Algorithmic trading - Overview. Views expressed herein are personal views of the author



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Algorithmic trading - Overview Views expressed herein are personal views of the author

Scenario 1 You are a fund manager and have Rs 500 Crores in hand (USD 83 million) to be invested. You have a highly talented research team which has selected 10 stock for you to invest. Question: How would you decide which broker to choose? And why? 2

Considerations for selection Reputation Market Pulse Efficiency of Bank office Research Execution? 3

Objectives (execution) Price optimization Avoid market disruptions Avoid un-necessary attention 4

Scenario 2 You have limited sum of money. You intend to take minimal risk. You observe there is always a difference in price between two exchanges for same security. Further, there is a difference between spot and futures prices. Question: What should you do? What risk do you face in doing so? 5

Leading corporations will be distinguished by their intelligent management of risk. Speed can also help manage risk! 6

Definition Algorithmic trading, also called automated trading, black-box trading, or algo trading, is the use of electronic platforms for entering trading orders with an algorithm which executes preprogrammed trading instructions accounting for a variety of variables such as timing, price, and volume Algorithmic trading is widely used by investment banks, pension funds, mutual funds, and other buy-side (investor-driven) institutional traders, to divide large trades into several smaller trades to manage market impact and risk. 7

Algorithmic Trading Strategies Algorithms can be broadly categorized into the following two categories Algorithms for Execution These programs execute stock market trades in such a manner best suited for purchase or sale of positions Two of the common execution algorithms are the VWAP & TWAP Trading Algorithms These algorithms actively try to make money. They track historical relationships between securities, assets or markets and then exploit minor deviations for quick gains. Examples: Arbitrage, bid-offer & Technical analysis Algorithms 8

TWAP Time Weighted Average Price This strategy simply breaks up a large order into equal parts and then dribbles buy or sell orders into the market evenly over the trading session This is also referred to as "iceberging This ensures that the price at which the investor buys or sells is not distorted by momentary blips in the market 9

VWAP Volume Weighted Average Price Calculated by weighting a stock s price quotes through the trading session with volumes traded at each price Algorithm s objective is to execute the order at a price that is as close as possible to this weighted average If the price of a buy trade is lower than the VWAP, it is a good trade and bad if the price is higher than the VWAP There can be variants in this algo 10

Arbitrage Algorithms These algorithms earn a spread from trading on anomalies between securities, trading venues or asset classes For example, simple arbitrage algorithms may earn a spread by buying a stock at Rs. X on the BSE and selling it at Rs. X+0.10 on the NSE The transactions have to be executed at rapid sucession 11

Technical analysis These are commonly used by technical analysts to identify a reversal in trends They then piggyback on it at an early stage to benefit from the momentum Track technical indicators such as the 50 or 200-day moving averages or relative strength index, to bet on stocks on the verge of breaking out or breaking down 12

High Frequency Trading Programs initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe Highly quantitative Positions are held for seconds Sensitive to latency and processing speed May involve Co-Location to save time Mostly employed by large firms Examples: Market making, News based trading 13

Events Black Monday 1987 October 19, 1987 markets fell 22%! beginning of circuit mechanism 2010 Flash crash DJIA dropped 9% and recovered 6% in fifteen minutes Insider trading (Sep 2013) directional trades within 2 milliseconds after Fed announcements in Chicago futures markets. Speed of light would take 7 milliseconds to reach Chicago. 14

Controls & Risk Management Pre-execution checks (order level checks) Price filters Volume filters Circuit filters Market volume checks Maximum value of orders Automated execution checks (avoid loops) Realtime checks 15

Controls & Risk Management Perform a thorough UAT of algos before implementation Restrict access to systems. Algo parameters and limits should only be changed by uninterested groups with management approval Need to balance false alerts limits should be balances 16

Indian environment Indian regulators require: Mock testing Auditor certification Periodic audits (change management, online risk management, risk parameters, data feeds) 17

There may be just one thing riskier than too much risk Too little 18

19 Thank you