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Why trading technology should be accessible to all

(Image credit: Image Credit: David McBee / Pexels)

Digital technologies are transforming the financial services sector with insurance, banking and investment now being remodelled through innovations such as big data analytics, blockchain and artificial intelligence (AI). Trading has undergone major changes in recent years, with algorithmic trading significantly increasing the speed and computing power of transactions in the markets. 

More recently, the use of AI has risen among the world’s top investors and firms. However, as with many emerging technologies, the most sophisticated trading algorithms have been kept in the hands of the elite, not shared with the wider trading community or everyday investors. Here, we take a look at why trading technology should be accessible to all.

For the few, not the many

The development of sophisticated algorithms and big data in trading has provided a significant strategic advantage to those able to get their hands on it. By providing the ability to recognise market and price inefficiencies such as price movement patterns, underrating and overrating, traders are able to react quickly to the markets at the right moment.

Access to these algorithms has so far been restricted to elite and high-end investors for several reasons. Firstly, high end investors haven’t wanted to share this strategy for fear of losing their advantage over competitors. Additionally, the calculating power needed to run algorithmic trading is so expensive that companies have held back this service due to clients’ unwillingness to pay the expense.

These algorithms also require large data sets to analyse for continuous developing, however, this is very costly to gather. Further, once collected, the data can only be utilised for strategic use by those well versed in the understanding of both trading economics and machine learning and AI. Infrastructure is crucial to successfully maintaining a technological trading system, with numerous servers needed to process the mass amounts of data required. Sufficient upfront funding is also essential to begin operating. To date, only the wealthiest investors or firms have had the cash to pay for this upfront. As such, these large, well-funded investors and institutions have dominated the market and made it difficult for low-end or casual investors to compete, ultimately creating an uneven playing field.

However, the playing field is beginning to level out thanks to the democratisation of AI-powered trading technology. By making these advanced trading algorithms available to lower-end and retail investors, as well as making the technology easier to use, the traditional financial institutions may soon no longer hold a monopoly over success in the markets.

The rise of AI

This disparity between high and low-end investors is slowly closing due to the increasing use of technology which can be harnessed by a broader range of investors. AI and machine learning software algorithms have been developed to constantly learn, find, produce, test and refine hundreds of algorithms for investment strategies every day, without fail or respite.

One of the key benefits of harnessing AI and machine learning in trading is that emotional or human influence, which may affect or slow down trading, is removed from the decision-making process. By using automated systems, the risk of incorrect data from human input will decrease significantly and streamline the data-sorting process by removing any time delays resulting from mistakes or uncertainty. Further, financial data, as well as anything that may have an impact on trading systems such as fundamentals or weather data, needs to be constantly sorted or cleaned every day to ensure the strategies continue to predict the best results. Humans are nowhere near as quick as doing this as the ever-learning AI algorithms.

The latest AI-driven trading technology uses this data to continually search for statistical market anomalies through methods such as pattern recognition, statistical and mathematical modelling, machine learning or in-house developed data visualisation software. This forms the basis of the unique process-driven trading approach that some companies are currently adapting to challenge the traditional trading market.

Utilising this technology has provided an advantage over traditional automated trading systems thanks to constant updates and the ability to harvest the smallest identified deviations and anomalies in trading patterns which are automatically fine-tuned by the machine learning algorithms. Additionally, the creative process of generating ideas, often involving lots of coding and unpredictable timespans, has previously had to take place in a limited, finite amount of time. However, with the adoption of machine learning systems, more strategies can be generated in significantly shorter time frames, ultimately leading to greater ROI.

Risk and reward

Firms use fluctuations in market volatility to their advantage by accumulating systematic, short-termed price anomalies from corporate news, events and times of high volatility, harnessing the benefits of the biggest risk to investor returns. This technology has now been designed to actively support the risk management process by creating the right portfolio to create the right blend of risk and reward. With companies beginning to democratise AI trading technology, the influence of more investors using this technology may reduce market volatility, to the benefit of all.

Crypto popularity

Alongside the rise of sophisticated technology in the financial sector, cryptocurrencies are steadily becoming a popular trading asset. Elite financial institutions have already entered the crypto market and have the upper hand through bringing years of trading experience and an ability to deploy advanced AI technology in the market. However, the majority of crypto investors do not have access to these trading technologies and are at risk of being squeezed out of profitable trading by high-end investors; despite the original decentralised nature and vision of cryptocurrencies.

Some companies are trying to combat this by democratising the AI technology and empowering non-traditional investors in the crypto market. This decentralisation of AI trading software will open doors to the cryptocurrency market, not only allowing smaller investors to compete with high-end investors but also to optimise payments. As virtual money with no national banks, states or resources behind it, the crypto market is very volatile with a high degree of speculation on exchanges and difficulty in the valuation of crypto coins – AI technology can again help reduce this volatility and protect all investors.

Wider market benefits

The move to democratisation of trading technology has been a slow one, with many elite and established institutional investors unwilling to share the key advantages that promise good returns. With superior technology, hidden market pocks and information advantages, these high-end investors have kept retailer investors from accessing this beneficial technology.

Always in the last place when investing, small investors lack the time and technology to improve their financial situations. Some small investors are dependent on income from trading returns for everyday living costs such as housing, bills and education for their children, in addition to working full time jobs. Elite investors and institutions have been denying these people access to superior technology which may dramatically improve their financial situation.

Previously, most investment products only offered imbalanced risk/return profiles, earning when the markets go up and collapsing with everything else. Available investment products are also complicated, laden with fees and difficult to access which adds to the struggle of the smaller investor hoping to make a break in trading. All this has led to a market inequality with many people struggling to change the disparity. By democratising trading technology, companies are allowing everyone to play on the same level playing field with easy-to-use technology and a choice in how much to invest.

Stefan Tittel, CEO, RISE
Image Credit: David McBee / Pexels

Stefan Tittel
CEO of RISE, a company focused on AI and machine learning in algorithmic trading. Tittel is an entrepreneur in FinTech, Blockchain, Crypto and has founded QUANTUMROCK Capital and Crossgate AG.