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市场调查报告书
商品编码
1479982

印度演算法交易市场评估：依组成部分、依方法、依功能、依类型、依最终用户、依地区、机会、预测（2018 财年-2032 财年）

India Algorithmic Trading Market Assessment, By Component, By Mode, By Function, By Type, By End-user, By Region, Opportunities and Forecast, FY2018-FY2032
出版日期: | 出版商: Market Xcel - Markets and Data | 英文 115 Pages | 商品交期: 3-5个工作天内

价格

印度演算法交易的市场规模预计将从2024 财年的10.8 亿美元增至2032 财年的26.1 亿美元，在2025 财年至2032 财年的预测期内复合年增长率为11.65%。还会增长。基于云端的解决方案的采用增加、对快速高效的订单执行的需求不断增长、对基于人工智慧的服务和市场监控的需求不断增长、个人可支配收入增加以及交易成本降低等因素正在推动演算法交易成为成长因素。

演算法交易是股票市场领域的技术进步。它是一个被编程为执行一组特定指令的过程，一种以超出人类能力的速度和频率发出有利可图的订单的演算法。数据集在股票市场中发挥着重要作用，每个统计数据都会被评估和使用，以造福所有参与者。这使投资者能够发现流动性潜力并做出更明智的交易选择。透过交易选择，降低交易成本，同时改善交易流程，减少市场波动，增加获利潜力。

报告显示，57%的金融机构认为人工智慧将使他们在市场上更具竞争力。 Streak Zerodha 最近推出了一项新功能 Streak Scanner，它允许您使用技术指标和运算子建立和运行股票、期货和选择权的扫瞄。该扫瞄器基于不同的细分市场，例如涨幅最大、亏损、烛台形态、范围突破、多头和空头期权。所有这些扫瞄器都处理 1 分钟资料。

网路使用量的增加推动市场成长

网路使用量的增加正在推动演算法交易市场的成长。随着互联网变得越来越普及，消费者更容易访问线上平台来获取有关线上交易的知识和资讯。线上交易严重依赖互联网，推动了演算法交易市场的成长。

根据 DataReportal 2024 报告，2024 年 1 月印度有 7.515 亿网路用户。年初印度的网路普及率为总人口的52.4%。另外，早期投资者依赖经纪人买卖股票，但现在他们藉由网路参与股票买卖。网上交易节省时间、精力和金钱。根据《印度时报》报道，到 2023 年，农村地区的活跃网路用户将达到 4.42 亿，超过城市地区的 3.78 亿。因此，互联网普及率的提高将推动演算法交易市场的成长。

市场监理的需求推动市场

市场监控或贸易监控涉及贸易数据的取得、分析和监控，以揭露市场滥用行为和其他金融犯罪，例如诈欺和内线交易。各国法规都规定了交易监控，以防止可能损害投资者利益并扰乱金融市场平稳运行的交易，例如内线交易、市场操纵和诈欺交易。高频交易引发了人们对市场稳定性和完整性的担忧。监控音讯、视讯和其他电子通讯对于识别欺诈性交易者活动是必要的。

基于人工智慧的工具可以根据语气、行话、短语和暗语将资讯置于上下文中，以揭示交易者的真实意图。如果订单下达或取消出现异常高峰，则会产生警报。识别洗钱技术，例如与同一交易对手的过度交易和无法访问的预订。 ALGO AIoT 是一种先进的 CMS 远端监控解决方案，由人工智慧和物联网提供支持，并由机器人流程自动化提供支持，可监控视讯并轻鬆检测威胁，同时降低成本和复杂性。对市场监控日益增长的需求促使了对具有监控功能的演算法交易系统的需求，从而推动了市场的成长。

