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Changing Notions of Risk Management in Financial Markets

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The presentation is a part of QuantInsti's Webinar on "Changing Notions of Risk Management in Current Markets" which was conducted on 10th August, 2015.

In the presentation Mr. Rajib Borah, Director and Faculty at QuantInsti, talks about a few major risk oversight issues in algorithmic trading, like:

a. How did Knight Capital lose $460 in 45 minutes?
b. Why was Deutsche Bank forced to close their Algorithmic Trading desk in Tokyo?
c. What went wrong at Infinium Capital while trading Crude ETFs and why were they fined $850,000?
d. What mistake caused HanMag Securities of Korea to lose 57 billion Korean Won in a few minutes?
e. and a few more

QuantInsti's (http://www.quantinsti.com) flagship offering is the 'Executive Programme in Algorithmic Trading' (EPAT) which is a comprehensive course covering all important aspects of Algorithmic Trading. Apart from detailed theoretical lessons, we provide our course participants in-house proprietary tools and other globally renowned applications in a simulated environment -- course participants can design, implement and test their strategies in such environment and build on their learning in the class.

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Published in: Economy & Finance
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Changing Notions of Risk Management in Financial Markets

  1. 1. QuantInsti Quantitative Learning Pvt. Ltd.
  2. 2. Rajib Ranjan Borah Co-Founder & Director, QuantInsti Quantitative Learning Pvt Ltd & iRageCapital Advisory Pvt Ltd Changing Notions of Risk Management in Financial Markets – Impact of Proliferation of Automated Trading Systems and Technology on Financial Markets
  3. 3. Table of Contents • Changing Trends in Trading • Major Automated Trading Risk Failures • Changing Trends in Trading Risk Management • Regulatory requirements • Q & A
  4. 4. Table of Contents • Changing Trends in Trading • Major Automated Trading Risk Failures • Changing Trends in Trading Risk Management • Regulatory requirements • Q & A Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  5. 5. Trading in the markets If you have a profitable trading strategy, then … Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  6. 6. Trading in the markets If you have a profitable trading strategy, then … • do it as frequently (don’t miss any opportunity) • scale it up (trade as many financial instruments) • don’t let emotions affect (greed & fear: traders’ biggest enemies) Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  7. 7. Trading in the markets If you have a profitable trading strategy, then … • do it as frequently (don’t miss any opportunity) • scale it up (trade as many financial instruments) • don’t let emotions affect (greed & fear: traders’ biggest enemies) Computers: • always at their seats • respond to opportunities in microseconds Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  8. 8. Trading in the markets If you have a profitable trading strategy, then … • do it as frequently (don’t miss any opportunity) • scale it up (trade as many financial instruments) • don’t let emotions affect (greed & fear: traders’ biggest enemies) Human eye can monitor 10- 15 stocks. Computers can track thousands simultaneously Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  9. 9. Trading in the markets If you have a profitable trading strategy, then … • do it as frequently (don’t miss any opportunity) • scale it up (trade as many financial instruments) • don’t let emotions affect (greed & fear: traders’ biggest enemies) Computers have no emotions Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  10. 10. Trading in the markets If you have a profitable trading strategy, then … • do it as frequently (don’t miss any opportunity) • scale it up (trade as many financial instruments) • don’t let emotions affect (greed & fear: traders’ biggest enemies) Trading is all about computations and computers do calculations faster Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  11. 11. Trading Today Inevitably, machines have taken over human beings Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  12. 12. Trading Today Inevitably, machines have taken over human beings Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  13. 13. Trading shifted from pits … Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  14. 14. …to computers Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  15. 15. …and even more computers Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  16. 16. Trading Landscape changes This revolution has been fast Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  17. 17. Effect of algo-trading … and this growth has been across asset classes Options FX Equity Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  18. 18. Options FX Equity Effect of algo-trading Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA … and this growth has been across asset classes
