This document discusses a comparative study of the Indian stock market and its international counterparts. It analyzes trends, similarities, and patterns in activities and movements between the Indian stock exchanges (BSE and NSE) and exchanges in other countries from 1995 to 2006. The study finds that Indian stock markets have become more integrated with global markets and react in tandem with global cues. It concludes that Indian exchanges are ready to further integrate if regulations are relaxed and a variety of instruments are introduced.
IRJET - Stock Market Analysis and Prediction using Deep LearningIRJET Journal
This document discusses using deep learning techniques to analyze stock market data and predict stock prices. It proposes a model that uses preprocessing, feature extraction, and machine learning algorithms like neural networks and K-nearest neighbors (KNN) classification to make predictions. The model is evaluated on stock market datasets containing attributes like date, price, volume. Feature extraction analyzes relationships between companies to better predict individual stock prices. Neural networks and KNN are used for prediction and KNN performed best when using single-company features alone. The goal is to help investors and fund managers make better investment decisions.
The Microsoft Certified Systems Engineer (MCSE) certification demonstrates expertise in designing and implementing Windows infrastructure solutions. The Cisco Certified Network Associate (CCNA) certification validates fundamentals of networking including IP addressing and OSI models. Cisco's CCNP certification focuses on advanced routing and switching skills needed for building converged network infrastructure.
A Study on Stock’s Volatility in Banking Sector using Technical AnalysisIRJET Journal
This document discusses a study on analyzing the volatility of stocks in the Indian banking sector using technical analysis tools. It aims to determine which banks perform better based on price fluctuations. The study uses tools like Bollinger bands and Relative Strength Index (RSI) to analyze weekly share price movements of six banks (Allahabad Bank, Bank of India, Oriental Bank of Commerce, Vijaya Bank, Corporation Bank, and Canara Bank) over three years. The results show that Canara Bank and Vijaya Bank exhibited the highest volatility and returns compared to other banks during the period. The analysis of technical indicators can help investors identify optimal times to buy and sell bank stocks and predict market movements.
IRJET- Data Analysis of Startups Investments and Funding Trends in IndiaIRJET Journal
The document analyzes investment and funding trends for startups in India based on a dataset from 2015 to 2017. Some key findings include:
- Consumer internet startups received the most funding, followed by technology and e-commerce startups.
- Seed funding and private equity were the most common investment types.
- Bangalore, Mumbai, and Delhi attracted the most investors and funding.
- January 2016 and June 2015-2016 saw peaks in monthly funding due to government initiatives like Startup India and Digital India.
ITG Investor provides an overview of Investment Technology Group, Inc.'s (ITG) international growth, robust balance sheet, and competitive platform. Key points include:
- International operations comprised 40% of ITG's total revenues and over half of pre-tax income in 2013, with opportunities for continued growth in Europe, Canada, and Asia.
- ITG has a strong balance sheet with $223 million in cash/equivalents and only $27 million in long-term debt as of March 2014.
- ITG's operating model and expense management provide attractive profit margins of 40-50% on incremental revenue.
This document discusses using machine learning techniques to predict stock market prices. It begins with an introduction to existing stock prediction methods like fundamental and technical analysis. The proposed system would use machine learning models to analyze historical stock price data and sentiment analysis of news articles to predict future stock prices, volatility, and market trends. The methodology section outlines different models, including using only historical prices, classifying sentiment of news, and aspect-based sentiment analysis. Features like stock price volatility, momentum, and index momentum would be used. The conclusion states that accurately predicting the complex stock market requires considering various factors.
Stock Market Prediction and Investment Portfolio Selection Using Computationa...iosrjce
This document discusses using computational approaches for stock market prediction and investment portfolio selection. It reviews literature on various techniques used, including linear programming, goal programming, data mining, and soft computing strategies. Soft computing approaches like neural networks, fuzzy logic, and genetic algorithms are highlighted as useful tools for analyzing the stock market to predict stock prices and guide investors. Key factors that impact the stock market are also examined, such as technical indicators, financial ratios, economic policies, and political environment. The objective is to study existing methods and help investors select profitable scripts to add to their portfolios.
