Algo trading has exploded for retail folks like us in India. It's no longer just for big institutions. With SEBI's new rules, you can jump in safely if you know the playbook. SEBI's Big Shift in 2025 SEBI changed the game for retail algo trading back in early 2025. They

Algo trading looks precise on paper. Backtests show smooth equity curves. Win rates look strong. Drawdowns appear controlled. Then you deploy live. And returns shrink. Not because the strategy stopped working. But because execution quietly reduced your edge. In India’s derivatives market, retail participation has surged sharply in recent

Algorithmic trading is on the rise among retail traders in India. What was hitherto the preserve of institutional and proprietary traders is now available to retail traders through APIs, platforms, and fintech solutions. The latest trends and developments indicate that retail algo trading is taking off at a rapid pace

Most beginners don’t struggle with automation itself. They struggle with forming a reliable, rules-based idea worth automating. Modern algo platforms can execute thousands of trades, manage positions, and run continuous logic, but none of that matters if the underlying strategy is unclear. A beginner-friendly platform should lower the learning

Backtesting is the first real validation step for any algorithmic trading idea. It allows you to run your strategy on historical market data and observe how it would have behaved under real conditions. Instead of relying on assumptions, you get measurable insight into risk, stability, execution quality, and long-term behaviour.

Algorithmic trading strategies are simply rule based systems that convert a trading idea into measurable, testable, and repeatable logic. Retail traders in India often approach automation by first picking a platform, but strategy selection comes earlier. Before you automate anything, you need to understand what kind of logic you are

Algo trading used to be largely an institutional-only domain. But with growing demand from retail users, the regulatory landscape has evolved. In 2025, Securities and Exchange Board of India (SEBI) introduced a formal framework to regulate algorithmic trading by retail investors a significant shift toward transparency, accountability, and safer participation.

Trend following as a trading framework relies less on prediction and more on disciplined execution. The strategy works by identifying established market direction and holding positions as long as that direction remains intact. But trend followers don’t succeed because they find trends. They succeed because they size positions systematically

Trend identification is the base layer of rule-based trading. If you misread the trend, every downstream decision entries, exits, position sizing, and risk control becomes unreliable. For retail algo traders, the problem isn’t a lack of indicators; it’s figuring out which ones reliably capture directional behaviour without introducing

Moving average crossover systems remain one of the simplest ways to test trend following behaviour, but they are often misunderstood. A crossover is not a prediction tool. It is a rule-based mechanism for identifying when price transitions from one regime to another. When you test them properly, they reveal how

Backtesting a trend following strategy is not just about throwing a moving average on a chart and checking how it looks. A proper test has a sequence. You define what you are trying to trade, write rules that a machine can understand, run them on clean data, and then stress

Comparing two trading strategies is not as simple as checking which one made more money. Raw returns hide instability, hidden leverage, drawdown depth, execution friction, and volatility sensitivity. A strategy that shows lower returns on paper may actually be far superior once risk is factored in. This is why professional

A buy-and-hold portfolio works well when markets rise steadily and volatility stays contained. Trend-following works well when markets break into strong directional phases or slide into prolonged downturns. Most retail traders discover that each approach has weaknesses on its own, but together they create a portfolio that grows consistently while