Algorithmic Trading
•
8 likes•1,636 views
This document provides an overview of algorithmic trading, including: - Algorithmic trading uses computer programs to automate trading processes like analysis, signal generation, and execution. Profits drive these systems through cost savings, commissions, or proprietary trading. - For broker trading, the objective is to minimize costs, while proprietary trading aims to maximize profits. Trading firms that take on risk stand to gain the largest share of profits. - The trade process involves pretrade analysis using fundamental, technical, or quantitative methods, generating trading signals based on entry and exit strategies and risk management, and then executing trades.
Report
Share
Report
Share
Recommended
Classification of quantitative trading strategies webinar ppt
There exist thousands of academic research papers written on trading strategies. Learn what these academics found out and how we can use their knowledge in the trading world.
The webinar covers:
- Overview of research in a field of quantitative trading
- Taxonomy of quantitative trading strategies
- Where to look for unique alpha
- Examples of lesser-known trading strategies
- Common issues in quant research
Learn more about our EPAT™ course here: https://www.quantinsti.com/epat/
Most Useful links
Join EPAT – Executive Programme in Algorithmic Trading: https://goo.gl/3Oyf2B
Visit us at: https://www.quantinsti.com/
Like us on Facebook: https://www.facebook.com/quantinsti/
Follow us on Twitter: https://twitter.com/QuantInsti
Access the webinar recording here: http://ow.ly/1YwO30dz5FD
Know more about EPAT™ by QuantInsti™ at http://www.quantinsti.com/epat/
Algorithmic trading
Algorithmic trading uses computers programmed to automatically place trades based on predefined rules. It allows for trading at speeds and frequencies that are impossible for human traders. The algorithms are based on factors like timing, price, quantity, or mathematical models. Algorithmic trading provides benefits like executing trades at optimal prices, placing trades instantly, reducing risks and costs. High frequency trading is a major part of algorithmic trading and attempts to capitalize on ultra-fast order placement across multiple markets. Algorithmic trading is used by different market participants and different trading strategies can be implemented through algorithms. Technical requirements and areas of concern for algorithmic trading are also discussed.
Algo Trading
The document provides an overview of algorithmic trading, including definitions, common components, and considerations for developing algorithmic trading strategies. It discusses the basic schema for algorithmic trading, including acquiring market data, analyzing the data, establishing conditions to trigger trades, and executing trades. It also covers related topics like risk management, portfolio management, data handling, and post-trade analysis. Additionally, it discusses different types of algorithmic trading strategies and considerations for backtesting strategies.
The Impact of Algorithmic Trading
Algorithmic trading (AT) is trading conducted via electronic platforms where buy and sell orders are automatically generated by quantitative models with little human intervention. AT strategies include execution algorithms like VWAP and TWAP that minimize market impact, and alpha generating algorithms like arbitrage and trend following that exploit short-term price anomalies. While AT increases market liquidity and price discovery, it can also increase short-term volatility. Experts note that high-frequency trading puts less privileged traders at a disadvantage due to its high costs and speed, though it benefits the market overall through greater liquidity.
Algo trading
Algorithmic trading utilizes mathematical models and computer algorithms to automatically make trades based on pre-programmed instructions. It is popular in developed nations and used by large institutional investors to help brokers develop trading strategies and obtain optimal prices for large transactions while minimizing market impact. Globally, algorithmic trading accounts for around 3% of total market turnover.
Algo trading(Minor Project) strategy EMA with Ipython
This document discusses algorithmic trading and presents a minor project on the topic. It introduces algorithmic trading and its objectives such as predicting stock prices and portfolio management. It describes the required software, architecture, strategies including simple and exponential moving averages, the algorithm and output graph. It also covers limitations and concludes by discussing future enhancements to algorithmic trading using artificial intelligence.
Algorithmic Trading: an Overview
EXANTE's lecture at Stockholm School of Economics in Riga.
– Objectives of algorithmic trading
– Various types of algorithms
– The process of creating one
– Testing and evaluation
– Understanding the possible pitfalls (and solutions)
Algorithmic Trading
Algorithmic trading, also called automated trading, black-box trading, or algo trading, is the use of electronic platforms for entering trading orders with an algorithm which executes pre-programmed trading instructions accounting for a variety of variables such as timing, price, and volume.
Recommended
Classification of quantitative trading strategies webinar ppt
There exist thousands of academic research papers written on trading strategies. Learn what these academics found out and how we can use their knowledge in the trading world.
The webinar covers:
- Overview of research in a field of quantitative trading
- Taxonomy of quantitative trading strategies
- Where to look for unique alpha
- Examples of lesser-known trading strategies
- Common issues in quant research
Learn more about our EPAT™ course here: https://www.quantinsti.com/epat/
Most Useful links
Join EPAT – Executive Programme in Algorithmic Trading: https://goo.gl/3Oyf2B
Visit us at: https://www.quantinsti.com/
Like us on Facebook: https://www.facebook.com/quantinsti/
Follow us on Twitter: https://twitter.com/QuantInsti
Access the webinar recording here: http://ow.ly/1YwO30dz5FD
Know more about EPAT™ by QuantInsti™ at http://www.quantinsti.com/epat/
Algorithmic trading
Algorithmic trading uses computers programmed to automatically place trades based on predefined rules. It allows for trading at speeds and frequencies that are impossible for human traders. The algorithms are based on factors like timing, price, quantity, or mathematical models. Algorithmic trading provides benefits like executing trades at optimal prices, placing trades instantly, reducing risks and costs. High frequency trading is a major part of algorithmic trading and attempts to capitalize on ultra-fast order placement across multiple markets. Algorithmic trading is used by different market participants and different trading strategies can be implemented through algorithms. Technical requirements and areas of concern for algorithmic trading are also discussed.
