Algo Trading Myths Debunked | Truth About Automated Trading

When people hear the term Algo Trading, most people think of it as something that’s only for big companies and professional traders. Some consider it so complicated that they back off before even trying it. But the reality is that today, in 2025, technology and new SEBI regulations have made it easier for everyone. Now, even retail traders can automate their trading with the help of free APIs and no-code platforms. In this blog, we’ll debunk these Algo Trading myths with the truth.

What Exactly Is Algo Trading?

Algo Trading, or Algorithmic Trading, is a method in which trading decisions are made by a system based on predetermined rules and logic, rather than by humans. These rules include price, volume, time, and other market indicators. Its primary purpose is to make trading fast, accurate, and emotion-free, so that every decision is based on data, not guesswork.

How It Works

Algo Trading isn’t difficult to understand. The entire process involves a few simple steps:

1. Developing a strategy : First, a trader uses their own thinking and experience to establish a rule, such as buying or selling at a certain price level.
2. Building the system : This rule is set up in the system as code or logic.
3. Connecting to the API : The system connects to brokers’ APIs (such as Pocketful, Zerodha, Dhan, etc.) to access live market data.
4. Backtesting : Before running the strategy in the real market, the same strategy is tested on historical data to determine its performance.
5. Live running : When the strategy is successful in testing, the system uses it in real trading.
6. Monitoring : The trader continuously monitors whether the system is trading correctly and makes changes if necessary.

Read Also: Best Algo Trading Platform in India

Myth 1: Algo Trading is only for large institutions

The Myth : Many people believe that Algo Trading is only for large fund houses, institutional investors, or hedge funds. They believe it requires significant capital, complex coding, and expensive servers. This is why many retail traders still shy away, believing that this technology is not for them.

The Reality : This thinking is now outdated. In 2025, Algo Trading will become simpler, more accessible, and more affordable than ever before. Today, even retail investors can easily start API-based trading without any complicated setup or large capital. Platforms like Pocketful have bridged this gap. Here, you can start automated trading by opening a Zero AMC Account and generating your own API in just a few minutes.

Step-by-Step Procedure to Start Algo Trading

Step	Description
1	Open a Free Account on Pocketful (Zero AMC)
2	Generate API by going to the dashboard
3	Connect your strategy to any Algo platform
4	Backtest and then deploy in Live Mode
5	Monitor your algorithm and optimize as needed.

Example : Let’s say you have ₹10,000 in capital and trade manually every day. By connecting to Pocketful’s API, you can automate your strategy such as “buy when the price rises above a certain level, sell when it falls below.” You no longer need to sit in front of the market; the system will automatically trade according to its rules.

Myth 2: Algo Trading requires coding or Programming skills

The Myth : Many new traders think they need to be proficient in Python or another programming language before they can start Algo Trading. This belief is so common that many people give up before even trying to learn. They believe that automated trading is impossible without coding.

The Reality : The truth is that knowing how to code is no longer necessary. There are many no-code and low-code platforms available today, where you can automate your trading strategy without writing a single line of code. Tools like the Pocketful API allow you to easily connect your trading logic to an Algo platform. There, you simply set conditions like, “Buy if the price goes above the support level, sell if it goes below.” The execution system handles the rest.

Example : Suppose you’re a retail trader with no programming knowledge. You activate Pocketful’s API, connect it to an algo platform, and enter your simple logic “If Nifty falls 1%, sell.”

Now, when the same market conditions arise, the system will automatically execute the trade without coding, without any technical hassle.

Algo Trading relies on thinking and strategy, not coding. Traders who intelligently craft their logic consistently outperform. Coding is now an option, not a necessity.

Myth 3: Algo Trading Always Leads to Profits

The Myth : Many traders assume that applying algorithms to trading will eliminate the possibility of losses. They believe that machines are more accurate than humans, so Algo Trading means “profit every time.” This belief is one of the most common and dangerous Algo Trading myths.

