Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 17, No. 1, 2024 280 Analysis on the Influence of Intelligent Algorithm Trading in Financial Market Gefan Dai Ningbo University of Finance and Economics, Ningbo, China Abstract: As a means to realize the intellectualization and automation of trading by using advanced mathematical models and computer technology, intelligent algorithm trading significantly improves the trading speed and efficiency, shortens the trad ing time window through millisecond decision-making and execution, reduces the potential losses caused by market fluctuations, and improves market liquidity and trading accuracy. However, it also brings risks such as technical failure and market manipulation. While emphasizing the trading opportunities of intelligent algorithm, this paper pays attention to its potential risks, and puts forward some suggestions on improving technology and strengthening supervision. The research points out that only through technological innovation, supervision strengthening and risk management can we ensure that intelligent algorithm trading can promote the development of financial markets without endangering market stability. In the future, with the technological progress and market maturity, the application prospect of intelligent algorithm trading will be broader. Keywords: Intelligent algorithm trading, Influence, Financial market. 1. Introduction The financial market is experiencing a data-driven revolution. In this revolution, intelligent algorithm trading, as a new trading method, is gradually changing the operation mode and trading behavior of the financial market. Intelligent algorithm trading uses advanced mathematical model and computer technology to quickly analyze market data and make trading decisions, which greatly improves the efficiency and accuracy of trading [1]. In recent years, with the integration and application of technologies such as big data, cloud computing and AI, intelligent algorithm trading has been widely promoted and applied worldwide [2-3]. It not only improves the transaction speed and volume of the financial market, but also optimizes the market structure to a certain extent, reduces the transaction cost and provides investors with more investment opportunities and strategic choices [4]. However, at the same time, the wide application of intelligent algorithm trading has also brought a series of new challenges and risks, such as technical risks and market manipulation risks, which need to be solved urgently. Therefore, in-depth study of the impact of intelligent algorithm trading on financial markets will not only help us better understand the operating mechanism and potential risks of this emerging trading method, but also provide useful reference and guidance for the healthy development of financial markets. The purpose of this paper is to discuss the opportunities and challenges brought by intelligent algorithm trading through in-depth analysis of its impact on financial markets, with a view to providing valuable insights and suggestions for relevant practitioners, investors and regulatory agencies. 2. Overview of Intelligent Algorithm Trading Intelligent algorithmic trading, referred to as algorithmic trading for short, is a way to automatically implement trading decisions by using advanced mathematical models, statistical methods and computer technology. It analyzes the market data in real time through the preset algorithm program, and automatically executes the trading operation according to the analysis results, thus realizing the intelligence and automation of the trading process. The core of intelligent algorithm trading lies in its "intelligence" and "automation" characteristics. Intelligence is mainly reflected in the in-depth analysis of market data and the accurate formulation of trading strategies. Through advanced data analysis techniques such as machine learning and deep learning, the algorithm can identify market trends, predict price fluctuations, and formulate the optimal trading strategy on this basis [5-6]. Automation is reflected in the high efficiency of transaction execution, and the algorithm program can respond and execute trading operations in milliseconds, which greatly improves the transaction efficiency. From the historical development, intelligent algorithm trading is gradually emerging with the continuous progress of computer technology. Early algorithmic trading mainly relied on simple automated scripts to perform basic trading tasks. Nowadays, with the rapid development of AI technology, intelligent algorithm trading has been able to handle more complex trading logic and strategies and become an important force in the financial market. In terms of technical principles, intelligent algorithm trading mainly relies on technologies such as big data analysis and machine learning. Big data analysis can help algorithm programs to quickly process massive market data and extract useful information. Machine learning technology can make the algorithm program self-learn and optimize, and constantly improve the accuracy and efficiency of trading strategy. 3. The Influence of Intelligent Algorithm Trading on Financial Market 3.1. Improve Market Efficiency The application of intelligent algorithm trading system significantly improves the trading speed and efficiency, and it 281 realizes millisecond trading decision-making and execution, which exceeds the ability of human traders. Through the preset strategies and parameters, algorithmic trading can monitor the market dynamics in real time and act quickly when the conditions meet, which not only greatly shortens the trading time window, but also effectively avoids the potential losses caused by instantaneous market fluctuations [7]. In addition, the wide adoption of algorithmic trading has also promoted the growth of market turnover, improved market liquidity, reduced transaction costs, and enhanced the depth and transparency of the market, because the algorithm can dynamically adjust the quotation according to the relationship between supply and demand, making the price closer to the real value of the market. At the same time, algorithmic trading improves the accuracy and reliability of trading by reducing human errors and emotional-driven decision-making deviations. The application of strict mathematical models and logical rules ensures the objectivity and consistency of trading decisions. In addition, intelligent algorithm trading is also an important promoter of financial market innovation. With the progress of machine learning and AI, it constantly learns and adapts to new situations, giving birth to new trading strategies and tools, enriching financial products and promoting market development [8]. More importantly, the algorithmic trading system has the ability to monitor market risks in real time, and protect investors' interests by setting stop-loss points and other risk control measures to help them better understand and manage market risks. 