  19. 19. Options FX Equity Effect of algo-trading Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA … and this growth has been across asset classes
  20. 20. Unfortunately, …. computers don’t think Effect of algo-trading Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  21. 21. Pros and Cons Trading algorithmically is generally more profitable
  22. 22. Pros and Cons Trading algorithmically is generally more profitable • Less downtime • No emotions (Greed & Fear) • React faster • Higher scalability • Accurate and faster calculations Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  23. 23. Pros and Cons Trading algorithmically is generally more profitable But … Systems are getting more complicated Traditional trading system Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  24. 24. Pros and Cons Trading algorithmically is generally more profitable But… Systems are getting more complicated Increasing likelihood of errors Automated trading system Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  25. 25. Pros and Cons Trading algorithmically is more profitable … … and more riskier Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  26. 26. Table of Contents • Changing Trends in Trading • Major Automated Trading Risk Failures • Changing Trends in Trading Risk Management • Regulatory requirements • Q & A Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  27. 27. Major algorithmic trading incidents - I • Credit Suisse, Nov 2007 – Incident: • Hundreds of thousands of cancel orders sent to the exchange • Orders clogged NYSE and affected trading of 975 stocks – Reasons: • Trader implemented code which could change parameters on clicking on spin button (without any need for confirmation) • With each click, orders were cancelled and resent – Fine/ Losses: • $150,000 fine Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  28. 28. • Infinium Capital, Feb 2010 – Incident: • 4612 trades on crude oil futures in 24 seconds – Reasons: • Strategy was designed to trade energy ETFs on the basis of crude prices • Trader configured crude oil futures on the basis of energy ETFs • Moreover, RMS was designed on the basis of ETF prices, not crude prices – Fine/ Losses: • $850,000 fine by CME Major algorithmic trading incidents - II Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  29. 29. • Deutsche Bank, June 2010 – Incident: • Sent orders for 1.24 million Nikkei 225 Futures & 4.82 million Nikkei 225 mini-futures in first few minutes • More than 10 times normal volume • Market dropped 1% on orders – Reasons: • Pair trade strategy used value of Nikkei ETF to quote Nikkei. At start of day, there was no price information in Nikkei ETF (because of a configuration change) • Error recognized immediately, 99.7% orders cancelled – Fine/ Losses: • Forced to close Algorithmic trading desk in Tokyo Major algorithmic trading incidents - III Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  30. 30. • BATS listing, Mar 2012 – Incident: • On the day of listing, stock price dropped 99% – Reasons: • Software bug in newly installed exchange matching engine - orders placed during auction session became inaccessible for stocks whose ticker symbols began with letters A to BFZZZ – Fine/ Losses: • IPO withdrawn Major algorithmic trading incidents - IV Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  31. 31. • Knight Capital, Aug 2012 – Incident: • Traded 154 stocks at bizarre prices (4 million trades for 397 million shares in 45 minutes): alternately bought at higher prices and sold at lower prices – Reasons: • Accidentally installed test software which incorporated an old piece of code designed 9 years ago • In one out of 8 production servers, new code was not installed by a technician • No process for second technician to review – Fine/ Losses: • Trading loss of $460 million in 45 minutes. Fine of $12 million • Knight Capital had to be rescued by Getco Major algorithmic trading incidents - V Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  32. 32. • Goldman Sachs, Aug 2013 – Incident: • Traded stock options at very erroneous prices at the exchange – Reasons: • Indication of interests were sent as actual orders to the exchange – Fine/ Losses: • Trading loss of $100 million Major algorithmic trading incidents - VI Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  33. 33. • Tel Aviv Stock Exchange, Aug 2013 – Incident: • Shares of Israel Corp. country's largest holding company fell sharply from 167,200 Israeli Shekels to 210 Shekels. – Reasons: • Trader wrongly entered Israeli Corp as scrip name instead of some other firm – Fine/ Losses: • All trades cancelled Major algorithmic trading incidents - VII Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  34. 