The Reality : Algo Trading is not a magic tool. It simply executes your strategy in a disciplined and emotion-free manner. If your strategy is incorrect or incomplete, the algorithm will produce the same results. Market conditions constantly change; the same logic doesn’t work all the time. Therefore, it’s important to constantly backtest, optimize, and review any strategy.

Furthermore, slippage, latency, and sudden market events (such as RBI policy announcements or geopolitical news) also impact performance. Therefore, an algorithm simply means automation, not a guarantee of profit.

Example : Suppose you’ve created a momentum-based algorithm that buys when the price rises. When the market is trending, it works very well. But when the market goes sideways, the same algorithm starts taking entries on incorrect signals, leading to losses. Therefore, it’s important to periodically refine the algorithm and optimize it according to changing market conditions.

The advantage of algo trading is that it brings discipline, but not certainty. Profit or loss depends on the quality of your strategy, market conditions, and risk management. A successful trader is one who constantly understands, tests, and improves their algorithm.

Myth 4: Algo Trading Requires a Lot of Money

The Myth : Most people believe that Algo Trading requires significant capital, an expensive setup, and numerous technical tools. They believe it’s only for those with millions of rupees in capital and high-end computer systems. This perception scares small traders away from even getting started.

The Reality : This is no longer the case. Today, in 2025, Algo Trading has become cheaper and easier than ever before. No longer does anyone need expensive servers or heavy software. On platforms like Pocketful, you can open a Zero AMC account and generate your own API for free. This API connects your trading to any Algo platform, allowing you to automate your strategy without significant capital. Cloud-based servers are now available for ₹300–₹500 per month, allowing even retail traders to take advantage of the automation.

Example : Let’s say you have just ₹5,000 or ₹10,000 in capital. You open an account on Pocketful, create an API, and set up your trading logic on a platform like Vertex. The system will now execute trades for you every day based on that logic, at no extra cost. This process is as cheap and easy as trading on a mobile app.

Myth 5: Once set up, Algo Trading “runs automatically”

The Myth : Many people believe that once they’ve set up Algo Trading, they don’t have to do anything; the system will automatically trade continuously, make money, and take care of everything. This is a “set it and forget it” approach. This thinking is a major misconception, often leading to losses for new traders.

The Reality : Many people believe that once they’ve set up Algo Trading, they don’t have to do anything; the system will automatically trade continuously, make money, and take care of everything. This is a “set it and forget it” approach. This thinking is a major misconception, often leading to losses for new traders.

Example : Suppose you’ve created a strategy that auto-trades Nifty futures twice a day.

One day, if the internet suddenly goes down or there’s a brief API glitch, your order could be delayed.

If you’re monitoring, you can immediately stop or correct it.

But if you leave the system completely unattended, that same delay could lead to losses.

Myth 6: Algo Trading is Completely Illegal in India

The Myth : Many people still believe that algo trading in India is against SEBI or exchange regulations.

The belief is widespread on social media and old forums that if a trader executes automated orders, their account may be blocked or they may face fines.

This fear keeps many new investors away from this modern technology.

The Reality : In fact, algo trading is completely legal in India provided you do it within the guidelines set by SEBI. SEBI already permitted API-based trading in 2022, and now every authorized broker is required to provide verified API access to its registered users.

This means that if you use the API of a recognized platform and execute your own strategy, it is considered completely compliant. Its purpose is to maintain market transparency and control, ensuring that no unregulated bot or auto-buy/sell script operates without oversight.

Example : Let’s say you’re running your strategy through a recognized API.

The system records every order associated with your name and client ID and verifies it within SEBI’s risk framework. If there’s a mistake or error, the order is immediately rejected or paused; this control is what makes it completely legal.

Myth 7: Algo Trading and High-Frequency Trading (HFT) are the same thing

The Myth : Many people believe that Algo Trading and High-Frequency Trading (HFT) are the same thing. According to them, each algorithm places millions of orders per second, and that’s why institutions control the market. This thinking is wrong and this misconception keeps many retail traders away from Algo Trading.