3.2. Reduce Transaction Costs In the financial market, the rise of intelligent algorithm trading is significantly changing the traditional trading mode, especially in reducing transaction costs, its advantages are increasingly prominent. Intelligent algorithm trading significantly reduces human intervention by automatically executing trading decisions. In traditional trading, traders need to manually analyze the market and judge the trading opportunity. This process is not only time-consuming, but also easily influenced by emotions, which increases the transaction cost. The intelligent algorithm can monitor the market dynamics in real time, quickly capture trading opportunities, avoid the delay and error of human judgment, and thus reduce the transaction cost caused by decision- making mistakes. Through machine learning and big data analysis, the algorithm can learn from historical trading data and identify more effective trading patterns. This not only improves the accuracy of the transaction, but also effectively reduces the average cost of each transaction by executing the transaction in batches. In addition, the algorithm can adjust the strategy in real time to adapt to market changes and avoid the cost increase caused by the lag of the strategy. The algorithm can execute transactions at millisecond speed, which avoids the slippage cost caused by price fluctuation. In addition, by optimizing the order type and execution strategy, the algorithm can effectively reduce the market impact, reduce the impact on the market price caused by a large number of transactions, and further reduce the transaction cost. 3.3. Enhance Market Stability Intelligent algorithm trading can quickly and accurately process a large number of data, including historical prices, trading volume, news events, etc., thus making more accurate market forecasts. This efficient information processing ability helps to improve market efficiency, make asset prices more reflective of their intrinsic values, and reduce market fluctuations caused by information asymmetry. Algorithm trading can participate in market trading 24 hours a day without human intervention, which greatly increases the liquidity of the market. High liquidity means that trading orders can be closed quickly, which reduces the impact of large transactions on market prices, thus reducing market volatility. The intelligent algorithm can dynamically adjust the trading strategy according to the market situation. For example, when there is excessive buying or selling in the market, the algorithm can take the opposite action to balance the relationship between supply and demand. This self- regulation mechanism helps to prevent the market from overheating or supercooling and maintain the stability of the market. Human investors are often influenced by emotions, such as panic or greed, which may lead to irrational trading behavior and increase market volatility. In contrast, intelligent algorithm trading is based on preset rules and logic, and it will not be affected by emotions, so it can reduce the instability caused by emotional trading. Intelligent algorithms can monitor market risks in real time and automatically implement risk control measures, such as stop loss and take profit. This automatic risk management is helpful to deal with sudden changes in the market in time, reduce potential losses, and thus maintain the overall stability of the market. Algorithm trading helps to discover the real value of assets more quickly by constantly analyzing market data and executing transactions. This price discovery function can reduce wrong pricing in the market, thus improving the stability of the market. 3.4. Challenges and Risks Although intelligent algorithm trading has brought many advantages, it is also accompanied by technical risks and market risks. Technically, complex computer systems and software are vulnerable to failures or programming errors, which may lead to unexpected trading behavior and even market turmoil. For example, the "lightning crash" in 2010 was caused by mistakes in high-frequency trading algorithms; Therefore, it is necessary to strengthen the redundancy and flexibility of the system, implement regular stress tests and simulation drills to ensure the stability under extreme conditions, and establish a rapid response mechanism to deal with unexpected situations in time. At the market level, there is a risk of increasing volatility, especially when the market changes sharply, a large number of algorithms trigger buying and selling orders synchronously, which may lead to abnormal price fluctuations and form a vicious circle; Therefore, it is necessary to introduce fuse mechanism and other market stabilization tools to restrain algorithm trading in extreme cases, and to promote the use of more robust algorithm design to reduce the sensitivity to short-term market fluctuations. The transaction of intelligent algorithm is faced with risks in many aspects, such as supervision, ethics, law and operation. In terms of supervision, its rapid development has caused the lag of the regulatory framework, and the existing regulations are difficult to effectively cope with emerging challenges; The solution lies in that regulators should constantly update laws and regulations, strengthen supervision, and work with industry experts