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市場調查報告書
商品編碼
1479982

印度演算法交易市場評估：依組成部分、依方法、依功能、依類型、依最終用戶、依地區、機會、預測（2018 財年-2032 財年）

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個工作天內

價格

印度演算法交易的市場規模預計將從2024 財年的10.8 億美元增至2032 財年的26.1 億美元，在2025 財年至2032 財年的預測期內複合年增長率為11.65%。還會增長。基於雲端的解決方案的採用增加、對快速高效的訂單執行的需求不斷增長、對基於人工智慧的服務和市場監控的需求不斷增長、個人可支配收入增加以及交易成本降低等因素正在推動演算法交易成為成長因素。

演算法交易是股票市場領域的技術進步。它是一個被編程為執行一組特定指令的過程，一種以超出人類能力的速度和頻率發出有利可圖的訂單的演算法。數據集在股票市場中發揮著重要作用，每個統計數據都會被評估和使用，以造福所有參與者。這使投資者能夠發現流動性潛力並做出更明智的交易選擇。透過交易選擇，降低交易成本，同時改善交易流程，減少市場波動，增加獲利潛力。

報告顯示，57%的金融機構認為人工智慧將使他們在市場上更具競爭力。 Streak Zerodha 最近推出了一項新功能 Streak Scanner，它允許您使用技術指標和運算子建立和運行股票、期貨和選擇權的掃瞄。該掃瞄器基於不同的細分市場，例如漲幅最大、虧損、燭台形態、範圍突破、多頭和空頭期權。所有這些掃瞄器都處理 1 分鐘資料。

網路使用量的增加推動市場成長

網路使用量的增加正在推動演算法交易市場的成長。隨著互聯網變得越來越普及，消費者更容易訪問線上平台來獲取有關線上交易的知識和資訊。線上交易嚴重依賴互聯網，推動了演算法交易市場的成長。

根據 DataReportal 2024 報告，2024 年 1 月印度有 7.515 億網路用戶。年初印度的網路普及率為總人口的52.4%。另外，早期投資者依賴經紀人買賣股票，但現在他們藉由網路參與股票買賣。網上交易節省時間、精力和金錢。根據《印度時報》報道，到 2023 年，農村地區的活躍網路用戶將達到 4.42 億，超過城市地區的 3.78 億。因此，互聯網普及率的提高將推動演算法交易市場的成長。

市場監理的需求推動市場

市場監控或貿易監控涉及貿易數據的取得、分析和監控，以揭露市場濫用行為和其他金融犯罪，例如詐欺和內線交易。各國法規都規定了交易監控，以防止可能損害投資者利益並擾亂金融市場平穩運行的交易，例如內線交易、市場操縱和詐欺交易。高頻交易引發了人們對市場穩定性和完整性的擔憂。監控音訊、視訊和其他電子通訊對於識別欺詐性交易者活動是必要的。

基於人工智慧的工具可以根據語氣、行話、短語和暗語將資訊置於上下文中，以揭示交易者的真實意圖。如果訂單下達或取消出現異常高峰，則會產生警報。識別洗錢技術，例如與同一交易對手的過度交易和無法訪問的預訂。 ALGO AIoT 是一種先進的 CMS 遠端監控解決方案，由人工智慧和物聯網提供支持，並由機器人流程自動化提供支持，可監控視訊並輕鬆檢測威脅，同時降低成本和複雜性。對市場監控日益增長的需求促使了對具有監控功能的演算法交易系統的需求，從而推動了市場的成長。

本報告針對印度演算法交易市場進行研究和分析，提供市場規模和預測、市場動態、主要參與者的現狀和前景等。

目錄

第一章研究方法

第 2 章專案範圍與定義

第 3 章執行摘要

第 4 章顧客回饋

  • 人口統計（年齡/群組分析 - 嬰兒潮世代和 X 世代、千禧世代、Z 世代、性別、收入 - 低收入、中等收入、高收入、地區、國籍等）
  • 市場認知度
  • 品牌知名度與忠誠度
  • 購買決策時考慮的因素
  • 演算法交易的頻率
  • 演算法交易方法

第五章印度演算法交易市場展望（2018-2032 財年）

  • 市場規模與預測
    • 金額
  • 依組件
    • 解決方案
    • 服務
  • 依方法
    • 雲
    • 本地
  • 依功能
    • 程式設計
    • 偵錯
    • 資料擷取
    • 回測、優化
    • 危機管理
  • 依類型
    • 股市
    • 外匯市場
    • 交易所交易投資信託
    • 債券
    • 加密貨幣
    • 其他
  • 依最終用戶
    • 短期交易者
    • 長期交易者
    • 個人投資者
    • 機構投資者
  • 依地區
    • 北
    • 南部
    • 東方
    • 西部和中部地區
  • 市佔率：依公司劃分（2024 財年）

第 6 章市場地圖（2024 財年）

  • 依組件
  • 依方法
  • 依功能
  • 依類型
  • 依最終用戶
  • 依地區

第七章宏觀環境與產業結構

  • 需求與供給分析
  • 監管框架和合規性
  • 價值鏈分析
  • PESTEL 分析
  • 波特五力分析

第 8 章市場動態

  • 生長促進因素
  • 抑製成長的因素（問題、限制因素）

第九章主要公司狀況

  • 前 5 名市場領導者的競爭矩陣
  • 前 5 位市場領導者的市場收入分析（2024 年）
  • 併購/合資企業（如果適用）
  • SWOT 分析（5 家市場公司）
  • 專利分析（如果適用）

第 10 章個案研究

第十一章演算法交易軟體價格分析

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 章策略建議

第14章關於我們公司，免責聲明

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