In this Article…

1. What FII Flow Data Actually Tells You

2. The Fortnight at a Glance

3. Theme 1: The India Energy Infrastructure Bet

4. Theme 2: The Commodity Play

5. Theme 3: The Systematic Unwind of IT, Healthcare, and Consumer Services

6. Theme 4: Financial Services Is Being Reduced, Not Exited

7. Theme 5: Oil and Gas Exit

8. What This Means in Aggregate

Before we begin the analysis, let me just brief you on what the FII flow data actually is.

What FII Flow Data Actually Tells You

Foreign Institutional Investors (FII) are the largest category of external participants in Indian equity markets. They include global pension funds, sovereign wealth funds, hedge funds, and large asset management firms operating out of the US, Europe, and Asia.

Their buying and selling moves prices, shifts sector valuations, and often precedes broader market trends by several weeks.

Look at the chart below. The green box marks a period of sustained FII buying from early 2023, and the black line shows total FII investment value climbing steadily through that phase. The two red boxes mark the major selling episodes in late 2024 and early 2026, with the black line dropping sharply each time. The correlation is direct. When FIIs buy consistently, markets rise. When they sell in streaks, markets fall.

Heavy Selling in the last 2 Months

FIIs have sold approximately ₹1,70,000+ crore of Indian equities in the last 2 months alone.

That number gets most of the attention. But the sectoral breakdown tells a different story.

Within the selling, there is a rotation happening. Certain sectors are being bought across every fortnight even as everything else is sold.

Understanding that rotation is more actionable.

The Recent Fortnight at a Glance

This article covers the data till the latest fortnight of April 16-30, 2026.

Total inflows this fortnight (Apr 16-30) were ₹15,592 crore. Total outflows were ₹28,301 crore. Net selling was ₹12,709 crore.

That ₹12,709 crore figure matters for context. The prior fortnight saw net selling of ₹48,141 crore. This is the smallest net outflow in six fortnights. Selling pressure is not gone, but the peak appears to have passed.

On the inflow side:

• Power received ₹4,956 crore and Capital Goods received ₹4,667 crore. These were the only two sectors with significant net buying.

• Metals and Mining added ₹2,416 crore and Construction added ₹2,199 crore.

• Everything else on the inflow side was marginal.

On the outflow side:

• Financial Services led all selling at ₹11,704 crore.

• Oil, Gas and Consumable Fuels lost ₹3,351 crore.

• IT lost ₹2,887 crore, Healthcare lost ₹2,445 crore, Consumer Services lost ₹2,434 crore, and Telecom lost ₹1,908 crore.

Five clear themes emerge when we connect the latest fortnight data with the previous fortnights.

Theme 1: The India Energy Infrastructure Bet

• FIIs are placing a concentrated, consistent bet on India’s physical energy buildout.

• Power at +₹4,956 crore and Capital Goods at +₹4,667 crore are the two largest inflows this fortnight by a wide margin. Construction at +₹2,199 crore adds a third leg to the same thesis. Together, these three sectors absorbed ₹11,822 crore in net buying even as everything else was being sold.

• India’s installed non-fossil fuel capacity has tripled to over 250 GW since 2014. India has committed to 500 GW of renewable capacity by 2030.

• Achieving that target requires an estimated ₹25-26 lakh crore in sectoral investment through FY2030. It is a contracted pipeline that underpins cash flows for Power sector companies.

• Capital Goods companies making turbines, transformers, switchgear, and transmission equipment are the direct supplier chain to power companies.

• FII buying in Capital Goods is not a separate bet. It is buying the enabler of Power’s growth. The two sectors move together because they are structurally linked.

• The Union Budget 2026-27 raised public capex to ₹12.2 lakh crore. Rail, roads, and urban infrastructure all create new demand centers that require uninterrupted power supply. This extends the Power sector opportunity beyond renewable generation alone.

• AI data centers are becoming a meaningful driver within this theme. Data centers in India require 24x7 reliable baseload power. Their expansion is creating a structural demand floor that makes Power sector cash flows increasingly predictable for foreign investors with long holding horizons.

• FIIs have been accumulating in Power and Capital Goods across multiple fortnights even as they sold out of almost everything else.

• The weight of Capital Goods in FPI holdings has risen 0.29% in FY27 to date. Power has risen 0.12%. Both are rising despite aggregate outflows.

