Impact of Algorithmic TradingGroup 5

What is Algorithmic Trading?Definition, characteristics and evolution

Overview

How is it done? Various AT strategies, about High Frequency Trading

How does AT impact the markets?Analysis of stock market volatilities, increase in liquidity

Expert opinion on ATInterview with Mr. Sanket Kapse (D E Shaw & Co.)

Opinion

Definition

Strategies

Impact

What is Algorithmic Trading?

• Trading conducted via Electronic Platforms• Buy or sell order of a defined quantity into a

quantitative model• Timing and size of the order are automatically

generated• Decisions are based on goals specified by the

parameters and constraints of the algorithm• Little or no human intervention

Evolution and Background

• Computerization of order flow began in the early 1970s

• Landmark: introduction of the NYSE’s “designated order turnaround” system (DOT)

• DOT routed orders electronically to the proper trading post, which executed them manually

• Program trading became widely used in S&P500 equity and futures markets by 1980s

• By 2009, High Frequency Trading firms accounted for as much as 73% of all US equity trading volume

EXECUTION ALGORITHMS

These programs execute stock market trades in such a manner that the prices aren’t influenced by momentary swings in the market.

Two of the common execution algorithms are the VWAP & TWAP

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, Scalping &Trend Following Algorithms

ALPHA GENERATING ALGORITHMS

Algorithmic Trading StrategiesAlgorithms can be broadly categorized into the following two “families”

VWAP

• 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

Volume Weighted Average Price

TWAP

• 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

Time Weighted Average Price

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. 100 on the BSE and selling it at Rs. 100.50 on the NSE

• The transactions must occur simultaneously to avoid exposure to market risk

Trend Following

• 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

High Frequency Trading

Special class of AT in which computers 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 only for brief periods• NO investment position at the day’s end• Sensitive to latency and processing speed• Mostly employed by large firms

Analyzing the Impact

• Pros: Increases Liquidity Leads to better price discovery

• Cons: Leads to market Volatility Puts the less privileged traders at a disadvantage

Increase in LiquidityAnalysis of 2002-2006 data from S&P500

Source: The Journal of Finance

Increase in LiquidityAnalysis of 2002-2006 data from S&P500

Source: The Journal of Finance

• 1987: was caused in part by dynamic portfolio insurance (a way of protecting losses in the market)

• 2010: The “Flash Crash” occurred as a result of HF Traders rapidly changing positions in a market void of Fundamental Buyers

• 2012: Knight Capital’s trading system flooded the market with erroneous trades

Market Volatility

Market Volatility

2010: Flash Crash

2012: Knight Capital

Case

1987: Stock

Market Crash

Expert View

• Mr. Sanket Kapse works as Finance and Operations Generalist at DE Shaw and Company where he takes care of the back office functions for the AT Portfolio

• According to him, AT is just a way of trading which is faster and smarter than how human traders can trade

• He believes that AT, being inherently expensive to implement, puts less privileged traders at a disadvantage

• However, he also agrees that AT, especially HFT leads to more liquidity and better price discovery

Interview with Mr. Sanket Kapse (DE Shaw & Co.)

THANK YOU