This document discusses a comparative study of the Indian stock market and its international counterparts. It analyzes trends, similarities, and patterns in activities and movements between the Indian stock exchanges (BSE and NSE) and exchanges in other countries from 1995 to 2006. The study finds that Indian stock markets have become more integrated with global markets and react in tandem with global cues. It concludes that Indian exchanges are ready to further integrate if regulations are relaxed and a variety of instruments are introduced.
IRJET - Stock Market Analysis and Prediction using Deep LearningIRJET Journal
This document discusses using deep learning techniques to analyze stock market data and predict stock prices. It proposes a model that uses preprocessing, feature extraction, and machine learning algorithms like neural networks and K-nearest neighbors (KNN) classification to make predictions. The model is evaluated on stock market datasets containing attributes like date, price, volume. Feature extraction analyzes relationships between companies to better predict individual stock prices. Neural networks and KNN are used for prediction and KNN performed best when using single-company features alone. The goal is to help investors and fund managers make better investment decisions.
The Microsoft Certified Systems Engineer (MCSE) certification demonstrates expertise in designing and implementing Windows infrastructure solutions. The Cisco Certified Network Associate (CCNA) certification validates fundamentals of networking including IP addressing and OSI models. Cisco's CCNP certification focuses on advanced routing and switching skills needed for building converged network infrastructure.
A Study on Stock’s Volatility in Banking Sector using Technical AnalysisIRJET Journal
This document discusses a study on analyzing the volatility of stocks in the Indian banking sector using technical analysis tools. It aims to determine which banks perform better based on price fluctuations. The study uses tools like Bollinger bands and Relative Strength Index (RSI) to analyze weekly share price movements of six banks (Allahabad Bank, Bank of India, Oriental Bank of Commerce, Vijaya Bank, Corporation Bank, and Canara Bank) over three years. The results show that Canara Bank and Vijaya Bank exhibited the highest volatility and returns compared to other banks during the period. The analysis of technical indicators can help investors identify optimal times to buy and sell bank stocks and predict market movements.
IRJET- Data Analysis of Startups Investments and Funding Trends in IndiaIRJET Journal
The document analyzes investment and funding trends for startups in India based on a dataset from 2015 to 2017. Some key findings include:
- Consumer internet startups received the most funding, followed by technology and e-commerce startups.
- Seed funding and private equity were the most common investment types.
- Bangalore, Mumbai, and Delhi attracted the most investors and funding.
- January 2016 and June 2015-2016 saw peaks in monthly funding due to government initiatives like Startup India and Digital India.
ITG Investor provides an overview of Investment Technology Group, Inc.'s (ITG) international growth, robust balance sheet, and competitive platform. Key points include:
- International operations comprised 40% of ITG's total revenues and over half of pre-tax income in 2013, with opportunities for continued growth in Europe, Canada, and Asia.
- ITG has a strong balance sheet with $223 million in cash/equivalents and only $27 million in long-term debt as of March 2014.
- ITG's operating model and expense management provide attractive profit margins of 40-50% on incremental revenue.
This document discusses using machine learning techniques to predict stock market prices. It begins with an introduction to existing stock prediction methods like fundamental and technical analysis. The proposed system would use machine learning models to analyze historical stock price data and sentiment analysis of news articles to predict future stock prices, volatility, and market trends. The methodology section outlines different models, including using only historical prices, classifying sentiment of news, and aspect-based sentiment analysis. Features like stock price volatility, momentum, and index momentum would be used. The conclusion states that accurately predicting the complex stock market requires considering various factors.
Stock Market Prediction and Investment Portfolio Selection Using Computationa...iosrjce
This document discusses using computational approaches for stock market prediction and investment portfolio selection. It reviews literature on various techniques used, including linear programming, goal programming, data mining, and soft computing strategies. Soft computing approaches like neural networks, fuzzy logic, and genetic algorithms are highlighted as useful tools for analyzing the stock market to predict stock prices and guide investors. Key factors that impact the stock market are also examined, such as technical indicators, financial ratios, economic policies, and political environment. The objective is to study existing methods and help investors select profitable scripts to add to their portfolios.