Theme 2: The Commodity Play

• Metals and Mining at +₹2,416 crore in the latest fortnight flipped from -₹1,198 crore in the prior fortnight.

• The immediate trigger was the US-China tariff escalation in early 2026. Chinese steel, aluminum, and base metal exports are being redirected away from the US market. This has created a global commodity repricing event. That is, in some markets, it created price pressure from oversupply. In others, it created supply tightness.

• India’s domestic steel companies benefit from this position. They have large captive ore bases and are selling into a domestic consumption story.

• The tariff disruption makes them relatively more attractive compared to producers exposed to the US-China trade corridor.

• Construction’s return to buying reinforces the commodity thesis. Infrastructure activity consumes steel, cement, and aggregates domestically.

• FII buying in both Metals and Construction at the same time is not a coincidence. It signals conviction on India’s internal demand for commodities, driven by the same capex cycle that is supporting Power and Capital Goods.

Theme 3: The Systematic Unwind of IT, Healthcare, and Consumer Services

• IT at -₹2,887 crore, Healthcare at -₹2,445 crore, and Consumer Services at -₹2,434 crore collectively account for ₹7,766 crore in outflows this fortnight.

• All three were FIIs’ primary overweight positions through FY2024. All three have been sold in nearly every fortnight since.

• The IT sell-off has two distinct layers.

  • The cyclical layer is US macro. Rising inflation expectations compress US growth forecasts, which reduce IT order books for Indian vendors. Deal ramp-up timelines are lengthening. Discretionary spending on legacy modernization is being deferred in favor of internal AI buildouts at large US enterprises.

  • The structural layer is more permanent. AI is fundamentally rethinking what software development costs. Agentic coding tools are compressing the number of engineers required to deliver the same output. Indian IT’s core value proposition was labor arbitrage at scale. That moat is being eroded from both ends. Clients are doing more with fewer seats, and the margin on each seat is under pressure.

• Large US enterprises that anchor the revenue of TCS, Infosys, Wipro, and HCL are actively renegotiating contracts. The conversation has shifted from “how many Engineers do we need” to “how much of this can AI handle.” FIIs see this structural shift clearly, and they are pricing it into their holdings.

• Telecom at -₹1,908 crore is being sold for a related reason. Telecom was the infrastructure play for India’s digital economy. If the software layer of the digital economy is being compressed by AI, the downstream demand assumptions for bandwidth, enterprise connectivity, and managed services weaken in parallel. The Telecom outflow is a downstream consequence of the IT thesis.

• Consumer Services has now seen 11 consecutive fortnights of net outflows. That is one of the longest single-sector selling streaks. Consumer Services includes hospitality, airlines, and discretionary experience spending. This sector’s sell-off is driven by war and global risk-off sentiment. High-PE consumption-driven sectors with limited margin buffer lose allocation first when global risk appetite contracts.

Theme 4: Financial Services Is Being Reduced, Not Exited

• Financial Services saw -₹11,704 crore this fortnight. That is the largest single-sector outflow.

• FIIs are reducing their Financial Services exposure, not exiting. The distinction matters. Reducing means they still hold a large position and are trimming. Exiting would mean a fundamental reassessment of the sector’s prospects.

• The evidence supports the reducing interpretation. Despite persistent net selling, the sector’s weight in FPI holdings has actually risen 0.57% in FY27 to date. The reason is price appreciation. Nifty Bank and Nifty Financial Services have both risen, so even as FIIs sell units, the rupee value of their remaining position has gone up.

• The selling in Financial Services is not a bear call on Indian banks or NBFCs. It is an emerging market risk-off response driven by two macro factors.

  • US 10-year yields remain elevated, making dollar assets more attractive relative to EM assets on a risk-adjusted basis.

  • The Iran conflict has added a geopolitical risk premium that reduces appetite for high-beta EM exposure.

• When either of those conditions reverses, Financial Services is likely to be the first sector where FII net buying returns. Historically, every major FII buying wave in India has started with Financial Services.

• If the April 30 fortnight is indeed a turning point in the aggregate selling cycle, watch Financial Services flows in the next two fortnights as the early indicator.

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Theme 5: Oil and Gas Exit

• Oil, Gas and Consumable Fuels has been consistently among the top three sectors for outflows across the last 12 months. This fortnight’s -₹3,351 crore continues that trend.

