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Algo Trading
Algo Trading

In today’s time, computers play an essential role in determining our lifestyle. That, in turn, influences how different sectors operate these days, making a prominent reliance on computer to run operations. Use of technology is really very much effective and influencing in all the fields.

Like many other sectors, stock markets, too, have started utilizing the capabilities of computers to facilitate trading. In algo trading, computer program makes suggestions to the traders by recording and analyzing their previous trading actions.

To define algo trading from a more theoretical perspective, let’s say it is the execution of stock marketing by using a predefined computer program. The algorithmic trading AKA algo trading is about feeding an algorithm (or a set of instruction, to make it easier to understand) into computer programs so that it can execute a trade when command conditions are met.

Fret not if the bookish definition makes it sound difficult to you to understand. Here we will break down the fundamentals of algorithmic trading to simplify the concept for you. And help you get a grip of the must-dos to ace algorithmic trading for optimum benefit!

The main funda of Algo trading with example

What works best in explaining the fundamentals of stock market trading is accompanying them relatable examples. That’s what we will do here taking a case study of share trading that most of you can relate.

Say, you meet a guy named Rahul, who looks up to moving average of last seven days to estimate price trend and determine trading options. In fact, Rahul says that he monitors DMAs regularly to decide if he would go long or short, depending on the prices going above or below the DMA.

Algo Trading 101 – Everything best you must know about it! 1
A trader works on the floor of the New York Stock Exchange (NYSE) in New York, U.S., on Wednesday, Jan. 2, 2019. U.S. stocks pared declines after a brutal start, with financial shares rebounding from a dismal December and crude staging a rally. Treasuries trimmed gains. Photographer: Michael Nagle/Bloomberg

Now, this exact behaviour can be fed to a computer program to instruct the system on deciding Rahul’s trading action in advance. That is, we can set an algorithm that would buy 200 shares of an entity if the price goes above the 7-day simple moving average and vice versa.

That’s algo trading, and the fundamental algorithmic principles behind it. We can definitely add other matrices depending on the trader’s preference. The computer will execute market data to make a trading decision as soon as the command conditions are met.

Why algo trading?

If you are curious to know why you need algo trading (or at least give it a try), you have to start thinking of it from the very beginning. Otherwise, no matter how many points we layout in front of you, it would sound like a purposive rant, and you won’t be convinced. 

  So, here’s a question for you. Why the world is relying on technology as much as it can?

Done with the thinking? If your answer is ‘feasibility’, you are right. Technology makes everything easier for us. No matter what your requirement is, a proper technology can deliver you most effective outcome with minimum to zero error, and it’s time savvy.

AI or artificial intelligence is a further advancement in the field of technology adoption by business sectors as well as households. The exciting thing about AI is that it can record past behaviour, track current data and perform actions accordingly. Moreover, it requires human effort to build the initial software only. After that, it can develop the model itself and improves it over time. Won’t you want this feasibility as a trader, especially when many of us already struggle with the complexity of the stock market? If yes, algo trading is what you need.

Moreover, emotional trading decision is a concern for many traders. In fact, the most rational and smartest trader too fall into emotional trap at once (practically speaking, not just once). That is reasonable because the basic principle of decision-making tells us that emotion does play a role in determining human actions. The correlation is quite prominent in case of stock trading. Traders often pursue over-optimism (or gets irrationally pessimistic about market conditions) and make trading decision driven by strong emotions. And that’s something, we can say, causes a trader’s nemesis.

The reason that algo trading is considered a promising alternative is that your greed or fear do not influence the trading here -automated trading works based on previously set criteria. So, it is absolutely free from human emotions associated with trading and dependent on data-driven algorithm. Also, in machine trading, you can enjoy the benefits of backtesting and optimization. In manual trading, it’s difficult to identify accurately what works for you and what does not. algo trading can do this exact thing in seconds by running an algorithm on past data recorded. This allows the system to know if certain things worked for you in the past, and take decisions accordingly.

Algo trading strategies

The theory behind any algorithmic trading strategy is to identify profitable trading opportunity, i.e. reflects improved earnings as well as is cost-efficient. Despite this common purpose, each strategy is different in terms of its take to identifying the opportunity.

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Trend-following strategies

The most widely recognized algorithmic exchanging methodologies follow DMA trend, channel breakouts, price movements, and other technical indicators associated with it. Here, computer software uses previous data to identify a trend and takes actions accordingly. These are the most straightforward and most uncomplicated procedures to practice algorithmic trading.

