Trending Now

In-Depth Analysis of the Semiconductor & IC Packaging…

New Articles

How Generative AI Can Be a Game Changer in Online Trading?

global trade AI
Global Logistics, Global Trade Daily, Technology

How Generative AI Can Be a Game Changer in Online Trading?

Leave a comment

A new age in the capital markets is expected to be ushered in by the development of generative AI, which has the potential to completely transform how we invest in, run, and value businesses. 

Read also: Top 5 Tips for Successful Online Stock Trading

The financial environment is about to change because of this technology, which includes models like OpenAI’s GPT-3 and GPT-4. It presents previously unheard-of possibilities for efficiency, accuracy, and innovation.

What does the Data Says?

According to McKinsey, generative AI might boost the impact of all artificial intelligence by 15–40%, or the equivalent of $2.6 trillion to $4.4 trillion yearly across a range of use cases.

According to Dimension Market Research, the size of the global market for generative AI in trading is projected to be USD 208.3 million by 2024 and USD 1,705.1 million by 2033. In 2024 the market is expected to grow at a compound annual growth rate (CAGR) of 26.3%.

The introduction of algorithmic trading, a form of automated trading carried out by a computer using an algorithm trained to identify historical trends, is when artificial intelligence (AI) first appeared in the stock market. Trading is now less prone to human error and more efficient. But generative AI is about to go further than that.

Advancement of Generative AI in Online Trading

The use of generative AI in FinTech has greatly changed online trading. With the sophisticated technologies available today, traders can evaluate large volumes of data in real-time, which helps them make better decisions and execute transactions accurately.

Here are some of the ways Generative AI can be useful:

1. Utilization in Trading Algorithms

GenAI is used in algorithmic trading, where it analyzes trends in market data and current conditions to predict future movements in the market. This procedure uses algorithmic pattern recognition and data analysis to automate trading across various financial assets.

2. Signal Generation in Trading

Generative AI carefully examines large amounts of information using AI skills to find subtle patterns and trends that frequently escape human notice. This analytical skill not only makes it easier to create creative trading methods but also makes it easier to spot profitable chances and makes it possible to implement more advanced risk management tactics.

3. Evaluating Risks and Detecting Fraud 

Leveraging its ability to process large data, generative AI can spot small anomalies that would escape human investigation. Encouraging anomalies and possible fraud promptly enhances security protocols and reduces financial concerns.

4. Structuring Market Dynamics Models

AI systems create artificial intelligence (AI)-generated data and use it to predict market dynamics. This helps to support portfolio management procedures and encourages the creation of novel trading methods. Trading decisions and investment portfolios should be improved with the incorporation of generative AI.

5. Replicate Risk Scenarios

With generative AI models, traders can improve their risk management techniques and better prepare for various market circumstances, including market crashes and sharp price swings.

Limitations of Online Trading with Generative AI

Even though generative AI has a lot of potential for trading, a few issues and restrictions must be resolved. 

1. Inadequate Accessibility and Quality of Data

The absence of high-quality and readily available data presents another challenge for generative AI in trading. Generative AI needs a lot of data, but getting and validating data can be challenging in the trading industry. Since precise and trustworthy data can be hard to get by, especially in emerging markets, financial data is notorious for being low quality. 

To increase the data quality, companies might need to recruit data scientists and analysts to supervise these systems and invest in new data-gathering and validation methods.

2. Inability to Interpret

Its difficulty in being interpreted is one of the hardest problems. It might be challenging for traders to comprehend how generative AI algorithms generate their predictions or recommendations because they are sometimes intricate and hard to grasp. This may cause people to mistrust the algorithm and be reluctant to utilize it in trading.

3. Concerns about Ethics and Regulations

The moral and legal questions these systems bring up are another obstacle to using generative AI in trading. Concerns regarding generative AI models’ potential for misuse and their effect on financial markets can arise, particularly in light of their absence of interpretability and transparency. 

For instance, some experts are worried that generative AI can participate in immoral or criminal activities like insider trading or manipulating the market.

Technologies Used in Stock Trading

The success of the stock market apps is attributed to various cutting-edge technologies that are always changing to satisfy consumer needs and market trends. Let’s examine how the newest technologies work with generative AI.

1. Blockchain Technology

With its reputation for being transparent and decentralized, blockchain technology has several uses in the stock trading industry.

Enhanced Security: Cryptographic security methods and unchangeable transaction records lower fraud and boost trader confidence.

Smart Contracts: Trade settlements can be automated and rule compliance can be guaranteed with the help of self-executing contracts written on blockchain technology.

Asset Tokenization: Tokenizing securities allows for fractional ownership of assets and simplified trading procedures.

Blockchain and Generative AI Integration

Integrating blockchain technology with generative AI can improve stock trading’s efficiency, security, and transparency:

Transparent Transactions: By guaranteeing transparent and auditable transaction records, blockchain’s decentralized ledger lowers the possibility of fraud and manipulation.