• The weight of Oil, Gas and Consumable Fuels in FPI holdings has declined 0.57% in FY27 to date. That is the single largest weight reduction of any sector. FIIs are reducing exposure in absolute rupee terms, not just as a percentage of a rising portfolio.

• Two dynamics explain the selling.

  • First, the macro headwind. Higher crude prices from West Asia tensions raise India’s import bill, worsen the current account deficit, and reduce the appeal of rupee-denominated assets. Global FPI debt flows out of India were negative at USD 1.9 billion in April 2026. Part of that is oil-linked.

  • Second, and more structurally, the energy transition is a real capital allocation decision. Money coming out of oil refiners and gas distributors is moving into power generators and capital goods manufacturers. It is a rotation from the old energy economy to the new one.

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What All This Means in Aggregate

When we connect the data from the previous fortnight, they tell a coherent story.

Exit the old economy: oil and gas, legacy IT labor arbitrage, rate-sensitive high-PE consumption plays.

Enter the new economy: India’s physical energy infrastructure, the capital goods supply chain, and domestic commodity demand.

Financial Services sits in the middle. It is being reduced due to macro conditions that have nothing to do with India’s banking fundamentals. It will likely be restored when those macro conditions improve.

What is already confirmed is the sectoral direction. FIIs have voted consistently with their money across multiple fortnights.

Power, Capital Goods, and domestic infrastructure are where global conviction sits right now. Everything else is either being trimmed or actively exited.

That’s it for today.

Disclaimer: Anand Ganapathy K is a SEBI-registered Research Analyst with SEBI registration number INH000016630. This post is purely for learning purposes. I do not recommend buying or selling stocks mentioned in this newsletter. I do not hold any positions in the stock discussed. Securities market investments carry market risks. Kindly review all related documents before investing.

Most retail traders are playing some of these games without ever asking one basic question: Is this a game I can actually win?

This article answers that. I will run each game through a two-filter test, show you which 4 games pass, and explain exactly why the rest are structured against you.

If you prefer watching this as a video, please find the link below. Otherwise, proceed to read this article.

The 20 Games You Can Play

Most Retail participants are playing one of these 20 games.

Some of these games have existed for decades. Some are made possible only by modern technology. But not all 20 are equal.

To identify which games you should actually play, you need a filter. Not gut feel. Not what your friend recommends. A proper filter with two hard conditions.

The Two-Filter Test

Every game you consider playing must pass the following two filters.

Filter 1 is positive expectancy over the long run. Over a large sample of trades, after accounting for all costs including bid-ask spread, slippage, brokerage, and transaction charges, your strategy must be profitable.

Filter 2 is no forced entry or forced exit. You must be able to exit on your own terms. Not because a clock ran out, not because a broker auto-squared your position at 3:20 PM, not because a margin call wiped you out before your thesis could play out.

Both filters must pass. Miss even one and the game is not for you.

Why Intraday Trading and Scalping Are Weak Hands

Let us start with the most popular game that retail traders play: intraday equity trading.

Both filters fail here.

On Filter 1, SEBI data for FY24 shows 71.5% of intraday equity traders lost money. Among traders who consistently do intraday trading for 500 days or more, 97% are net losers. The positive expectancy simply does not exist after costs.

The structural reason for this is important to understand. A significant amount of intraday volume on Indian exchanges is executed by algorithms. HFT firms and market makers have sub-millisecond execution and co-location advantages inside the exchange itself. They are physically closer to the matching engine than any retail trader can ever be.

On Filter 2, intraday trading fails completely. Your broker will auto-square off positions between 3:20 and 3:25 PM regardless of whether your trade is in profit or loss. If you are trading futures intraday, a margin call can force you out mid-trade. You have no control over your exit.

You might have a green day occasionally. Over a long run, the expectancy does not hold up and the forced exits make it worse.

Strong Hand #1: Investing

Now for the games you should actually play.

Investing passes both filters cleanly.

On Filter 1, the Nifty 50 TRI has delivered a 13.5% CAGR over 25 years. This is before stock selection, before any active strategy. Just being in the market has positive expectancy. Add a disciplined stock selection framework and that expectancy improves further.

On Filter 2, no one can force you out of a position. Once you hold a stock, it is legally yours. No expiry, no margin call, no auto-squareoff. You exit only when you choose to.

