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Algorithmic Trading india

Algorithmic Trading is a systematic trading that utilizes very advanced mathematical models for making transaction decisions in the financial markets. It’s all about organizing quantitative algorithms to progression, observe and administer trading decisions. In simple words Algorithmic trading is use of automatic software before investing in financial market. Stock exchanges across the globe are planning to legalize algo trading. India is one of the first among all the stock exchanges to regulate algo trading.

Experts say since algo trading is a cutting edge application it must be traded, regulated, executed and monitored properly. This automatic trading software offers its users facility of swift execution of trades and quicker recognition of arbitrage opportunities. It allows trader to focus on researching strategies and securities by eliminating the time involved in trade execution. At present, nearly 17 per cent to 18 per cent of trading on the National Stock Exchange (NSE) and Bombay Stock exchange (BSE) is following algorithmic trading concept and is expected to rise by 60-70 per cent within next four years.

Algo trading procedure starts with creation of a trading strategy. This human made trading strategy is then converted into automatic software also called algo by experts. Software experts create this tactic trading on basis of certain parameters and convert it into high level computer language. Algo means computer aided software and is divided into two parts. The first part of algo is detection of a selling or buying opportunity which involves exact time to buy or sell and what to buy or sell (asset class- debt, share, equity, mutual fund, currency, and commodity). The other part is the implementation logic which describes how the trade will be carried out. Price, volume, timing, etc are some of the aspects of algorithms.

Operating Algorithmic trading is not an easy task due to complexities involved in it. It requires special skills and proficiency. It necessitates understanding of strategy or domain knowledge and code development. Code development demands a powerful command over high level computer programming language where as strategy or domain knowledge simply involves deeper knowledge of prevailing stock trends in various sectors. Many trading consultancies took advantage of opportunity and established their own training programmes and institutes. This Demand for algorithmic trading jargon has grown swiftly in money market.

Major benefit of automated trading is that it can instantly track the financial market and order the trades when positive conditions are favorable. This automated software can perform several activities which could not be done manually. To name some, to make crucial decision on the basis of complicated calculations, ordering a trade the moment it becomes available. Automated trading is mainly used by the high class financial institutions and investors and is considerably being identified all over the world.

Algo trading is here to stay and it is the future of trading,'' said Deena Mehta, chairperson of the capital market committee of the IMC and former director of the Bombay Stock Exchange.Dr Gangadhar Darbha, executive director of a securities firm said, Algo trading is not about technology alone. It will change the entire trading environment.''

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High Probability Trading Strategies

Algorithmic trading involves the use of electronic platforms in order to enter trading orders with an algorithm that decides on various aspects of the order like timing, price, and quantity of the order. In many cases it also initiates the order without human intervention.Pension funds, mutual funds, and other buy side (investor driven) institutional traders make extensive use of algorithmic trading to divide large trades into several smaller trades with an aim to manage market impact, and risk. Sell side traders, like market makers and some hedge funds, brings liquidity to the market, resulting in the automatic generation and execution of orders.

" High Probability Trading Strategies " is a special class of algorithmic trading, where computers make detailed decisions with an aim to initiate orders on the basis of information received electronically, much faster than human traders can process the information they observe. As a result, a dramatic change has occurred in the market microstructure, especially in the context of how liquidity is provided.Any investment strategy, like market making, inter-market spreading, arbitrage, or pure speculation (including trend following) may use algorithmic trading.

Some of the investment strategies that are followed in today's scenario are:

1. Trend following : This investment strategy tries to take advantage of long-term, medium-term, and short-term moves occurring in various markets. Traders using this approach apply current market price calculation, moving averages and channel breakouts for the purpose of determining the general direction of the market and for generating trade signals.

2. Pair trading : This is a market neutral trading strategy that enables traders to profit from almost any market condition, whether it is uptrend, downtrend, or sidewise movement.

3. Delta neutral strategies : This describes a related financial securities portfolio where the value of the portfolio remains constant owing to small changes in the value of the underlying security.

4. Arbitrage : Arbitrage is defined in different ways. An economist and a finance person would define it as the practice of availing the benefit of a price difference between two or more markets. This helps to strike a combination of matching deals that can capitalize upon the imbalance. And the resulting profit is the difference between the market prices. An academician would define arbitrage as a transaction that at any probabilistic or temporal state does not involve any negative cash flow but involves a positive cash flow in at least one state. Simply said, it is the possibility of a risk-free profit at zero cost.

5. Mean reversion : This is a mathematical methodology that is used for stock investing. However, it can be applied to other processes as well. The idea behind mean reversion is that both the high and low prices of a stock are temporary and that the price of a stock price tends to have an average price over time.

6. Scalping : This is another method of arbitraging small price gaps that have been created by the bid-ask spread. Scalpers make an attempt to act like traditional market makers or specialists. Making the spread implies buying at the bid price and selling at the ask price, resulting in a gain on the bid/ask difference.

7. Transaction cost reduction : Majority of strategies that are referred to as algorithmic trading (as well as algorithmic liquidity seeking) fall into this category. Here large orders are split up into several smaller orders, that are entered into the market over time. This strategy is called "iceberging".