34. • Everbright Securities, Aug 2013 – Incident: • Rogue algorithm kept buying – index moved up 6% intraday • Did not inform regulators, shorted the artificial bubble – banned from prop trading forever for insider trading – Reasons: • Algorithm did not check position limits and kept sending orders – Fine/ Losses: • Banned from prop trading forever for insider trading Major algorithmic trading incidents -VIII Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  35. 35. • HanMag Securities, Dec 2013 – Incident: • HanMag exercised wrong call and put options • 36,100 trades in a few minutes – Reasons: • Error in automated profit taking trade program (interchanged puts with calls) – Fine/ Losses: • Some firms returned money back to HanMag (Optiver returned $600k trading profits) • Eventual loss of 57 billion Korean Won Major algorithmic trading incidents - IX Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  36. 36. • United Airlines mini-flash crash – Incident: • On Sep. 7, 2008 United Airlines had a downward price spike – Reasons: • Google’s newsbots picked up an old 2002 story about United Airlines possibly filing for bankruptcy • News Analytics based automated traders reacted to it Major algorithmic trading incidents - X Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  37. 37. • Dow Jones mini-flash crash – Incident: • On Apr 23, 2013 Markets dropped 0.8% momentarily – Reasons: • Twitter account of news publisher hacked – false news of White house explosion • News Analytics based automated traders reacted to it Major algorithmic trading incidents - XI Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  38. 38. Table of Contents • Changing Trends in Trading • Major Automated Trading Risk Failures • Changing Trends in Trading Risk Management • Regulatory framework in India • Q & A Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  39. 39. Traditional Risks Traditionally trading operations focused on following risks … • Market Risk • Credit / Counter-party Risk • Financial Risk • Liquidity Risk • Regulatory Risk Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  40. 40. Automated Trading Risks Automated trading requires additional focus on • Market Risk • Credit / Counter-party Risk • Financial Risk • Liquidity Risk • Operational Risk • System Risk • Greater focus on Natural Disaster Risk • Regulatory Risk (Automated Trading related) Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  41. 41. Issues with Algo-Trading • Orders flow without human control – Higher reliance on technology – GIGO (Garbage Input → Garbage Output) • Before a human can realize (and then respond) → tremendous damage would happen already • Trades happen at such a fast pace → positions could become huge in no time – Real-time monitor of positions, exposures, regulation checks Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  42. 42. Algo-trading system risks • System and Operational Risks specific to automated trading can be classified into the following categories: – Access – Consistency – Quality – Algorithm – Technology – Scalability Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  43. 43. Algo-trading system risks • Such System and Operational risks have to be handled pre-order – Within the application – Before generating an order in the Order Management System • Moreover, it is pertinent that the trader understands the internal working of the black-box Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  44. 44. Algo-trading system risks Automated trading platform – system architecture Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  45. 45. RISK Risk Handled in Methodology App OM Access Connectivity to an exchange goes down Y Y Heart-beats Exchange disconnects you Y Heart-beats Network issue Y Hardware, Operating System Consistency Market Data is stale Y Y Time-stamp Analytics are running in real- time (huge processing time) Y Time-stamp OM adaptor is responding in real time Y Time-stamp Quality Market - data is garbled Y Common RMS rule Loss of liquidity during high- volatility Y Common RMS rule Algo-trading system risks Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  46. 46. RISK Risk Handled in Methodology App OM Algorithmic Margin breached Y Common RMS rule Exposure limit set by exchange Y Common RMS rule Risk limits exceeded Y Check for acknowledgements before sending order Incorrect strategy setting leading to continual mistrades Y Y PnL fluctuation check -do- Y Order throttle rate -do- Y Fat finger settings check -do- Y Max Value Traded Incorrect order generation Y Y Price range check Order throttle Y Exchange reject limit Algo-trading system risks Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  47. 47. RISK Risk Handled in Methodology App OM Technology Hard disk gets full Independent check Virus /Trojan Firewall, Anti-virus System Crash Operating System Application crash Y Heart-beat to check application Protocol Mismatch Third-party software compatibility check Algo-trading system risks Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  48. 