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At present automation has changed our lifestyle. Now we are getting more and more depended on technology day by day. It has changed the way of business/investing. Now we got several types of robots or tech to do our work for us even online trading. In 2008, SEBI allowed automated trading in India. Since then, the number of companies that use algorithmic trading has increased, with current estimates put the figure at 50% of the total volume. This figure is still low when compared to developed countries like the US where trading volume more than that in India, 70-80% of trades done through algorithmic trading. This makes a career in algorithmic trading in India all the more interesting, where the concept is still relatively new in comparison with developed countries. Let’s try to understand 5 essential facts about algorithmic trading in India. Prerequisites Before You Start Algorithmic Trading Both stock exchanges, the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) have different prerequisites before you can get the approval to start algorithmic trading. Technically, a person can become a member of the trade and direct trade through the exchange by meeting certain criteria. The members of the exchange (s) can apply for direct approval by the exchange. On the other hand, non-members can apply for approval through their broker. Approval is a multi-step process the right to participate with the relevant algorithmic trading strategy in a trading environment pretend, get it approved by the auditor to give a demonstration to exchange for the approval of the strategy. One should note that any change in the algorithm must go through an approval process before it can be implemented the exchange. The Role Of Co-Location In The Market It is known that the first to react to the news can use it to their advantage. In the race to be the fastest to respond, most of the high-frequency trading (HFT) firms rent space in a rack server on the same network right on the spot exchange itself. This is referred to as the ‘co-location’. The advantage of co-location of reduced latency, which is the time your system needs to respond to any trigger, as the company can respond quickly when compared with those who house their servers away from the exchange. This idea, your data has to travel less distance, resulting in a faster response. Co-location is generally required only for HFT strategies such as arbitrage, market making, etc. that require a high level of technology and infrastructure spending and therefore used mainly by institutions and proprietary trading houses. Interestingly, India has one of the co-location charges the lowest among peer exchanges worldwide. From the perspective of a retailer or individual, Co-location has led to a more efficient market because of a decrease in bid-ask spreads, as market makers can respond more quickly to new updates and is able to offer much more stringent price. One study by Aite Group a few years ago in the US has pegged the savings to retailers/individuals at nearly $ 250 per year! Type Of Algorithmic Strategies Contrary to popular opinion, not all algorithms designed for high-frequency trading. There are various algorithms other than arbitrage and market-making algorithms designed by institutional investors and retail traders to trade in the market using the algorithm. Some popular algorithms including: Momentum / Trend Following – The algorithm is trying to find the company’s stock price trends by using technical indicators and / or quantitatively different to analyze the available information. Once these are identified, the trader can place a trade depending on the perceived profitability of the strategy. Statistical Arbitrage – One example is a statistical arbitrage trading partner where we see the ratio/spread between a stock price, co-integrated. If the value of spread beyond the expected range, then you buy a stock that has gone down and sell stocks that have outperformed in the hope that the spread will return to normal levels. Statistical arbitrage can work with a hundred or more of the shares in the portfolio are classified according to a number of factors and can be fully automated from the perspective of both analysis and execution. Machine Learning Algorithm Based – In simple terms, the use of historical data and feeding this market for machine learning algorithms that they have been designed. the data is divided into data training data and testing. Machine learning algorithms to learn patterns and features of the training data and trains itself to take a decision as to identify, classify or predict new data or results. algorithms continue to learn from the positive/negative, to improve accuracy and performance. Order-To-Trade Ratios Help Monitor The Market The ratio of order-to-trade is the ratio of the number of orders sent to the exchange, with the number of orders that can be traded. A ratio of 2: 1 would indicate that only half of the total orders received are traded and the rest remain pending or to be canceled/rejected. The significance of this ratio is the fact that the exchange punishes a company with a high frame rate trade as one might weigh on the exchange infrastructure by sending commands that are not expected, or worse, not intended for trading. Indian exchanges enforce penalties on companies that have a ratio of order-to-trade high for orders that prices outside the trading price range mentioned. Development Of Strategies And Research Tools With the advent of online research tools, many traders are increasingly looking out for online resources and backtesting platform in an effort to enhance the trading models and strategies. The latest automated trading platform like SGT Markets been granted access to market data vendors, and also a platform to build and evaluate their algorithmic trading strategies using statistical and computational power. They also use several types of Forex trading signals in order to become more successful because these days every trader uses Forex signals. In the end, algo trading has brought a new era to online trading. Though it’s not 100% dependable but if you stay vigilant then you can profit consistently from this technology.

