Algotrading for retail: how to trade bots without millions

In 2023, Renaissance Technologies, one of the most closed—end funds in the world, once again showed what most consider impossible: more than 60% per annum, and at a stable distance.

There are no brilliant traders at the monitor, no "market senses" — just code, statistics and billions of dollars that seem to find their own way to profit.

Investors received higher premiums than in any US bank. Guaranteed income, minimal risks, and a beautiful legend about “money that earns itself.”

But is it really that simple?

What is hidden behind the dry word algorithm, which promises to get rid of emotions, fatigue and mistakes?

Is it possible to transfer decision—making to your program and still sleep soundly?

And most importantly, where is the boundary between automation and the illusion of control?

We used to think that the future of the market has already arrived. That robots trade better than humans, and everyone now has access to smart strategies. But is it worth believing in it enough to entrust the code line with the fate of the deposit?

Let's try to figure it out. Without pathos and without promises of easy money — just facts, figures and a bit of irony.

(If you are not yet familiar with the principle of speculating on price differences, I advise you to start with our article on CFD trading in order to understand the basis of how the automated trades market works.)

How many percent of the market is occupied by algorithms: the real share of algotrading in 2025

When analysts talk about "increased volatility" or "abnormal volumes," most imagine traders furiously clicking Buy and Sell in the hope of catching a move.

But in reality, these are not people. This is the code.

According to JP Morgan, today more than 70% of transactions on the US stock market are carried out by algorithms.

In Forex, this figure is even higher — about 92%, according to statistics from Bank for International Settlements.

Yes, ninety-two.

That is, while a private trader is thinking about whether to open a long in EUR/USD, the market manages to fly through hundreds of micro transactions that he does not even know about.

The irony is that it is those who believe in the "manual mastery" of trading who most often compete not with other people, but with bots. Algorithmic trading works around the clock, trades on micro—spread shifts, analyzes correlations between sectors - and does it without coffee, sleep, or emotional breakdowns.

If you look at these numbers, it's not a disaster — it's an evolution.

The market has become mathematical, and a person simply ceases to be the main player. But an important question remains: what role does a retail trader have in a world where price is shaped not by supply and demand, but by speed and code logic?

The answer is not as hopeless as it seems. Some of the tools that once cost millions are now open to everyone. Let it be in miniature, but with the same principles.

(→ If you are still at the stage of manual analysis, I advise you to start with an article about the RSI, MACD and VWAP indicators — they most often become the foundation for the first trading algorithms.)

How to launch a trading bot for a private trader: Pine Script, Python and other tools

When it comes to algotrading, many people have pictures of server rooms, engineers with glasses, and formulas on a blackboard in their heads, as if we were talking about NASA, not the market.

In fact, everything is much simpler. Today, a retail trader can assemble his algorithm in just an evening — and this is no exaggeration.

Let's start with the most popular tool, Pine Script.

TradingView didn't just invent the language, it made it an accessible entrance to automation.A couple of lines of code and your indicator turns into a system of signals. A few more minutes and she is already sending notifications or even opening deals (via connection to a broker). The main advantage of Pine is its transparency: you see how the logic works, you can change it and test it on history.

But if you want more control, welcome to the Python world.

Everything opens up here: API access to exchanges, connection to brokers, statistical analysis, machine learning, and real-time order management. It sounds complicated, but it's essentially the same Excel, only without restrictions and with the potential to manage transactions rather than spreadsheets. There are ready—made libraries — ccxt, Backtrader, Zipline - that allow you to run a robot even without deep programming knowledge.

Another important element is cloud servers (VPS).

The same “vigilant bot” that works while you sleep needs a place to live. The VPS allows you to keep the algorithm online 24/7 — without fear that the lights will turn off or the laptop will fall asleep. This is what turns a retail trader from an observer into a player who can automate not only the analysis, but also the transactions themselves. However, it's worth remembering: automation is not a magic button. Each script is still the same strategy, just without hands and emotions. And if the logic of the strategy is lame, the bot will simply make mistakes faster and more stable than a human.

(→ If you trade through prop firms, check out the material about online prop companies — many of them already allow the use of trading bots and API access to automate transactions.)

How algotrading works: the path from strategy to the first trade

At first glance, everything is simple: I wrote a strategy, pressed "Run" — and watch how the score grows. In reality, there is a whole ecosystem of solutions, checks, and potential pitfalls between the idea and the deal. Algorithmic trading does not start with code, but with logic.

You need to understand what exactly you want to automate: trend strategy, pullbacks, breakouts, or level work. Code is just a tool, and it will follow your mistakes with the same zeal as it follows your discoveries.

When the idea is formulated, backtesting begins — checking the strategy on historical data. This is the moment when most traders first encounter the harsh truth: what looks beautiful on a chart often loses its luster in numbers. Fitting a story is an eternal disease of beginners. The code gives out +300% of last year's profit, but in reality it breaks down after the first news from the Fed.

Next is optimization and filters. We add restrictions on volume, volatility, and hourly ranges. We set up risk management: stops, takes, protection from repeat orders.

Does it sound boring? But in vain. This is where sustainable systems are born. Without these layers, the code turns into a poetic manifesto — beautiful, but useless.

The algorithm then switches to real-time. Through an API or a broker gateway, it begins to read the flow of quotes and execute orders. Each decision is not a "guess/miss", but a statistically calculated action with a known risk in advance. This is where many people realize that algotrading is not magic, but a discipline in numbers.

Do you want an example of the irony of fate?