48. RISK Handled in Methodology App OM Scalability Number of applications & portfolios that can be handled Y Y Number of exchanges that can be connected Y Number of symbols that can be handled Y Y Order of complexity of computations Y Algo-trading system risks Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  49. 49. Table of Contents • Changing Trends in Trading • Major Automated Trading Risk Failures • Changing Trends in Trading Risk Management • Regulatory requirements • Q & A Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  50. 50. • Half-yearly system audit conducted only for algorithmic trading facility • Members are required to provide following information on NSE- ENIT: – details of all algorithmic strategies in the template provided – auditor certificate • Audit provides following reports: – Summary report: Ratings of ‘Strong’, ‘Medium’ or ‘Weak’ on each broad areas (which is to be submitted to exchange via NSE-ENIT) – Detailed report • In case audit report has a rating of Weak, the member is required to submit an ATR (Action Taken Report) to exchange • Auditors to provide report on their letter heads: – List of all strategies approved Audit Process & Requirements Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  51. 51. SEBI’s broad guidelines on Algorithmic Trading (Circular CIR/MRD/DP/09/2012 dated 30 Mar 2012): Guideline for exchanges: • The stock exchange shall have arrangements, procedures and system capability to manage the load on their systems in such a manner so as to achieve consistent response time to all stock brokers. The stock exchange shall continuously study the performance of its systems and, if necessary, undertake system up gradation, including periodic up gradation of its surveillance system, in order to keep pace with the speed of trade and volume of data that may arise through algorithmic trading. SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  52. 52. • In order to ensure maintenance of orderly trading in the market, stock exchange shall put in place effective economic disincentives with regard to high daily order-to- trade ratio of algorithmic trading orders of the stock broker. Further, the stock exchange shall put in place monitoring systems to identify and initiate measures to impede any possible instances of order flooding by algorithms. • The stock exchange may seek details of trading strategies implemented through algorithmic trading for such purposes viz. inquiry, surveillance, investigation, etc. SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  53. 53. • The stock exchange shall include a report on algorithmic trading on the stock exchange in the Monthly Development Report (MDR) submitted to SEBI inter-alia incorporating turnover details of algorithmic trading, algorithmic trading as percentage of total trading, number of stock brokers / clients using algorithmic trading, action taken in respect of dysfunctional algorithms, status of grievances, if any, received and processed, etc. • The stock exchange shall synchronize its system clock with the atomic clock before the start of market such that its clock has precision of atleast one microsecond and accuracy of atleast +/- one millisecond. SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  54. 54. • Stock exchange shall ensure that the stock broker shall provide the facility of algorithmic trading only upon the prior permission of the stock exchange. Stock exchange shall subject the systems of the stock broker to initial conformance tests to ensure that the checks mentioned below are in place and that the stock broker’s system facilitate orderly trading and integrity of the securities market. Further, the stock exchange shall suitably schedule such conformance tests and thereafter, convey the outcome of the test to the stock broker. SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  55. 55. Guideline to brokers: • The stock broker, desirous of placing orders generated using algorithms, shall submit to the respective stock exchange an undertaking that - – The stock broker has proper procedures, systems and technical capability to carry out trading through the use of algorithms. – The stock broker has procedures and arrangements to safeguard algorithms from misuse or unauthorized access. – The stock broker has real-time monitoring systems to identify algorithms that may not behave as expected. Stock broker shall keep stock exchange informed of such incidents immediately. – The stock broker shall maintain logs of all trading activities to facilitate audit trail. The stock broker shall maintain record of control parameters, orders, trades and data points emanating from trades executed through algorithm trading. – The stock broker shall inform the stock exchange on any modification or change to the approved algorithms or systems used for algorithms. SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  56. 