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Where exactly is Datamatics headed after 100% returns in 3 months?



About Company:

Datamatics offers consultancy, IT, data management, and business process management services. Robotics, artificial intelligence, and machine learning algorithms are used in its services. The company’s headquarters in Mumbai is present throughout America, Australia, Asia, and Europe.

The business was founded in 1987 and first provided computer and electronic data processing services. Later, information technology-enabled services with robotic process automation were introduced.

Share price – 587.05 (-1.05%) -7.40 on 14-06-2023

Market cap – 3461 crores.

  • The stock has given a Break out of the cup and handles breakout pattern in the daily chart.
  • We can see the volumes of the stock were also increasing as on 31-05-2023 it was 600.06K and on 01-06-2023 there was 1.68milliom stock was traded.
  • This shows that a lot of money has been invested in the stock, which is a good signal to Buy.
  • If we see in a monthly chart the stock was in consolidation from the last 2 years in the range between 230 to 370 which it broke in May month.
  • The stock is showing a positive movement in the daily and monthly chart as it is above its 50 Moving average and 50 Exponential moving average and the RSI is 70, which shows the stock will go more upside.

Fundamentals of Stocks:

  • The stock has a P/E of 16.5 and the sector P/E is 29 which shows the stock is undervalued.
  • ROE is almost debt free
  • The ROCE of last year is 25%
  • ROC for the 1 year is 65% and for 2 years it is 280%

 Future Target:

  • In the upcoming 12-18 months the stock can reach a target of 950-1000.


Why is Algorithmic trading popular?



What is the basic meaning of an Algorithm?

Before we learn about algorithmic trading let u see what is an algorithm. An algorithm is a basic set of instructions that is used to solve a set of problems or to perform a set of computations. The algorithm finds its use in mathematics and computer science. A stock market is a market in which a trader uses his analytical skills and research skills to perform trades. When we apply a technical indicator to a chart, the calculations behind the indicator are all algorithms. Let us see how a basic algorithm looks like

We understood what an algorithm looks like from the above image. Now let us see a brief introduction to trading.

What is trading?

Stock market trading involves buying and selling shares of various companies. A trader who wishes to trade opens a Demat account through one of the discount brokers. Then he can add stocks to his watchlist, from where he begins to trade. When the trader wishes to buy stocks from a company, he places a buy order, and he buys stocks from the stock market, similarly when a trader wishes to sell stocks, he places a sell order, which enables him to sell stocks to the market. In this trading, the trader does trading manually without the use of algorithms or computer programs. This kind of trading is called manual trading.

Disadvantages of Manual trading

  • A trader is a human filled with human emotions such as fear of loss, revenge on previous loss, and other behavioral biases. If he trades based on these emotions, he will take illogical trading decisions.
  • In the stock market, every trade takes milliseconds to execute. A manual trader, if he has less experience in trading may take much time to complete his trade. Though this delay is not much significant, can incur a few losses to the trader.
  • A manual trader will not be able to multitask. For example, he finds it difficult to monitor various companies’ shares or various modes of investments like stock, commodities, and derivatives at the same time.

To overcome the shortcomings of manual trading, algorithmic trading came into use.

What is algorithmic trading?

Algorithmic trading involves the usage of computer codes to enter or exit the trade once certain criteria in the stock market are met. This trading is also known are algo trading and also known as automated trading. There are various trading platforms that use algo trading software that provides algorithmic trading to users. Prominent algo trading software in India is

  • Zerodha Streak
  • Zerodha Algoz
  • Tradetron Tech
  • Algo Test
  • Quantiply
  • Algobulls

History of Algorithmic Trading

In the early 1970s New york stock exchange introduced the “designated order turnaround” system. In this system, orders are electronically routed to trading posts. After introducing electronic markets, NYSE came up with program trading. This program trading consists of pre-programmed trades to automatically enter and exit trades depending on various strategies. This “program trading” was initially used in index arbitrage. Index arbitrage is a trading strategy that strives to benefit from the price movements of various indexes. We will see how algorithm trading came into the scene after the initial introduction by NYSE.

  • In 2001, the decimalization changed the minimum tick size from US$ 0.0625 to US$ 0.01 per share. This could have triggered liquidity in the market leading to the usage of computer algorithms to execute orders at better prices.
  • In 2001 IBM published a research paper at the Joint Conference on Artificial Intelligence. Two algorithmic strategies are shown in this paper which continuously outperforms human traders.
  • Many broker-dealers were offering algorithmic trading strategies to clients such as Chameleon by BNP Paribas, Stealth by Deutsche Bank, Sniper, and Guerilla developed by Credit Suisse

Studies in 2006 showed London Stock Exchange consist of 40% of trades by algorithmic traders and by 2008 European and American markets consisted of 80% of algorithmic traders. Algorithmic trading and High-frequency trading(HFT) have been the subject of public debate since the US Securities and exchanges commission and Commodity futures trading commission said in reports that an algorithmic trade entered by a mutual fund company led to the 2010 Flash crash.

