Denis Beaudoin

Founder & CEO, FINALTIS

Thierry Bechu

Global Macro Fund Manager – 1798, Lombard Odier AM

Stratégies Quantitatives

Les objectifs du cours

The objective of this class is to understand the key features of quantitative strategies in general and more particularly of technical analysis. On one hand, the idea is to prepare student to be able to use technical analysis in order to have a consistent market analysis with a special focus on psychology To give the means to apply a simple technical analysis on a financial market with prices forecasts in order to define an investment strategy purely based on TA. On the other one, the course present what exactly are quantitative strategies, how do they work. Finally, some visits to quantitative asset management teams will be part of the course.

Plan du cours

Part 1: Instructor 1

1/ Introduction:

• Financial markets and investors psychology.
• Key pilars of technical analysis A and Dow theory.
• Random walk theory - History of TA.

2/ Chart Analysis

• Different types of charts (bar charts, candlesticks, points & figures..)
• Supports & résistances
• Trends
• Major chart patterns.

3/ Technical Analysis

• Filters and moving averages
• Bollinger bands
• Technical oscilators (RSI, stochastics, macd, DMI...).

4/ Cycles analysis

• key economic and market cycles (from Juglar to Kondratiev), why cycles exist, how to use cycles.
• Contrary opinion and Inter-market analysis

5/ Trading

• Key concepts of trading
• Systematic trading (CTAs, Turtles exemple)
• Discretionary trading
• Risk and money management
• Trading psychology

 

Part 2 : Instructor 2

Class #1: 3 hours

1/ Introduction : "All of us know what, some of us know how, very few of us know why", attributed to Simon Sinek (Start with Why)

2/ Quant is not (primarily) about mathematics, statistics or technology: it is about markets, logics and people.

 

3/ Quant 101 or quant basics: "I believe the past repeats itself"

• What does it mean to be a quant investor?
• Why quant investing?
• What is a financial market to a quant investor?
• What is a quant manager? Operational, legal and compliance framework
• A brief history of quant.

4/ Quant Strategies: how to benefit from the past repeating itself?

• Quantitative vs systematic vs automated
• What are the underlyings?
• Two distinct natures: relative value vs directional
• Divergence, convergence, contrarian, non contrarian
• Liquidity, volatility, event, dispersion, correlation
• Which time frame?
• Data cleaning, Models, Back testing, paper trading and trade execution

5/ Last but not least: when the past does not repeat itself

• "I have never seen a bad back test": curve fitting, overfitting and other pitfalls
• "Models do die too": why?, when?, how?, do's and don'ts
• "Execution is key": from paper to live trading
• Fat tails, extreme risks, parameters vs history, don't forget operations

6/ To wrap it up:

• Back to basics :markets, men and machines
• No free lunch
• What is at stake ?
• Transparency and meaning

Class #2: 3 hours

Opening the "black box": Statistical Arbitrage from back testing to risk mastering

• The case for Statistical Arbitrage: why can it work?
• Backtesting illustrated: equity market neutral baskets
• The Ornstein-Ulhenbeck process
• The Min-Max algorithms
• The case for and the environment of automated execution: DMA, MTFs, dark pools, low latency, ...
• When can't it work? Examples of Q3 2007, Q4 2007, Q2-Q3 2010
• Chasing risks when being market neutral: VaR, CVaR, stress tests
• How to include the strategy in broader portfolios?

Class #3 & Class #4: 6 hours

Case studies

• These classes will involve between 3 and 5 hours of preparation on the part of the students:After paying visits to selected Paris-based quantitative asset managers in teams of 3/4 students, Presentations of the findings to the class.

For each team 20/30 minutes presentation followed by 20 minutes discussions.

Bibliographie

Béchu T., E. Bertrand and J. Nebenzahl, 2008, L'analyse Technique: Théories et méthodes - Economica - 6ème édition.

Examen

Test: theoretical questions (50%) - market case (50%).