Abstract
Modernization in computers and Machine Learning have created new opportunities for improving the methods involved in trading, Changes have been noticed parallelly at the level of investment decisions, and at the faster executions of trades via algorithms. Nowadays 90% of the trades are placed by algorithms, to execute a transaction, algorithms that follow a trend and construct a set of instructions are used in algorithmic trading. It executes the trades more precisely by precluding the effect of human feelings on trading. It all started way back in the 20th century and nowadays it’s becoming more and more competitive, with more big players entering the market every day. Our research aims to advance the market revolution by developing an Algorithmic Trading approach that will automatically trade user strategies alongside its own algorithms for intraday trading based on different market conditions and user approach, and throughout the day invest and trade with continuous modifications to ensure the best returns for day traders and investors.
Highlights
Black-box trading is known as “Algorithmic trading”, is a mechanism of performing traditional trades without any human interposition, it is basically a digital version of trading strategy that could be based on the event, price, patterns, news, quantity, mathematical model, etc
It is becoming very competitive day-by-day, earlier only actuary’s and institutional traders have access to the data and they took advantage and increased the Sharpe ratio and annual returns, Studies shown a new algo-trading trend emerged out of the blue, Fin-Tech enabled mobile apps have been deeply penetrated into the Trading market with the help of cheaper data plans provided by big Indian telecom giants
Anyone who doesn’t know how to write a code is not encouraged as it might lead to poor results/returns, so to solve this issue some of the platforms created no code algo-trading services these platforms allow you to trade without any coding knowledge helps the user to backtesting and automate the trades based on Rule-based strategy
Summary
Black-box trading is known as “Algorithmic trading”, is a mechanism of performing traditional trades without any human interposition, it is basically a digital version of trading strategy that could be based on the event, price, patterns, news, quantity, mathematical model, etc. Chinthapalli Amarnath Reddy, Department of Computer Science Mallareddy College of Engineering and Technology, MRCET Campus Hyderabad, India like jio , airtel, etc, resulted in the rise of retail trades. These fin-tech-enabled trading applications got approved way back in 2010 by the Securities and Securities and Exchange Board of India (SEBI) but it wasn’t as prevalent as it is today. Few advantages of algo trading: a) Historical Assessment (Backtesting) b) Efficiency c) Rule-Based implementation d) Comparison e) Higher Frequency
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