The edge in this game is time in the market and compounding. The dominant players are FIIs, DIIs, mutual funds, and long-term retail investors. Retail can replicate the one thing that creates an edge here: patience.

Strong Hand #2: Positional Trading

Positional trading is buying a stock and holding it for a few weeks to a few months.

On Filter 1, this game has positive expectancy. The momentum factor is well-documented across decades of market research. Multiple multi-factor models have also proven to perform well over longer time horizons.

On Filter 2, there are no forced exits as long as you are trading unleveraged. You own the stock outright. No expiry date, no margin call. Your system triggers the exit, not your broker.

The edge here is trend identification and thesis discipline. Execution matters less than strategy. The dominant players are systematic funds and disciplined, experienced retail traders. That last category is one you can belong to.

Strong Hand #3: Hedged Options Selling

One of the popular ways of hedged option selling is executing a spread. For example, selling a put option while simultaneously buying a put option at a lower strike as a hedge. The loss is defined upfront. There is no unlimited downside like naked options selling.

The primary purpose here is to capture theta decay. The position earns money as time passes, assuming the market does not move aggressively against you.

On Filter 1, this strategy has positive expectancy when executed systematically. The theta you collect must exceed the net cost of the spread over time. When structured properly, it does.

On Filter 2, there are no forced exits. Because the loss is already capped by the hedge, there are no margin call risks. You can hold the position till expiry without any forced intervention.

One important condition: this game should be played by pledging your long-term investments, not by putting fresh cash at risk. At least 70% of your portfolio should be in long-term holdings first. Then you pledge those holdings and deploy hedged options selling on the margin.

Strong Hand #4: Portfolio Hedging

Portfolio hedging applies to retail investors who have built a portfolio of at least 15 to 20 lakhs.

By putting systematic hedges in place, you can protect your portfolio from large drawdowns during crashes.

Good hedges limit drawdowns to manageable levels during 30 to 40% market crashes. Some hedging structures are what I call zero-loss strategies, where the cost of the hedge is recovered regardless of market direction. More advanced setups can be structured so both the portfolio and the hedge are profitable over time.

The Scorecard

The table below summarizes all games. 4 games are strong hands that you should be playing. 3 are marginal. 13 are weak hands that you should avoid as Retail.

A few notes on the marginal zone.

Swing trading, which is holding for a few days, has some edge on paper. But in practice, if you execute 300 to 400 trades a year as swing traders typically do, transaction costs consume a large portion of the theoretical edge. Investing and positional trading achieve better outcomes with far fewer trades.

Positional options buying can work in a discretionary manner, specifically when you identify that a particular trend is strong enough to justify the options premium cost. Doing it systematically, week after week, does not hold up. The expectancy drops when done frequently.

IPO investing has some edge during certain market cycles but the dominant players are institutions and HNIs who get preferential allocations. Retail gets the scraps.

What You Should Play

Four games. That is it.

1. Invest in quality businesses and hold for the long term. Index Investing with proper Asset Allocation should do.

2. Add positional trading once you have a systematic approach to trend identification.

3. Layer in hedged options selling by pledging your investments once your portfolio is meaningful.

4. Add portfolio hedging once you cross 15 to 20 lakhs.

Everything else, intraday trading, BTST, scalping, margin trading, futures, weekly options buying, naked options selling, is either structurally stacked against you or dominated by players you cannot compete with.

The broker is the guaranteed winner in the weak hand games. They charge interest on leveraged positions, collect brokerage on every trade, and are probably making market and extracting value from the other side of your trades.

Stick to the 4 strong hands. That is enough to do very well over time.

I give you a Flexi-Wealth System and In-Depth Research to build a Life-Long Portfolio that works across market cycles.

Disclaimer: Anand Ganapathy K is a SEBI-registered Research Analyst with SEBI registration number INH000016630. This post is purely for learning purposes. I do not recommend buying or selling stocks mentioned in this newsletter. I do not hold any positions in the stock discussed. Securities market investments carry market risks. Kindly review all related documents before investing.

This article is about that gap. It has a name. It has a mechanism. Let us explore.

The Problem That Hides in Plain Sight

Start with a simple trade. You plan to buy an stock/option at ₹100. Your target is ₹105. Your stop loss is ₹98. On paper, this trade gives you a planned profit of +5 on a win and a planned loss of -2 on a stop out.