This document discusses using computational approaches for stock market prediction and investment portfolio selection. It reviews literature on various techniques used, including linear programming, goal programming, data mining, and soft computing strategies. Soft computing approaches like neural networks, fuzzy logic, and genetic algorithms are highlighted as useful tools for analyzing the stock market to predict stock prices and guide investors. Key factors that impact the stock market are also examined, such as technical indicators, financial indicators, economic policies, and political factors. The objective is to study existing methods for predicting the Indian stock market and selecting optimal investment portfolios.
Algorithmic Trading and its Impact on the MarketIRJET Journal
The document discusses algorithmic trading and its impact on markets. It begins by defining algorithmic trading as trading executed by computer programs using predetermined rules and strategies, allowing for much faster and higher-volume trades than human traders can perform manually. The document then reviews several related studies that have found both benefits and drawbacks of algorithmic trading, such as improved pricing efficiency but also increased short-term volatility. Finally, it outlines the methodology for developing and backtesting algorithmic trading strategies before discussing the benefits algorithmic trading provides in the Indian stock market context.
Impact of Capital market reforms on the Indian Stock Market since Globalisationinventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
This document reviews stock trend prediction using a combination of effective multi-technical indicators. It discusses several past studies that have examined various combinations of technical indicators for predicting stock trends, including the use of moving averages, MACD, RSI, Bollinger Bands, and OBV individually and together. The document also proposes that a strategy combining multiple complementary indicators into a single model could improve prediction performance over the use of individual indicators alone.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both these capabilities are very important for an investor in order to obtain maximized profit and minimized losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends and market conditions. Technical analysis helps to understand stock prices behavior with regards to past trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase investment performance by taking into account the global performance and the proposed combination of effective multi technical indicator strategy model.
A project report on equity evaluation of top 3 it companies at stock exchangeBabasab Patil
This document provides an analysis of the equity valuation of the top 3 IT companies in India - Wipro, Infosys, and TCS. It summarizes their financial performance over the last 5 years and uses various valuation models to determine the future stock prices of these companies. While the Indian stock market and IT sector boomed in the late 1990s and early 2000s, IT stocks have underperformed the market in recent years. The analysis aims to understand the reasons for this and provide strategies for profitable long-term investment in these company equities.
The Indian securities market has undergone significant reforms and developments over the past decade to modernize practices and increase efficiency. Key changes include shortening the settlement cycle from T+5 to T+2 in line with global standards, introducing automated trading systems, and dematerializing shares to reduce settlement risk. New products like derivatives and ETFs have also been introduced to diversify the market and attract more investors. Looking ahead, further corporatization of brokers and streamlining of processes will help make the Indian market more competitive globally.
The document provides an overview of the Indian derivatives market. It discusses key components such as the structure of securities markets, derivatives trading, and the components that make up the derivatives market. It also covers current trends in derivatives globally and in India, including growth in market size. Details on options and futures trading in India are given. The document discusses consumer profiles, how derivatives are traded, typical trading time frames, and growth in key market segments. It provides an analysis of top stock broking firms in India. [/SUMMARY]
An impact of ict on the growth of capital market empirical evidence from indi...Alexander Decker
This document examines the impact of information and communication technology (ICT) on the growth of the Indian stock exchange. It discusses two schools of thought on how ICT impacts capital markets, with one arguing it increases volatility and risks, and the other arguing it makes markets more efficient. The document aims to determine how ICT adoption has impacted stock market development indicators and business operations in India. It reviews literature showing ICT automates exchanges, reduces costs, increases liquidity and trading. The results indicate selected variables like the number of stockbrokers and investors accessing ICT have been significantly affected, and ICT has overall contributed to growth in the Indian capital market.