Automation of Smart Contracts: Based on predetermined market conditions, trade execution, and settlement procedures can be automated by smart contracts driven by generative artificial intelligence.

Trade without middlemen: Peer-to-peer trade is made possible by decentralized exchanges driven by blockchain technology and generative artificial intelligence.

2. Internet of Things (IoT)

IoT devices enable real-time data collecting and analysis for stock trading when they are connected to the internet:

Market monitoring: In real-time, sensors and devices collect information on trade volumes, asset performance, and market circumstances.

Predictive analytics: To forecast market movements and improve trading tactics, data from IoT devices can be fed into generative artificial intelligence (AI) models.

Trade Execution: By executing trades based on insights from IoT, automated trading algorithms can reduce latency and human interaction.

Generative AI and IoT Integration

Stock traders may now analyze data in real-time and make well-informed decisions by integrating IoT devices with generative AI:

Real-Time Data Integration: Generative AI models examine continuous streams of market data provided by IoT sensors to detect trading possibilities and hazards

Automated Trading Strategies: AI systems can initiate transactions on their own, maximizing the efficiency and timing of trade execution by utilizing insights given by the Internet of Things.

Scalable Infrastructure: AI and cloud-based IoT platforms allow responsive and scalable trading infrastructures that can manage massive amounts of data and transactions.

3. Big Data Analytics

Big data analyzes vast amounts of data to find correlations, patterns, and trends in the behavior of the stock market

Data processing: Examines large databases, such as economic indicators, social media trends, and historical market data.

Pattern Recognition: Recognizes trends and irregularities in the market to guide trading plans and risk control.

Real-time insights: Gives traders and investors timely information in real-time to enable them to make informed decisions.

Generative AI and Big Data Analytics Integration

Stock trading is revolutionized by big data analytics, which processes enormous datasets to produce actionable insights and streamline decision-making procedures:

Processing Data in Real Time: Allows quick identification of trends and abnormalities in streaming market data.

Forecasting using Modeling: Utilizes both historical and current data to predict trading volumes, asset values, and market trends.

Evaluation of Risk: Enhances risk management tactics by evaluating various data sources to assess portfolio risks.

4. Natural Language Processing (NLP)

Reads and analyzes textual data to derive sentiment analysis and market insights.

News and Social Media Analysis: Keeps an eye on social media posts and news stories to determine the market mood.

Event detection: Finds noteworthy occurrences and news that could affect market activity and stock prices.

Automated Reporting: Produces reports and summaries in real-time by analyzing textual data.

Generative AI and NLP Integration

By analyzing and understanding textual data from news stories, social media, and financial reports, natural language processing (NLP) enhances stock trading:

Identifying Events: Enables proactive decision-making by identifying news and important events that could impact stock prices and investor behavior.

Automated Analysis: Produces reports and summaries in real-time based on the analysis of textual data, increasing the effectiveness of decision-making.

Sentiment Analysis: Evaluates public opinion and investor mood to forecast market movements and improve trading tactics.

Conclusion

Naturally, there are many advantages to using generative AI in trading. It has a huge potential. The application of generative AI has the potential to revolutionize the way traders and financial institutions function, from increased prediction accuracy and efficiency to the creation of new trading concepts.

The lack of interpretability, the availability and quality of data, and ethical and legal issues are some obstacles and constraints that must be overcome. Despite these obstacles, generative AI in trading has a lot to offer the financial markets.

About Author

Gaurav Belani is a senior SEO and content marketing analyst at Growfusely, a SaaS content marketing agency specializing in content and data-driven SEO. With over seven years of experience in content marketing, he enjoys sharing his knowledge in a wide range of domains, including eCommerce, human capital management, and B2B SaaS. His work has been featured in several reputable business and tech publications.

 

digital currencies
Archives, Banking, Global Trade Daily

Central Banks to Adopt Their Own Digital Currencies to Eliminate Potential Risks

Leave a comment

Digital currencies backed by central banks, or central bank digital currencies (CBDCs), are becoming a reality for residents in a few countries around the world. The evolution from checks, to debit cards, and now to digital payments give cause to wonder if we really need cash anymore. While economists agree that we still need cash for now, some governments are discussing the effects of implementing a CBDC nationally. 

However, not everyone is as interested in the prospect of implementing a nationwide digital currency. Commercial lending and banking would be affected, as the widespread use of CBDCs could take a bite out of commercial deposits and put the industry’s funding in jeopardy. But with China currently developing a digital Yuan, that leaves government and supply chain leaders wondering about the potential trade risks of not competing in the global economy with CBDCs. 

Luckily, lawmakers have come up with a slew of solutions that include strict regulations and controls, hard limits on transfers and holdings, and a long-term transition period before the new digital assets could be launched in full effect. In the meantime, central bankers in the US are contemplating adopting their own digital tokens for instant, low friction international transactions. 