The math works. The strategy has positive expectancy. Run it long enough and you should come out ahead. At 50% win rate, every two trades nets you ₹3 on average.

That is the plan. Here is what actually happens.

Why Good Strategies Bleed

You try to buy at ₹100. Your order gets filled/executed at ₹101. That is ₹1 slippage on entry. The trade goes your way. You try to sell at ₹105. You get ₹104 instead. Another ₹1 slippage on exit. Your planned ₹5 profit becomes ₹3.

Now take the losing trade. You bought at ₹101 due to entry slippage. Your stop was at ₹98. It triggers. You get ₹97 instead of ₹98. Exit slippage of ₹1. Your planned -₹2 loss becomes -₹4.

Look at one win and one loss together.

On paper: +5 and -2 = net +3.

In reality: +3 and -4 = net -1.

A strategy that looked profitable on paper delivered a net loss in practice. Nothing changed about the setup. Only the execution costs came into play.

This is the P&L gap. And it grows with every trade you take.

What Is Slippage?

Slippage is the difference between the price you expected and the price you actually got.

You open your trading terminal. You see the option trading at ₹136.05. You place a buy order. By the time the order reaches the exchange and gets matched, the price is ₹138. You are already ₹2 behind before the trade has even had a chance to work in your favour.

The prices on your screen are already delayed. They are not real-time. The exchange sends data to your broker. The broker displays it on their platform. It travels through your internet connection. By the time you see ₹136.05, that number is already stale.

Why Slippage Happens: The 10 Layers

Your order does not go directly from your finger to the exchange. It passes through at least ten distinct layers before it gets filled. Each layer adds delay. Each delay creates a window for the price to move before your order gets executed.

The table below breaks this down layer by layer, including who it affects and how much delay each one introduces.

Let me explain these.

• Screen data delay. The prices on your screen are already 50 to 500 milliseconds old. The exchange sends data to your broker, the broker displays it, and it travels through your internet connection. By the time you see a price, it is stale.

• Human reaction time. If you are placing orders manually, the time between seeing a price and clicking buy can add another 200 to 500 milliseconds. Algo traders skip this layer entirely.

• Broker platform and risk check. Before your order moves anywhere, your broker runs margin checks and pre-trade risk filters. This adds another 200 to 250 milliseconds to every single order.

• Algo platform relay. If you use an algo platform, the signal has to travel from the platform to the broker’s API before the order is even placed. The algo platform relay is the one most algo traders underestimate. Depending on the platform and its server load, this layer alone can introduce anywhere from 1,000 to 15,000 milliseconds of delay. That is one full second to fifteen seconds. In a fast-moving market, that is a big delay.

• Broker-to-NSE leased line. Once your broker sends the order to the exchange, it travels over a physical leased line. That network transit adds another 5 to 30 milliseconds.

• NSE order validation. The exchange runs its own checks on your order before allowing it into the queue. Another 1 to 5 milliseconds gone.

• Exchange queue and price-time priority. Your order enters a queue. NSE gives priority first to the best price, then to orders that arrived earliest at that price. Where your order lands in that queue is completely random from your perspective. This is why slippage cannot be predicted in advance.

• HFT co-location repricing. High frequency trading firms are located inside the exchange. They can see buying aggression in the order flow and raise their offer prices before your order is matched. By the time your order fills, the price has already moved against you. This one is structural and unavoidable for retail traders.

• Order book walking. If you want to buy 1,000 Quantity but only 520 are available at the best price, you get those 520 at one price and the rest at the next level. The larger your order, the worse this gets.

• Post-fill confirmation delay. After your order executes, the exchange sends confirmation back to your broker, and your broker sends it back to you. If your strategy places a second order only after the first one confirms, this 100 to 300 millisecond delay directly affects the execution of the next leg.

The Numbers That Should Make You Stop

We have a cost simulator on our website. These are numbers from a real example. I will take you through it. You can access it here.

Inputs on the left hand side:

• ₹5 lakh capital,

• 20 trades per day,

• 100% profitable days,

• 1:1 risk-to-reward,

• ₹100 average premium,

• 200 quantity,

• bid-ask spread of 0.25%,

• slippage of 0.5%.

Result on the right hand side of the pic above:

• Gross profit for the year: ₹12,50,000. This is the profit before any costs.