The Reality : In fact, Algo Trading and HFT are two different technologies. Both use algorithms, but the purpose and scale are completely different. Algo Trading refers to automated trading based on predefined logic, which can be performed by any trader, retail or professional. High-Frequency Trading (HFT) occurs at the institutional level, executing millions of orders in microseconds. This requires ultra-fast connectivity and co-location servers, which ordinary investors do not have.

Comparison

Aspect	Algo Trading	High-Frequency Trading (HFT)
User	Retail and Institutional Traders	Institutional Firms Only
Execution Speed	Milliseconds to Seconds	Microseconds
Cost	Cost-effective (Cloud or API)	Very expensive (Dedicated Servers)
Objective	Logical Automation	Speed-Based Arbitrage
Access	For everyone	Limited, under regulatory control

Example : Suppose you’ve created a strategy that trades the Nifty index based on RSI and moving averages. This strategy executes trades two or three times a day—this is Algo Trading.

Now a large firm is executing arbitrage trades in microseconds from a co-location server at NSE—this is HFT. Both have different objectives and are not substitutes for each other.

Myth 8: Algorithms are smarter than humans

The Myth: Many people believe that once an algorithm is created, it becomes smarter than humans and will make the right decision in every situation. They believe that machines are free from emotions and therefore can never make mistakes. This thinking leads many traders to blindly trust them, and this is where the mistakes begin.

The Reality : An algorithm is certainly fast, but not “smart.” It only does what you teach it, no more or less. If your rules are incomplete or market conditions suddenly change, even an algorithm can make the wrong trade. Machines can read data, but they don’t understand context. For example, if there is a major economic change in the budget one day, the algorithm may take a trade in the wrong direction based on past data. Therefore, human decisions and market sense are always essential. A successful trader is one who trusts the algorithm but monitors the final decision.

Example : Suppose your algorithm is based on a trend-following strategy. It consistently buys at rising prices. One day, the government suddenly implements a new tax rule, and the market immediately reverses. The algorithm places an order in the previous direction, resulting in a loss. If you had monitored it, you could have prevented it.

Myth 9: If a strategy is successful in backtesting, it will yield similar profits in the live market.

The Myth : Many new traders think that if their strategy performs well in backtesting, they will achieve the same results in the live market. For them, backtesting means “final approval,” meaning that if the strategy showed a profit on past data, it will always work. But the reality is quite different.
The Reality : Backtesting is an initial test of any strategy, not a guarantee of success. Because conditions in live markets are constantly changing, many factors such as volatility, slippage, liquidity, internet delays, and human intervention affect results. Sometimes, traders optimize a strategy so much that it only performs well on past data; this is called curve fitting. Such strategies fail in real-time because they aren’t prepared for changing conditions. Therefore, successful algo traders always conduct forward testing and paper trading to verify the strategy in live conditions.
Example : Suppose you created a breakout strategy that consistently showed profits based on the past three years of data. But when you deployed it in the live market, false breakouts began occurring, and the strategy went into losses. The reason is simple: market behavior changed, but the strategy remained the same.

Myth 10: Complex Algorithms Are Always More Profitable

The Myth : Many traders believe that the more complex a strategy, the greater the profit.

They think that by adding a lot of indicators, ratios, and conditions to an algorithm, it will work perfectly in every market situation.

This is why many beginners waste both time and money creating unnecessarily complex systems.

The Reality : In the trading world, complexity doesn’t always mean efficiency.

In fact, the more conditions you add, the more your algorithm is prone to “curve fitting.” Such strategies may produce excellent results on historical data, but fail in the real market because they lose flexibility. The most stable and successful strategies are often simple ones, such as trend-following, momentum, or mean-reversion, which have fewer indicators and clear logic.

Simple systems are easier to understand, maintain, and optimize.

Example : Let’s say you’ve created an algorithm that incorporates RSI, MACD, Bollinger Bands, EMA crossovers, and five other filters. This strategy produces excellent results in backtesting, but when you run it live, performance drops due to lag and conflicting signals. In contrast, a simple moving average-based strategy works consistently because its logic is clear and stable.

