Quantitative Trading

  • Duration: 5 Hours  
  • Access: 3 Months
  • Desktop Only
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Quantitative trading is a subset of the broader topic of quantitative finance, and covers all aspects of using mathematical methods in trading markets. In today’s world, this generally means using computers to perform the necessary calculations and often the trading itself.
  • This course is only suitable for desktop use.

Quantitative Trading

  • Duration: 5 Hours  
  • Access: 3 Months
  • Desktop Only
Write your awesome label here.
Quantitative trading is a subset of the broader topic of quantitative finance, and covers all aspects of using mathematical methods in trading markets. In today’s world, this generally means using computers to perform the necessary calculations and often the trading itself.
  • This course is suitable for desktop use only. To register, please access through a desktop.

Course Outline

Recognize the various quantitative trading techniques used in the market and how differing business models and needs influence the use of different techniques. Delve into the foundational aspects of quantitative trading with a strong emphasis on comprehensive understanding. Acquire deep insights into sell-side and buy-side dynamics, algorithmic trading strategies, arbitrage, and high-frequency trading (HFT). Develop proficiency in leveraging data analytics, machine learning techniques, and robust risk management practices. Explore portfolio construction methodologies through real-world case studies.

What You Will Learn

Topic 1: An Introduction

  • Key Definitions & Terminology
  • Sell-Side Quantitative Trading
  • Buy-Side Quantitative Trading
  • General Quantitative Trading Techniques

Topic 2: Sell-Side

  • Sell-Side Business Model
  • Pricing

Topic 3: Buy-Side

  • Buy-Side Business Model
  • Trading Strategies

Topic 4: Algorithmic Trading

  • Execution Desks & Technology
  • Evolution & Development of Algo Trading
  • Execution Algorithms

Topic 5: Arbitrage & HFT

  • Arbitrage
  • High Frequency Trading (HFT)

Topic 6: Data & Machine Learning

  • Overview
  • Alternative Data
  • Big Data & Expert Data
  • Biases
  • Machine Learning (ML)
  • Supervised & Unsupervised ML
  • Dimension Reduction
  • Data Clustering

Topic 7: Risk Management

  • Risk & Risk Management in Trading Businesses
  • Risk Numbers
  • Risk Calculations
  • Portfolio Risk
  • Using Risk Numbers

Topic 8: Portfolio Construction

  • Risk & Portfolio Construction
  • Modern Portfolio Theory (MPT)
  • Sharpe Ratio
  • MPT Assumptions
  • Portfolio Constraints
  • Portfolio Construction Challenges
  • Other Portfolio Management Concepts

Topic 9: Case Studies

  • Market-Making: Fat Fingers & Poor Operations
  • Pricing: Inappropriate Models
  • Hedging: Unsuitable Infrastructure
  • Rule-Based Risk Management: AAA-Rated Securities
  • Asset Management: Hedge Fund Collapse
  • Lessons Learned

Gain a professional asset allocation certificate

Gain Industry Knowledge and a Certification

 Test your knowledge throughout each tutorial with
regular review questions
  End each tutorial with a short, graded test designed to enhance knowledge retention.
  Gain a shareable professional certification.

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