2.[7 14]an impact of ict on the growth of capital market-empirical evidence f...Alexander Decker
This document examines the impact of information and communication technology (ICT) on the growth of the Indian stock exchange. It discusses two schools of thought on how ICT impacts capital markets, with one arguing it increases volatility and risks, and the other arguing it makes markets more efficient. The document aims to determine how ICT adoption has impacted stock market development indicators and business operations in India. It reviews literature showing ICT automates exchanges, reduces costs, increases liquidity and trading. The results indicate selected variables like the number of stockbrokers and investors accessing ICT have been significantly affected by ICT adoption in India.
1 presentation on dynamic adjustment towards target capital structureNajma soomro
This study examines the dynamics of capital structure for Indian manufacturing companies. It finds that companies have target capital structures determined by firm-specific factors like size, tangibility, profitability, and market-to-book ratio. The speed of adjustment to the target leverage is affected by the size of the company, growth opportunities, and the distance between the target and observed leverage. The study contributes to understanding how Indian companies determine and adjust towards their optimal capital structures.
The document provides an introduction to algorithmic trading, which involves using computer programs and models to automate trading decisions and transactions. It discusses how algorithmic trading has grown significantly in recent years, with some markets seeing over 80% of trades executed algorithmically. The document also outlines some of the common types of algorithmic trading strategies used and software companies that provide platforms to develop algorithmic trading systems.
The document discusses a study conducted on hedging strategies at Anand Rathi Shares and Stock Brokers Limited. The study focuses on hedging equity positions using stock futures at different strike prices on the National Stock Exchange. The objective is to analyze the effectiveness of hedging at various portfolio levels. Sample companies were selected from industries like banking, pharma, IT and telecom. Primary data on stock futures was collected from the NSE website. The limitations included a small sample size and data collected over a short period.
This document summarizes a research article that analyzes the performance of mutual fund schemes in India. It discusses how the mutual fund industry in India grew significantly in the pre-recession period from 2006-2007 due to overall GDP growth and positive investor sentiment. However, during the recession period of 2008-2009, the industry witnessed a decline as markets fell. After the recession, the industry struggled to regain its previous growth. The document also examines the use of principal component analysis to identify relevant variables that influence mutual fund performance.
This document discusses technological developments in the Indian banking sector and analyzes the impact of electronic banking (e-banking) on banks' financial performance. It outlines key events in India's e-banking development like the introduction of debit/credit cards, electronic funds transfer, real-time gross settlement systems. The document also examines different studies that have analyzed the relationship between e-banking investments and banks' profitability and productivity, with mixed findings. Committee reports from the Reserve Bank of India on computerization and e-banking in the 1980s-1990s are also summarized.
AN ANALYSIS OF STOCK MARKET PERFORMANCE AND FUNDAMENTALS OF INFRASTRUCTURE CO...Ashley Carter
This document appears to be a thesis submitted by three students - Nitesh Pattnaik, Shashank Srivastava, and Yash Sachdev - to the National Institute of Construction Management and Research in partial fulfillment of their Post Graduate Programme in Advanced Construction Management. The thesis analyzes the stock market performance and fundamentals of infrastructure companies in India. It includes an introduction, literature review, methodology, experimental analysis of stock market performance and financial fundamentals, and conclusions.
This document provides an overview and highlights of Investment Technology Group, Inc. (ITG). Some key points:
- ITG has achieved product parity internationally and international operations comprised 40% of revenues and 65% of net income in 2013.
- ITG has a robust balance sheet with $223 million in cash/equivalents and only $27 million in long-term debt as of March 2014.
- ITG has four main product groups - Electronic Brokerage, Research/Sales/Trading, Platforms, and Analytics. Electronic Brokerage accounted for 53% of revenues in 2013.
This document provides an overview and highlights of Investment Technology Group, Inc. (ITG). Some key points:
- ITG has achieved product parity internationally and in 2013, international operations comprised 40% of revenues and 65% of net income.
- ITG has a robust balance sheet with $223 million in cash/equivalents and only $27 million in long-term debt. They actively repurchase shares.