Algo Trading
The document provides an overview of algorithmic trading, including definitions, common components, and considerations for developing algorithmic trading strategies. It discusses the basic schema for algorithmic trading, including acquiring market data, analyzing the data, establishing conditions to trigger trades, and executing trades. It also covers related topics like risk management, portfolio management, data handling, and post-trade analysis. Additionally, it discusses different types of algorithmic trading strategies and considerations for backtesting strategies.
The Impact of Algorithmic Trading
Algorithmic trading (AT) is trading conducted via electronic platforms where buy and sell orders are automatically generated by quantitative models with little human intervention. AT strategies include execution algorithms like VWAP and TWAP that minimize market impact, and alpha generating algorithms like arbitrage and trend following that exploit short-term price anomalies. While AT increases market liquidity and price discovery, it can also increase short-term volatility. Experts note that high-frequency trading puts less privileged traders at a disadvantage due to its high costs and speed, though it benefits the market overall through greater liquidity.
Algo trading
Algorithmic trading utilizes mathematical models and computer algorithms to automatically make trades based on pre-programmed instructions. It is popular in developed nations and used by large institutional investors to help brokers develop trading strategies and obtain optimal prices for large transactions while minimizing market impact. Globally, algorithmic trading accounts for around 3% of total market turnover.
Algo trading(Minor Project) strategy EMA with Ipython
This document discusses algorithmic trading and presents a minor project on the topic. It introduces algorithmic trading and its objectives such as predicting stock prices and portfolio management. It describes the required software, architecture, strategies including simple and exponential moving averages, the algorithm and output graph. It also covers limitations and concludes by discussing future enhancements to algorithmic trading using artificial intelligence.
Algorithmic Trading: an Overview
EXANTE's lecture at Stockholm School of Economics in Riga.
– Objectives of algorithmic trading
– Various types of algorithms
– The process of creating one
– Testing and evaluation
– Understanding the possible pitfalls (and solutions)
Algorithmic Trading
Algorithmic trading, also called automated trading, black-box trading, or algo trading, is the use of electronic platforms for entering trading orders with an algorithm which executes pre-programmed trading instructions accounting for a variety of variables such as timing, price, and volume.
Algorithmic trading
An Brief Introduction to Algorithmic Trading and some key features that are needed to develop an Algorithmic Trading software.
Algorithmic Trading
Algorithmic trading is the automated execution of trading orders using computer programs and models. It aims to minimize costs, maximize fill rates, and reduce execution risk through faster and more reliable execution platforms and more accurate prediction models. Trends driving its growth include market electronification, a desire for anonymity and efficiency, and regulatory changes. Common algorithm types include arrival price, TWAP, VWAP, and MOC models. Areas of concern include lack of visibility, algorithms reacting to each other, and missing the trader's intuition. The process involves developing and testing trading strategies through backtesting before implementing them on execution platforms to trade.
Top 8 Forex Trading Strategies That Pro Traders Use
In this slideshow find the best Forex trading strategies including chart patterns, price rejection, correlation trading, volume-price analysis, long term daily and weekly trading, news and sentiment trading strategies. Besides, you will learn the best money and risk management methods and also the best advice by the experts to control your psychology during your trades.
Volatility Trading - Hedge Fund Strategies
Volatility trading strategies seek to profit from changes in a asset's volatility. Volatility measures how much the price of an asset fluctuates over time. There are several types of volatility strategies including volatility dispersion trading which buys options on index components and sells options on the overall index, volatility spreads which use option combinations to profit from different implied volatilities, and gamma trading which aims to benefit from unexpected events causing large price moves. Volatility is important for options as their pricing depends on assumptions about future volatility.
Quant trading with artificial intelligence
Foster discussion on the practical approach of applying artificial intelligence (AI) in quant trading and avoiding the common pitfalls and the opportunities and future of quant trading.
Financial trading is the space in which people have to make decisions under uncertain uncertainty and requires decisions to be explained. However, most AI algorithm (e.g. neural network) are black-box and serves well under only constrained environment (e.g. Go / Atari). Therefore, it is important to gather domain knowledge such that AI (e.g. PGM) could have more cognitive ability to provide a white-box explanation for their trading decisions.
If AI could provide a clearer visibility on the reality & present, it can assist human to provide faster, more-accurate and more-informed investment decisions. With a better understanding of the world, we can allocate resources more efficiently and ultimately create a better world to live.
Video for the slides:
https://www.youtube.com/watch?v=sideoQYAVDM&t=351s
"A Framework-Based Approach to Building Quantitative Trading Systems" by Dr. ...
Contrary to popular wisdom the difference between a retail quant trader and a professional portfolio manager is not in "having better trade entry and exit rules". Rather it is the difference in how each approaches the concepts of portfolio optimisation and risk management.
Both of these topics are synonymous with heavy math, which can be off-putting for beginner retail systematic traders. Hence, it can be extremely daunting for those without institutional experience to know how to turn a set of trading rules into a robust portfolio and risk management system.
In this talk, Mike will discuss how to take a typical retail quant strategy and place it in a professional quantitative trading framework, with proper position sizing and risk assessment, without resorting to pages of formulas or the need to have a PhD in statistics!
Algo trading with machine learning ppt
This document discusses algorithmic trading using machine learning. It introduces algorithmic trading and its advantages over human trading. The objectives are to maximize profits with minimum capital and predict stock prices using machine learning. Python is used to develop the trading platform. The architecture includes exchanges, servers to receive and store market data, and applications to interface and manage orders. Strategies discussed include analyzing candlestick patterns and volume. A proposed algorithm uses machine learning on historical data to generate buy signals. Limitations include algorithms not being 100% accurate and not universal. Future enhancements may include greater use of artificial intelligence as technology advances.