to formulate 282 reasonable policies. On the moral and legal level, there is the phenomenon of unfair competition by using information asymmetry, and there is even the danger of manipulating the market and damaging the rights and interests of other investors; In this regard, we should strengthen market supervision, severely crack down on illegal activities, and enhance market transparency to ensure a level playing field. In terms of operational risk, although the algorithm reduces direct human intervention, errors may still occur in parameter setting, system monitoring and maintenance; Therefore, it is necessary to pay attention to personnel training and management, ensure the professional level and sense of responsibility of operators, and improve the internal control system to minimize the probability of human error. To sum up, as a new trading method, intelligent algorithm trading brings efficiency improvement and liquidity increase, but it is also accompanied by a series of challenges and risks. Only by constantly improving technology, strengthening supervision, improving transparency and strengthening risk management can we ensure that intelligent algorithm trading will promote the development of financial markets and will not pose a threat to market stability. 4. Application Scenarios and Prospects of Intelligent Algorithm Trading Intelligent algorithm trading is widely used in financial markets, covering all aspects from transaction execution to risk management. By optimizing trading strategy and execution process, algorithmic trading helps to improve market efficiency and reduce trading success, especially in stock, foreign exchange and futures markets. Table 1 shows the application scenarios of intelligent algorithm trading in these markets. Table 1. Application scenarios and advantages of intelligent algorithm trading in financial markets Market category Application scenario advantage Example Strategies: stock Transaction execution Reduce market impact and transaction cost. Volume Weighted Average Price (VWAP), Time Weighted Average Price (TWAP) risk management Adjust trading strategy in real time to control risks. Risk model Arbitrage strategy Using price difference to realize risk-free arbitrage Statistical arbitrage Minimization of market impact Hide trading intentions and reduce price shocks. Iceberg order foreign exchange Liquidity management Improve market liquidity and reduce volatility. Liquidity provision Transaction cost optimization Minimize transaction costs VWAP Market microstructure Affect the bid-ask spread and trading volume distribution TWAP futures price discovery Speed up information dissemination and improve the efficiency of price discovery High frequency data market efficiency Reduce unnecessary price fluctuations High frequency trading (HFT) Diversification of trading strategies Realize a variety of complex trading strategies Trend tracking and hedging In the stock market, intelligent algorithm trading is often used for high-frequency trading and quantitative investment strategy. For example, some institutional investors use machine learning algorithms such as support vector regression (SVR) to predict the trend of stock prices and formulate trading strategies accordingly [9]. These strategies can make buying and selling decisions in milliseconds, which greatly improves the trading efficiency and profitability. In addition, intelligent algorithms can also help investors optimize their portfolios and reduce risks. The volatility and high leverage of the foreign exchange market make intelligent algorithm trading have significant advantages in this field. The algorithm can quickly identify market trends and trigger a stop-loss mechanism, when necessary, thus effectively controlling risks. At the same time, through intelligent risk management, algorithmic trading can help investors achieve more stable returns in the foreign exchange market. In the futures market, intelligent algorithm trading is widely used in arbitrage trading, trend tracking and volatility trading. The algorithm can monitor the market, price, position and other data in real time, and automatically perform trading operations according to the preset strategy. This not only improves the accuracy and efficiency of the transaction, but also reduces the risk brought by human intervention. With the technological progress and market maturity, the application prospect of intelligent algorithm trading in the financial market is very broad, showing several major development trends: First, technological innovation continues to be promoted, and the development of AI and big data gives the algorithm stronger data processing and strategy execution capabilities, enhancing its market competitiveness; Second, the scope of market application is constantly expanding, from the existing fields of stocks, foreign exchange and futures to more financial fields such as bonds and derivatives. With the improvement of market awareness and the lowering of technical threshold, the application of algorithmic trading will be more extensive; Third, the regulatory policies are gradually improved. Faced with the popularity of algorithmic trading, the regulatory agencies will strengthen supervision and improve relevant policies to ensure fair and transparent markets, and the role of industry self-regulatory organizations will also be enhanced to jointly promote the healthy and orderly development of algorithmic trading. Nevertheless, investors should pay attention to potential risks and take appropriate risk management measures while enjoying the convenience brought by algorithmic trading. 5. Conclusion The influence of intelligent algorithm trading in financial market is various. Through efficient data processing and automatic transaction execution, it significantly improves transaction speed and market efficiency, reduces transaction costs, and enhances market liquidity and stability. At the same 283 time, intelligent algorithm trading also promotes financial innovation, enriches trading strategies and tools, and provides investors with more diversified choices. 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