BY DIVYAN AGGARWAL
Evolving has been a part of human nature from the beginning of time. This need to constantly evolve has been the leading factor behind the intellectual growth and technological advancement that we as a society have achieved over the course of history.
Economies of the world have been introduced to one such technological advancement by the name of Algorithmic Trading. Algorithmic trading (also called automated trading, black-box trading, or algo-trading) uses a computer program that follows a defined set of instructions (an algorithm) to place a trade. The trade, in theory, can generate profits at a speed and frequency that is impossible for a human trader. The defined sets of instructions are based on timing, price, quantity, or any mathematical model.
Let us understand this with an example:-
Suppose an investor makes trades on the basis of this criteria:
Buy 100 shares when it’s relative strength index falls before 30. (Relative strength index is a technical indicator that helps measure whether a share is overbought or oversold.)
Sell the shares when it’s RSI surpasses 70.
On the basis of this information the algo programme will buy or sell the shares when the conditions are met.
Benefits of Algo Trading
Trades are executed at the best rate precisely on time to avoid any significant price changes.
Multiple trade orders can be placed accurately and instantly at reduced transaction cost.
Multiple market conditions can be studied simultaneously and the best strategy can be formulated based on historical and technical data available.
Chances of human errors based on emotional and psychological factors are eliminated.
Algo Trading Strategies
Any strategy for algorithmic trading requires an identified opportunity that is profitable in terms of improved earnings or cost reduction. The following are common trading strategies used in algo trading:
1. Trend Following Strategies- The most common strategy is following trends such as RSI, price movement, volume etc. Executing trades on completion of these pre-set trends is one of the simplest algo trading strategies as it doesn’t involve any price prediction.
2. Index Fund Rebalancing- To bring their holdings up to par with their respective benchmark indexes, index funds have set rebalancing periods. This generates attractive opportunities for algorithmic traders, who earn from projected trades that yield 20 to 80 basis points profits right before index fund rebalancing, depending on the number of stocks in the index fund. For timely execution and the best prices, such deals are initiated using algorithmic trading algorithms.
3. Mathematical Model-based Strategies– Proven mathematical models, like the delta-neutral trading strategy, allow trading on a combination of options and the underlying security.Delta neutral is a portfolio approach that uses several positions to balance positive and negative deltas, resulting in a total delta of zero for the assets in issue. When the price of the underlying security changes, the delta measures how much the price of an option changes. The Geeks’ position will move between positive, negative, and neutral as the underlying assets’ values alter. Investors that want to keep their portfolios delta neutral must modify their holdings accordingly. Options traders employ delta-neutral tactics to profit from either implied volatility or option time decay. Delta-neutral strategies are also used for hedging purposes.
4. Mean Reversion- Every stock’s high and low prices are transient, and they tend to revert to their mean prices on a regular basis. Identifying and establishing a price range, as well as designing an algorithm based on it, permits trades to be done automatically when the price of an asset breaks in and out of its stated range, are all part of the Mean Reversion approach.
5. Percentage of Volume- This algorithm continues sending partial orders until the trade order is entirely filled, based on the defined participation ratio and the volume transacted in the market. When the stock price reaches user-defined levels, the “steps strategy” sends orders at a user-defined percentage of market volume and increases or decreases this participation rate.
These are some of the most common and widely used strategies in algo trading. As we can see, implementing such algo trading strategies allows the traders to take maximum advantage of the market by maximizing profits and minimizing risks.
Development of Algo Trading in India
The concept of algo trading has started taking shape in the Indian market. However there are certain underlying concerns in the mind of the market regulator: Securities and Exchange Board of India. The services of algo providers are being increasingly used by investors. However, one the major problem is that these algos based on API (Artificial Programming Interface) are being implemented without the required requisite approvals from the exchange. It is impossible to distinguish algo and non algo trades as APIs can not be traced back to the brokers. This kind of unregulated and unapproved algos pose a risk to the market and can be misused for systematic market manipulation as well as to take unfair advantage of new investors. Since these third-party algo providers and vendors are unregulated, there is also no investor grievance redressal mechanism in place.
In response to such concerns SEBI has issued a consultation paper. “There is a need to create a regulatory framework for algo trading. All orders emanating from an API should be treated as an algo order and be subject to control by stock broker and the APIs to carry out algo trading should be tagged with the unique algo ID provided by the stock exchange granting approval for the algo. Stock broker needs to take approval of all algos from the exchange. Each algo strategy, whether used by broker or client, has to be approved by exchange and as is the current practice, each algo strategy has to be certified by Certified Information Systems Auditor (CISA)/ Diploma in Information System Audit (DISA) auditors.” SEBI paper says.
SEBI has proposed that a system should be developed that provides unique identification ids to algo trades so that they can be traced back to the brokers who have access to client orders, order confirmation and margin information. Such a verification system would help ensure transparency and accountability.
Conclusion
Thus it can be concluded that algo trading will deepen the stock markets and aid retail investors who are not full-time engaged in stock trading and more such advantages. However, its regulated implementation in the markets of the world will take some time. It will require efforts from both, the regulatory bodies and the market to adapt to this concept. But once implemented it has the potential to bring about numerous opportunities for investors in the future through its unprecedented benefits.
ABOUT THE AUTHOR
Hi, my name is Divyan Aggarwal. I like to read about technology, finance and science. I am also very much into sports. I am an avid fan of Football, Table Tennis, Basketball, Tennis, F1 and UFC. I myself am a National Level Table Tennis and Taekwondo player. I live my life by one of my favorite quotes of all time, “We are not happy when we are winners, we are winners when we are happy.”
Disclaimer: The views expressed in this article are the author’s own and do not necessarily reflect the views of the organization.
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