• The strategy wins on all 250 trading days.

• Total costs = ₹19,23,087.

• brokerage and other statutory charges ₹4,23,087,

• bid-ask spread cost ₹5,00,000,

• slippage cost ₹10,00,000.

• Net Profit = a loss of ₹6,73,087. On a capital of ₹5 lakh. That is capital wiped out.

A strategy with 100% profitable days, no losing trades at all, still ends the year deep in the red. The only reason is execution costs. This is what active intraday trading with high trade frequency looks like when you account for the real cost structure.

How to Reduce Slippage

Here is what you can actually control.

Cap intraday trades at 6 per day (12 main orders). Every trade is two orders: one to enter, one to exit. 12 orders per day is the ceiling. Beyond that, the cumulative slippage on all those fills starts to overwhelm whatever edge the strategy has. In practice, most strategies that take more than 12 orders per day end up net negative after accounting for execution costs.

Completely avoid scalping and high frequency trading. At very short timeframes, the slippage and bid-ask spread as a percentage of the trade's potential profit are simply too high. A strategy might look profitable at the gross level, meaning before costs. But once you apply realistic bid-ask spread percentages and slippage, the net result is a loss. This is not a recoverable situation by tweaking the entry or exit. The entire approach needs to change.

Avoid low premium options. Low-premium options have a wide spread relative to their price. On a ₹20 option, a ₹0.50 bid-ask spread is already 2.5% of the premium. Add slippage on top and the cost of entering and exiting can easily reach 4 to 5% per round trip. The probability of a trade being profitable has to overcome that cost hurdle before any profit starts.

Track every fill. Expected price versus actual price. This is the discipline most traders skip. If you do not track your fill quality, you have no idea where your money is going. Tracking this data shows you whether your execution is getting better or worse, whether a particular algo platform is adding unnecessary delay, and whether certain times of day produce worse fills. It is the only way to understand and improve your actual execution quality over time.

Don’t Donate Money

If you have low capital, say ₹1 to 2 lakhs, and you are trying to scalp or take 40 to 50 trades a day, that combination is particularly dangerous. The math does not work even with a good strategy. The execution costs will consistently outpace any edge the strategy carries.

The market has sophisticated participants on the other side. HFTs sitting inside the exchange. Market makers who earn the spread every time.

If you trade excessively with low capital, you are basically donating money to brokers, exchange HFTs, market makers, and other stakeholders.

The only sustainable path for a retail trader is fewer, better trades, with larger premiums, and a clear understanding of what execution actually costs.

Understanding slippage is crucial. It is the difference between a strategy that survives and one that quietly bleeds your account.

That’s it for today.

I have covered the topic in more detail in the video below. If you prefer watching, do check it out.

We give you a Flexi-Wealth System and In-Depth Research to build a Life-Long Portfolio that works across market cycles.

Disclaimer: Anand Ganapathy K is a SEBI-registered Research Analyst with SEBI registration number INH000016630. This post is purely for learning purposes. I do not recommend buying or selling stocks mentioned in this newsletter. I do not hold any positions in the stock discussed. Securities market investments carry market risks. Kindly review all related documents before investing.

Or why trading more to recover losses only makes things worse?

Or how Props and FIIs make a profit to the tune of ₹60,000 crore in the same market that you are trading while your account keeps losing?

These are not random outcomes. There is one concept that connects all the 3 questions above.

Once you understand it, you will never look at your trades, your backtest, or your capital the same way again.

If you prefer watching over reading, I have covered this article in much more detail in the video below. Else, keep reading.

Let us look at some data before getting into the concept.

Who Is Actually Making Money in F&O Trading?

SEBI released the following data in 2025.

Proprietary traders earned ₹33,037 crore gross in FY24. FPIs earned ₹27,965 crore. Individuals and others collectively lost ₹61,212 crore in the same year.

This is not one bad year for retail traders. It has happened every time in the past, and it will happen every time in the future also. This is the structural reality of the market.

The natural question is: What exactly are props and FPIs doing that retail traders are not?

Almost All of It Comes from Algos

96% of proprietary trader profits in FY24 came from algo trading. For FPIs, that number was 97%. Non-algo profits were marginal for both categories.

This tells you something important. The edge these institutions hold is not gut feel or discretionary trading. It is systematic, algorithmic execution at a very large scale.

