Q-Trade Bootcamp 2015

The knowledge Hub for Quantitative Trading

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Quantitative, Algorithmic Trading & HFT

H F T - Artificial Intelligence - Machine Learning - Statistical Arbitrage
Trend following - Trading System - Portfolio Optimization

-Q-Trade BootCamp in points:

Intensive Program: Boost your experience in HFT, Artificial Intelligence, Statistical Arbitrage, Machine Learning, Trend following, Trading Systems, Portfolio Optimization.
Real track-records: Selected professionals and academics who have “real track-records and really something to say” in each topic for sharing their knowledge and real experiences.
Material: Selected theory, traders’ hints, models and related working codes in Matlab®, R and Python.
Network: Meet&link Quant Traders, Strategists, Fund Managers, Asset Management Company, Investors from all over the world.
The -Q- Trade bootcamps is practical, interactive , business oriented
and with an optimal balance between:


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Induction Day - May 11

What you need to know to build-up and manage a trading system

  • Programming Foundation (1.5h)

    Programming 101


    • Programming tools in R, Python and Matlab
    • User-defined functions
    • Data I/O and financial providers download
    • Plotting functions
    • Functions for random and stochastic variables
  • Quantitative Analysis Intro (2.0h)

    Manuele Monti

    • Time series analysis
    • Returns and Normality test (+coding)
    • Correlation, Co-Integration Analysis (+coding)
    • Basic Stochastic processes (Random Walk, Brownian Motion, GBM, Mean Reversion)
  • Trading System Structure (2.0h)

    Giordano Frezza

    • Trading system process: from the idea to the automatic trading
    • Data base management
    • Fees: spread, market impact, brokers
    • Risk and performance quantitative parameters (+ coding)
    • Objective/predictor, optimization, multi objective function (+ coding)
    • IN/OUT and smoothing analysis (+ coding)
    • Backtesting and execution (+ coding)
    • Updating and Handling Risk Management in Automated systems
  • Risk Management (1.5h)

    Manuele Monti

    • Risk Metrics, factors
    • Risk models and measures (VaR, ES, CVaR, PaR, CFaR)
    • Primer on risk management analytical and numerical techniques

Qtrade Bootcamp - May 12

Trading Strategies

  • Trend-following strategies (2.0h)

    Trend-following strategies

    Giordano Frezza

    • Rho analysis, time series dependence based on autocorrelation (Levich-Rizzo) (+ coding)
    • Trend following trading system example (+ coding)
  • Dispersion Trading and Correlation Modelling (2.5h)

    Simone Siragusa (2.5h)

    • Volatility Modelling (+coding)
    • Variance pitfalls
    • Exponential smoothing
    • GARCH and Leverage effect
    • Realized variance
    • Correlation Modelling (+coding)
    • Value at risk and the needs of covariance
    • Cluster analysis
    • Modelling Conditional covariance and correlation
    • Monte Carlo Analysis with different covariance matrixes
    • Implied volatility arbitrage and the case of dispersion trading
    • Correlation risk and hedge fund returns
  • Statistical Arbitrage via Kalman Filter(2.0h)

    Rocco Mosconi, Mattia Manzoni

    • Kalman filter: a latent variable model applied to a systematic trading strategy
    • An alternative to cointegration
    • An “in house” custom solution (+ coding)
    • Backtesting

Qtrade Bootcamp - May 13

Statistical Arbitrage

  • Statistical Arbitrage (7.0h)

    Statistical Arbitrage

    Ernest P.Chan (7.0h)

    • Stationarity and cointegration of time series
    • Stationarity and mean-reversion: the practical benefits.
    • Cointegration vs correlation.
    • Mean-reversion trading of pairs and triplets
    • Finding hedge ratio through linear regression (LR).
    • Order-dependence of hedge ratio based on LR.
    • Finding hedge ratio through Johansen test.
    • Case study: The breakdown of cointegration of GLD-GDX, the economic reasons and the remedy.
    • Half-life of mean-reversion
    • Practical importance of half-life.
    • The Ornstein-Uhlenbeck formula.
    • Risk management of mean-reversion strategies
    • Index arbitrage
    • Trading an ETF against a basket of its component stocks.
    • Constructing a basket : linear regression, constrained optimization
    • Long-short portfolio
    • Long-short portfolio strategy of stocks in the S&P 500

