Basics of Algorithmic Trading: Concepts...
The algorithm can be based on a variety of factors such as pricing, timing, quantity, and other variables. Market participants gain from algorithmic …
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This exodus seems to be accelerated by the introduction of revolutionary technology and its innovative use. Some of the changes that are already manifesting will develop to their full potential such as automated financial advisory online and the use of blockchain. With the appropriate regulatory intervention, the future of trading could be a more egalitarian and inclusive one.
High-frequency trading is increasingly pervading modern financial markets, especially stock markets. It uses algorithms to evaluate markets and carry out orders, taking into account the prevailing market conditions. It enables not only the speedy execution of orders, but also high turnover rates. High-frequency trading has also extended access to financial markets to a larger number of participants globally, creating a surge in opportunities, volumes and volatility.
Although popular in equity markets currently, high-frequency trading will come to be used for other assets such as bonds, foreign exchange, options and futures as well. It has also led to traders widely embracing the strategies of straddle, strangle and butterfly spreads. High-frequency trading is among a plethora of complex strategies that have been under the scanner of regulators to assess their effect on the stability and integrity of the market.
High-frequency trading will better the quality of markets, increase efficiency, create more liquidity and narrow spreads. Propelled by developments in machine learning, high-frequency trading has helped make markets more efficient by allowing price formation, improving linkages and lowering the cost of trading.
The future of trading in financial markets will largely be dependent on developments in artificial intelligence. The shift from humans to algorithms for financial advice is already evident in many financial firms. Moreover, as machines learn from exchanges between people without necessarily being programmed for it, they can pick up on frauds and other anomalies, recognise new patterns, and automate and expedite timely decision making.
As more and more financial information becomes available to investors and traders, it will become difficult for humans to keep tabs on it all. Such an explosion of information can only be collated, read and understood by automation and artificial intelligence. AI will be able to analyse, gather and interpret the large availability of data and learn from it. This will assist high-frequency trading and fund managers.
This does not necessarily mean that AI will come to replace humans in the trading space. In fact, experts argue that the final call will still be with investment advisors or other human professionals who possess emotional intelligence.
Algorithms are already being used to assess risk profiles, financial goals and other investment details in order to create personalised investment portfolios. This may give rise to customisable robo-advisors accessible just a click away - on your web or smartphone. They will be able to self-learn and book profits or allocate funds.
Such a breed of advisors will be cheaper than a human professional, and may come with an annual fee. In the future, such advisors could also be poured into a digital avatar, not unlike virtual assistants available today.
Passive investments are on the rise and are speculated to continue growing in the future. They facilitate accurate identification of opportunities and trends around the world, and are expected to become more complex in the future.
A good example of passive investment is exchange-traded funds (ETFs) which pool finances raised from a number of investors in order to buy assets like bonds, shares and derivatives. Such passive investment strategies are focused on making maximum returns with minimal buying and selling, by using a buy-and-hold strategy for the long term. It is attractive to investors given that it is cheaper, simpler and more tax-effective.
ETFs that use derivatives have had a history of being dangerous for the overall market. Now, as ETFs are expanding to other asset classes than equities and becoming more complex, it would be wise to watch out for the repercussions of the speed with which they allow trades to take place, or their reaction to a surprise external event. Regulators must keep an eye out for these passive investment products and gauge their effect on the market.
Blockchain is the technology behind cryptocurrencies such as Bitcoin. It is a ledger of transactions in which information is stored in a chronological manner. While transactions such as cheques and trades on the stock market are controlled by a central authority and take time to process, blockchain transactions are carried out within minutes, and help banks save money. Moreover, they are less likely to be manipulated. In the future, banks will perhaps be some of the first institutions to adopt blockchain.
The Reserve Bank of India (RBI) cautioned against Bitcoin in 2013. It has since changed its position and now holds that blockchain technology can help in the prevention of fraudulent transactions and counterfeiting of currency. Moreover, a consortium of 30 big banks has been formed to step up research on blockchain solutions and design.
Decentralised Finance (DeFi), which is based on blockchain is seeing innovations that would revolutionise financial products. In the future, it could become more mainstream and make room for smarter transactions and contracts. The absence of reliance on a central body will allow for new-age derivative contracts and prediction markets.
A huge amount of data is produced in financial markets every minute, the storage and evaluation of which is important in real-time. Cloud computing can provide storage as well as instant, real-time access to this large amount of data. Moreover, analytics can make sense of this data quickly and efficiently in ways that humans cannot.
The RBI has raised alarms about this use of analytics. However, the use of technology for such analysis can help predict the market and investor sentiment. This can perhaps be done based on social media reactions to news around a company and alter the way investors trade.
Evidently, the future of trading will be heavily reliant on groundbreaking technology and how it can be leveraged and used in various forms. Although there is much scepticism around some pieces of technology such as blockchain, future innovations will be able to draw them out to the mainstream and encourage investors’ faith in them.
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