Quantitative Trading
This months speaker is Quantitative Researcher Yann-Shin Aaron Chen. Chen grew up in Taipei and moved to Southern California when he was a teenager. He participated in numerous math and physics competitions in high school and was ranked in the top 24 students in the US Physics Olympiad. He obtained a B.A. in mathematics at U.C. Berkeley, and got his PhD also at Berkeley in 2012. During his graduate studies, he did a summer internship at Morgan Stanley. After graduation, he joined Citadel, one of the largest hedge funds in US, as a quantitative researcher and worked there for 5 years. He left Citadel a few months ago, and he is now looking forward to his next venture.
Quantitative trading is a relatively new field in the world of finance. With the advances of information technology and data science, quantitative trading has generated significant interest in the past decade. In his talk, Aaron will cover the basic facts about quantitative trading and open the floor for questions. This short presentation is intended for people that are not in this industry and want to learn more about it.
ORDER BLOCK ENTRY.pptx
The document provides an overview of order block trading strategies and abbreviations used. It introduces the founders and their SH/SMS-BMS-RTO strategy for analyzing the forex market. A list of abbreviations is also defined, including order block (OB), previous day high (PDH), and shift in market structure (SMS) that are helpful for understanding their approach. Contact information is provided to find the founders on WhatsApp and Telegram.
Simple scalping secret strategy
What are some of the advantages of using a scalping strategy to trade the forex market? - Quick profits Entry and exit is usually done within a couple of minutes. This allows for quick profits but can lead to quick losses as well. - Exit is usually within 20 minutes or less - Lots of trades Strategy uses 3 Indicators The strategy uses 3 indicators: pivot points, Fibonacci retracement and the Stochastic Oscillator. The 3 main pivot points both above and below the pivot are used for this system: S1, S2, S3 and R1, R2, R3. The Fibonacci retracement values used are the 0.618, the 0.382 and the 0.500 levels. The Stochastic Oscillator is set at 5,3,3.
Forex trade presentation
The document provides an overview of foreign exchange trading (forex), including:
1) It defines forex as the global market for trading currencies and discusses some key terms and concepts like currency pairs, pips, leverage, etc.
2) It outlines the history of major developments in international monetary systems and the forex market.
3) It discusses the scope and growth of the forex market in India and factors influencing it.
4) It provides tips for forex traders, emphasizing the importance of education, having a trading plan and strategy, and managing risks.
Automated Trading
This document discusses automated trading and the role of computer science. It describes how traders observe markets to detect patterns and build prediction models. A system is proposed that learns patterns automatically using machine learning. Computer science helps by developing very reactive systems using algorithms to efficiently process high-dimensional market data and make objective trading decisions. Challenges include developing accurate prediction models that address overfitting, non-analytical objective functions, and reducing the dimensionality of order book data to determine a fair price. The document outlines how computer science areas like networks, operating systems, hardware, data management, and design practices help build high-performance automated trading infrastructure.
QuantConnect - Introduction to Pairs Trading
Introduction to pairs trading on the QuantConnect platform. Webinar provided by Interactive Brokers. Learn the fundamentals of pairs trading in a non-technical manner. Using the research environment we'll investigate XOM and CVX for cointegration; and then backtest them in QuantConnect.
Order book dynamics in high frequency trading
An important task of high-frequency trading is to successfully capture the dynamics in the Data. Empirical Data on Indian Exchanges show that 95% of all NEW orders are placed within 5 ticks of best-bid and best-ask. The Quantinsti® Replacement Matrix shows that most of the orders that are being replaced are among the top 3 levels and these replacements allow us to visualize and generalize about market behaviour. This matrix gives a visual representation of the cost metrics and replacement behaviour.
Execution Algorithms provide a price which is between Limit Order Execution and Market Order Execution. Market Orders guarantee execution within a certain time but the price that it may get the trader remains uncertain. Limit Order guarantees the price but it may remain un-executed if price moves away. Most Execution Algorithms balance between these two order types.
The speaker, Mr. Gaurav Raizada, discusses Quantinsti® Replacement Matrix in the webinar along with basics on order book management theory for high frequency traders.
Quant insti webinar on algorithmic trading for technocrats!
The webinar links the key concepts of Algorithmic Trading to Engineers and Technology Graduates. It is aimed at explaining Algo Trading Basics in way that is easily understandable and palatable.
This video is part of a webinar taken by Gaurav Raizada on 14th May, 2013 at QuantInsti, Mumbai. The webinar was about Algorithmic and High Frequency trading career for technocrats with detailed discussion about this domain and different skill sets required to excel in this industry.
Algorithmic Trading-An Introduction
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.
Learn A Simple Range Trading Strategy
Click here for more information on range trading
http://www.netpicks.com/simple-range-trading-strategy/
Here is some information on range trading:
It’s been said that a market only trends 30% of the time.
I can’t quantify that figure but having a range trading strategy to take advantage of the other 70% is good business.
Range trading is not difficult however it does require discipline and a method of determining when a trading range is in play.
For more information on range trading click here:
http://www.netpicks.com/simple-range-trading-strategy/
Candlestick cheat-sheet-rgb-final
The document discusses candlestick patterns and how to interpret them. It explains that candlesticks show the battle between buyers and sellers over a period of time. Bullish candlesticks indicate an upward trend and buying pressure, while bearish candlesticks signal a downward trend and selling pressure. It provides examples of common bullish formations like bullish engulfing and morning star, and bearish formations such as bearish engulfing and evening star. The document encourages attending a workshop to see these patterns in live markets.
RSI Strategy
The document introduces the RSI indicator strategy for trend reversals on timeframes of 5-15 minutes for currency pairs like EURUSD and GBPUSD. It explains that RSI shows when the price is overbought or oversold, signaling trend reversals back within its 30-70 trading range. It provides instructions on how to set up the RSI indicator on a 1-minute candle chart using a period of 5, and describes buying put options when RSI drops below 70 from overbought conditions or call options when RSI rises above 30 from oversold conditions.