Most algorithms break not because of the market, but because of... the Internet. Yes, yes, a connection failure, an overflowing buffer, a hung server — and the “genius bot" turns into a silent observer. Therefore, professionals duplicate the systems, install protective filters, and even send important signals to Telegram. Algotrading is not only about logic, but also about engineering thinking.

Why automation does not guarantee profit: the main mistakes in algotrading

The main misconception of beginners in algotrading is simple: “the bot is smarter than me, so it won't make a mistake.”

Spoiler alert: he'll make mistakes—and often. Just without emotion.

The problem is not with the code, but with the people who write it. Automatic trading does not eliminate the human factor — it only packages it into a script. If a trader does not understand how the market works, the bot will repeat the same mistakes, only faster and more disciplined. The most common mistake is overfitting, or fitting a story. When an algorithm perfectly trades the past, but is powerless against the future. In the tests, the chart is like a stairway to heaven, in reality — three losing days in a row and the error "division by zero".

It would be funny if it didn't hurt so much.

Another problem is ignoring market regimes. The algorithm written for the trend is simply dying in the sideways. He continues to “look for momentum” when the market has been standing still for a long time. That is why professionals always keep several strategies with different logic, distributing risks between them.

Well, the classic is the lack of control. A retail trader launches a bot and goes to work, confident that he will return to profit. But the algorithm is not an employee. He doesn't adapt, doesn't learn from mistakes, and doesn't understand the news. On the day of the release of CPI data or the Fed report, he can open a position against the flow simply because the code does not say “do not touch the market in case of panic.”

There is also a downside. Algorithms are disciplined to the point of callousness. They don't get greedy, they don't take revenge on the market, and they don't “wager.” And that's their strength. But only if their logic is built correctly. So automation is not a “way not to think.” It's a tool that enhances what you already have. If the strategy is bad, the bot will speed up the drain.If the system is well thought out, it will save you from routine decisions and human disruptions.

The future of algotrading: Artificial intelligence and trading automation in 2025

If in the early 2010s the market seemed to be an arena between people and machines, now this line has almost been erased.Algotrading has ceased to be the prerogative of funds with billions of dollars in budgets.It has become a tool available to anyone who is willing to understand at least a little bit about the code and data.In 2025, the key word is intelligence.Not the one in the trader's head, but the one embedded in the algorithms.

AI systems no longer just follow orders - they learn.They analyze news, read the tone of tweets, predict volatility through machine learning models, and even adjust their own parameters in real time. What seemed like “Bloomberg fiction" five years ago is now working in retail terminals. But with this comes a new dilemma.

Previously, a trader relied on a strategy, but now he relies on a model trained on data that he himself does not always understand. And here the main question arises: who controls whom — a bot trader, or a bot trader? Automation is evolution, but not salvation. It does not negate the understanding of the market, it simply stops forgiving it. Every mistake is now more expensive because the execution speed is equal to the loss rate. But the potential is higher: one well-functioning algorithm is able to overtake the market month after month.

Most likely, everything is moving in this direction. Not to a world without traders, but to a world where the trader and the code act as partners. One sets the direction, the other does not make mistakes in arithmetic. The irony is that the smarter algorithms become, the more human understanding is valued—the ability to interpret, adapt, and feel the moment. AI can count billions of data, but it doesn't yet know what "intuition after a stop" is. And this is where the retail trader still has an advantage.

FAQ: Frequently Asked Questions about algotrading

Is it possible to make money on algotrading without programming experience?

Yes, you can. Platforms like TradingView allow you to create simple strategies in Pine Script — even without knowledge of Python. But it is important to understand that “without code” does not mean “without logic.” If you don't understand how the strategy works, no bot will make it profitable.

What programming languages are used for algotrading?

The most popular are Python, Pine Script, and MQL5 (for MetaTrader).

Python is a universal choice for API, machine learning and optimization.

Pine Script is the best start for retail, especially if you work with TradingView.

How many percent of transactions in the market are made by algorithms?

According to JP Morgan and Bank for International Settlements, more than 70% of stock market transactions and about 92% of Forex transactions are performed by algorithms. That is, most of the volume is no longer people, but code.

Is it possible to run a trading bot on your home computer?

Theoretically— yes, but in practice it is better to use a VPS server.

It provides a stable 24/7 connection and protects the algorithm from failures.

A bot that freezes due to a Windows update is not the best way to test a strategy.

Do I need a broker for algotrading?

Yes. The trading bot works through the broker's API, which allows you to send signals and execute trades. Without a broker, a bot is just a program that does not send orders anywhere.

Is it possible to use trading bots in prop firms?

Many modern online prop firms already allow the use of trading bots if the strategy is transparent and does not violate risk limits.

Is AI trading possible for retail?

Yes, and it's already working. AI models analyze news, social media, and the tone of headlines, helping algorithms adapt to the market.

But it's important to remember that artificial intelligence enhances strategy, not replaces it.

What are the main risks in algotrading?

— Overfitting (fitting the story).

— Errors in the code and network connections.

— Ignoring fundamental events (Fed reports, CPI, earnings).

The main risk is to assume that the bot will "do everything by itself."

How much does it cost to launch your own trading bot?

The minimum cost is from $ 10-30 per month for a VPS + API subscription.

If you use Python, add the cost of data and testing (about $20-50 per month).

You can start Pine Script on TradingView for free.

Is it worth switching to algotrading in 2025?

Yes, if the goal is to systematize trading and remove emotions.

Not if you're looking for a "magic profit button."

Algotrading is not a substitute for a trader, but his amplifier.