Alumni Masterclasses
Continue to learn, and delve deeper into specific subjects, with the CQF's Masterclasses. Once again, every single one of these Masterclasses are included in the CQF's fees. All alumni have perpetual access to these courses for the rest of their careers, but they are in no way compulsory (ie. you do not have to watch or study them to gain the CQF). The full list comprises more than 70 hours of additional material:
Volatility, Advanced Modelling with PC Workshops
This course takes a critical look at the most important unknown in derivatives pricing: volatility. The main modelling approaches are all presented, along with their advantages and disadvantages. Concepts are studied from both a scientific and a practical point of view with the goal being to give the delegates the deepest possible understanding of the significance of their choice of model. Paul Wilmott brings to this course many years as a mathematical modeller in scientific disciplines as well as his experience forecasting volatility and as a partner in a very successful hedge fund. This Masterclass will feature spreadsheet and VBA workshops.
Tutor: Paul Wilmott
Duration: 2 days, recordings are separated into 8 sessions
What you will learn:
- Important volatility forecasting methods
- The different meanings of volatility
- Calibration to market prices, representing the skew and smile
- Deterministic volatility surfaces
- Stochastic volatility
- Uncertain volatility
- Robustness and minimizing model error, static hedging
- Volatility, static and dynamic hedging and portfolio theory.
VG Modelling: Pricing Financial Derivatives in Equity and Credit Risk
This course provides an introduction to the use of the Variance Gamma (VG) based models for equity and credit risk. The course takes a practical approach to describing the theory of advanced models, and features many examples of how they may be used to solve problems in finance, with emphasis on the pricing of financial derivatives. Starting from the analysis of data, we build up models driven by the nowadays popular VG Lévy processes that incorporate stylized features like jumps and stochastic volatility.
Both the mathematical modelling and the numerical aspects are covered. Key topics are addressed, including option pricing, calibration, Monte Carlo simulations, exotic options and credit risk. The course also avoids unnecessary mathematical formalities.
Tutor: Wim Schoutens
Duration: 2 days, recordings are separated into 8 sessions
What you will learn:
- See more realistic VG models for stocks and credit risk work on real data
- Which Levy processes are useful for financial modelling purposes and which are not?
- How to price an option surface of vanillas under advanced models within a second
- Learn about the very recent multivariate VG models that can be calibrated on univariate vanilla surfaces
- Learn about the new credit risk models driven by Levy processes and see how they can nicely capture the CDS term structure
- Learn how to simulate fast VG based models:
- to price exotics
- to run scenarios for risk-management purposes
- to simulate your insurance-linked products under a more advanced setting.
Exotic Equity Derivatives, Pricing and Hedging
Exotic Equity Options, Pricing and Hedging is a detailed course on the pricing and hedging of exotic equity derivatives, starting from the analysis of data to build up a vanilla pricing model and then extending this to exotic, over-the-counter products. We examine the mathematical modelling and the numerical aspects, as well as choice of model and dynamic and static hedging. Many real-life term sheets will be analysed. The course will feature spreadsheet and VBA workshops.
Tutor: Paul Wilmott
Duration: 2 days, recordings are separated into 8 sessions
What you will learn:
- The Black-Scholes pricing and framework
- How to categorise exotic options
- The mathematics of path dependency and decision processes
- Pricing models
- Hedging strategies
- Numerical methods for pricing.
Behavioral Science In Finance: Phenomena, Diagnosis, Therapy
This one day course will give an overview of the latest research in behavioral economics and discuss its implications for market participants. It will challenge the view that individuals take rational decisions provided that they have access to full information.
The course is in two parts. The first part focuses on anomalies in financial markets and their behavioural explanation. Inefficiencies include the affect of weather, seasons and daylight changes on stock prices; overconfidence and excess trading; loss aversion, regret aversion and the winner/loser asymmetry. The second part focuses on life cycle saving and investment. It will discuss the new paradigm of wealth planning and will argue that campaigns to increase financial literacy are inefficient and may even be counterproductive.
Tutor: Henriette Prast
Duration: 1 day, recordings are separated into 4 sessions
Operator Methods in Fixed Income and Credit
Operator methods are an emerging framework for modelling financial derivatives. The first half of this course covers Stochastic Monetary Policy Models for Interest Rate Derivatives, and applications to callable CMS spread range accruals. The second half covers Structural Models for Credit Equity Derivatives and applications to bespoke synthetic CDOs. Operator methods are an emerging framework for modelling financial derivatives. The key numerical engine is Level-3 BLAS and in particular martix-matrix multiplication routines which typically execute on off-the-shelf, massively parallel multi-core GPU's as opposed to CPU's. The mathematics is adapted to this engine and relies on linear algebra and functional analysis as opposed to measure theory and stochastic calculus. From the modelling viewpoint, this framework allows one to specify and calibrate semi-parametric models which are flexible enough to incorporate econometric estimates, thus avoiding the need to restrict oneself to analytically solvable models.
Tutor: Claudio Albanese
Duration: 2 days, recordings are separated into 8 sessions
Intraday High-Frequency Trading: From Empirical Evidence to Quantitative Optimization
This course covers factors that affect intraday trading, how to capture intraday statistical invariants, and how to understand and implement quantitative formalization of intraday trading.