A Guided Tour of Machine Learning for Traders by Tucker Balch at QuantCon 2016
The document provides an overview of a guided tour of machine learning techniques for traders given by Tucker Balch, a professor of interactive computing at Georgia Tech. It discusses decision trees, k-nearest neighbors, and reinforcement learning algorithms. It also highlights an example trading strategy that uses decision trees to classify stock sentiment data and technical factors to generate long and short signals. Backtests show the combined strategy achieved annual returns over 30% with lower maximum drawdowns than the market.
Electronic Trading: A Primer
Not only does electronic trading continue to make our financial markets more competitive, but it has brought numerous benefits to all investors This presentation seeks to provide an overview of the evolution of electronic trading, provide clear definitions of often misused terms, and demystify electronic trading strategies like high frequency trading.
Among the topics discussed in this presentation:
The modernization of our financial markets using electronic trading
Definitions of electronic trading, algorithmic trading and high frequency trading
The Securities and Exchange Commission and high frequency trading
The Commodity Futures Trading Commission and high frequency trading
Regulatory framework in place to safeguard investors who invest in markets where electronic trading is prevalent
Hendrik Isebaert - Showpad & Ghent - Enterprise Software in Flanders - Stanfo...
Talk by Hendrik Isebaert, Showpad (Ghent), at Stanford Engineering on January 28 2019, Session #3: 'Flanders : From WW1 Battlefields to Global Leadership in Enterprise Software & Semiconductors'.
Website: http://www.StanfordEuropreneurs.org
YouTube Channel: https://www.youtube.com/user/StanfordEuropreneurs
Twitter: @Europreneurs
More Related Content
What's hot
Algorithmic trading
An Brief Introduction to Algorithmic Trading and some key features that are needed to develop an Algorithmic Trading software.
Algorithmic Trading
Algorithmic trading is the automated execution of trading orders using computer programs and models. It aims to minimize costs, maximize fill rates, and reduce execution risk through faster and more reliable execution platforms and more accurate prediction models. Trends driving its growth include market electronification, a desire for anonymity and efficiency, and regulatory changes. Common algorithm types include arrival price, TWAP, VWAP, and MOC models. Areas of concern include lack of visibility, algorithms reacting to each other, and missing the trader's intuition. The process involves developing and testing trading strategies through backtesting before implementing them on execution platforms to trade.
Top 8 Forex Trading Strategies That Pro Traders Use
In this slideshow find the best Forex trading strategies including chart patterns, price rejection, correlation trading, volume-price analysis, long term daily and weekly trading, news and sentiment trading strategies. Besides, you will learn the best money and risk management methods and also the best advice by the experts to control your psychology during your trades.
Volatility Trading - Hedge Fund Strategies
Volatility trading strategies seek to profit from changes in a asset's volatility. Volatility measures how much the price of an asset fluctuates over time. There are several types of volatility strategies including volatility dispersion trading which buys options on index components and sells options on the overall index, volatility spreads which use option combinations to profit from different implied volatilities, and gamma trading which aims to benefit from unexpected events causing large price moves. Volatility is important for options as their pricing depends on assumptions about future volatility.
Quant trading with artificial intelligence
Foster discussion on the practical approach of applying artificial intelligence (AI) in quant trading and avoiding the common pitfalls and the opportunities and future of quant trading.
Financial trading is the space in which people have to make decisions under uncertain uncertainty and requires decisions to be explained. However, most AI algorithm (e.g. neural network) are black-box and serves well under only constrained environment (e.g. Go / Atari). Therefore, it is important to gather domain knowledge such that AI (e.g. PGM) could have more cognitive ability to provide a white-box explanation for their trading decisions.
If AI could provide a clearer visibility on the reality & present, it can assist human to provide faster, more-accurate and more-informed investment decisions. With a better understanding of the world, we can allocate resources more efficiently and ultimately create a better world to live.
Video for the slides:
https://www.youtube.com/watch?v=sideoQYAVDM&t=351s
"A Framework-Based Approach to Building Quantitative Trading Systems" by Dr. ...
Contrary to popular wisdom the difference between a retail quant trader and a professional portfolio manager is not in "having better trade entry and exit rules". Rather it is the difference in how each approaches the concepts of portfolio optimisation and risk management.
Both of these topics are synonymous with heavy math, which can be off-putting for beginner retail systematic traders. Hence, it can be extremely daunting for those without institutional experience to know how to turn a set of trading rules into a robust portfolio and risk management system.
In this talk, Mike will discuss how to take a typical retail quant strategy and place it in a professional quantitative trading framework, with proper position sizing and risk assessment, without resorting to pages of formulas or the need to have a PhD in statistics!
Algo trading with machine learning ppt
This document discusses algorithmic trading using machine learning. It introduces algorithmic trading and its advantages over human trading. The objectives are to maximize profits with minimum capital and predict stock prices using machine learning. Python is used to develop the trading platform. The architecture includes exchanges, servers to receive and store market data, and applications to interface and manage orders. Strategies discussed include analyzing candlestick patterns and volume. A proposed algorithm uses machine learning on historical data to generate buy signals. Limitations include algorithms not being 100% accurate and not universal. Future enhancements may include greater use of artificial intelligence as technology advances.
Quantitative Trading
This months speaker is Quantitative Researcher Yann-Shin Aaron Chen. Chen grew up in Taipei and moved to Southern California when he was a teenager. He participated in numerous math and physics competitions in high school and was ranked in the top 24 students in the US Physics Olympiad. He obtained a B.A. in mathematics at U.C. Berkeley, and got his PhD also at Berkeley in 2012. During his graduate studies, he did a summer internship at Morgan Stanley. After graduation, he joined Citadel, one of the largest hedge funds in US, as a quantitative researcher and worked there for 5 years. He left Citadel a few months ago, and he is now looking forward to his next venture.
