Quantitative Investment Strategies

London Financial Studies

Short course

In London

£ 2,790 + VAT

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Description

  • Type

    Short course

  • Location

    London

  • Duration

    2 Days

  • Start date

    Different dates available

Quantitative investment strategies are technology intensive techniques covering a broad investment spectrum ranging from systematic managed futures and algorithmic strategies to high frequency trading. These investment strategies have grown in importance to represent in excess of 60% of the aggregate volume traded on certain developed markets exchanges in 2013.

This course gives participants a comprehensive overview of a fast growing area at the forefront of financial innovation as well as a framework for the application and assessment of quantitative investment strategies.

Facilities

Location

Start date

London
See map
34 Curlew Street, se12nd

Start date

Different dates availableEnrolment now open

About this course

Portfolio managers & traders
Investment officers
Strategists
Risk managers
Auditors, compliance and regulators
Quants and IT personnel

An understanding of stochastic calculus and MATLAB/C++ is preferred, but not necessary to follow this course.

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Reviews

This centre's achievements

2016

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 16 years

Subjects

  • Investment
  • Trading
  • IT risk
  • Risk
  • Algorithmic Trading
  • Market
  • Testing
  • Technology
  • Investment strategies
  • Algorithmic
  • Matlab
  • Risk Management
  • Splitting Alpha
  • Beta
  • ULLDMA
  • DMA
  • SMA
  • Market Liquidity
  • HFT strategies

Teachers and trainers (1)

Julien Dauchez

Julien Dauchez

Teacher

Julien Dauchez is a quant-trained derivatives and investment strategy specialist with over 16 years’ experience in capital markets. Julien started his career in Fixed Income at Lehman Brothers in London in 1998. After 7 years, Julien joined Barclays Capital where he headed a derivatives structuring and marketing team in New York. Upon his return to London in 2010, he joined the asset management arm of Barclays where he originated UCITS and and fund solutions for institutional and retail-oriented clients.

Course programme

Day One

Quantitative investment strategies overview
  • Identifying new sources of alpha
  • The variety of QIS: CTA, event trading and deviations arbitrage
  • Time series analysis
  • Arms race in technology
Building & testing an algorithmic trading strategy
  • Mean reversion and momentum in finance
  • Stationarity, co integration and factor models
  • Statistical significance hypothesis testing
  • MATLAB basics
  • Data mining pitfalls
Workshops:
  • Decomposing an algorithmic trading strategy
  • Identifying drivers in a time series
  • Assessing statistical significance
  • Strategy backtesting
  • Defining portfolio rebalancing rules
  • Setting risk limits
Implementing quantitative investment strategies
  • Portfolio construction
  • Portfolio optimization through Bayesian techniques and Black Litterman model
  • Transaction costs and trade execution
  • Risk management
Using quantitative strategies for hedging purposes
  • Defining and monitoring 3 sigma events
  • Limitations of price log normality assumption
  • Cross asset correlation in non normal market conditions
  • Systematic tail risk hedging
Workshops:
  • Assessing tail risk hedging strategies by asset class
  • Building a simple S&P put spread strategy
  • Determination and optimization of the strategy’s cost of carry
Day Two

Splitting Alpha and Beta in Quantitative Investment Strategies
  • Limits of traditional indexing
  • Fundamental factor based Smart Beta indices
  • Risk controlled indices
Implementing Smart Beta Strategies
  • Picking the right asset class and market
  • Strategy induced technical challenges
  • Managing implementation risks
Workshops:
  • Analysis of a Smart Beta index
  • Comparing the risks and returns of smart beta indices against traditional investment benchmarks
  • Devising an index based Smart Beta investment strategy
  • Liquidity and transaction costs management in Smart Beta strategies
High Frequency Trading (HFT)
  • Overview of the HFT world
  • Understanding HFT strategies
  • ULLDMA and co location
  • Real time risk management of HFT strategies
Challenges raised by algorithmic trading strategies
  • Algorithmic trading testing markets safeguards
  • The impact of algorithmic trading on transactions costs and market liquidity
  • Computerized trading in the MiFID and MAD environment
Workshops:
  • Understanding how a HFT platform operates
  • Order placement and execution (DMA/SMA)
  • Latency reduction techniques
  • Services offered by exchanges

See related categories

Quantitative Investment Strategies

£ 2,790 + VAT

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