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Computer Chip

Knowledge of Financial Markets

Dive deep into the intricacies of financial markets. Explore the dynamics of various asset classes, market behavior, and the factors influencing investment decisions.

Quantitative Techniques:

Mastering quantitative methods and modeling not only enhances your ability to analyze complex financial data but also empowers you to make informed decisions, driving strategic and sustainable success in the dynamic landscape of finance.

Quantitative Risk Management 

Acquire expertise in utilizing  methodologies to automate risk analysis, construct advanced risk models, and optimize financial procedures.  learn how to detect ,mitigate and manage various risk associate with tech and capital markets 

Data Analytics

Gain a comprehensive understanding of data analysis techniques. Learn how to harness the power of data to make informed decisions and drive business insights.

Coding for Automation

Master the synergy of AI and coding for streamlined automation in the finance sector. Develop expertise in programming languages and AI techniques, empowering you to automate tasks, craft sophisticated trading algorithms, and enhance efficiency in financial processes.

Infrastructure Proficiency

learn how to build an AI powered fully automated algorithm infra with proper cloud management, and data management, order management ,risk management and monitoring dashboards 

 Where Education Meets Opportunity

01

Introduction to Algorithmic Trading

  • What is algorithmic trading?

  • Benefits and risks of algorithmic trading at QuantGlobal.

  • Different types of algorithmic trading strategies used at QuantGlobal.

  • How to develop and implement algorithmic trading strategies at QuantGlobal.

02

Knowledge of financial market

03

Statistics

  • Market Fundamentals: Understanding the basic principles and concepts of financial markets, including asset classes, market participants, and trading mechanisms.

  • Data Analysis: Utilizing data analytics tools and techniques to process, analyze, and interpret financial market data, including historical price and volume data.

  • Technical Analysis: Exploring technical indicators and chart patterns to make informed trading decisions.

  • Basics of Statistics

  • Probability 

  • Linear algebra

  • Time service analysis

04

QuantGlobal's Proprietary Trading Strategies

  • Learn about QuantGlobal's proprietary trading strategies and how to implement them

  • Understand the underlying logic and principles of each strategy

  • Gain insights into how QuantGlobal uses these strategies to generate consistent returns

  • Trend following strategies

  • Mean reversion strategies

  • Statistical arbitrage strategies

  • Momentum strategies

05

Programming for Algorithmic Trading

  • Introduction to Python programming 

  • Python libraries for algorithmic trading used at QuantGlobal.

  • How to write and backtest algorithmic trading strategies in Python at QuantGlobal.

06

 Machine learning for algo trading

07

  • Introduction to machine learning

  • Supervised learning 

  • Unsupervised learning 

  • Reinforcement learning

Back-testing

  • Data Selection: Choosing relevant historical data, including price, volume, and order book data, for back-testing purposes.

  • Performance Metrics: Understanding and applying various performance metrics such as Sharpe ratio, maximum drawdown, and profitability to evaluate strategy performance.

  • Drawdown Analysis: Analyzing and managing the maximum drawdown to ensure the strategy's risk profile is acceptable.

08

Risk Management

  • Different types of risks

  • How to measure and manage risk at QuantGlobal.

  • Position sizing 

  • Stop-loss orders

  • Backtesting for risk at QuantGlobal.

09

Algorithmic trading system

  • System design and architecture

  • Order execution

  • Back-testing and optimisation

  • LIve trading

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