Quantitative trading is a relatively new field in the world of finance. With the advances of information technology and data science, quantitative trading has generated significant interest in the past decade. In his talk, Aaron will cover the basic facts about quantitative trading and open the floor for questions. This short presentation is intended for people that are not in this industry and want to learn more about it.
ORDER BLOCK ENTRY.pptx
The document provides an overview of order block trading strategies and abbreviations used. It introduces the founders and their SH/SMS-BMS-RTO strategy for analyzing the forex market. A list of abbreviations is also defined, including order block (OB), previous day high (PDH), and shift in market structure (SMS) that are helpful for understanding their approach. Contact information is provided to find the founders on WhatsApp and Telegram.
Simple scalping secret strategy
What are some of the advantages of using a scalping strategy to trade the forex market? - Quick profits Entry and exit is usually done within a couple of minutes. This allows for quick profits but can lead to quick losses as well. - Exit is usually within 20 minutes or less - Lots of trades Strategy uses 3 Indicators The strategy uses 3 indicators: pivot points, Fibonacci retracement and the Stochastic Oscillator. The 3 main pivot points both above and below the pivot are used for this system: S1, S2, S3 and R1, R2, R3. The Fibonacci retracement values used are the 0.618, the 0.382 and the 0.500 levels. The Stochastic Oscillator is set at 5,3,3.
Forex trade presentation
The document provides an overview of foreign exchange trading (forex), including:
1) It defines forex as the global market for trading currencies and discusses some key terms and concepts like currency pairs, pips, leverage, etc.
2) It outlines the history of major developments in international monetary systems and the forex market.
3) It discusses the scope and growth of the forex market in India and factors influencing it.
4) It provides tips for forex traders, emphasizing the importance of education, having a trading plan and strategy, and managing risks.
Automated Trading
This document discusses automated trading and the role of computer science. It describes how traders observe markets to detect patterns and build prediction models. A system is proposed that learns patterns automatically using machine learning. Computer science helps by developing very reactive systems using algorithms to efficiently process high-dimensional market data and make objective trading decisions. Challenges include developing accurate prediction models that address overfitting, non-analytical objective functions, and reducing the dimensionality of order book data to determine a fair price. The document outlines how computer science areas like networks, operating systems, hardware, data management, and design practices help build high-performance automated trading infrastructure.
QuantConnect - Introduction to Pairs Trading
Introduction to pairs trading on the QuantConnect platform. Webinar provided by Interactive Brokers. Learn the fundamentals of pairs trading in a non-technical manner. Using the research environment we'll investigate XOM and CVX for cointegration; and then backtest them in QuantConnect.
Order book dynamics in high frequency trading
An important task of high-frequency trading is to successfully capture the dynamics in the Data. Empirical Data on Indian Exchanges show that 95% of all NEW orders are placed within 5 ticks of best-bid and best-ask. The Quantinsti® Replacement Matrix shows that most of the orders that are being replaced are among the top 3 levels and these replacements allow us to visualize and generalize about market behaviour. This matrix gives a visual representation of the cost metrics and replacement behaviour.
Execution Algorithms provide a price which is between Limit Order Execution and Market Order Execution. Market Orders guarantee execution within a certain time but the price that it may get the trader remains uncertain. Limit Order guarantees the price but it may remain un-executed if price moves away. Most Execution Algorithms balance between these two order types.
The speaker, Mr. Gaurav Raizada, discusses Quantinsti® Replacement Matrix in the webinar along with basics on order book management theory for high frequency traders.
Quant insti webinar on algorithmic trading for technocrats!
The webinar links the key concepts of Algorithmic Trading to Engineers and Technology Graduates. It is aimed at explaining Algo Trading Basics in way that is easily understandable and palatable.
This video is part of a webinar taken by Gaurav Raizada on 14th May, 2013 at QuantInsti, Mumbai. The webinar was about Algorithmic and High Frequency trading career for technocrats with detailed discussion about this domain and different skill sets required to excel in this industry.
Algorithmic Trading-An Introduction
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.
Learn A Simple Range Trading Strategy
Click here for more information on range trading
http://www.netpicks.com/simple-range-trading-strategy/
Here is some information on range trading:
It’s been said that a market only trends 30% of the time.
I can’t quantify that figure but having a range trading strategy to take advantage of the other 70% is good business.
Range trading is not difficult however it does require discipline and a method of determining when a trading range is in play.
For more information on range trading click here:
http://www.netpicks.com/simple-range-trading-strategy/
Candlestick cheat-sheet-rgb-final
The document discusses candlestick patterns and how to interpret them. It explains that candlesticks show the battle between buyers and sellers over a period of time. Bullish candlesticks indicate an upward trend and buying pressure, while bearish candlesticks signal a downward trend and selling pressure. It provides examples of common bullish formations like bullish engulfing and morning star, and bearish formations such as bearish engulfing and evening star. The document encourages attending a workshop to see these patterns in live markets.
RSI Strategy
The document introduces the RSI indicator strategy for trend reversals on timeframes of 5-15 minutes for currency pairs like EURUSD and GBPUSD. It explains that RSI shows when the price is overbought or oversold, signaling trend reversals back within its 30-70 trading range. It provides instructions on how to set up the RSI indicator on a 1-minute candle chart using a period of 5, and describes buying put options when RSI drops below 70 from overbought conditions or call options when RSI rises above 30 from oversold conditions.
A Guided Tour of Machine Learning for Traders by Tucker Balch at QuantCon 2016
The document provides an overview of a guided tour of machine learning techniques for traders given by Tucker Balch, a professor of interactive computing at Georgia Tech. It discusses decision trees, k-nearest neighbors, and reinforcement learning algorithms. It also highlights an example trading strategy that uses decision trees to classify stock sentiment data and technical factors to generate long and short signals. Backtests show the combined strategy achieved annual returns over 30% with lower maximum drawdowns than the market.