Myth 11: Algo Trading doesn’t require risk management

The Myth: Many people think that when the system is trading automatically, there’s no need to worry about risk. They believe that the algorithm can handle every situation and prevent losses. This thinking is extremely dangerous, because automation doesn’t mean “risk-free.”

The Reality: Every strategy, whether manual or automated, comes with risks.

An algorithm does what it’s told. If you don’t include risk-control parameters, it can even increase losses. Therefore, it’s important to include rules like stop-loss, maximum drawdown limit, and position sizing in every algorithm. Furthermore, it’s wise to include emergency halt (kill switch) or circuit-breaker logic so that the system can stop itself in case of an unexpected situation.

Example: Suppose your strategy involves intraday scalping and you forget to set a stop-loss. If the market suddenly reverses, the algorithm will continue to take trades, increasing losses. However, if a risk limit is set in the system, it will automatically close at the set loss.

Myth 12: Algo Trading is Only in Equities

The Myth: Many traders believe that Algo Trading is limited to the stock market or the equity segment. According to them, it is not applicable in derivatives, commodities, or forex.

The Reality: Today, Algo Trading is used in almost every segment—equities, futures, options, commodities, and currencies. Trading APIs and cloud-based systems have made multi-segment trading much easier. Now, you can automate trades in Nifty futures, gold contracts, or USD-INR pairs from a single system.

Example: An options trader can automate their strategy—such as, “If Nifty goes up 1%, close a short straddle.” Or a commodity trader can set up auto-entries at moving average crossovers in gold futures.

Myth 13: Algo Trading Requires Expensive Data Feeds

The Myth: Many people believe that algo trading requires high-speed and expensive data feeds, which only large institutions have access to. Because of this, retail traders think they can’t perform well without accurate data.

The Reality: Today, almost all registered brokers in India offer real-time market data APIs to their clients at a very low cost. Furthermore, cloud platforms come with pre-integrated data connections, eliminating the need for a heavy subscription. Historical data is also now easily available online, making backtesting and analysis easier than ever.

Example: A retail trader can run a daily strategy by pulling intraday prices and volume data from their broker’s basic data API. They don’t need an institutional-grade feed; just reliable internet and a stable platform are sufficient.

Myth 14: Algo Trading Means Zero Emotional Involvement

The Myth: Many traders think that emotions have no place in Algo Trading and that once automation is introduced, the role of humans is eliminated.

They believe that factors like fear, greed, or patience no longer matter.

The Reality: Although Algo Trading reduces emotional errors, the role of humans does not disappear. Behind every strategy lies a trader’s thinking, logic, and judgment.

The algorithm only executes what the human tells it. If the trader changes their strategy or stops early in panic, those same emotions also affect the automation.

Example: Sometimes a trader believes the market will move in the opposite direction and shuts down the system mid-trade, even though the system’s logic is still valid. In such cases, it is human emotion that causes the loss, not the algorithm.

Myth 15: Algo Trading will completely replace humans

The Myth : Some people believe that in the future, the need for human traders will disappear and algorithms and AI will take over. This fear is especially prevalent among traditional traders, who believe that automation will take over their jobs.

The Reality: Algo Trading doesn’t replace humans, but rather empowers them. Machines are fast, but they lack judgment, creativity, and adaptability. When a market event occurs, such as a policy change, a geopolitical crisis, or an emotional panic, only humans can make the right decisions. In fact, the world’s most successful funds adopt a human-machine approach, where logic is based on automation. It is based on data, but the direction is determined by humans.

Example: Suppose geopolitical tensions increase in the global market one day. The algorithm takes normal trades based on historical data, but an experienced trader immediately stops the strategy and saves capital. This is the difference between humans and machines.

Conclusion: The future of Algo Trading is not “machine vs. human,” but “machine with human.” The trader who balances both will be the real winner in the future.

Read Also: Top Algorithmic Trading Strategies

Conclusion 

Ultimately, Algo Trading isn’t magic, but rather a clever tool. It frees you from emotions and brings discipline and precision, but success still depends on human thinking, strategy, and control. Technology helps the decision is still yours.

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