2 DAY EXECUTIVE WORKSHOP ON ALGORITHMIC TRADING

Transcription

1 NSE Management Development Programme Series DAY EXECUTIVE WORKSHOP ON ALGORITHMIC TRADING An initiative under

2 P R O G R A M M E OVERVIEW Technology has revolutionized the way financial markets function and the way financial assets are traded. Technology development across global markets has necessitated a multidimensional approach for understanding the Importance of Algorithmic Trading. It is imperative to develop domain knowledge expertise in quantitative and qualitative algorithmic trading skills.it helps to understand the market in a better manner and often allows us to frame difference strategies as per the market movements. Given the current market scenario and dynamism, Algorithmic Trading has attracted attention more than ever before. The concepts are multi-fold and are applicable across all financial markets: equities, fixed income, currencies-domestic or global. In view of this, NSE presents a comprehensive workshop on Algorithmic Trading for analysts, dealers, traders, consultants, and other market practitioners. The course provides an opportunity to learn Algorithmic Trading. PROGRAMME OBJECTIVE NSE's MDPs aims to enhance the competitiveness of executives of all levels in the financial industry. It is designed to assist professionals to take on a leadership role in their position individually and collectively, while improving their knowledge. NSE's MDPs are vital for practicing professionals and managers who are keen to take on leaderships roles with their organizations. NSE's MDPs attract some of the finest faculty from industry. Participants learn from both the rich practical experience of the faculty, as well as from the diverse experience of fellow learners. It provides an ideal platform for gaining new insights in order to be successful. NSE also conducts dedicated workshops for corporate and financial institutions, especially designed for Traders, corporate executives and entrepreneurs. ABOUT QUANTINSTI Launched in 2010, QuantInsti (QI) is a globally unique concept of practical education on algorithmic trading by industry professionals. The core offering of QI is E-PAT (Executive Program in Algorithmic Trading). E-PAT is a 4-month (100 contact hours) online as well as in class course conducted on the weekends. Participants also do a project on an live-industry topic after the course work. The course is broadly divided into three segments: (I) advanced statistics, (ii) quant strategies and (iii) financial computing and technology. Till date around 200 professionals have successfully completed this program (17 batches) from Asia, Europe, America and Africa. This program is targeted towards professionals from the quant, trading, analytics, risk or financial-technology domains. In addition, QI is also the official partner of Fitch Learning's CQF program in India, and conducts workshops /educational programs in collaboration with financial institutions, exchanges, educational institutes. 1

3 P r o g r a m C o n t e n t Day 1 Demystifying Algorithic Trading Decoding the jargon: Quant Trading, Algorithmic Trading, Automated Trading, High Frequency Trading, Ultra-High Frequency Trading Evolution of algorithmic trading - Globally Evolution of algorithmic trading - India Why should you do Algorithmic Trading - Benefits of Algorithmic Trading? Global & Indian trends - volumes generated, etc System Architecture and its impact on trading performance Internal components of an algorithmic trading platform ( OMS, CEP, RMS, Adaptors, tickstore, eventstore, etc) and their interaction External components - adaptor communication with destinations, communication standards and protocols (FIX, etc), TAP servers, multi TAP and invitation management Technological setup for Indian markets - network connectivity (scenarios, message rates); different trading environments (mock, test); colocation vs non-colocation; tbt vs snapshot; native api vs FIX connectivity Build vs buy decision ('building tools in house' vs 'buying off the shelf products') Technological innovations for algorithmic trading Latency, methods of measuring latency, standard latency benchmark figures Software innovations - low latency codes, Hardware innovations - cpu affinity vs scalability, FPGA vs ASIC, strategy on hardware, hardware configurations Tools available for Indian markets - software, hardware, etc Tool-box set of Algorithmic Trading Statistics, Quant Finance, Computing Key Statistical concepts relevant for designing algorithmic trading strategies Different types of algorithmic trading strategies High/ultra high frequency strategies Execution strategies: TWAP, VWAP, IS, etc Alpha seeking strategies: - market-making, arbitrage Different types of arbitrage strategies (structural and statistical) Equity segment strategies: Index Arbitrage, Mean reversion, momentum, technical analysis, pair trading Option Strategies: Dispersion, Volatility Spreads, Variance Swaps, Jelly Rolls, Skew trades Multiple exchange strategies: Smart Order Routing strategies Order Book Dynamics based trading strategies What are different global firms doing? Process of developing an algorithmic trading strategy Entire life-cycle involved in designing & operating an algorithmic trading strategy Working with high frequency data - managing tick databases Normalizing and cleansing data Hypothesis formulation Machine learning methodologies to automate strategy development Rules and Regulations Auditing Process and Requirements (NSE defined) SEBI recommendations on audit Exchange audits Technology and System audits Compliance Requirements Strategy approval process for Indian exchanges Global trends in regulations 2