What's hot (20)
Top 8 Forex Trading Strategies That Pro Traders Use
Top 8 Forex Trading Strategies That Pro Traders Use
"A Framework-Based Approach to Building Quantitative Trading Systems" by Dr. ...
"A Framework-Based Approach to Building Quantitative Trading Systems" by Dr. ...
Quant insti webinar on algorithmic trading for technocrats!
Quant insti webinar on algorithmic trading for technocrats!
A Guided Tour of Machine Learning for Traders by Tucker Balch at QuantCon 2016
A Guided Tour of Machine Learning for Traders by Tucker Balch at QuantCon 2016
Similar to Algorithmic Trading
Electronic Trading: A Primer
Not only does electronic trading continue to make our financial markets more competitive, but it has brought numerous benefits to all investors This presentation seeks to provide an overview of the evolution of electronic trading, provide clear definitions of often misused terms, and demystify electronic trading strategies like high frequency trading.
Among the topics discussed in this presentation:
The modernization of our financial markets using electronic trading
Definitions of electronic trading, algorithmic trading and high frequency trading
The Securities and Exchange Commission and high frequency trading
The Commodity Futures Trading Commission and high frequency trading
Regulatory framework in place to safeguard investors who invest in markets where electronic trading is prevalent
Hendrik Isebaert - Showpad & Ghent - Enterprise Software in Flanders - Stanfo...
Talk by Hendrik Isebaert, Showpad (Ghent), at Stanford Engineering on January 28 2019, Session #3: 'Flanders : From WW1 Battlefields to Global Leadership in Enterprise Software & Semiconductors'.
Website: http://www.StanfordEuropreneurs.org
YouTube Channel: https://www.youtube.com/user/StanfordEuropreneurs
Twitter: @Europreneurs
Building A Trading Desk On Analytics
This document discusses how analytics are used in modern electronic trading businesses. It provides an overview of how the trading business has evolved from manual to highly automated and analytics-driven. It describes the infrastructure needed to support analytics, including high-performance databases and quantitative modeling tools. It then gives examples of how analytics are applied to pricing, hedging, client analysis, and algorithmic trading through quantitative models trained on large datasets. Key challenges discussed include managing large data volumes and market volatility. The document emphasizes the importance of domain expertise, data quality, and simple yet effective quantitative models.
Trading Analytics
A short overview of a real-world trading system and the analytical infrastructure required to support it
1. introduction to E-commerce
introduction to E-commerce, Electronic commerce, EDI, CS802E,
e-commerce ,edi ,electronic data interchange ,traditional commerce ,buyer and seller ,origin of e-commerce ,business process ,impact of e-commerce ,value chain analysis ,company value chain ,case studies on e-commerce ,advantages of e-commerce ,disadvantages of e-commerce
Millimetric.io - NOAH18 London
Company Pitch by Millimetric.io at the NOAH Conference 2018 in London, Old Billingsgate 30-31 October 2018.
Igal Rotem, Credorax - NOAH18 London
Three conferences organized by NOAH Advisors aim to connect capital with entrepreneurs across Europe and Israel. NOAH Advisors is an investment banking boutique specializing in mergers and acquisitions and financing for European internet companies. They have extensive experience advising on transactions in the internet sector and relationships with investors and corporations.
How to Create a Crypto Exchange Platform - Simplified Guide.pptx
If you are an entrepreneur or a startup who wants to enter the crypto space but has no idea about the platform, check here to know How to Create a Crypto Exchange Platform? as a Simplified Guide and hire a cryptocurrency exchange development company
Transcom's investor roadshow, London, March 2014
Transcom provides outsourced customer care, sales, technical support, and credit management services through contact centers and work-at-home agents in 26 countries. In 2013, Transcom saw revenue increase by 7.9% to €653.2 million due to growth across all regions. Key priorities for 2014 include improving operational performance in underperforming regions and increasing profitable growth opportunities through expanding existing client relationships and broadening the client base. Transcom also aims to strengthen its focus on corporate social responsibility through programs centered around people development, equality and diversity, and community engagement.
ICT Convergence: Consolidation or Shakeout Stage!
Breakthrough Insights
Value Creation Leads
Levers for Value Capture
Spheres of Action
Outlook Notes
E-Business, Main Ideas of E-Business, E-Business Cycle
In this slides
E-Business definition , Main Ideas of E-Business, E-Business Cycle and generation of E-BUSINESS
Selecting the right provider for your contract
The document provides guidance on selecting the right provider for a contract through the EU procurement process. It summarizes the two stage selection process, including understanding requirements in stage one and the procurement in stage two. Stage one involves defining needs, applicable procurement methods, and developing a procurement strategy. Stage two details designing selection criteria, issuing requests for proposals, evaluating bids, and selecting a provider. The document emphasizes the importance of clear communication, transparency, and following best practices to ensure a fair compliant process.
Selecting the right provider for your contract
The document provides guidance on selecting the right provider for a contract through the EU procurement process. It outlines a two-stage restricted procedure approach including defining requirements, issuing a Prior Information Notice and Pre-Qualification Questionnaire to shortlist tenderers, and issuing an Invitation to Tender. Key aspects covered include classifying the contract, identifying stakeholders, defining value for money, and designing evaluation criteria. Lessons emphasized consulting widely, having clear expectations, applying a market test, and ensuring contract notices are exact to avoid challenges.
ITG Investor Presentation February 2014
ITG provides investment research, trading platforms, and analytics to institutional investors. It has unique assets like its POSIT block crossing network and Triton execution management system. ITG has experienced international growth, with international operations accounting for 40% of revenues and 65% of profits in 2013. ITG has a strong balance sheet with $262 million in cash and only $30.3 million in long-term debt. It utilizes share buybacks to return capital to shareholders.