Tutor: Charles-Albert Lehalle
Duration: 1 day, recordings are separated into 4 sessions
What you will learn:
- The factors that affect intraday trading
- How to capture intraday statistical invariances (volume, volatility curves, etc.)
- Understanding and implementing research on quantitative formalization of intraday trading.
Volatility, Advanced Modelling with PC Workshops
This course takes a critical look at the most important unknown in derivatives pricing: volatility. The main modelling approaches are all presented, along with their advantages and disadvantages. Concepts are studied from both a scientific and a practical point of view with the goal being to give the delegates the deepest possible understanding of the significance of their choice of model. Paul Wilmott brings to this course many years as a mathematical modeller in scientific disciplines as well as his experience forecasting volatility and as a partner in a very successful hedge fund. This Masterclass will feature spreadsheet and VBA workshops.
Tutor: Paul Wilmott
Duration: 2 days, recordings are separated into 8 sessions
What you will learn:
- Important volatility forecasting methods
- The different meanings of volatility
- Calibration to market prices, representing the skew and smile
- Deterministic volatility surfaces
- Stochastic volatility
- Uncertain volatility
- Robustness and minimizing model error, static hedging
- Volatility, static and dynamic hedging and portfolio theory.
VG Modelling: Pricing Financial Derivatives in Equity and Credit Risk
This course provides an introduction to the use of the Variance Gamma (VG) based models for equity and credit risk. The course takes a practical approach to describing the theory of advanced models, and features many examples of how they may be used to solve problems in finance, with emphasis on the pricing of financial derivatives. Starting from the analysis of data, we build up models driven by the nowadays popular VG Lévy processes that incorporate stylized features like jumps and stochastic volatility.
Both the mathematical modelling and the numerical aspects are covered. Key topics are addressed, including option pricing, calibration, Monte Carlo simulations, exotic options and credit risk. The course also avoids unnecessary mathematical formalities.
Tutor: Wim Schoutens
Duration: 2 days, recordings are separated into 8 sessions
What you will learn:
- See more realistic VG models for stocks and credit risk work on real data
- Which Levy processes are useful for financial modelling purposes and which are not?
- How to price an option surface of vanillas under advanced models within a second
- Learn about the very recent multivariate VG models that can be calibrated on univariate vanilla surfaces
- Learn about the new credit risk models driven by Levy processes and see how they can nicely capture the CDS term structure
- Learn how to simulate fast VG based models:
- to price exotics
- to run scenarios for risk-management purposes
- to simulate your insurance-linked products under a more advanced setting.
Exotic Equity Derivatives, Pricing and Hedging
Exotic Equity Options, Pricing and Hedging is a detailed course on the pricing and hedging of exotic equity derivatives, starting from the analysis of data to build up a vanilla pricing model and then extending this to exotic, over-the-counter products. We examine the mathematical modelling and the numerical aspects, as well as choice of model and dynamic and static hedging. Many real-life term sheets will be analysed. The course will feature spreadsheet and VBA workshops.
Tutor: Paul Wilmott
Duration: 2 days, recordings are separated into 8 sessions
What you will learn:
- The Black-Scholes pricing and framework
- How to categorise exotic options
- The mathematics of path dependency and decision processes
- Pricing models
- Hedging strategies
- Numerical methods for pricing.
Behavioral Science In Finance: Phenomena, Diagnosis, Therapy
This one day course will give an overview of the latest research in behavioral economics and discuss its implications for market participants. It will challenge the view that individuals take rational decisions provided that they have access to full information.
The course is in two parts. The first part focuses on anomalies in financial markets and their behavioural explanation. Inefficiencies include the affect of weather, seasons and daylight changes on stock prices; overconfidence and excess trading; loss aversion, regret aversion and the winner/loser asymmetry. The second part focuses on life cycle saving and investment. It will discuss the new paradigm of wealth planning and will argue that campaigns to increase financial literacy are inefficient and may even be counterproductive.
Tutor: Henriette Prast
Duration: 1 day, recordings are separated into 4 sessions
Operator Methods in Fixed Income and Credit
Operator methods are an emerging framework for modelling financial derivatives. The first half of this course covers Stochastic Monetary Policy Models for Interest Rate Derivatives, and applications to callable CMS spread range accruals. The second half covers Structural Models for Credit Equity Derivatives and applications to bespoke synthetic CDOs. Operator methods are an emerging framework for modelling financial derivatives. The key numerical engine is Level-3 BLAS and in particular martix-matrix multiplication routines which typically execute on off-the-shelf, massively parallel multi-core GPU's as opposed to CPU's. The mathematics is adapted to this engine and relies on linear algebra and functional analysis as opposed to measure theory and stochastic calculus. From the modelling viewpoint, this framework allows one to specify and calibrate semi-parametric models which are flexible enough to incorporate econometric estimates, thus avoiding the need to restrict oneself to analytically solvable models.
Tutor: Claudio Albanese
Duration: 2 days, recordings are separated into 8 sessions
Intraday High-Frequency Trading: From Empirical Evidence to Quantitative Optimization
This course covers factors that affect intraday trading, how to capture intraday statistical invariants, and how to understand and implement quantitative formalization of intraday trading.
Tutor: Charles-Albert Lehalle
Duration: 1 day, recordings are separated into 4 sessions
What you will learn:
- The factors that affect intraday trading
- How to capture intraday statistical invariances (volume, volatility curves, etc.)
- Understanding and implementing research on quantitative formalization of intraday trading.