4 Day 2 Working on Algorithmic Trading Platforms - I Complex Event Processing on Algorithmic Trading Platforms Working with exchange simulators and testing strategies Risk Management specific to Algorithmic Trading Risk Management for Trading Operations - different sources of risk, evaluation methodologies to quantify and set limits Additional Risk Management issues in Automated Trading Common errors encountered in Algorithmic Trading Case studies of all major failures globally on Algorithmic Trading Risk Management requirements for Indian Exchanges Working with Quant Tools Statistical big-data analytics using R Using R with Excel Performance Evaluation and Portfolio Management Determining profitability of strategies using Sharpe ratio, Sortino ratio, Jensen's alpha, RaROC, Treynor Ratio, etc Leverage Space Theory to allocate resources across strategies Building Quant Tools Practical exercise to build Options Portfolio Management Tools for algorithmic trading What next Exchange innovations Competitive Landscape New generation strategies - Machine Readable News based strategies, etc Future studies Literature review of books, study material and research papers on algorithmic trading 3

5 P R O F I L E O F S P E A K E R S 4 Gaurav Raizada Gaurav Raizada is a Director at iragecapital Advisory Private Ltd., leads the firm's advisory practice in India on the Systems, Performance and Strategies. He has consulted extensively with core focus on strategy development and execution including trading systems development, latency reduction, optimization and transaction cost analysis. An area of specific focus for Gaurav has been working with clients in high frequency trading-proprietary desk, brokerages, and banks. His current areas of research are High Frequency Econometrics, Structured Products and Transaction Cost Analysis. Prior to iragecapital, Gaurav worked with Axis Bank as a Forex-Interest Rates Derivatives Trader. He also worked as a Performance Engineer at Veritas Software, where he picked up the feel for Optimization. Gaurav has a post graduate degree in management from Indian Institute of Management, Lucknow and a B.Tech. in Chemical Engineering from Indian Institute of Technology, Kanpur. Kunal Kumar works in the Trading Strategy Team at iragecapital Advisory, responsible for developing new strategy along with fine-tuning existing ones. His focus area extends to process automation and maintaining trading infrastructure. Prior to that, he worked at ICICI Bank headquarters in their Treasury team, helping International Institutional clients with their FX, Bonds and Derivatives requirements. He has also interned with Religare Capital Markets in Investment Banking Division and Tata Steel. Kunal holds a Post Graduate in Management Degree from IIM Calcutta and Engineering Degree (B.E.) from Birla Institute of Technology in Electronics & Communication, where he was among the department toppers. He also holds an FRM Degree from Global Association of Risk Professionals (GARP). Nilesh Koshe Kunal Kumar Nilesh Koshe works as Quantitative Associate at iragecapital Advisory in their Derivative strategy team. His focus area is data modelling using machine learning techniques, automating trading decision for algo trading. Prior to irage Capital, he worked with one of the leading Investment Bank as Derivative Strategist, proving derivatives solution to buy side clients including insurance funds, pension funds etc. He served in Asian and European markets. Nilesh completed his graduation from Indian Institute of Technology, Delhi with Dual Degree in Electrical Engineering and Information & Communication Technology. He worked on modelling Ambient Ocean noise using long range dependent process as his masters thesis. Nilesh has interest in Abstract algebra and Neural Networks. He led his college Athletics team at Inter IIT sports meet and now he is a seasoned marathoner. Rajib Ranjan Borah Rajib Ranjan Borah is a co-founder and director at iragecapital & QuantInsti. In the past 10 years, he has worked in various key roles related to automated trading in US, Europe & Asia with pioneering firms from the industry like Bloomberg LP, Optiver LLP, iragecapital - in roles spanning from designing and trading HFT strategies, technology for low latency trading, and strategy advisory to a consortium for starting a new commodity derivative exchange. A national Olympiad finalist, Rajib has twice represented India at the World Puzzle Championships. Rajib is a computer engineering graduate from NIT Surathkal and has a management degree from IIM Calcutta. He regularly speaks on topics related to automated trading, option derivatives and quantified news analytics at conferences & seminars across US, Europe & Asia.

