The Rise of Retail APIs: How India’s New-Age Investors Are Writing Their Own Trading Script

By Trivesh D, COO, Tradejini

We are seeing a new kind of trader emerge in India: young, curious, and digitally fluent. They are not just staring at charts or chasing tips anymore. They are writing code, testing strategies, and building trading systems that reflect their thoughts.

This shift toward algo trading is real. Fintech brokers offering easy access to APIs, SDKs, and hands-on learning support have accelerated it. What used to feel like a niche corner of the market is becoming mainstream, especially among engineers, finance grads, and even first-time investors willing to explore.

Today, close to 60–70% of trading volumes in India’s cash and derivatives segments are driven by algos or high-frequency systems. That tells you where the momentum is headed, not just in tools, but in mindset.

Why APIs are becoming as essential as charting tools?
Charting tools help traders analyze. But APIs help them act. A signal on a chart still needs manual execution, which may delay the trade. APIs shrink the gap between decision and execution to milliseconds. For active traders, that speed means everything.

Once traders set up their automated scripts, third-party platforms facilitate execution using open APIs provided by stockbrokers. Traders with coding expertise develop their strategies in Python or other languages and execute orders with ease. This is exactly why brokers are investing heavily in developer support, sandboxes, and plug-and-play APIs.

Profiles of solo traders building their own algos

So, who are these traders using the algo? Many of them are not from traditional finance backgrounds. They are self-taught, experimental, and powered by community learning.

Some are software engineers who write strategies in Python using Pandas and broker APIs, then link them with Telegram bots for real-time monitoring. Others are finance students deploying code through cloud platforms like AWS Lambda. Chartered accountants and consultants often use Excel with webhooks or integrate off-the-shelf algo platforms to automate their hedging or directional strategies.

A growing number of traders are using these systems to pursue profits in a more structured and disciplined way. While some use algos to generate passive income, others do it to avoid emotional decision-making. But all of them are looking for something repeatable and reliable.

Not all algos make money, and that’s the point
One of the biggest myths around algo trading is that once you deploy a bot, profits will just follow. But the reality is simpler, an algo is only as good as the logic behind it. If your system is flawed, the algo won’t save you. It’ll just speed up the losses.

We also see traders chasing accuracy without understanding context. A 90% accuracy rate sounds great until you realise it triggers just one trade a month. On the flip side, a system firing 50 trades a day with poor win rates often leads to deeper drawdowns. When traders start tweaking their algos out of frustration after a few losing days, it’s still emotion just hidden behind code.

Role of AI
Tools like ChatGPT have opened up new possibilities for retail algo traders. You can now write cleaner code, debug faster, and even brainstorm new ideas with AI assistance. But let’s be clear. ChatGPT is not a strategy generator. It’s a support system, not a substitute for thought.

Yes, AI can help scrape news, detect volume spikes, or analyze market sentiment in real-time. But the core logic? That still needs to come from the trader. The edge doesn’t lie in the tool. It lies in the clarity of thought behind how you use it.

Used wisely, AI can help you make better decisions. Used blindly, it only accelerates the bad ones. And that’s where many new traders trip up, they chase shortcuts. But there are none. The goal is not to make quick profits. The real edge is consistent thinking, built over time.

Regulators step in to make retail algo safer
Under the new rules, brokers must offer secure APIs with proper authentication, IP whitelisting, and full audit trails. Retail traders are free to build, test, and deploy their strategies, but within defined, compliant boundaries.
This isn’t about restriction. It’s about creating room for innovation without compromising market safety. Algo access is no longer a grey area. It’s regulated, supported, and growing rapidly, which’s good for everyone involved.

From Clicks to Code
The future of trading in India isn’t just about speed; it’s about control. Traders today want independence, personalisation, and smarter execution. They’re not waiting around for tips or calls. They are building systems that mirror their own thinking.

The solo trader has evolved into part analyst, part coder, part entrepreneur. That’s why APIs are no longer back-end tools. They have become front-line essentials. The modern retail trader isn’t just clicking buttons, they are writing their own scripts and calling their own shots.