56. SEBI later laid out additional guidelines pertaining to Audit (Circular CIR/MRD/DP/16/2013 dated 31 May 2013): • The stock brokers/ trading members that provide the facility of algorithmic trading shall subject their algorithmic trading system to a system audit every six months in order to ensure that the requirements prescribed by SEBI / stock exchanges with regard to algorithmic trading are effectively implemented • Such system audit of algorithmic trading system shall be undertaken by a system auditor who possesses any of the following certifications: – CISA (Certified Information System Auditors) from ISACA; – DISA (Post Qualification Certification in Information Systems Audit) from Institute of Chartered Accountants of India (ICAI); – CISM (Certified Information Securities Manager) from ISACA; – CISSP (Certified Information Systems Security Professional) from International Information Systems Security Certification Consortium, commonly known as (ISC) SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  57. 57. • Deficiencies or issues identified during the process of system audit of trading algorithm / software shall be reported by the stock broker / trading member to the stock exchange immediately on completion of the system audit. • In case of serious deficiencies / issues or failure of the stock broker / trading member to take satisfactory corrective action, the stock exchange shall not allow the stock broker/ trading member to use the trading software till deficiencies / issues with the trading software are rectified and a satisfactory system audit report is submitted to the stock exchange. Stock exchanges may also consider imposing suitable penalties in case of failure of the stock broker/ trading member to take satisfactory corrective action to its system within the time-period specified by the stock exchanges. SEBI guidelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  58. 58. • The audit process shall broadly cover the following aspects: – Approved features and system parameters implemented in the trading system – Adequacy of input, processing and output controls should be tested – Adequacy of the application security should be audited – Event logging and system monitoring – Robust Password management standards – Network management and controls – Backup systems and procedures – Business continuity and disaster recovery plan – Proper Documentation for system processes – Security features such as access control, network firewalls and virus protection should be actively managed Audits Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  59. 59. • The stock broker, desirous of placing orders generated using algorithms, shall satisfy the stock exchange with regard to the implementation of the following minimum levels of risk controls at its end - – Price check – Quantity check – Order Value check – Cumulative Open Order Value check – Automated Execution check - an algorithm shall account for all executed, un-executed and unconfirmed orders, placed by it before releasing further order(s) – Pre-defined parameters for automatic stoppage in the event of a runaway situation / execution in a loop – All algorithmic orders are tagged with a unique identifier provided by the stock exchange in order to establish audit trail Audits Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  60. 60. • System compliance requirement for CTCL on annual basis: – Members to submit to the exchange the system audit report every year (for the year ended Mar 31) after getting the CTCL trading facility audited from any qualified auditor – Report to be submitted through NSE-ENIT by April 30 • System compliance requirement for Algorithmic Trading Facility on half yearly basis: – Members to submit the System Audit Report for the half year ended March 31 (i.e. for the period from October 01 to March 31) and September 30 (i.e. for the period April 01 to September 30), after getting the Algorithmic trading facility audited from any qualified auditor Audit Timelines Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  61. 61. • Algorithm to be executed in Mock Trading environment – logs to be certified by auditor • Algorithm to be executed in Test market at NSE – logs to be certified by auditor • Apply to exchange for strategy demonstration date with following documents: – Strategy document – Risk Management document – Network Architecture – Auditor certificates (both Mock market and Test market) – Application form (signed by director/senior management) • Algorithm to be demonstrated with exchange Strategy Approval Process Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  62. 62. • After approval from exchange, member applies for trading ids (NEAT ids) • NEAT ids converted to CTCL ids for particular vendor. Vendor of software intimated about ids and confirmation obtained • Member uploads location code details (12 digits) along with dealer details under CTCL ID before commencing trading • Member can trade as either PRO or on behalf of CLIENTS. – For PRO trading, PRO Undertaking, PRO Location Undertaking must be submitted. PRO enablement should also be done for the particular trading id. Strategy Approval Process Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  63. 