- ITG's main product groups are electronic brokerage, research/sales/trading, platforms, and analytics. They provide dark pools, algorithms, smart order routing, research, and trading/portfolio tools globally.
How to Invest in Cryptocurrency for Beginners: A Complete GuideDaniel
Cryptocurrency is digital money that operates independently of a central authority, utilizing cryptography for security. Unlike traditional currencies issued by governments (fiat currencies), cryptocurrencies are decentralized and typically operate on a technology called blockchain. Each cryptocurrency transaction is recorded on a public ledger, ensuring transparency and security.
Cryptocurrencies can be used for various purposes, including online purchases, investment opportunities, and as a means of transferring value globally without the need for intermediaries like banks.
Navigating Your Financial Future: Comprehensive Planning with Mike Baumannmikebaumannfinancial
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This document discusses using computational approaches for stock market prediction and investment portfolio selection. It reviews literature on various techniques used, including linear programming, goal programming, data mining, and soft computing strategies. Soft computing approaches like neural networks, fuzzy logic, and genetic algorithms are highlighted as useful tools for analyzing the stock market to predict stock prices and guide investors. Key factors that impact the stock market are also examined, such as technical indicators, financial indicators, economic policies, and political factors. The objective is to study existing methods for predicting the Indian stock market and selecting optimal investment portfolios.
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International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
This document reviews stock trend prediction using a combination of effective multi-technical indicators. It discusses several past studies that have examined various combinations of technical indicators for predicting stock trends, including the use of moving averages, MACD, RSI, Bollinger Bands, and OBV individually and together. The document also proposes that a strategy combining multiple complementary indicators into a single model could improve prediction performance over the use of individual indicators alone.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both these capabilities are very important for an investor in order to obtain maximized profit and minimized losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends and market conditions. Technical analysis helps to understand stock prices behavior with regards to past trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase investment performance by taking into account the global performance and the proposed combination of effective multi technical indicator strategy model.
A project report on equity evaluation of top 3 it companies at stock exchangeBabasab Patil
This document provides an analysis of the equity valuation of the top 3 IT companies in India - Wipro, Infosys, and TCS. It summarizes their financial performance over the last 5 years and uses various valuation models to determine the future stock prices of these companies. While the Indian stock market and IT sector boomed in the late 1990s and early 2000s, IT stocks have underperformed the market in recent years. The analysis aims to understand the reasons for this and provide strategies for profitable long-term investment in these company equities.
The Indian securities market has undergone significant reforms and developments over the past decade to modernize practices and increase efficiency. Key changes include shortening the settlement cycle from T+5 to T+2 in line with global standards, introducing automated trading systems, and dematerializing shares to reduce settlement risk. New products like derivatives and ETFs have also been introduced to diversify the market and attract more investors. Looking ahead, further corporatization of brokers and streamlining of processes will help make the Indian market more competitive globally.
The document provides an overview of the Indian derivatives market. It discusses key components such as the structure of securities markets, derivatives trading, and the components that make up the derivatives market. It also covers current trends in derivatives globally and in India, including growth in market size. Details on options and futures trading in India are given. The document discusses consumer profiles, how derivatives are traded, typical trading time frames, and growth in key market segments. It provides an analysis of top stock broking firms in India. [/SUMMARY]
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This document examines the impact of information and communication technology (ICT) on the growth of the Indian stock exchange. It discusses two schools of thought on how ICT impacts capital markets, with one arguing it increases volatility and risks, and the other arguing it makes markets more efficient. The document aims to determine how ICT adoption has impacted stock market development indicators and business operations in India. It reviews literature showing ICT automates exchanges, reduces costs, increases liquidity and trading. The results indicate selected variables like the number of stockbrokers and investors accessing ICT have been significantly affected, and ICT has overall contributed to growth in the Indian capital market.