Swift: Towards a customer-oriented go-to-market approach
This document discusses SWIFT's goal of implementing a more harmonized and customer-centric go-to-market approach. It notes that SWIFT faces challenges due to a changing global landscape, more complex markets, and evolving customer behaviors. The document outlines a project to assess SWIFT's current marketing and sales practices, develop a new customer-focused framework and tools, provide training to enable teams, and operationalize changes through governance and adoption measures. The goal is to improve customer insights, marketing skills, collaboration between teams, and SWIFT's competitive positioning in the market.
Session 9 fall 2014
The document discusses milestones and pitch decks for startups seeking investment. It provides examples of qualitative and quantitative milestones that could demonstrate proof of concept, such as having a minimum number of users, paying customers, or revenue. The document also outlines the key components of an effective pitch deck, including problem/solution, market opportunity and traction, business model, competition, and team. Investors are looking for milestones that clearly reduce risks and proof that the startup can gain traction in the market.
Successful E Auctions
Spend Solutions is a UK-based procurement firm specializing in eProcurement, purchase-to-pay, and eAuctions. They have extensive experience managing successful eAuction events across industries for both goods and services. An eAuction is an internet-based activity used to negotiate prices for purchasing or selling direct materials, capital, or services, either privately with a few bidders or openly with little restriction. eAuctions replace conventional paper tendering and negotiations, and are best used when there are many qualified suppliers, a commodity product, excess market capacity, and price is a key selection factor. Benefits include average savings of 18%, faster decision making, a full audit trail, and scalability from self
amit.ppt
This document discusses the key aspects of developing a successful e-business. It defines e-business and outlines three generations that trace its evolution from static online catalogs to highly integrated customer-centric systems. Developing e-business requires building reliable systems for security, collaboration, payments and more. The document also covers e-business models, transforming companies to adopt e-business, and the importance of understanding customers to provide personalized, relevant experiences across multiple devices.
Apohan equity tech platform pitch deck ppt v50 08-02-2022 aj
Apohan is making the world's first strategic transaction platform. The highly ambitious new generation of SMEs need services for transactions (such as equity funding or JV) to grow. SMEs neither have a management capable of carrying out complex transactions nor know how to avail these services from consultants. Hence, strategic transactions are nearly absent in SMEs & the reason is lack of a economical, reliable service platform. Apohan's platform would bring the strategic transactions to the doorsteps of SMEs. Our platform caters to all ecosystem stakeholders, all parts of the transaction value chain & we capture exhaustive information of a business needed to take conclusive transaction decisions. Our platform is made to increase the success rate of transactions, reduce the cycle time, break the long broker chains & reduce the transaction costs. Apohan realizes counselling, screening & success charges. The company expects to close an unprecedented 100 transactions a day within 10 years. On the competition front, hardly 0.1% of fintech companies are in the transaction space & there is no transaction management platform in the whole world.
Webinar – Pricing & Regulations: Will you be able to justify your valuations ...
Webinar – Pricing & Regulations: Will you be able to justify your valuations when the regulator comes calling?
For Asset Managers, Shadow Banking and the means to be able to monitor more accurately the quality of service being provided by your Third Party Administrator is growing in importance, combined with regulatory topics such as EMIR and changes in CCP clearing.
For Fund Accounting and Administration service providers serving this community, the imminent arrival of market infrastructure changes such as T2S and CSDR, means the need to be operationally efficient and adaptable to change becomes ever more important. Market reputation is also an increasing focus and worry, plus competitive edge.
This webinar looks at the requirements of both communities and explores what practitioners should be doing to meet the imminent arrival of shadow banking regulations and market infrastructure changes.
Topics include:
• Case study of European Fund Administration, presented by M. Verdure, CIO of EFA
• A short live demonstration of GAIN Portfolio Pricing
Speakers:
• Jean-Marc Verdure, CIO and Director of Organization, European Fund Administration
• Olivier Kenji Mathurin, Head of Product Marketing and AIM Research Lab, AIM Software
Date: Tuesday 17th June, 2014
RECORDED SESSION: http://www.aimsoftware.com/news/webinar-pricing-regulations-now-available-on-demand
Similar to Algorithmic Trading (20)
Hendrik Isebaert - Showpad & Ghent - Enterprise Software in Flanders - Stanfo...
Hendrik Isebaert - Showpad & Ghent - Enterprise Software in Flanders - Stanfo...
How to Create a Crypto Exchange Platform - Simplified Guide.pptx
How to Create a Crypto Exchange Platform - Simplified Guide.pptx
E-Business, Main Ideas of E-Business, E-Business Cycle
E-Business, Main Ideas of E-Business, E-Business Cycle
Swift: Towards a customer-oriented go-to-market approach
Swift: Towards a customer-oriented go-to-market approach
Apohan equity tech platform pitch deck ppt v50 08-02-2022 aj
Apohan equity tech platform pitch deck ppt v50 08-02-2022 aj
Webinar – Pricing & Regulations: Will you be able to justify your valuations ...
Webinar – Pricing & Regulations: Will you be able to justify your valuations ...
Recently uploaded
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
MySQL InnoDB Storage Engine: Deep Dive - Mydbops
This presentation, titled "MySQL - InnoDB" and delivered by Mayank Prasad at the Mydbops Open Source Database Meetup 16 on June 8th, 2024, covers dynamic configuration of REDO logs and instant ADD/DROP columns in InnoDB.
This presentation dives deep into the world of InnoDB, exploring two ground-breaking features introduced in MySQL 8.0:
• Dynamic Configuration of REDO Logs: Enhance your database's performance and flexibility with on-the-fly adjustments to REDO log capacity. Unleash the power of the snake metaphor to visualize how InnoDB manages REDO log files.
• Instant ADD/DROP Columns: Say goodbye to costly table rebuilds! This presentation unveils how InnoDB now enables seamless addition and removal of columns without compromising data integrity or incurring downtime.
Key Learnings:
• Grasp the concept of REDO logs and their significance in InnoDB's transaction management.
