Certificate Program in AI for Derivative Valuations(CPAIDV)
- Offered byIndian Institute of Quantitative Finance
Certificate Program in AI for Derivative Valuations(CPAIDV) at Indian Institute of Quantitative Finance Overview
Duration | 3 months |
Start from | 1st Mar'25 |
Total fee | ₹68,000 |
Mode of learning | Online |
Official Website | Go to Website |
Credential | Certificate |
Certificate Program in AI for Derivative Valuations(CPAIDV) at Indian Institute of Quantitative Finance Highlights
- Earn a certificate after completion of course from Indian Institute of Quantitative Finance
Certificate Program in AI for Derivative Valuations(CPAIDV) at Indian Institute of Quantitative Finance Course details
Individuals working in investment banking, asset management, or trading who want to enhance their skills in derivative valuations using AI
Professionals responsible for assessing and managing the risks associated with derivative products who wish to leverage AI for improved risk assessment
Overview of financial derivatives, including options, futures, and swaps
Introduction to key AI and machine learning concepts relevant to finance
Techniques for collecting, cleaning, and preparing financial data for analysis
Importance of data quality and feature selection in derivative valuations
Understanding the risks associated with derivatives and how AI can mitigate them
The Certificate Program in AI for Derivative Valuations (CPAIDV) is designed to equip participants with the knowledge and skills to apply artificial intelligence and machine learning techniques to the valuation of financial derivatives
This program blends theoretical foundations with practical applications, enabling professionals to enhance their valuation methodologies and improve decision-making in the derivatives market
Program Schedule
Saturdays and Sundays
Program Timing
4:00 PM to 8:00 PM IST (UTC +5:30)
Certificate Program in AI for Derivative Valuations(CPAIDV) at Indian Institute of Quantitative Finance Curriculum
Derivative Products
Standardized or Plain-Vanilla Derivatives
Linear versus Non-Linear Payoffs
Exotic Derivatives
Structures Products
Derivative Pricing Framework
Stochastic Processes& Modelling
Risk Neutral versus Real World Pricing
Fair Valuation Principles
Derivative Portfolio Risk
AI & ML Models for Derivative Pricing & Valuation
High Dimensional Problem & Data Sets
Deep Learning Paradigm
Neural Networks - Multi Layer Perceptron, Artificial NN, Feed Forward NN, Recurrent NN (LSTM & GRU)
Model Hyperparameters Tuning & Optimization
Explainable AI
Model Algorithmic Bias & Model Uncertainty
Model Performance Evaluation Metrics
AI & ML Explainability & Interpretability
Responsible AI
Data Privacy & Security
Regulatory Ask & Expectations