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This study examines the dynamics of capital structure for Indian manufacturing companies. It finds that companies have target capital structures determined by firm-specific factors like size, tangibility, profitability, and market-to-book ratio. The speed of adjustment to the target leverage is affected by the size of the company, growth opportunities, and the distance between the target and observed leverage. The study contributes to understanding how Indian companies determine and adjust towards their optimal capital structures.
The document provides an introduction to algorithmic trading, which involves using computer programs and models to automate trading decisions and transactions. It discusses how algorithmic trading has grown significantly in recent years, with some markets seeing over 80% of trades executed algorithmically. The document also outlines some of the common types of algorithmic trading strategies used and software companies that provide platforms to develop algorithmic trading systems.
The document discusses a study conducted on hedging strategies at Anand Rathi Shares and Stock Brokers Limited. The study focuses on hedging equity positions using stock futures at different strike prices on the National Stock Exchange. The objective is to analyze the effectiveness of hedging at various portfolio levels. Sample companies were selected from industries like banking, pharma, IT and telecom. Primary data on stock futures was collected from the NSE website. The limitations included a small sample size and data collected over a short period.
This document summarizes a research article that analyzes the performance of mutual fund schemes in India. It discusses how the mutual fund industry in India grew significantly in the pre-recession period from 2006-2007 due to overall GDP growth and positive investor sentiment. However, during the recession period of 2008-2009, the industry witnessed a decline as markets fell. After the recession, the industry struggled to regain its previous growth. The document also examines the use of principal component analysis to identify relevant variables that influence mutual fund performance.
This document discusses technological developments in the Indian banking sector and analyzes the impact of electronic banking (e-banking) on banks' financial performance. It outlines key events in India's e-banking development like the introduction of debit/credit cards, electronic funds transfer, real-time gross settlement systems. The document also examines different studies that have analyzed the relationship between e-banking investments and banks' profitability and productivity, with mixed findings. Committee reports from the Reserve Bank of India on computerization and e-banking in the 1980s-1990s are also summarized.
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This document appears to be a thesis submitted by three students - Nitesh Pattnaik, Shashank Srivastava, and Yash Sachdev - to the National Institute of Construction Management and Research in partial fulfillment of their Post Graduate Programme in Advanced Construction Management. The thesis analyzes the stock market performance and fundamentals of infrastructure companies in India. It includes an introduction, literature review, methodology, experimental analysis of stock market performance and financial fundamentals, and conclusions.
This document provides an overview and highlights of Investment Technology Group, Inc. (ITG). Some key points:
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This document provides an overview and highlights of Investment Technology Group, Inc. (ITG). Some key points:
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June 20, 2024
CRYPTOCURRENCY: REVOLUTIONIZING THE FINANCIAL LANDSCAPE AND SHAPING THE FUTURE
Cryptocurrency: Revolutionizing the Financial Landscape and Shaping the Future
Cryptocurrency, a digital or virtual form of currency that uses cryptography for security, has revolutionized the financial landscape. Originating with Bitcoin's inception in 2009 by the pseudonymous Satoshi Nakamoto, cryptocurrencies have grown from niche curiosities to mainstream financial instruments, reshaping how we think about money, transactions, and the global economy.
#### The Genesis of Cryptocurrency
The birth of Bitcoin marked the beginning of the cryptocurrency era. Unlike traditional currencies issued by governments and controlled by central banks, Bitcoin operates on a decentralized network using blockchain technology. This technology ensures transparency, security, and immutability of transactions, fundamentally challenging the centralized financial systems that have dominated for centuries.
Bitcoin was conceived as a peer-to-peer electronic cash system, aimed at providing an alternative to the traditional banking system plagued by inefficiencies, high fees, and lack of transparency. The underlying blockchain technology, a distributed ledger maintained by a network of nodes, ensures that every transaction is recorded and cannot be altered, thus providing a secure and transparent financial system.