6 WHO SHOULD ATTEND? The workshop is ideal for Traders, Investors, Brokers, Sub-brokers, Dealers, Fund Managers, Corporate Executives, Financial Intermediaries, Media, Journalist & anyone who wants to learn Algorithm Trading. W O R K S H O P D E T A I L S MANAGEMENT DEVELOPMENT PROGRAM IS A TWO DAY EXECUTIVE WORKSHOP Date: June 27 and 28, 2015 Time: 10:00 AM to 5:30 PM Venue: NSE, Exchange Plaza, C-1, Block-G, Bandra Kurla Complex, Bandra-Kurla Complex, Mumbai FEE & REGISTRATION Training fee: Rs 18,000 plus 12.36% Tax (Total: Rs 20,225/-) The fee includes tuition, presentation material, etc. (Special discount of 10% for a group of 3 or more participants attending together as a team.) PAYMENT MODE: DEMAND DRAFT AND ONLINE PAYMENT Account payee demand draft drawn in favour of "NATIONAL STOCK EXCHANGE OF INDIA LIMITED", payable in Mumbai, should reach NSE at least seven days before the commencement of the program. FOR ANY FURTHER QUERIES AND FOR ONLINE PAYMENT OPTION PLEASE CONTACT Mr. Rohan Sawant/ Mr Harbir Singh Mehrolia (Mob: ) Landline: /48 hmehrolia@nse.co.in/crmsupport-mum@nse.co.in Limited Seats 5

7 MDP NOMINATION FORM 2 DAY EXECUTIVE WORKSHOP ON ALGORITHMIC TRADING Step 1. Take a printout of this Nomination Form Step 2. Fill the Nomination Form with the required details Step 3. Make a Demand Draft of Rs 18,000 plus 12.36% Tax (Total: Rs 20,225/-) payable at Mumbai in favour of "National Stock Exchange of India Limited" Step 4. Send the Demand Draft along with completed registration form and Copy of pan card to Mr. Rohan Sawant/ Mr Harbir Singh Mehrolia (Mob: ) National Stock Exchange of India Limited Exchange Plaza, C-1, Block-G, Bandra Kurla Complex, Mumbai Landline: /48 hmehrolia@nse.co.in/crmsupport-mum@nse.co.in Details Participant Participant Participant Name id Mobile Date of Birth Designation Organisation Years of experience in Stock Market Sponsored by: a) Self b) Company How did you come to know about the program: a) SMS b) c) Facebook d) NSE website e) Friends Correspondence Address:... Pin Code:... Programme Opted For: Date:... Payment Details: Amount (Rs.)... Demand Draft No.... Date of DD... Bank...

8 NATIONAL STOCK EXCHANGE OF INDIA LTD. Exchange Plaza, Plot no-c1, G block, Bandra-Kurla Complex Bandra (E), Mumbai Tel No - (022) cc_nse@nse.co.in Website: