance of being profitable, the probability for an AlgoTest trader is 4x higher. This is a testament to the effectiveness of our process-first approach and the value of our tools and educational resources.

By embracing our vision and mission, we aim to continue championing the cause of the retail trader, providing them with the best possible tools and knowledge to succeed in the financial markets.

** Disclaimer

It’s on a gross basis before brokerage, taxes, and charges. Also, it’s only for the positions booked through AlgoTest.

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