#### The Proliferation of Altcoins
Following Bitcoin's success, thousands of alternative cryptocurrencies, or altcoins, have emerged. Each of these altcoins aims to improve upon Bitcoin or serve specific purposes within the digital economy. Notable examples include Ethereum, which introduced smart contracts – self-executing contracts with the terms of the agreement
13 Jun 24 ILC Retirement Income Summit - slides.pptxILC- UK
ILC's Retirement Income Summit was hosted by M&G and supported by Canada Life. The event brought together key policymakers, influencers and experts to help identify policy priorities for the next Government and ensure more of us have access to a decent income in retirement.
Contributors included:
Jo Blanden, Professor in Economics, University of Surrey
Clive Bolton, CEO, Life Insurance M&G Plc
Jim Boyd, CEO, Equity Release Council
Molly Broome, Economist, Resolution Foundation
Nida Broughton, Co-Director of Economic Policy, Behavioural Insights Team
Jonathan Cribb, Associate Director and Head of Retirement, Savings, and Ageing, Institute for Fiscal Studies
Joanna Elson CBE, Chief Executive Officer, Independent Age
Tom Evans, Managing Director of Retirement, Canada Life
Steve Groves, Chair, Key Retirement Group
Tish Hanifan, Founder and Joint Chair of the Society of Later life Advisers
Sue Lewis, ILC Trustee
Siobhan Lough, Senior Consultant, Hymans Robertson
Mick McAteer, Co-Director, The Financial Inclusion Centre
Stuart McDonald MBE, Head of Longevity and Democratic Insights, LCP
Anusha Mittal, Managing Director, Individual Life and Pensions, M&G Life
Shelley Morris, Senior Project Manager, Living Pension, Living Wage Foundation
Sarah O'Grady, Journalist
Will Sherlock, Head of External Relations, M&G Plc
Daniela Silcock, Head of Policy Research, Pensions Policy Institute
David Sinclair, Chief Executive, ILC
Jordi Skilbeck, Senior Policy Advisor, Pensions and Lifetime Savings Association
Rt Hon Sir Stephen Timms, former Chair, Work & Pensions Committee
Nigel Waterson, ILC Trustee
Jackie Wells, Strategy and Policy Consultant, ILC Strategic Advisory Board
2. What is Algorithmic Trading?
• Stock market is influenced by diverse forces and factors which even the most
brilliant investors fail to comprehend.
• The quant revolution, started in early 1970s in US, believe that it is possible
to capture the relationship among these forces and factors using reliable
mathematical models.
• This paves way to the birth of algorithmic trading – any order generated
using automated executed logic (SEBI, 2012).
3. How trading algorithms are working?
Monitor
financial
markets
Discover
overlooked patters
and anomalies
Buy/Sell
signals
Allocation of
money
Trading
strategies
4. High Frequency Trading
• Only half the game is lucrative trade ideas.
• The trader who moves fast in the market often holds a competitive edge.
• High Frequency Trading is a type of algorithmic trading which is latency sensitive and is
characterized by a high daily portfolio turnover and high order to trade ratio.
• Average holding time of a stock – 22 seconds (Yan Ohayan)
• HFTs are trading at a speed of 64 millionth of a second (the average processing speed of
human brain is 9/10 of a second).
5.
6. Algorithmic Trading in India
• In 2008, SEBI introduced algorithmic trading in India by
allowing Direct Market Access Facility to institutional
investors.
• DMA allows brokers to provide their infrastructure to
their clients, thereby they can access exchange trading
system without broker’s intervention, leads to lower cost
per transaction.
• Indian stock market adopts so quickly to algorithmic
trading. In 2016, nearly 50% trading in India are
algorithmic and there was 8 times jump in the action of
leading HFT firms in the year 2019 in India (Kriplani,
2019).
7. Co-Location Facility
• In 2010, NSE started co-location facility by
providing 54 server racks to clients.
• Co-location involves placing the servers of
HFT firms in the same floor where the
exchange server is located, which enables to
trade in microseconds.
8. India Flash Crash
• AT attracts more and more interest in the
academic community, after the India Flash Crash
on October 5, 2012.