This Modern world is a gift from technology. With the help of the technologies now people are doing the IMPOSSIBLES. Technology has changed our way of life. At present, there are many different strategies for managing the investment portfolio. But did you know you can automate trading in order to become more profitable than ever? Algorithmic trading stocks automatically place orders based on the price and other conditions. You also may know it by automated trading or robot trading. Automated trading or robot trading is the future of the online trading industry. Before You use ROBOT TRADING, Keep This In mind that you have to research a lot about this platform because it's just a technology. As a result, it can cause mechanical errors. So, you have to choose the best auto trading platform. And also you will have to gain a vast amount of knowledge regarding it. Specifically you've to know -- - The Basics - History of Algorithmic Trading - How It Works - Pros and Cons Therefore, without any further discussion, let's dive right in. Algorithmic Trading: The Basics An algorithm is a procedure where one solves the problem, usually math. Usually, they require the following steps for solving said problem. Also, usually involving repetition. Similarly, algorithmic trading, also called algo-trading, is a computer program trading by following certain steps in a particular order. In short, stock trading through computer automation. Above all, seeks the highest possible returns on trade in the most efficient manner. Also referred to as automated trading or black-box trading, algorithmic trading market using several variables in the algorithm. These variables include price, time, and volume. Algorithmic Trading History The algorithm trading entered the world U.S.financial with a computerized trading system in the 1970s. The New York Stock Exchange took the biggest step in 1976 when it introduced the Order Turnaround (DOT) designated system that send orders to the right of traders to specialist data on the trading floor. In the last decade, automated trading accounts for over 60% of all trades. In 2014, author Michael Lewis describes algorithmic and high-frequency trading with his flash Boys. He explains rear electronic trading infrastructure and talking to traders and business owners who use them. While he noted that the computerized technology can trade even faster than any human. How it works In algorithmic trading, traders take advantage of the computer program to the requirements set to trade. For example, to buy 100 shares when the specified number of shares moved below a predetermined price. Similarly, it could sell 100 shares when it moves above a certain price threshold. The program then monitors the stock price. After fulfilling these criteria, the computer automatically acts in accordance with pre-programmed to buy or sell orders. With algorithmic trading, the trader does not need to manually make a trade. Pros and Cons Algorithmic trading can be a powerful trading tool. As a result, the modern financial world to use it for several reasons. First, it allows to impose trade on the speed and accuracy is much higher than trading manually created. Trades happen almost instantaneously, lower price fluctuation changes between the trader decisions and actual trades. There is also a lower chance of human error rather than as a human trader makes a trade. Meanwhile, automated trading often has lower costs with no human traders involved. But this method is not without its downfalls trading. For one, while the automated algorithmic trading systems can streamline trade, making them more accurate and efficient, there is also the possibility that the system could fail. This can cause investors to lose potential investment opportunities. Having a trading human monitors often wise counsel. It can ensure the trade occurs as specified. The trading method does not account for the emotional aspect of trading. While this may initially seem like a good thing. After all, who does not make a trade only on the basis of emotional experience or anecdote only to have the tank? But algorithms can only take you so far, and in some cases, what works, in theory, may not translate well to the market for various reasons. Think of market volatility, inherent risks, and the like. Using Algorithmic Trading The current financial market using algorithmic trading applications. It is often paired with high-frequency trading, which makes a large number of trades at high speeds in a variety of market sectors. Artificial intelligence has created a deep learning algorithms that look for more profitable trading. As a result of traders and programmers who work on the algorithm become more profitable on their own. institutional investors and brokers greater use Algo trading, but so mutual funds, pensions, and another large-scale investment vehicle. However, hedge funds asking for amateur programmers to write algorithms, pay them a commission for code that is very profitable. High-speed internet and fast, inexpensive computers have made trading algo a favorite among day traders. The Bottom line Ideally, algorithmic trading can achieve both results and the speed of trade traffickers can not. For that reason, it is a cornerstone of the modern financial world. However, this method is not without its downsides, of over-automation for the failure to take into account the real market conditions. In the end, if you want to use an automated trading platforms then you'll also have to make up your mind about losing all your capital. But if you use the rules and regulations and choose the best and trusted automated trading platform then you'll get the results.

Hi guys, algorithmic trading or automated trading has changed the trading systems. Now, with automated trading, a trader can earn more profits in less time. Today, I will discuss some benefits of algorithmic trading. Therefore, without wasting time, let's start. Algorithmic trading (also called automated trading, trading in a black box or algo trading) uses a computer program that follows a set of instructions (algorithms) to exchange. Trade, in theory, can generate profits at a speed and frequency impossible for human traders. The instruction set is defined according to any time, price, quantity or mathematical model. In addition to profit opportunities for traders, automated trading makes the market more liquid and trading more systematic, despite the impact of human emotions on trading activities. Benefits of trading algorithms Automated trading offers the following advantages: The trade is executed at the best price. The placement of trading orders is instant and precise (there is a possibility of high execution at the desired level). The trade is timed correctly and directly to avoid significant price changes. Reduce transaction costs Automatic controls simultaneously on various market conditions. Reduce the risk of manual errors when placing trades. Algo-trading can be retested using historical and real-time data available to see if it is a viable trading strategy. Reduce the possibility of mistakes made by human traders on the basis of emotional and psychological factors. Algo-trading is used in various forms of trading and investing activities, including: Investors or medium and long-term buying companies - pension funds, mutual funds, insurance companies - use Algo to buy large quantities of stocks when they do not want to influence the price of the shares by investing separately. Short-term traders and sellers - market makers (such as brokerages), speculators and arbitrage - benefit from the automatic execution of trades; In addition, algo trading helps to create sufficient liquidity for sellers in the market. Systematic traders - trend followers, hedge funds or two-way traders (neutral trading strategies that combine long positions with short positions in pairs of highly correlated instruments, such as two stocks, traded funds exchange (ETF) or currencies) effective to schedule their trading rules and let the trading program automatically. Algorithmic trading provides a more systematic approach to active trading than intuition-based or trader-based instincts.