The next logical question is: What are these algos actually doing?

Are these Algos Directional or Non-Directional?

There are ~1,000 prop and FII entities in total. On the other side, there are crores of retail traders.

Each retail trader averages ₹11,824 per transaction and makes roughly 875 transactions per year (Source: NSE & SEBI)

Think about what this means structurally.

Retail traders collectively generate few crores of transactions every single day. Props and FPIs are mostly the counterparty to these crores of transactions. That is, they are on the opposite side.

Effectively, Props are making small profits per trade across crores of trades. This business model is only possible with a non-directional strategy.

A directional strategy, on the other hand, works by taking fewer, larger bets. You hold them long enough for the thesis to play out. Profit per trade is high. Trade count is low. So, Props are not doing this.

The Prop model is the exact opposite. High trade count. Very small profit per trade.

That structure can only mean one thing. That is Market Making.

What are Market Making Algos

Market makers do not predict where the market is going. They are not long or short based on a view.

They sit on both sides of the order book continuously. They place limit orders to buy and sell simultaneously.

Look at the market depth of the Nifty options below. All these orders that you see are limit orders and are mostly placed by the market makers (Props).

Every time a retail traders sends a market order, a market maker’s (PROP) limit order is on the other side of that transaction.

They enable your transaction. In return, they collect a small fee on every single trade.

To understand this better, you need to know the concept of bid ask spread.

What Is Bid-Ask Spread?

Open any options contract. I have loaded the NIFTY 23,300 call option below. You will see two prices in the market depth. Bid and Offer.

The bid is the highest price a buyer is willing to pay.

The ask (or offer) is the lowest price a seller is willing to accept.

The bid is ₹239.2 and the ask is ₹239.7 as in the above pic.

If you buy at market price, you pay ₹239.7. If you immediately sell at market price, you receive ₹239.2. That gap of ₹0.50 is the fee you paid to the market maker. That is, you paid it to the PROP Traders.

That spread as a percentage is almost 0.21% of the Premium. That is a hidden cost that you dont see.

It does not sound like much. But every single trade you take, on both the buy and the sell, carries this cost. It adds up fast. I will show you a detailed calculation later in the article.

This is one of the reasons why Props are making thousands of crores every year. Almost guaranteed.

Here is a simple way to understand this.

Have you gone to Airport Money Exchange Counter?

USD/INR trades around ₹93.9 in the open market. Walk up to an airport forex counter and ask to buy $1. You will pay around ₹95. Come back from your trip and try to sell that dollar back. You will get only ₹89.

You buy above the market rate. You sell below the market rate. The ₹6 difference is pocketed by the exchange counter. That is their bid-ask spread.

Now ask yourself: would you go to that counter 10 times in a day to transact dollars?

Of course not. One transaction costs you ₹6. Ten transactions cost you ₹60.

You would go once when you need dollars and once when you return. That is it.

But in the markets, most traders do exactly this. They believe more trades means more opportunity. It does not.

More trades means more spread paid to market makers, more brokerage paid to brokers, and more taxes paid to the government.

Market Making Is Everywhere

Market making is not unique to Indian options. It happens across every asset class and every market in the world. Equities, bonds, currencies, commodities.

Wherever there is a buyer and a seller, there is almost always a market maker sitting in between, collecting the spread on every transaction.

It is also one of the most consistently profitable trading activities in the world. Not because market makers are smarter. But because the structure of the market guarantees them a fee on every single trade, regardless of direction.

This is what you need to understand before you trade any instrument. Is market making prevalent in this instrument? If the answer is yes, then making consistent intraday profits becomes extremely difficult.

You are essentially fighting an entity that gets paid whether the market goes up or down, and gets paid every single time you transact. Props are doing exactly this.

In liquid options like Nifty and BankNifty, market making activity is very high. The market maker’s edge compounds across millions of trades every day.

This is also the reason why scalping, intraday options buying and overtrading in Nifty and BankNifty are almost always losing strategies for retail traders.

Every time you enter and exit quickly, you are paying the spread twice. Once on the entry and once on the exit. Do this ten times a day and the spread alone will erase whatever small profit your strategy was trying to capture.

Why Your Profitable Strategy still loses

Whenever I backtest or forward test a strategy, I simulate the total market cost of the strategy using the calculator below. You can access the calculator here.