• Because of the Flash Crash, the NIFTY index
dropped as much as 15.6 percent within minutes
and then experience a speedy V-shared recovery
after a brief trading pause (Dalko & Wang,
2019).
• Johnson et. al (2013), reported a sharp rise in so-
called ultra-fast extreme events. They noted the
occurrence of 18520 crashes and spikes between
the years of 2006-11.
10. Impact of AT in India
This paper aims to provide a compendium of existing researches on AT in
India, which is very few in fact, in order to answer the following two important
questions:
1) What is the impact of Algo Trading on the quality of Indian Stock
Market?
2) What are the areas of concern in using Algorithmic Trading in India?
11. Algorithmic Trading & Market Quality
Gomer et. al (2011) postulates that stock market quality is mainly determined
by three parameters viz.,
1) liquidity
2) volatility
3) efficiency
12. Impact of AT on Market Liquidity
• After CLT, Latency dropped from 30 microseconds to 2 microseconds
(Aggarwal, 2013).
• Securities with higher algorithmic trading have lower liquidity costs and order
imbalance thus reduces the risk of intraday liquidity. (Thomas, 2014).
• Due to CLT large number of shares are available for trade and a reduced
imbalance is found between the number of share available to buy and sell.
(Syamala & wadhwa, 2020).
13. Impact of AT on Market Volatility
• There is a sharp drop in the volatility of prices and the volatility of
transaction costs after the increase in AT (Aggarwal, 2013; Thomas, 2014).
• Volatility has significantly reduced for the post AT period in comparison to
pre AT period in NSE (Iyer et. al, 2019).
• The speed of information adjustment in the stock market has improved a
lot, which had led to more intensive data analysis by the investors which has
led to a significant reduction in arbitrage opportunities, thereby reducing
order imbalance and volatility. (Jain, 2020)
14. Impact of AT on Market Efficiency
• Jawed & Chakrabarti (2018) examined whether increased AT intensity caused by the introduction of
co-location trading facilities improve the productive efficiency of the Indian stock indicies by
measuring the change in speed of information adjustment and change of persistence before and after
the introduction of co-location for Indian Indices.
• Their study reveals that, on the whole, the speed of information adjustment into the prices increased
while the persistence of older information decreased, for NSE after the introduction of the exogenous
event of CLT.
• There is an improvement in the overall productive efficiency of the leading Indian Indices, Midcap
and Smallcap indices being the prominent beneficiaries.
• Syamala & Wadhwa (2020) also proved in their study that AT improve overall price efficiency.
15. Areas of Concern in Using AT
• Lack of visibility, algorithms action on other algorithms, choice of algorithm
to use and absence of intuition are the areas of concern in using AT in India.
(Kumar & Puttan, 2015).
• AT imposes serious costs on the major function that securities markets
perform: allocating capital efficiently and productively across the real
economy. While quantitative models and advanced programming bring
considerable computational power to markets, they also generate risk of
information loss at significant cost to allocative efficiency. (Yadav, 2015)
16. Areas of Concern in Using AT
• AT traders might involve in unethical practices to get more benefits and
hence may seriously distort the process of price discovery (in reality, stock
prices are not discovered; they are made, they are fabricated). (Dubey et. al
2017).
• AT doesn’t facilitate capital formation. India’s capital formation rate has been
consistently declining at a CAGR -4.10% in the last 9 years, whereas the
volume in AT in last 7 years has been growing at the rate of 5.11%. (Mehra
& Vajpayee, 2018)
17. Conclusion
• This paper examined several studies which have proved the causal impact of AT on
the reduction in the overall transaction costs, order imbalance and order volatility.
• Despite its growing popularity and acceptance in India, one of the important issues
addressed by academic researchers is its negative impact on price discovery and
capital formulation, which are the fundamental functions of a capital market.
• Having said that, there is nothing to fear about AT as it is a natural evolution of the
securities markets. (Gomar et. al, 2011)
• Like all other technologies, AT enables sophisticated market participant to achieve
legitimate rewards on their investments – especially in technology – and
compensation for their market, counterparty and operational risk exposures.