本报告针对印度演算法交易市场进行研究和分析，提供市场规模和预测、市场动态、主要参与者的现状和前景等。

目录

第一章研究方法

第 2 章专案范围与定义

第 3 章执行摘要

第 4 章顾客回馈

  • 人口统计（年龄/群组分析 - 婴儿潮世代和 X 世代、千禧世代、Z 世代、性别、收入 - 低收入、中等收入、高收入、地区、国籍等）
  • 市场认知度
  • 品牌知名度与忠诚度
  • 购买决策时考虑的因素
  • 演算法交易的频率
  • 演算法交易方法

第五章印度演算法交易市场展望（2018-2032 财年）

  • 市场规模与预测
    • 金额
  • 依组件
    • 解决方案
    • 服务
  • 依方法
    • 云
    • 本地
  • 依功能
    • 程式设计
    • 侦错
    • 资料撷取
    • 回测、优化
    • 危机管理
  • 依类型
    • 股市
    • 外汇市场
    • 交易所交易投资信託
    • 债券
    • 加密货币
    • 其他
  • 依最终用户
    • 短期交易者
    • 长期交易者
    • 个人投资者
    • 机构投资者
  • 依地区
    • 北
    • 南部
    • 东方
    • 西部和中部地区
  • 市占率：依公司划分（2024 财年）

第 6 章市场地图（2024 财年）

  • 依组件
  • 依方法
  • 依功能
  • 依类型
  • 依最终用户
  • 依地区

第七章宏观环境与产业结构

  • 需求与供给分析
  • 监管框架和合规性
  • 价值链分析
  • PESTEL 分析
  • 波特五力分析

第 8 章市场动态

  • 生长促进因素
  • 抑製成长的因素（问题、限制因素）

第九章主要公司状况

  • 前 5 名市场领导者的竞争矩阵
  • 前 5 位市场领导者的市场收入分析（2024 年）
  • 併购/合资企业（如果适用）
  • SWOT 分析（5 家市场公司）
  • 专利分析（如果适用）

第 10 章个案研究

第十一章演算法交易软体价格分析

第十二章主要公司展望

  • Quadeye Securities Private Limited
  • AlgoBulls Technologies Private Limited
  • Utrade Solutions Private Limited
  • Trade Rays LLP
  • Open Futures & Commodities Private Limited
  • Kiwi Capital Private Limited
  • AlphaGrep Securities
  • Dolat Capital Market Private Limited
  • Graviton Research Capital LLP
  • Iragecapital Advisory Private Limited

第 13 章策略建议

第14章关于我们公司，免责声明

Product Code: MX11327

India algorithmic trading market is projected to witness a CAGR of 11.65% during the forecast period FY2025-FY2032, growing from USD 1.08 billion in FY2024 to USD 2.61 billion in FY2032. Factors such as increased adoption of cloud-based solutions, rising demand for fast and efficient order execution, growing demand for AI-based services and market surveillance, rising disposable income of individuals, and declining transaction costs are responsible for the growth of algorithmic trading in the country.

Algorithmic trading is a technological advancement in the stock market sector. It is a process programmed to perform a set of specific instructions, that is, an algorithm for placing an order to generate profits at a high speed and frequency exceeding human power. The data set plays a significant role in the stock market, wherein every statistic is evaluated and used for the benefit of all the parties involved. It enables the investor to discover possibilities of liquidity and make more informed trading choices. Through trading choices, the transaction cost is reduced while improving trade processes, reducing market volatility, and increasing profit potential.

According to the report, 57 percent of financial organizations agree that AI will give them a competitive edge in the markets. Streak Zerodha has recently introduced a new feature Streak Scanner which allows one to create and run scans across equities, futures, and options using technical indicators and math operators. The pre-built scanners are based on segments such as top gainers and losers, candlestick patterns, range breakouts, long and short build-up for options, and many more. All these scanners run on a 1-minute data.

Increasing Internet Usage Fueling the Market Growth

Increasing Internet usage is driving the growth of algorithmic trading market. The rising penetration of the internet helps consumers gain access to online platforms where they can increase their knowledge and information about online trading. Online trading is highly dependent on the internet, boosting the growth of the algorithmic trading market.

