Course description
In a universe where financial trading goes at a speed that is challenging for people to maintain, knowing algorithm trading techniques and models gets highly important. Attending this Rcademy program will equip you with a broad knowledge of the principles that successfully steer algorithm trading methods, hedge capital, and the grounding initiation to financial approach and finance behavior. The course covers various factors of the algorithm and high-frequency trading. Participants will limit order book tasks and develop trading algorithms in this program. Specifically, there will be an analysis of acquisition techniques or optimal liquidation methods by combining industry orders, limited orders, or both.
What are algorithmic and high-frequency trading?
Algorithmic trading and high-frequency trading (HFT) uses computer algorithms to execute trades in financial markets. Algorithmic trading can be used for many purposes, including executing large orders, finding profitable trading opportunities, and managing risk. HFT, on the other hand, is a type of algorithmic trading that focuses on executing trades at high speeds and taking advantage of very short-term market inefficiencies.
Upcoming start dates
Suitability - Who should attend?
Who should attend?
The Algorithmic and High-Frequency Trading Course by Rcademy is ideal for:
- Marketers
- Company portfolio leaders
- Trading desk directors
- Risk managers
- Risk regulators
- Hedge fund managers
- Net worth leaders
- Specialists in asset allocation
- Managers who are net worth
Outcome / Qualification etc.
By the end of the Algorithmic and High-Frequency Trading Course by Rcademy, all the participants should be able to:
- Determine algorithm and high-frequency trading and the impacts they have on the industry
- Determine thebenefits and risks of the methods and funds developedaround the algorithm
- Analyze the trends in the market which affect the future of the space
- Illustrate how a trader creates and tests an algorithm technique
- Apply the knowledge learned to explain the various methods used to structure quantitative trading strategies for multiple types of financial markets.
- Apply the skills to become top industry professionals
- Determine the association between current technologies and future progressive trading
- Understand the primary behavioral and classical finance levels and how theoretical trading techniques get applied in practice.
Training Course Content
Module 1: Introduction to Algorithmic and High-Frequency Trading
- An overview of the automated trading techniques and algorithms as their building blocks
- The market factors ofalgorithm trading, in-house creation or IP licensing, continuous improvement needs, and revenue strategies
- Trends in algorithm trading and their effects on the industry
- Trends in the future projections in the algorithm trading chances in the global industry
- The technique of initiating of algorithm trading procedure company and technical challenges, target industry which best fits business issues and goals
Module 2: The Quant Design of the Worldwide Equity Industry
- Illustrate the various market event categories and how they impact the order book
- Illustrate the techniques of high-frequency trading from their establishment in 1980 by the current today
- What exchange circuit and dark pools circuit breakers
- Organization execution and order book traits algorithms flow management
- Description of how the modern order book-controlled markets get controlled
Module 3: The Basics of High-Frequency Trading
- Description of the modern industry microstructure favoring high-frequency trading
- The advantages and disadvantages of high-frequency trading for the global financial structure
- The variation between technology-controlled high-frequency companies and regular financial trading industries
- Bespoke multi-asset trading algorithms and their methods of operations
Module 4: Algorithmic Tools
- Heuristic and mathematical factors of algorithms
- Scalability, speed, and precision include creating trade-offs and their competitive advantage to implement algorithmic trading regarding the primary three aspects.
- Information technology structure for the industry creation and market-taking activities from the trading to server’s screens, software levels, and all the hardware and effectively incorporating them
- Algorithmic trading techniques’ life cycle and their algorithmic factors
- Market taking and making with the use of algorithmic trading
Module 5: Developing and Testing of Algorithmic and High-Frequency Trading Models
- Implementation of templates for algorithms and their testing techniques
- Creation of backtests and stress regulators methods for algorithms
- Drawdown containment, dynamic risk, and yield monitoring in the algorithmic trading
- Coherent and concurrent yield maximization in all diverse markets
- Needs to modify a person’s algorithmic trading activities and off the self-software structures for algorithmic trading
Module 6: Interactive Brokers Algo Trading and Back Testing Trading Techniques
- Coding or jobs competition and top books on Algo trading
- Datasets/FIXML/FIX/API/ machine studying algorithms
- Backtesting for programming language
- Consideration of backtesting, capital raising, and backtesting types
- Database storage models, data types, data frequency, and sources of data
- Interactive brokers giving the first Quantopian and algorithmic trade
Module 7: High-Frequency Trading Methods
- Illustration of the various types of order and how they get used by high-frequency trading companies to utilize modern industry microstructure maximally
- Description of the various legal and illegal high-frequency models
- Different techniques used by high-frequency traders in the market to trade
Module 8: Going Live
- Quants’ and traders’ vital responsibility in the initiation stage
- Modification of markets and algorithms; utilizing spreads, prevention of bias in the industry correlations, multi-factor Hegde techniques, and worldwide embedding
- Company techniques for sustainable development and profitability of algorithmic trading activities
- Review of the position the algorithmic trading will be in the coming years from today
Module 9: Understanding of Data Garbage in and Garbage Out.
- Data storage and data sources
- An overview of the importance of the cleanliness of data
- Basic methods of cleaning data
- Inaccurate testing, evil tricks, and market tricksters
Module 10: Programming Basics: Loops
- Studying how to code loops
- Practical examples for the loops
- Learning to program
- Debugging and code errors
- Functions of codes
- Practice exercises for functions
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Rcademy
Rcademy is a global training and consultation organisation set out to bridge the gap between you now and what you can be in the near future. We are facilitators of knowledge impartation. Our team of established and experienced training enthusiasts...