It is more so as these strategies don’t include making any price estimations or market predictions. It facilitates trading depending on favourable trend, which is simple to practice through algorithms keeping apart the complicity of predictive analytics. Utilizing 50-and 200-day DMAs is a well known trend-following technique. Tracking DMAs regularly allows the software to decide on behalf of a trader if the trader should go long or short, depending on the prices going above or below the DMA.

This trend-following strategy of algo trading works primarily because of the long list of emotional mistakes and behavioural biases that a trader can make. However, the noteworthy point here is that the trends won’t last forever. Especially, once it reaches the peak, it can exhibit a swift reversal. Therefore, traders have to be cautious about high volatility that this strategy carries. It is, therefore, essential to focus on proper risk management techniques and time your buys and sells to avoid losses.

Arbitrage opportunities

Algo trading strategies often use computer functions to identify arbitrage opportunities as soon as possible. Traders can thereafter make use of the identified arbitrage opportunity to gain more profit. Purchasing a dual-listed stock at a lower price in one market and all the while selling it at a higher price in another market offers the value differential as risk-free arbitrage or profit.

A similar activity can be performed for stocks versus futures instruments. The reason is that price differentials do exist over a period. Executing a program to identify such price differentials and placing orders accordingly can create beneficial opportunities to the trader.

Index fund re-balancing

Index funds need defined periods of rebalancing to make their holdings at par with respective benchmark indices. This makes beneficial trading options for algorithmic traders, who benefit from expected trading that offer 20 to 80 basis points profit for the number of stocks in the index fund just before index.  Algorithmic trading initiates such trading for timely execution of trade at the best price.

Mathematical model-based strategies

The Mathematical Model-based Strategies are about maintaining the portfolio delta at zero. In Mathematical Model-based Strategies, it places the trades to offset the positive and negative deltas to maintaining the portfolio delta at zero. These strategies of algo trading work on a combination of options and its underlying security to meet the requirement. One prominent example of such Mathematical Model-based Strategies can be delta neutral strategy. Other Mathematical Model-based Strategies can appear profitable depending on the goal and objective of the trader. 

  • Mean reversion (It assumes the high and low prices to be temporary phenomena that revert to the mean value over periods.)
  • VWAP (Volume-Weighted average price, where the algorithm breaks up a large order into dynamically set smaller set of orders using stock-specific past volume profiles.)
  • TWAP (Time-weighted average price, where the algorithm breaks up a large order into dynamically set smaller set of orders using equally divided time slots between start and end time.)
  • POV (Percentage of Volume, where the algorithm creates partial orders as per the market trade volume and participation ratio.)
  • Implementation shortfall (Minimizes execution cost of order)  

A further delve in understanding algorithm trading strategies

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The trading strategy behind utilizing algo trading at its fullest requires understanding the steps involved in setting the right strategy for a particular trader. Like other things, our trading pattern and objectives too vary from other traders operating in the market. So, it would be a foolish thing to implement a strategy that you observe or hear about working for someone else.

For mastering the art of stock market trading, you have to be open to ideas and observe what’s happening around you. But that does no way mean that you adapt to a herd mentality and sought after what certain experts are suggesting. The suggestion coming from the desk of an expert is something you must note, as it consists of years of real experience and knowledge that the expert possesses.

However, when it comes to decision-making, it’s crucial to put your goals first and analyze strategies accordingly. So, in case you feel you need an expert-suggestion or find someone’s advice interesting to try, have a one-to-one chat and present your case there. You will not only have a clearer understanding of the strategy, and you can actually learn how to implement the strategy for maximum benefit.

There are plenty of strategies that you can select from for algo trending. Each strategy has an algorithm set to ensure compatibility with its purpose. So, the algorithm executes the orders accordingly to meet your requirement. An interesting thing to mention here is that, though the system is automated and works on its own, it’s the trader setting the algorithm. So, the trader is the one who select which strategy to follow depending on personal goals and market conditions.

Machine learning in trading

Machine learning in trading is used to predict significant short-term movements in price levels at a particular confidence level. Machine learning in algo trading is beneficial to eliminate certain common problems associated with algo trading models. In most of the cases, the strategy models are usually static, that is they don’t change over time unless some human intervention is made.

However, machine learning allows trading models to analyze a sufficiently large volume of data. Also, it can improve the modelling through such analysis.  