On the left-hand side of the calculator, the inputs, and on the right-hand side, you will see the output. You can enter the details of your strategy on the left-hand side to get an estimate of the total market cost.

Assume you have ₹2 lakh capital.

You risk 1% per day, which is ₹2,000. Your risk-reward is 2:1, so you target ₹4,000 on winning days. You win 60% of the days. Your strategy deploys 10 trades per day.

I have entered the details above in the calculator, and I got the total market costs on the right hand side.

On paper, the gross profit of this strategy is ₹4 lakh per year. The strategy looks excellent before the costs.

Let us now deduct the costs. Here is the actual cost structure of this strategy:

• Regulatory costs (brokerage, STT, transaction charges, GST, stamp duty) come to approximately ₹1,59,000 per year. Most traders know this and account for it in their brokerage calculator.

• Bid-ask spread at 0.21% per trade comes to approximately ₹75,000 per year. Most traders never account for this.

• Slippage at 0.5% per trade comes to approximately ₹1,87,000 per year. This is the difference between the price you expect and the price you actually get. We will cover slippage in detail separately in another article. For now, just understand that there will always be slippage.

Total market cost is ₹4,21,000.

Your gross profit was ₹4,00,000. Your total costs are ₹4,21,000. The strategy is now a loss-making one.

An extraordinary strategy on paper becomes a loss-making strategy in practice. The reason is not bad entries or bad exits. The reason is bid-ask spread, slippage, and cost.

Why ₹1-2 Lakh Capital Is Not Enough for Trading

With ₹1-2 lakh trading capital, the math simply does not work.

The fixed costs alone are significant relative to the capital base. Regulatory costs, bid-ask spread, and slippage eat into a disproportionately large portion of your profits.

If you trade with ₹1-2 lakh in F&O, you will not be profitable even if your strategy is genuinely good. The market structure does not allow it.

Action Points for you

You should implement these things immediately.

1. Every backtest you do hides bid-ask spread, slippage, and regulatory costs. Always add these three before concluding that a strategy is profitable. After accounting for all three, very few strategies retain a genuine edge.

2. ₹1-2 lakh capital for F&O trading is not enough. Some good strategies start returning real profits only above ₹5 Lakh. That too, you should first invest for the long term and then pledge those holdings and only trade in F&O.

3. More trades is not more opportunity. Every additional trade is a donation to market makers, to brokers, and to the government. Traders who survive long enough take fewer trades. Aim for a maximum of one to two adjustments per day. If your strategy is still in a loss after two adjustments, close the trade for the day. Avoid scalping, intraday options buying, and over-trading.

4. Avoid F&O trading till you build at least 15 lakhs in capital. Once you build a capital of 15 lakhs, you can use F&O for hedging and income generation. You can do both Hedging and Income Generation by pledging your investments. Do not trade in F&O for speculation. The only people who win are the Brokers, Props, Exchange, SEBI and the Government.

A Mental Model for Survival

Most traders spend their time changing their rules. A new indicator. A new entry signal. A new stop loss level.

The ones who survive understand something deeper. There is a structure to markets that cannot be changed. And there are principles that must never be broken.

Think of it in 3 layers.

1. Structure includes bid-ask spread, taxes, and slippage. These costs exist. They will always exist. In trading, you should always know who is on the other side. Understanding structure tells you the minimum edge your strategy needs to have before it can be profitable.

2. Principles include risk management and position sizing. These must not be broken. Never ever.

3. Rules include your charts, your indicators, your specific entry and exit criteria. These can be different for different people. And they keep changing.

The ones who survive understand the structure and never break the principles.

The Devil is in the Details

The bid-ask spread is not a small detail. It is the mechanism through which bulk of the ₹61,000 crore flows from retail traders to market makers (Props) every single year.

Understanding it does not mean you should stop trading. It means you should trade less, trade smart, and always know the true cost of every transaction before you enter a position.

In the upcoming weeks, I will be covering more topics around market structure and other key areas.

Disclaimer: Anand Ganapathy K is a SEBI-registered Research Analyst with SEBI registration number INH000016630. This post is purely for learning purposes. I do not recommend buying or selling stocks mentioned in this newsletter. I do not hold any positions in the stock discussed. Securities market investments carry market risks. Kindly review all related documents before investing.