• Discover the advantages of dynamic REDO log configuration and how to leverage it for optimal performance.
• Understand the inner workings of instant ADD/DROP columns and their impact on database operations.
• Gain valuable insights into the row versioning mechanism that empowers instant column modifications.
Containers & AI - Beauty and the Beast!?!
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Keywords: AI, Containeres, Kubernetes, Cloud Native
Event Link: https://meine.doag.org/events/cloudland/2024/agenda/#agendaId.4211
A Deep Dive into ScyllaDB's Architecture
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
Must Know Postgres Extension for DBA and Developer during Migration
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
Call Girls Chandigarh🔥7023059433🔥Agency Profile Escorts in Chandigarh Availab...
Call Girls Chandigarh🔥7023059433🔥Agency Profile Escorts in Chandigarh Available 24/7
Getting the Most Out of ScyllaDB Monitoring: ShareChat's Tips
ScyllaDB monitoring provides a lot of useful information. But sometimes it’s not easy to find the root of the problem if something is wrong or even estimate the remaining capacity by the load on the cluster. This talk shares our team's practical tips on: 1) How to find the root of the problem by metrics if ScyllaDB is slow 2) How to interpret the load and plan capacity for the future 3) Compaction strategies and how to choose the right one 4) Important metrics which aren’t available in the default monitoring setup.
Essentials of Automations: Exploring Attributes & Automation Parameters
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Astute Business Solutions | Oracle Cloud Partner |
Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Gursev Pirge, PhD
Senior Data Scientist - JohnSnowLabs
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Demystifying Knowledge Management through Storytelling
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
QA or the Highway - Component Testing: Bridging the gap between frontend appl...
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
"Choosing proper type of scaling", Olena Syrota
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
ScyllaDB Tablets: Rethinking Replication
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
AWS Certified Solutions Architect Associate (SAA-C03)
AWS Certified Solutions Architect Associate (SAA-C03)
Recently uploaded (20)
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...
Must Know Postgres Extension for DBA and Developer during Migration
Must Know Postgres Extension for DBA and Developer during Migration
Call Girls Chandigarh🔥7023059433🔥Agency Profile Escorts in Chandigarh Availab...
Call Girls Chandigarh🔥7023059433🔥Agency Profile Escorts in Chandigarh Availab...
Getting the Most Out of ScyllaDB Monitoring: ShareChat's Tips
Getting the Most Out of ScyllaDB Monitoring: ShareChat's Tips
Essentials of Automations: Exploring Attributes & Automation Parameters
Essentials of Automations: Exploring Attributes & Automation Parameters
Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
Demystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through Storytelling
QA or the Highway - Component Testing: Bridging the gap between frontend appl...
QA or the Highway - Component Testing: Bridging the gap between frontend appl...
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
AWS Certified Solutions Architect Associate (SAA-C03)
AWS Certified Solutions Architect Associate (SAA-C03)
Algorithmic Trading
- 1. Algorithmic Trading Giuseppe Nuti, Mahnoosh Mirghaemi, Philip Treleaven, and Chaiyakorn Yingsaeree UK Centre in Financial Computing, London IEEE Computer Society, Nov. 2011 Advisor : DR. Jenq-Shiou Leu Student : Chia-Yun Chan Date : 2014/10/27
- 2. Outline • Introduction • Trade Objective • Trade Execution • Trade Process o Pretrade Analysis o Trading Signal Generation • Conclusion
- 3. Introduction • In electronic financial markets, algorithmic trading is the use of computer programs to automate one or more stages of the trading process: pretrade analysis (data analysis), trading signal generation (buy and sell recommendations), and trade execution. • Profits drive any algorithmic trading system— whether in the form of cost savings, client commissions, or proprietary trading.
- 4. Trade Objective • Broker Trading o Minimize the cost of trading • Proprietary Trading o Maximize the profit • The Clients V.S Trading Firm o Who takes on the trading risk, takes the lion’s share of the profits
- 5. Trade Execution • Order list • Buy and Sell • Rank by price and order arrival time • First in, first out Time Price Quantity 09:00:01 99 20 09:00:11 99 4000 09:00:13 99 980
- 8. Pretrade Analysis • Fundamental analysis • Technical analysis o Technical analysis aims to predict future price movements based on asset price history • Quantitative analysis o Quantitative analysis treats asset prices as random and uses mathematical and statistical analysis to find a suitable model for describing this randomness
- 9. Trading Signal Generation • Entry strategies • Exit strategies • Risk management
- 11. Conclusion • Trading strategies • Ultrahigh-frequency trading o Buying and selling of stocks at extremely fast speeds with the help of powerful computers. They can scan dozens of markets simultaneously, execute thousands of orders a second, and alter strategies in a matter of milliseconds
Editor's Notes
- 程式交易不只是寫程式而已 還要了解金融市場和交易機制 都是很深很複雜的 因此這次我選擇報告magazine
- 在電子金融市場 演算法交易是利用電腦程式去自動地進行一個或是多個交易階段 交易前分析（數據分析），交易信號的產生（買，賣的建議），並執行交易。 利潤是整個演算法交易系統的重心 無論是在成本節約，客戶佣金和自營交易
- Broker Trading Minimize the cost (market impact cost or time) of trading
- Trading signal generation consists of the portfolio construction model. This model takes as its inputs the results of the alpha, risk, and transaction cost models and decides what portfolio of financial instruments should be owned going forward and in what quantities. At trade execution, the execution model executes the trades, making several decisions with constraints on (actual) transaction costs and trading duration. The most general decision is the trading strategy followed by the venue and order type.
- 基本面分析 技術分析 技術分析的目的是基於對資產價格的歷史來預測未來價格走勢 定量分析 定量分析把資產價格作為隨機的，利用數學和統計分析，以找到一個合適的模型來描述這種隨機性