63. RMS for strategy approval RMS Description Manual Trading disabled Manual orders are disabled for auto-trading systems Trade Price Protection Limit Order should be within x% of last price Quantity Freeze Limit For each instrument an order size freeze limit is set Price Range Check Order should not breach the circuit limit (daily price range) of an instrument FII restricted list FIIs cannot trade in a select set of stocks (RBI directed) Market Wide Protection Limit Cannot trade derivatives to increase Open Interest beyond a threshold Shares available for selling Overnight long position that is available per share for selling Automated Trading enabled Automated trading to be enabled for a select list of instruments only Index change check Cannot send buy orders if Index moves up beyond a point. Likewise for sell orders Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  64. 64. RMS Description Client Position Limit Maximum position that a client can have in a particular stock Margin Limit If a threshold of the available margin is reached, then the application should not send orders to increase the position further Position Value Check Net Position value per instrument Order Value Max Order Value RMS for strategy approval Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  65. 65. Table of Contents • Changing Trends in Trading • Changing Trends in Trading Risk Management • Major Automated Trading Risk Failures • Regulatory framework in India • Q & A Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  66. 66. Contacts For 4-month Executive Program in Algorithmic Trading: contact@quantinsti.com E-PAT: 4 month weekend online program (3hrs every Sat + Sun) • Statistics • Quant Strategies • Technology (programming on algorithmic trading platform) For algorithmic trading advisory: contact@iragecapital.com To reach me directly: rajib.borah@iragecapital.com Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  67. 67. E-PAT Statistics and Econometrics Financial Computing & Technology Algorithmic & Quantitative Trading QI’s E-PAT course Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  68. 68. E-PAT Statistics and Econometrics Financial Computing & Technology Algorithmic & Quantitative Trading E-PAT course structure - module I Basic Statistics Advanced Statistics Time Series Analysis  Probability and Distribution  Statistical Inference  Linear Regression  Correlation vs. Co-integration  ARIMA, ARCH-GARCH Models  Multiple Regression  Stochastic Math  Causality  Forecasting Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  69. 69. E-PAT Statistics and Econometrics Financial Computing & Technology Algorithmic & Quantitative Trading E-PAT course structure - module II Programming Technology for Algorithmic Trading Statistical Tools  Intro to Programming Language(s)  Programming on Algorithmic Trading Platforms  System Architecture  Understanding an Algorithmic Trading Platform  Handling HFT Data  Excel & VBA  Financial Modeling using R  Using R & Excel for Back-testing Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  70. 70. E-PAT Statistics and Econometrics Financial Computing & Technology Algorithmic & Quantitative Trading E-PAT course structure - module III Trading Strategies Derivatives & Market Microstructure Managing Algo Operations  Statistical Arbitrage  Market Making Strategies  Execution Strategies  Forecasting & AI Based Strategies  Pair Trading Strategies  Trend following Strategies  Option Pricing Model  Dispersion Trading  Risk Management using Higher Order Greeks  Option Portfolio Management  Order Book Dynamics  Market Microstructure  Hardware & Network  Regulatory Framework  Exchange Infrastructure & Financial Planning (Costing)  Risk Management in Automated systems  Performance Evaluation & Portfolio Management Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  71. 71. E-PAT Statistics and Econometrics Financial Computing & Technology Algorithmic & Quantitative Trading Project work E-PAT course structure - project Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  72. 72. Copyright © 2013 by QuantInsti Quantitative Learning Private Limited. Although great care has been taken to ensure accuracy of the information in this presentation – however the author (and QuantInsti) accepts no liability or warranty for the precision, correctness or completeness of any statement, estimate or opinion. QuantInsti also accepts no liability for the consequences of any actions taken on the basis of the information provided. The slides of this presentation cannot be taken separately from the whole set of slides. Prior approval from QuantInsti is necessary before usage of this presentation for educational and (or) commercial purposes. This document provides an outline of a presentation and is incomplete without the accompanying oral commentary and discussion. Disclaimer Changing Trends in Trading → Major Failures → Changing Trends in Risk Mgmt → Regulations → QA
