When you place a trade on NSE, who takes the other side?
Increasingly, the answer is: a computer. And not a neutral one — a system built by a proprietary desk or a foreign fund whose entire purpose is to be on the profitable side of your order. The data on how that is going is not subtle.
The market is already algorithmic
Algorithmic trading crossed 53% of NSE cash-market turnover in 2024, overtaking manual order flow for the first time, per NSE data reported in the trade press. That share has since edged up to 54% for FY26 to date, per NSE’s own Market Pulse data. In equity derivatives, the concentration is starker: co-located algorithms account for over 62% of turnover, up from around 7% in 2010.
Co-location means the trading server sits in the exchange’s own data centre, microseconds from the matching engine. That is a structural advantage retail will never match from a home broadband connection, and it is worth being honest about that up front.
The asymmetry, in the regulator’s numbers
SEBI’s September 2024 study did something unusual: it traced where the money went. The findings, for FY24:
- 96% of proprietary traders’ profits came from algorithmic trading.
- 97% of foreign portfolio investors’ profits came from algorithmic trading.
- Only about 13% of individual traders used algos at all.
That gap has only widened since. Individual traders lost a net ₹1.05 lakh crore in FY25 alone, up 41% from FY24, SEBI’s July 2025 follow-up study found, taking the FY22-FY25 total to roughly ₹2.87 lakh crore. That money is overwhelmingly captured by algorithmic counterparties. Individual traders are, in aggregate, the liquidity those systems are designed to harvest. And they are bringing discretionary, emotion-driven decisions to a contest the other side has automated. Why 93% of F&O traders lose walks through the loss side of this data in more depth.
You cannot win on speed. You can win on discipline.
Here is the important distinction, because it separates a realistic response from a fantasy.
There are two broad edges in markets. The first is latency: being faster than everyone else to react to a price. That edge belongs to co-located HFT desks, and retail cannot contest it. Full stop.
The second is systematic edge: holding a disciplined, rules-based exposure to a factor such as momentum, value, quality, or low volatility, and rebalancing it consistently over months and years without letting fear or greed interrupt the process. This edge does not require microseconds. It requires that your decisions be defined as rules, tested against history, and executed the same way every time.
That second edge is exactly what the winning side already industrialised, and exactly what retail has lacked the tools to run.
Where saral.money fits
saral.money gives retail the systematic primitive, not the latency one. You build a strategy as a visual pipeline: a universe flows into filters, into cross-sectional ranking, into position sizing, into a portfolio output. It is backtested on 15+ years of NSE and BSE data, then runs the same way at every rebalance — no second-guessing, no holding a loser because selling hurts.
The honest framing matters here, so let us be precise about what this is and is not:
- It is not an HFT platform. saral will not out-run a co-located algo, and it does not try to. If your strategy depends on reacting to a tick faster than the market, this is the wrong tool.
- It is a way to run the kind of patient, rules-based, factor-driven strategy that institutions use — but that no-code Indian platforms have not offered for equity portfolios.
Beating the machines at their own game was never the plan. The plan is to stop bringing a discretionary decision to a contest the other side has automated, and to run the one edge retail actually has: process.
What to try next
Browse the strategy templates to see what a systematic equity strategy looks like as a pipeline, then run one through the backtester on a survivorship-bias-free Nifty 500 universe. Forget the magic number: the goal is to replace “I think this will work” with “here is how this rule behaved across fifteen years, including the years it hurt.”