Languages used in Algorithmic trading

Python– Python is a high-level, general-purpose programming language, which acts as a support language for software developers, building control, management, and testing. It is easy to use and versatile, and a larger population uses Python.

Java- Java is a high-level, robust, object-oriented programming language and secure programming language

C++- C++ is one of the world’s popular programming languages which is found in operating systems, Graphical user interfaces, and embedded systems.

R- R is a language and environment for statistical computing and graphics.

Let us take examples to understand Algo trading better.

Examples of Algo trading

We will consider that trader A is planning to buy stocks of company X. He is a person who trades depending on moving averages. If trader A wishes to do short-term trading he chooses a 12 or 26-day moving average(MA). On the other hand, if he chooses to do long-term trading he chooses 50-200 MA.

If the short-term moving average cross over the long-term moving average it creates a bullish pattern and when the short-term moving average crosses under the long-term moving average bearish pattern is formed. So If trader A is applying algo trading to this trade, he applies for programs in such a way that the program places a buy call when the bullish pattern appears or places a sell call when the bearish pattern appears. Thus, trader A does not need to fix his views on the price movement, but just use algo trading instead.

Here the input is given in terms of moving average, sometimes in long-term trading, if an investor wishes to buy a stock once it gives 4% higher returns as compared to its present return, an algo trading helps the investor achieve it without the anxiety of overlooking it. Similarly, the investor can sell it if it gives a lesser return than expected.

Instead of using only one factor like moving average or return percentage, algo trading can give commands with a combination of controlling factors too.

Types of Algo trading

  • One type is Bridges, where a trader buys a 3rd party algo trading platform and adds it as a plug-in to his currently using trading platform. For example, if a trader uses Zerodha for trading, he can choose an algo software like AlgoTest. This AlgoTest is compatible with IIFL, Fyer Duck, Trading View, Zerodha, etc.
  • API is an Application programming interface. Here the trading platform provides the algo software in its platform itself. These Algos which the broker provides to its customers are known as discretionary algorithms. For example, Zerodha offers Zerodha Streak and Angel One offers Smart API.

Algo trading strategies in the market

  • Trend strategies
  • Arbitrage opportunities
  • 52-week low-high
  • Mean reversion strategy
  • Momentum strategy
  • Statistical arbitrage and much more.

Does SEBI allow Algorithmic Trading?

SEBI is the regulator of the stock market in India, it monitors any activity that poses a threat to investor’s safety and security of funds. SEBI issues regulations whenever it notices abnormality in the market. Likewise, SEBI has mentioned in its notice that ” StockBroker is responsible for all the algos emanating from its API and redressal of any investors dispute. Definition of obligations of stock broker, investor, and 3rd party algo vendor is necessary. The stock broker is responsible for assessing the suitability of the investor prior to offering the algo facility. SEBI does not recognize 3rd party Algo providers. The stock broker has to make sure the 3rd party algo provider with whom the broker has an agreement, shall use the name of the broker as part of their testimonial, provided agreement-related advertisement guidelines are met”.

Is Algo trading a pressing priority?

There are several advantages of Algo trading like

  • High speed

The time taken to execute a trade in algo trading is very high in comparison with manual trading. When a large number of trades executing happens in the market, algo trading executes it in a second, thus making a profit using the buy/sell spread.

  • High accuracy

As the orders are pre-entered in the algorithms, the probability of errors is very less. We can achieve a very accurate order execution

  • Negligent behavioral bias

There are lots of behavioral biases by which a trader tends to lose money like loss aversion bias, confirmation bias, ownership bias, Gambler’s fallacy, Anchoring, Herd mentality, and, much more. Algo trading eliminates all biases and avoids losses due to human emotions.

  • Backtesting

Backtesting is a strategy used to test a financial model on previously available data. A trader can achieve more success by improving the time he performs backtest on historical data to improve the accuracy of the model.

Algo trading is already been widely used by QIPs, mutual fund companies, insurance agencies, etc. But SEBI issues guidelines and regulations to protect retail investors from frauds happening from unregulated sources in the stock market. Algo trading will gain momentum and popularity in the future and SEBI will be monitoring all the activities of both brokerage firms and 3rd party algo vendors. Before choosing any algo trading platform or strategy, investors should remain vigilant in protecting their money.