Qtrade Bootcamp - May 14

Artificial Intelligence and Portfolio Optimization

  • Forecasting and Artificial Intelligence Based Strategies (4.0h)

    Forecasting & Artificial Intelligence Based Strategies

    Ernest P.Chan

    • General paradigm of machine learning.
    • AI techniques
    • Stepwise linear regression
    • Classification and regression trees (CART)
    • Neural networks
    • Genetic algorithm
    • Bayesian networks
    • Support Vector Machines (SVM)
    • Predicting returns of a portfolio using stepwise linear regression, CART, neural network, and SVM (+coding)
  • Portfolio Optimization (3.0h)

    Ernest P.Chan

    • Markowitz mean-variance optimization as applied to strategies.
    • Theoretical derivation of Kelly formula.
    • Exercise: Testing the implications of Kelly formula.
    • Exercise: Finding the optimal allocations of N strategies based on Kelly formula.
    • Simpler ways to allocate leverage.
    • Exercise: Experimenting with variations of the optimization scheme to achieve better out-of-sample performance.
    • Portfolio Optimization

Qtrade Bootcamp - May 15

Market Making, Volume Impact and High Frequency Trading

  • Market Making Strategies (3.0h)

    Yiran Liu (3.0h)


    • Definition of Market Maker
    • Difference between Proprietary Trading and Market Making
    • Let’s start a simple Market Making Shop (business Model Market Maker)
    • Profit and Risk of our Business

    Market Making Strategies

    • Plain Market Making (Non Offset, Full Offset, Direction and Timing)
    • Risk Analysis of such strategies: Adverse selection
    • Other source of Market Making costs

    Optimal Control Problem

    • A Toy Example of optimal control
    • Hamilton-Jacobi_Bellman Equation
    • Feynman Kac Theorem
    • Solving HUB Equation

    Modelling Key Components

    • Market Model
    • Order Arriving Model
    • Inventory Model
    • Spread Model
    • Utility Function
    • Extend the Optimal Control Problem

    Numerical Solution (+coding)

    • Assemble the Component Models into a whole system
    • Simulation of Client Order Arrivals and Market Dynamics
    • A test of applying same model on real market price

    Statistical results and analysis

    • Factor analysis + coding, chart and tables

    What to consider if we want to use the pure math idea into production

    • May try to improve Price Model
    • More sophisticated directional betting factor
    • More Factors to put in to control, such as spread
  • API Broker connection

    Michele Bogliardi

    • Propietary APIs
    • APIs vs strategies (i.e. Spread Trading, HFT)
    • Python, R and Matlab APIs
    • Example: Matlab API in multiple Spread Trading
  • Market Volumes Analysis (1.0h)

    Antonio Lengua

    • Mechanic of market volume
    • From discretional to systematic trading
  • HFT based on Order Imbalance (1.5h)

    Rocco Mosconi, Mattia Manzoni

    • Quantitative Trading Strategies based on High Frequency Data
    • The leading informative content of order imbalance indicator
    • The role of sampling rule with high frequency data: Time vs. Volume Clock approaches

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11-15 May 2015

Starting at 9am


Milan, Italy

Talent Garden


real experience, real track-records, really something to share

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Register to the event

° Super-early registration discount (30% off) registering by 10/03/2015
° Early registration discount (20% off) registering by 27/04/2015
° Further discount for the 4-days bootcamp for academics** and groups of more than one professional delegate*

* Group of delegates: two delegates extra 10% off, three or more delegates extra 15% off
* Academics: 40% off the full 4 Days registration (before 30/04/2015), 30% off the full registration (after 30/04/2015)
** MSc and PhD Students, Graduates (in the last 6 months before registration), researchers, university interns

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Sponsor and Technology Partners

QTrade 2015 will attract the best talents, executives and institutions such as:
Asset Management Companies - Brokers - Hedge Fund Managers - Fintech Incubators - Quant Analysts - Traders - Quant Researchers and Academics

Sponsor The Event


Talent Garden Milano

Rovereto Metro Station

Talent Garden
Milan Central Station


Grant Application

Full and partial registration fee grants are offered by

Submissions are CLOSED (Deadline was 22/04/2015)

To register click here
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