According to the DataReportal 2024 report, 751.5 million internet users were there in India in January 2024. The internet penetration rate in India stood at 52.4 percent of the total population at the start of the year. Also, earlier investors were purely dependent on their brokers for trading but now they are participating more in buying and selling shares with the internet help. It has saved time, energy, and money by trading online. According to the Times of India, the rural region recorded 442 million active internet users exceeding the urban region which saw 378 million users in 2023. Therefore, increasing internet penetration will fuel the growth in the algorithmic trading market.

Need for Market Surveillance Boosts the Market

Market or trade surveillance includes capturing, analyzing, and monitoring trade data to reveal market abuse and other financial crimes such as rogue trading and insider trading. National regulations govern trade surveillance to prevent insider trading, market manipulation, and unauthorized trades, which could harm investors and disrupt the smooth functioning of financial markets. High-frequency occasions have provoked concerns about market stability and integrity. Surveillance of voice, video, and other electronic communication is necessary to identify fraudulent behavior among traders.

AI-based tools can contextualize information based on tone, jargon, phrases, and code words to reveal the true intent of traders. They generate alerts during abnormal spikes in order placements and cancellations. They identify money laundering techniques, such as excessive trading, with the same counterparties and inaccessible booking. ALGO AIoT - an advanced remote monitoring solution by CMS powered by AI and IoT and driven by robotic process automation. It monitors footage and easily detects threats while saving on costs and complexity. The increasing need for market surveillance demands algorithmic trading systems with surveillance capabilities, propelling market growth.

Western India to Dominate the Market Share

Western region is expected to dominate India algorithmic trading market share as many investors participate in two biggest and only stock exchanges of India, i.e., National Stock Exchange and Bombay Stock Exchange situated in Mumbai. There are many agencies based here that have access to limited amounts of personal data making it easier for them to funnel funds into their businesses and thus enable them to grow at a faster rate than usual. The extensive use of algorithmic trading in financial institutions and banks is promoting growth in the industry. Moreover, the increasing deployment of algo-trading technology by trading companies is introducing lucrative opportunities in the market.

Cloud Dominates the Market

Cloud computing has become important in the financial industry, as digitalization is becoming heavily dependent on it. Traders use cloud services for backtesting, trading strategies, and run-time series analysis. They chose cloud computing as it is capital-intensive to build one's data center for services like storing data, backup and recovery, and trading networks. Cloud-based trading offers the benefits of remote servers for trade execution which are generally accessed over the internet. It reduces onsite IT infrastructure costs and expands the cloud's power to test and model trades.

One of the significant benefits of the cloud is business agility, leveraging the ability to easily access technology, and continuous innovation provided by cloud service providers, along with a pay-as-you-go model, which allows a trader to experiment and go for new technologies and solutions without high investments. Flexibility and availability are two characteristics of cloud-based algorithmic trading that are anticipated to fuel the development of an algorithm trading market in the future. Algo Bulls is an AI-supported algo trading platform with approx. 10 thousand plus cloud-based servers, it provides hassle-free trading with 500 plus AL-driven algo trading strategies.

Stock Market to Dominate India Algorithmic Trading Market Share

The stock market segment dominates India algorithmic trading market share with around 80% of equity transactions carried out through algorithmic trading. The stock market is considered one of the leading asset classes for trading in a controlled environment. Algorithms are gaining online popularity, and many big customers are demanding them. These algorithms examine every price and trade in the stock market, identifying liquidity opportunities, and transforming information into trading results. It reduces trading costs and helps stock traders manage their trading processes.

Cryptocurrencies are projected to grow significantly. The main advantage of algorithmic trading is that it will allow users to execute certain crypto trades at an electrifying speed on multiple indicators. Algorithmic trading offers returns for firms with the ability to absorb the prices and gain profits.