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Market Basics

The Impact of Options Trading on Stock Prices: A Comprehensive Analysis



Options trading can have a significant impact on stock prices, both directly and indirectly. In this article, we will explore the various ways in which options trading influences stock prices, including through delta hedging, volatility effects, and market sentiment.

1. Delta Hedging

Delta hedging is a trading strategy used by investors to mitigate the risk of changes in the price of an option by buying or selling the underlying asset. For instance, if an investor purchases a call option on a stock, they may also buy shares of the stock to offset the risk of a potential price decrease. This buying pressure created by delta hedging can contribute to pushing up the stock price.

2. Volatility Effects

Volatility plays a crucial role in options trading and can indirectly impact stock prices. Options prices tend to be higher when there is higher market volatility and lower when volatility is low. Investors are willing to pay more for options when they expect significant price movements in the underlying asset. Thus, an increase in options trading activity can lead to higher volatility in the underlying asset, which, in turn, may result in higher stock prices.

3. Market Sentiment

Options trading can be a reflection of market sentiment, which is a measure of how bullish or bearish investors feel about a particular asset. When there is a substantial amount of options trading on a specific stock, it can indicate a strong bullish or bearish sentiment towards that stock. This sentiment can influence stock prices in the direction of the prevailing sentiment.

4 . Supply and Demand Dynamics

The primary ways options trading impacts stock prices is through changes in supply and demand dynamics. As investors buy and sell options contracts, it affects the perceived interest in the underlying stock. When there is a surge in demand for call options (the right to buy the stock), it indicates bullish sentiment, potentially leading to higher stock prices. Conversely, an increase in demand for put options (the right to sell the stock) signals bearish sentiment and could result in lower stock prices.

5. Volatility and Implied Volatility

Options trading can introduce additional volatility to the stock market. The prices of options themselves are influenced by market volatility expectations, which are measured by implied volatility. If there is heightened uncertainty or news events surrounding a stock, implied volatility may rise, leading to more expensive options. As a result, the stock price may experience larger swings as traders adjust their positions to factor in the changing volatility.

6. Options Expiration and Pinning

Options have an expiration date, and as that date approaches, traders may adjust their positions or decide to exercise their options. This behavior can lead to increased trading activity and volatility as the expiration date nears. Additionally, “options pinning” or “options max pain” refers to the phenomenon where the stock price gravitates toward the price that causes the most options contracts to expire worthless, benefiting options writers. This pinning effect can influence short-term stock price movements, especially around expiration dates.

7. Hedging Strategies

Market makers and professional traders use options as part of their hedging strategies to manage risk in their portfolios. When they sell options, they often hedge their positions by buying or selling the underlying stock. This hedging activity can affect the stock’s price by creating additional buying or selling pressure. For instance, when market makers sell call options, they may buy the underlying stock to hedge against potential losses, leading to increased demand and higher prices.

8. Impact on Investor Sentiment

Options trading can impact investor sentiment and perception of a stock. Unusual options activity, such as a surge in call buying, may be interpreted as a signal of positive expectations for the stock’s future performance. On the other hand, heavy put buying might lead to negative sentiment and dampen the stock’s price.

9. The Small and Indirect Impact

While options trading can have a notable impact on stock prices, it is essential to understand that this influence is typically more pronounced in the short term rather than the long term. The effects can be more significant for highly liquid stocks with higher volatility levels. However, in general, the impact of options trading on stock prices might be small and challenging to predict due to the complexities of the options market and other influencing factors.

Option Pricing Model

Here is a table of the most common option pricing models:

Black-Scholes modelA mathematical model that uses five inputs to price options: the strike price, the current stock price, the time to expiration, the risk-free rate, and the volatility.
Binomial modelA discrete-time model that prices options by assuming that the underlying asset can only move up or down by a certain percentage in each time step.
Monte Carlo modelA simulation-based model that prices options by randomly generating a large number of possible price paths for the underlying asset.
Heston modelA stochastic volatility model that prices options by assuming that the volatility of the underlying asset is itself a stochastic process.
SABR modelA simplified version of the Heston model that is easier to calibrate and use.

