2021-5-20 15:35 |
Trading has evolved considerably over the last 50 years, with most functions today being executed by programs and machines. Artificial Intelligence finds a wide array of application scenarios in trading – from data processing to signals and portfolio adjustments, it is believed that it could soon completely take over most tasks that are still performed by humans, including decision making.
Another novel technology that has a particularly wide scope of use cases in fintech and trading is blockchain. Many claim that blockchain can eliminate some of the most pressing issues in the financial sector such as high transactional fees, lack of transparency and security in traditional methods, informational asymmetries and intermediaries. In this article, we will take a closer look at the use cases of AI and blockchain for trading, analyze their potential synergy effects and introduce a new blockchain initiative that has made its mission to not only take a major step towards a future of trading that is greatly underpinned by technological innovation but to also bring this technology in the hands of the average investor.
Use cases of AI and machine learning in online tradingThe use of Artificial Intelligence and machine learning in trading is not new – in fact, similar concepts emerged in 1980 after professional traders acknowledged the impact of algorithmic trading on the sector and the need for sophisticated automation and data processing. Ever since then, new solutions are being introduced regularly and especially with the latest advances in AI, the rate at which AI penetrates trading has increased exponentially over the past decade. It is believed that wide adoption of AI in trading can result in less market volatility due to the lower degree of subjectivity and the lesser influence of emotion over stock prices, which seems to be an optimal state for the trading landscape.
Here are some of the use cases of AI and how they have changed trading.
Quantitative analysis
Artificial Intelligence is already being used for the development of liquidity searching algorithms, data mining and advanced analytics programs. The technology has an unmatched potential in the analysis of large data pools and their interpretation. What is more, an AI can then design predictions about the future prices of stocks based on probability models, which depend on a variety of factors and variables. Over time, these models are perfected by constantly testing their own hypotheses in simulated risk scenarios and drawing fact-based decisions from their results and comparing them to the actual market reality.
Trading signals and advisory
With the progress AI has achieved in trading, the emergence of robo advisors does not come as a surprise. These programs can analyze the market data provided to them and then design tailor-made suggestions to traders, which can be directly applied in their trading strategies. Portfolio adjustments delivered through completely automated software might seem impossible, but they already exist. However, such advanced tech is only available to a handful of large enterprises and big market players, remaining a black box for the average traders, who are struggling to turn a profit even though the stock market is currently in an upsurge.
Blockchain enters the sceneThe immutability of blockchain records and the potential the technology brings in eliminating intermediaries are the revolutionary properties that can allow it to become an industry-standard in fintech and trading. Many big industry players and banks have long started exploring the application scenarios of blockchain – Robinhood, Citigroup, Credit Suisse, ING and JP Morgan are just several examples of big names in the financial sector that are already working on their own innovative blockchain solutions.
While scientific research is still lacking to empirically prove the point that the benefits of AI and blockchain are multifold, the two technologies can work very well in conjunction with each other in the context of trading and collaborative data sharing. Particularly in the creation of automated trading bots that can process and analyze data, blockchain can add the needed layer of security and transparency, making sure that the AI is tamper-proof and is operating according to the trader’s best interests. What is more, blockchain complements a trading environment that is supported by AI analysis by removing intermediary parties between the traders and the markets, resulting in lower fees for the participants.
The Dohrnii project to combine AI and blockchainDohrnii is the first financial empowerment ecosystem that combines AI and blockchain to empower the individual traders by giving them access to a technology that is still reserved to a handful of investment banks and hedge funds and educating them about the subtleties of trading. The ecosystem consists of several core dimensions – the trading academy, aimed at educating traders based on their specific profile and past experience, the backend technological infrastructure, which consists of AI modules and blockchain technology working together in conjunction and the front end, where traders get personalized signals as well as suggestions by the Robo advisor and can execute automated trades.
Dohrnii has scheduled a full rollout of the ecosystem on both mobile and web in 2022. If you are interested in learning more about the project, its mission and future plans, visit https://dohrnii.io/en
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