What is Central Bank Digital Currency?

A CBDC is the virtual form of a certain fiat currency. You can think of it as an electronic record or a digital token of how currency is spent, held, and moved. CBDCs are issued and regulated by central banks and backed by the credit of their issuer. They aren’t really a new kind of money, it just changes the way we track transactions. 

While seemingly very similar at first glance, CBDCs are not cryptocurrencies. Cryptocurrencies are digital currencies that are secured by cryptography and exist on decentralized blockchain networks. Bitcoin and other cryptocurrencies are not backed by any government or banking entity and are purely digital currencies. CBDCs, in contrast, are backed by legal tender and are only a digital representation of fiat money.

Part of the draw to create CBDCs is inspired by their crypto-cousins’ distributed ledger technology. DLT, or blockchain technology, refers to the digital infrastructure and protocols that allow access, validation, and continuity across a vast network. This means that, in contrast to fiat currency that exists today, digital currencies can be tracked and verified in real-time, limiting the risk of theft and fraud. 

Blockchain technology is usually associated with cryptocurrency, but it has the potential for numerous applications that could help governments organizations and banking entities run more smoothly with accountability and transparency. Another reason why countries are drawn to CBDCs is they have the ability to help increase banking access for otherwise underbanked populations. 

Currently, there are 81 countries exploring CBDCs. China is racing ahead of the pack with their development of the digital Yuan, putting pressure on countries that will want to remain competitive. It raises the question of whether China will at some point accept only digital currency, meaning other countries would need their own CBDCs to remain competitive on a global scale. 

China’s digital Yuan

China has long been known to resist cryptocurrencies and crypto trading, so when the news broke that their central bank has been developing a CBDC there was some confusion. However, it has now become clear that the Chinese government is creating an environment where citizens who want to use digital currencies like crypto will have to use the digital Yuan, removing any competition from DeFi banking initiatives. 

Before their crackdown on Bitcoin and crypto, local investors made up 80% of the crypto trading market. This shows promise when it comes to the adoption of the digital Yuan, with so many Chinese citizens open to adopting and spending digital currency. 

They have already started real-world trials in a number of cities and are expecting the digital Yuan to increase competition in China’s mobile payments market. It is still not entirely clear how users will hold and spend the new digital Yuan whenever it is available nationwide. Right now the most popular form of mobile payment in the country relies on QR codes scanned by merchants. 

Alipay and WeChat Pay could eventually integrate CBDC functionality, and smartphones could also potentially be used as a digital wallet for CBDCs. There is still a lot to be discussed, tested, and fixed before the digital Yuan can be distributed nationwide, but China is currently the country closest to rolling out its own CBDC. 

Where does the United States stand?

Crypto thefts, hacks, and frauds amounted to about $1.9 billion in 2020, so many leaders have reservations when it comes to enforcing and regulating CBDCs in the US. But there is evidence that CBDCs would have no issues being adopted by the American people. Crypto aside, the digital payments sector is booming with about 75% of Americans already using digital payments apps and services. 

But there is not yet a single widely accepted infrastructure available that could handle CBDCs, and lawmakers are lagging behind when it comes to regulations for fintechs as it is. The US could take a page from China’s book and explore adding CBDC functionality to existing banking fintechs like Chime, Paypal, and ApplePay. According to online trader Gary Stevens from Hosting Canada, it would also be wise to look at banks that offer trading services as well. 

“In the US, banks offering online trading services (such as Merrill Edge through Bank of America) tend to provide a seamless client experience,” says Stevens. “They strive to provide a consistent login interface between the bank and its brokerage arm, making switching between these platforms easier. This also makes other tasks like moving money between these accounts more flexible. Therefore, US residents have come to expect a more integrated, holistic experience with similar core functionality.”

The Future of CBDCs

The onset of the pandemic has created the perfect storm for CBDCs to come to fruition. Telework, online education, and streaming services have experienced growth while brick-and-mortar establishments have suffered. The same is true for the financial services industry. Banks have struggled to compete with fintech solutions, and more people are utilizing digital payments than ever before. 

Since CBDCs are such a new technology, there is still much to learn when it comes to implementing CBDCs nationwide and around the globe. Offline accessibility and resilience are only a couple of concerns regarding digital currency adoption worldwide. Other issues include user privacy, using private and public blockchain networks, and how digital currencies will be exchanged on a global scale. Only time will tell how central banks choose to seriously pursue this route to make it more mainstream. 

Conclusion

There are a lot of details still up in the air regarding CBDCs, as well as a considerable amount of research, testing, and development left to unfold. But one thing is clear: central bank digital currencies are already under development. Whether you are getting into online trading or just like the convenience of e-payments, they might be coming to a digital wallet near you sooner than you think.