Technical requirement for algo trading

Implementing the set of rules or the algorithm using algo trading software requires nothing more than a standard laptop or PC with mid-level configuration. The most challenging part is to convert the recognized method into an inclusive automated procedure. Here we mean making the backtesting and optimization work effectively to have access to the trading account, analyze data to place trading orders.

Lots of debate still surrounds the meaning of software architecture. Here, in the context of the said purpose of this article, we define software architecture as an infrastructure that can specify, deploy, and execute application components providing user functionality. A computer software system has to satisfy its functional and non-functional requirements to support algorithm trading efficiently.

One thing that we have to mention alongside the technical requirement is the non-functional requirement of the system architecture. In other words, the requirements for machine trading or algorithmic trading can be divided broadly into these two areas. Non-functional requirements specify measures by which system performance is measured. A concerning part here is that a computer software system satisfying its functional requirements, may still not meet user expectations.

Let’s explain this issue with an example to make it more apparent to the readers. Say, an algo trading software submits trades but not on time. Here, despite the software performing the set functions, it fails to meet the efficacy standard and would cause financial losses to the trader.

The non-functional requirements that algo trading software has to take into consideration can make the process complicated to an extent. Moreover, the obligations evolve over time with new requirements coming into the scene. So, the only way to meet these obligations and make the software work like a charm is to be careful about the requisites for designing and implanting the architecture.

Benefits of algo trading

If algorithmic trading is creating a buzz these days, that’s because it appears to be significantly beneficial over manual trading. Machine trading minimizes the errors that often reduce the credibility of trading manually.


Since algorithms for algo trading are written beforehand and performs automatic executions, the key advantage is speed. In fact, the speed is measured in fractions of second in case of algorithmic trading. This is undoubtedly faster than what humans can ever perceive. Human actions always seem to appear time-consuming and require a remarkable degree of patience and dedication to get the work done accurately within a given time frame. In the case of computer operation, the impact of time constraint on the process is reduced. This allows the traders to avail more opportunities and better prices in stock trading.


Let’s talk human here. Happens to us all, right? There lies the comparative advantage of machine trading. In executing trading automatically, an algo trading software can help you avoid pitfalls associated with manual entry of market and trading data.

The computer software is made to ensure that it enters the correct order for the trader based on previously recorded data. So, you can act smart by relying on an algorithm that is tested by the experts to identify and omit human errors.

As a human, we cannot nullify human error; that’s impossible from both practical and scientific perspective. But we can adopt technology to safeguard us from the ill impacts of these human errors on us. That’s the main advantage of algo trading to put it simply.

Reduced trading cost

Are you one of the very many people, who feel that the trading cost is eating their profit? This space is for you then. Let’s address the transactional cost here. If you are doing manual trading, it is must for you to monitor the market as much as you can, so that you don’t miss an opportunity. That raises the transactional cost in hefty.

But with automated trading, the algorithm allows you to utilize trading opportunities without continuous supervision. As you reduce the cost of supervising the market continuously, it reduces the time for trading and thereby lowers the transactional costs.   

Now when we make it clear to you the basics of algo trading as well share the smart strategies, it’s time to act on it. Analyze your trading pattern today, and go automated for a more efficient, profitable trading experience. If you are skeptical about trying this new trading style all by yourself, you can consult an expert. That’s going to make your trading experience better without any mess or stress!

Algo trading Plans | Only for Fyers & Alice Blue Demat account holders

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Type 1 : Copy my signals and trades

Plan A : Open your demat account with us in Fyers and Alice Blue

  • Trade with Rs. 3 Lakh+ capital : No any kind of charge
  • Trade with Rs 1-3 Lakh Capital : Rs. 999 monthly per user per month for algo trading server cost.
  • Less than Rs 1 Lakh : You can’t copy our tradesOpt Plan C/ Plan D

Plan B : Already have your demat account in Fyers or Alice Blue

  • Charges : Rs 1999 / user per segment per month. Note : If Capital Less Than 1 Lakh | You Can’t copy my trades – Opt Plan C/ Plan D

Type 2 : Don’t want to copy my signals and trades

Plan C : Open your demat account with us in Fyers and Alice Blue

  • One time installation : Rs 4999 + Rs 1999 monthly charges per use per month for live data feeds along with alog trading server cost.

Plan D : Already have your demat account in Fyers or Alice Blue

  • One time installation : Rs 9999 + Rs 1999 monthly charges per use per month for live data feeds along with algo trading server cost.