Algorithmic trading

Introduction

Algorithm-based trading includes the use of API access and trading automation using the same. In other words, it is a trade generated using automated execution logic.

In algorithm-based trading settings, the system automatically monitors stock prices and initiates an order when meeting a predetermined request. This system eases the burden on traders as they do not have to monitor stock prices in real-time and place manual orders.

Trading Algorithm in Practice

The trader follows these simple trading methods:

● Buy 50 stocks in stock if its 50-day average exceeds the 200-day moving average.

● Sell stocks if its 50-day moving average is less than the moving average of 200 days.

Advantages of Algorithm Trading

Algo -trading offers the following benefits:

● Trading is done at the best prices.

● Trading order is fast and convenient

● Trading is planned and done quickly to avoid major price fluctuations.

● Reduce operating costs.

● Simultaneous automatic testing in multiple market conditions.

● Reduce the risk of manual errors when trading.

● Algo-trading can also be tested using available historical and real-time data to determine if it is a viable trading strategy.

● Reduce the risk of human error based on emotional and psychological factors.

Algorithm trading strategies

The following are trading strategies used in algo-trading:

• Trend Following Strategies

The most common algorithmic trading strategies include moving average trends, channel outflows, price movement, and related technical indicators. It may be easier to use algorithmic trading strategies because they are not involved in any kind of price prediction or prediction. Commercialization is based on the potential for desired trends, which are very easy to implement using algorithms without complex analysis. The use of 50- and 200-day moving averages have become very popular.

• Arbitrage opportunities:

If you buy a stock that is listed twice at a lower price in another market and sells it at a higher price in another market, the price difference has no related risk and thus a risk-free profit is called arbitrage. The same process is used in stocks compared to future instruments as the difference in price exists at different times. Identifying such price differences and placing smooth orders has the potential for profitable arbitrage.

• Index Fund Rebalancing:

Index values ​​refer to periods that re-measure hold to balance with the help of appropriate indicators. This creates a range of profitable opportunities, which they can spend on the expected 20- to 80-point profit margin and the number of stocks in the index fund before the index fund is renewed. Such trades are done on time and are listed at the best prices.

• Strategies Based on the Mathematical Model

Statistical models, which include a mid-delta trading strategy, as well as an option or combination of options that are less secure.

• Trading Range

Mean strategy reversion strategy is based on the idea that high or low commodity prices are temporary and are consistent with their average value on a regular basis. Proper recognition and definition of price range and the use of an algorithm allow trading to take place automatically when the price of an asset enters and exits its predetermined range.

Technical Requirements for Algorithmic Trading

. The following are the technical requirements for Algorithmic Trading:

1) Computer programming information should be familiar with the required trading strategy programs; one can hire programmers or pre-made trading software.

2) Network communication and how to use trade platforms to place orders is a basic thing to have.

3) One should also have access to market data feeds to monitor the algorithm for arbitrage opportunities while placing orders.

4) System evaluation, appropriate infrastructure, and skills are required before we live in real markets.

5) Previous data acquisition is required for retrospective testing as well as a piece of information for a set of complex rules that are useful for algo trading.

Example of Algorithmic Trading

20 short shares of INR / USD if INR / USD rises above 1.2. For every 5 points that go up in INR / USD, close short with 2 shares. For every 5 points that fall in INR / USD, increase the short area by 1 share

Buy 100,000 shares in ONE PLUS if the price drops below 100. For every 0.1% price increase above 100, buy 1,000 shares. For every 0.1% decrease in the value of less than 100, sell 1,000 shares.

Regulation by SEBI to regulate Algorithmic Trading

As mentioned earlier, Sebi proposed an algo-based trading framework by trading investors made using API access and automated trading initiatives. In the case of algorithms used by store investors using APIs, it is difficult to identify algo-based trading details.

“This unregulated/unregulated algo threatens the market and can be misused to exploit markets in an orderly fashion and to attract potential investors by assuring them of high profitability. The potential losses in the event of an algo strategy fail largely for investors. As these suppliers/sellers of foreign companies are not regulated, there is also no way to address investor grievances, ”said the Department’s discussion paper.

Therefore, Sebi suggested that all orders “coming out of the API should be considered as algo orders and be under the control of stock traders and that the trading APIs of Algo should be marked with the unique algo ID provided by the -Stock Exchange grant. authorization of algo “.

The market regulator also said that the stockbroker “needs to get the approval of all the Algo Exchange. Each Algo strategy, whether used by a trader or client, must be approved by the Exchange and as is the current practice, each algo strategy must be approved by the Certified Information Systems Auditor (CISA) / Diploma in Information System Audit (DISA). ). Sebi urges stockbrokers to use the appropriate technical tools to ensure that appropriate checks are in place to prevent “unauthorized alteration / algo adjustment”.

The market regulator also suggested that stockbrokers could provide in-house algo strategies developed by an authorized dealer or outsourced the algo provider / seller of a foreign company by making a formal agreement with each third-party supplier/dealer for its services. are used by the seller.

It adds that the stock trader is responsible for all algos from its APIs and for resolving any investor disputes.

“The obligations of a stockbroker, investor and third-party provider/broker/dealer must be defined separately. The stockbroker is responsible for assessing the investor’s suitability before offering an algo location. No recognition will be given in exchange for the third party algo provider/seller who creates the algo, ”said Sebi.

Sebi said two-factor authentication should be built across such a system that provides access to the investor in any API / algo trade.

The market regulator sought public comment until January 15 on his proposal to trade algo..

Conclusion

Algorithmic trading is where you use computer codes and software to open and close trading according to established rules such as price movement points in the lower market. If current market conditions are similar to any predetermined conditions, trading algorithms can buy or sell orders for you – saving you time by eliminating the need to scan the markets in person.

Credits-

Content- Ishita, Sahil Pruthi, and Kashish

Infographics- Charvi, Vandita