Future Market Scenario (2025 - 2032F)

Algorithms will advance in grace and power as technology advances, changing the way financial markets are going to operate. Due to its high speed, efficiency, data-driven decision-making, and risk-management skills, algorithm trading software has a significant advantage in a market where trading is extremely competitive. As observed, algorithmic trading is the future of the stock market.

Robo trader is India's most advanced algo trading SaaS Platform which is reliable and easily accessible. It speeds up the trading profit cycle by customizing the strategies based on market behavior. Robo trading allows one to place two more orders while placing the first intraday order. Among these two orders, the role of the first is to ensure speculated profit, and the second is to protect you from incurring high losses due to erratic price swings in the market.

Key Players Landscape and Outlook

The algorithmic trading market is highly competitive as the top players expand their geographical boundaries by strategically collaborating and acquiring local players to gain a strong regional grip. Innovation in technology and new product launches attract a huge customer base which in turn increases the revenue. The growing trading volume is expected to create great opportunities for market players in the algorithmic trading market. Leading players focus on mergers, acquisitions, and partnerships to remain competitive.

Leading algorithm-based trading firm Graviton Capital Research LLP consolidates its grip on the market growing its revenue by 70-100% in 2023. It uses complex algorithms and powerful computers for trade execution. Their key strategy is trade execution at lightning speeds.

Table of Contents

1.Research Methodology

2.Project Scope & Definitions

3.Executive Summary

4.Voice of Customer

  • 4.1.Demographics (Age/Cohort Analysis - Baby Boomers and GenX, Millennials, Gen Z; Gender; Income - Low, Mid and High; Geography; Nationality; etc.)
  • 4.2.Market Awareness
  • 4.3.Brand Awareness and Loyalty
  • 4.4.Factors Considered in Purchase Decision
    • 4.4.1.Software Name
    • 4.4.2.Computer Programming
    • 4.4.3.Price
    • 4.4.4.Execution Speed
    • 4.4.5.Functions
    • 4.4.6.Average Trade
    • 4.4.7.Promotional Offers & Discounts
  • 4.5.Frequency of Algorithmic Trading
  • 4.6.Mode of Algorithmic Trading

5.India Algorithmic Trading Market Outlook, FY2018-FY2032F

  • 5.1.Market Size & Forecast
    • 5.1.1.By Value
  • 5.2.By Component
    • 5.2.1.Solution
      • 5.2.1.1.Platform
      • 5.2.1.2.Software Tools
    • 5.2.2.Services
  • 5.3.By Mode
    • 5.3.1.Cloud
    • 5.3.2.On-Premises
  • 5.4.By Function
    • 5.4.1.Programming
    • 5.4.2.Debugging
    • 5.4.3.Data Extraction
    • 5.4.4.Back-Testing and Optimization
    • 5.4.5.Risk Management
  • 5.5.By Type
    • 5.5.1.Stock Market
    • 5.5.2.Foreign Exchange Market
    • 5.5.3.Exchange-Traded Funds
    • 5.5.4.Bonds
    • 5.5.5.Cryptocurrencies
    • 5.5.6.Others
  • 5.6.By End-user
    • 5.6.1.Short-Term Traders
    • 5.6.2.Long-Term Traders
    • 5.6.3.Retail Investors
    • 5.6.4.Institutional Investors
  • 5.7.By Region
    • 5.7.1.North
    • 5.7.2.South
    • 5.7.3.East
    • 5.7.4.West and Central
  • 5.8.By Company Market Share (%), FY2024

6.Market Mapping, FY2024

  • 6.1.By Component
  • 6.2.By Mode
  • 6.3.By Function
  • 6.4.By Type
  • 6.5.By End-user
  • 6.6.By Region