  73. 73. Addendum
  74. 74. Risk Management Process • Phase 1: Setting risk management structure & policies • Dedicated risk department • Completely cut off from trading department • Full autonomy & powers to risk department • Approval process for each new product and operation introduced Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  75. 75. Risk Management Process • Phase 2: Identifying sources of risk • Market Risks • Credit / Counter-party Risks • Financing Risks • Operational Risks (Systems, Mechanical, Criminal) • Regulatory Risks • Liquidity Risks (Exogenous & endogenous) • Natural disasters, political, terrorism, etc Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  76. 76. Risk Management Process • Phase 3: Evaluating risk components • Market Risks : • Sensitivity Analysis • Total Greeks, Dividend, Currency exposures • What-if scenario analyses • VaR analysis • Stress tests Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  77. 77. Risk Management Process • Phase 3: Evaluating risk components • Credit / Counter-party Risks • Basel II IRB method (Internal Rating Based Method) Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  78. 78. Risk Management Process • Phase 3: Evaluating risk components • Financing Risk Probability of downgrade * interest rate hike * Size of portfolio Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  79. 79. Risk Management Process • Phase 3: Evaluating risk components • Regulatory Risk Probabilities of new Regulations- Is estimated from News Analysis & Historical Data Examples… • Short Selling Ban • Margin Increase • Taxes Introduced Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  80. 80. Risk Management Process • Phase 3: Evaluating risk components • Operational Risks (Systems, Mechanical, Criminal) • Robustness of a System • System Load handling capacity • Maximum order flow before system detects failure • Maximum leeway in error while setting parameters Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  81. 81. Risk Management Process • Phase 3: Evaluating risk components • Liquidity Risks • Liquidity adjusted VaR L-VaR = VaR + Liquidty Adjusted Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  82. 82. Risk Management Process • Phase 3: Evaluating risk components • Natural Disaster, Political Risk, Terrorism • Risk v/s Uncertainty • News Analysis Have the potential to wipeout portfolios Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  83. 83. Risk Management Process • Phase 4: Setting risk limits • Market Risks : • Total cash exposure • Exposure to geography • Exposure to sector • Exposure to asset class • Exposure to assignment / delivery risks (settlement risks) • Settlement Type (future vs cash) • Exposure to interest rates • Exposure to exchange rates Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  84. 84. Risk Management Process • Phase 4: Setting risk limits • Credit / Counter-party Risks • Maximum exposure to any counter-party • Maximum exposure per credit rating level • Financing Risks • Maximum amount borrowed per counter-party • Repayment period for loans • Rho exposure Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  85. 85. Risk Management Process • Phase 4: Setting risk limits • Operational Risks (Systems, Mechanical) • Max exposure per strategy • Max orders per second • Max orders in a day • Max exposure per application • PnL fluctuation per application • Price Range check • Max order size • Max Value Traded • Net Value of portfolio Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  86. 86. Risk Management Process • Phase 4: Setting risk limits • Operational Risks (Criminal/Fraud/ Theft, etc) • Access Control • Transparency of operations • Rotation of team members • Audit (internal & external) • Centralized PnL reconciliation • Independent verification of price to pricing models • Online Infiltration & Virus Protection Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  87. 87. Risk Management Process • Phase 4: Setting risk limits • Liquidity Risks • Maximum exposure per instruments of each liquidity category • Total exposure per liquidity category • Natural disasters • Score-card approach • Similar to one used By Insurance/ Actuaries Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
  88. 88. Risk Management Process • Phase 5: Designing systems with strict adherence to risk controls • Centralized system which summarizes net position & exposure • Asset classes, Interest rates, Exchange rates, Volatility, Dividends, Counter parties • What if Analysis • Centralized control of all trading operation • Pre trade controls Phase 1 Phase 2 Phase 3 Phase 4 Phase 5

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