The Black-Scholes model is the most widely used option pricing model, but it is not without its limitations. The model assumes that the underlying asset follows a geometric Brownian motion, which is a continuous-time random walk. This assumption is not always accurate, especially in the short term. The Binomial model and the Monte Carlo model are more accurate than the Black-Scholes model, but they are also more computationally expensive.
The choice of which option pricing model to use depends on a number of factors, including the type of option, the time to expiration, and the volatility of the underlying asset. In general, the Black-Scholes model is a good starting point, but it may be necessary to use a more complex model if the underlying asset is volatile or if the option has a long time to expiration.
Black-Scholes modelSimple to use, widely availableAssumptions may not be accurate
Binomial modelMore accurate than the Black-Scholes modelComputationally expensive
Monte Carlo modelMost accurate option pricing modelComputationally very expensive
Heston modelMore accurate than the Black-Scholes modelAssumptions may not be accurate
SABR modelSimplified version of the Heston modelLess accurate than the Heston model


Options trading can exert both direct and indirect influence on stock prices. Delta hedging can create buying pressure on the underlying asset, pushing up stock prices. Volatility effects can result in increased options prices and subsequently higher stock price fluctuations. Additionally, options trading activity can reflect market sentiment, leading to stock price movements in the direction of prevailing sentiment. However, it is important to recognize that the impact of options trading on stock prices is typically more pronounced in the short term, and predicting its effects can be challenging. As with any investment activity, thorough research and consideration of the risks are crucial when engaging in options trading.

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Finance World

Market Operators: Driving Stock Market Efficiency




In the complex stock market world, various players are involved, each with their distinct roles. Market operators among these participants are essential in enabling and controlling trade operations. Market operators, sometimes referred to as exchange operators or stock exchange operators, are organizations in charge of regulating the operation of stock exchanges, fostering a positive trading environment, and guaranteeing honest and open market practices. This blog explores market operators’ roles, effects, and difficulties within the financial ecosystem to shed light on their existence and relevance in the stock market.

Understanding Market Operators’ Roles

Businesses oversee and manage the primary exchanges where financial instruments like stocks, bonds, and derivatives are bought and sold. These market intermediaries link buyers and sellers, typically commercial businesses or nonprofit institutions.

1. Creating and maintaining a Trading Platform: Market operators create a reliable trading platform where investors can place deals. This entails putting the required technical framework for high-frequency trading in place, keeping up order matching systems, and ensuring that trading operations run without interruption.

2. Market regulation: Market administrators uphold laws and norms to keep the playing field level for all participants. They take action to stop insider trading, market manipulation, and other illicit activities.

3. Listing and Delisting: Market operators oversee the procedure for companies to be listed on the stock exchange and make sure they adhere to strict eligibility requirements. To protect the caliber and reputation of the listed companies, they also supervise the delisting of businesses that no longer adhere to the exchange’s rules.

4. Market Surveillance: Market operators constantly watch trade activity for any suspicious or out-of-the-ordinary behavior that could jeopardize the market’s integrity. They work to quickly spot any market abuses by utilizing cutting-edge surveillance equipment.

Market Operators’ Effects on Trading

1. Liquidity and Efficiency: Market operators promote liquidity by giving buyers and sellers a centralized platform where they may quickly identify counterparties for their deals. As a result, securities are exchanged at fair and open prices, which improves market efficiency and price discovery.

2. Investor Confidence: Knowledgeable market operators running a well-managed stock exchange boost investor confidence. The market operators’ competence and efforts lead to more people participating in the market with increased confidence in the safety of their investments and the limited risk of market manipulation.

3. Market Innovation: Market actors frequently drive innovation in the financial sector. They consistently work to provide cutting-edge trading procedures, better technologies, and new trading tools that can adjust to shifting market dynamics.

4. Economic Growth: An efficient stock market, managed by skilled market participants, can promote economic growth. It promotes entrepreneurship and investments across various industries by giving businesses access to finance via the issuance of stocks.

Issues Facing Market Operators


Despite playing a crucial role, market participants face several difficulties in ensuring efficient market operations:

1. Technological Complexity: The dynamic nature of the financial markets necessitates an advanced and durable technological foundation. They must invest in technology to guarantee continuous trade, fend off cyberattacks, and manage growing data quantities.

2. Compliance with Regulations: Market participants are subject to strict regulatory frameworks directing business conduct. Complying with these rules can be difficult and time-consuming when launching new goods and services.

3. Market Fragmentation: As financial markets have become more internationalized, the proliferation of several trading platforms has exacerbated market fragmentation. To ensure seamless trade, they must develop a mechanism to link these dispersed marketplaces.


Market operators are essential to promoting a fair, effective, and transparent trading environment. They guarantee market integrity and investor confidence by giving investors a platform to trade on and implement market laws. Market participants continue to adapt and innovate despite obstacles like technical complexity and regulatory compliance, making a substantial contribution to the expansion and stability of the global financial system. Understanding their function as investors and stakeholders enables us to make wiser choices and better navigate the volatile stock market.

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