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:

Programme

download area

Induction Day - May 11

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


  • Programming Foundation (1.5h)

    Programming 101

    Tutors

    • 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)

    Introduction

    • 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

Download Brochure

When

11-15 May 2015

Starting at 9am

Where

Milan, Italy

Talent Garden

Tutors

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

Where

Talent Garden Milano

Rovereto Metro Station

Talent Garden
Milan Central Station

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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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