7.Macro Environment and Industry Structure

  • 7.1.Supply Demand Analysis
  • 7.2.Regulatory Framework and Compliance
    • 7.2.1.Securities & Exchange Board of India Guidelines and Policies
    • 7.2.2.RBI Guidelines and Policies
    • 7.2.3.Monetary and Fiscal Policies
    • 7.2.4.Taxation Policies
  • 7.3.Value Chain Analysis
  • 7.4.PESTEL Analysis
    • 7.4.1.Political Factors
    • 7.4.2.Economic System
    • 7.4.3.Social Implications
    • 7.4.4.Technological Advancements
    • 7.4.5.Environmental Impacts
    • 7.4.6.Legal Compliances and Regulatory Policies (Statutory Bodies Included)
  • 7.5.Porter's Five Forces Analysis
    • 7.5.1.Supplier Power
    • 7.5.2.Buyer Power
    • 7.5.3.Substitution Threat
    • 7.5.4.Threat from New Entrant
    • 7.5.5.Competitive Rivalry

8.Market Dynamics

  • 8.1.Growth Drivers
  • 8.2.Growth Inhibitors (Challenges and Restraints)

9.Key Players Landscape

  • 9.1.Competition Matrix of Top Five Market Leaders
  • 9.2.Market Revenue Analysis of Top Five Market Leaders (in %, FY2024)
  • 9.3.Mergers and Acquisitions/Joint Ventures (If Applicable)
  • 9.4.SWOT Analysis (For Five Market Players)
  • 9.5.Patent Analysis (If Applicable)

10.Case Studies

11.Algorithmic Trading Software Pricing Analysis

12.Key Players Outlook

  • 12.1.Quadeye Securities Private Limited
    • 12.1.1.Company Details
    • 12.1.2.Key Management Personnel
    • 12.1.3.Products & Services
    • 12.1.4.Financials (As reported)
    • 12.1.5.Key Market Focus & Geographical Presence
    • 12.1.6.Recent Developments
  • 12.2.AlgoBulls Technologies Private Limited
  • 12.3.Utrade Solutions Private Limited
  • 12.4.Trade Rays LLP
  • 12.5.Open Futures & Commodities Private Limited
  • 12.6.Kiwi Capital Private Limited
  • 12.7.AlphaGrep Securities
  • 12.8.Dolat Capital Market Private Limited
  • 12.9.Graviton Research Capital LLP
  • 12.10.Iragecapital Advisory Private Limited

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work

13.Strategic Recommendations

14.About Us & Disclaimer

List of Tables

  • Table 1. Pricing Analysis of Products from Key Players
  • Table 2. Competition Matrix of Top 5 Market Leaders
  • Table 3. Mergers & Acquisitions/ Joint Ventures (If Applicable)
  • Table 4. About Us - Regions and Countries Where We Have Executed Client Projects

List of Figures

  • Figure 1.India Algorithmic Trading Market, By Value, In USD Billion, FY2018-FY2032F
  • Figure 2.India Algorithmic Trading Market Share (%), By Component, FY2018-FY2032F
  • Figure 3.India Algorithmic Trading Market Share (%), By Mode, FY2018-FY2032F
  • Figure 4.India Algorithmic Trading Market Share (%), By Function, FY2018-FY2032F
  • Figure 5.India Algorithmic Trading Market Share (%), By Type, FY2018-FY2032F
  • Figure 6.India Algorithmic Trading Market Share (%), By End-user, FY2018-FY2032F
  • Figure 7.India Algorithmic Trading Market Share (%), By Region, FY2018-FY2032F
  • Figure 8.By Component Map-Market Size (USD Billion) & Growth Rate (%), FY2024
  • Figure 9.By Mode Map-Market Size (USD Billion) & Growth Rate (%), FY2024
  • Figure 10.By Function Map-Market Size (USD Billion) & Growth Rate (%), FY2024
  • Figure 11.By Type Map-Market Size (USD Billion) & Growth Rate (%), FY2024
  • Figure 12.By End-user Map-Market Size (USD Billion) & Growth Rate (%), FY2024
  • Figure 13.By Region Map-Market Size (USD Billion) & Growth Rate (%), FY2024