Paradigms of trading strategies formulation

Paradigms of Trading Strategy Formulation
How and Why of A Trading Strategy Design
By
Shaurya Chandra
Faculty QuantInsti
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Housekeeping
• Headset Requirement:
• Q&A: Question/answer session will happen after the
webinar.
• Web Recordings: Webinar's recordings will be mailed
to you in 3-4 working days.

Some Hard Truth about Trading..
• You might get some
stock trading tip here
& there…...
• But, it takes a real hard
work to make profit
consistently!!

Steps in Trading Strategy Formulation
Hypothesis Formulation
Back-Testing & Optimization
Coding Strategy in Trading Platform
Simulator Testing
Trading Live in the market

Designing a Trading Strategy
Choose your game!! Markets have place for everyone…
• Question one needs to answer, what type of
strategy one wants to follow??
– Trend Following Trading Strategy??
– Arbitraging??
– Mean reversion??
• Statistical Arbitrage
– Market Making??
• Other key areas:
– Stop Loss and Profit taking
– Sufficient Sample Trades
• Statistics helps to formulate your hypothesis

Ok, hypothesis is formed, so what??
• Need to check-
– Estimation of Past performance for the designed
hypothesis!
– Result/ Performance stats should back your
hypothesis
– Investors needs to be shown numbers to validate the
substance in the analysis.
• Hence, Back-testing is important…
• Back-testing is process by which trader subjects
the market to the designed trading rules to check
the performance in past

Process in Back-Testing
• Choose a detailed historical data with
following characteristic:
– Sufficient data number of data points so as to
create sufficient sample of trades (at-least 100+
trades)
– Should be in sufficient details with various market
scenario being handled like (bullish, bearish etc..)
• Make provision for brokerage and slippage
cost
• Beware of over fittings!!

Forward Testing & Optimization
• Suppose, a strategy deploys N- day Moving Average for
the signal generation, now the question trader face is:
What should be the value of N??
• Following process in involved:
– Divide the data into 2 parts. Say we call them, A & B, 80%
and 20% respectively, in terms of number of data points
– Apply Back-testing and optimize the value of N for some
parameter on dataset A. Arrive at value of N say ‘n1’
– Now, Back-test on dataset B with the value ‘n1’
– If the results parameter is same as that of dataset A, keep
the value of n1, else try with next best.

Some typical Parameters to be estimated…
• Total Returns (CAGR)
• Hit Ratio (i.e. Success Ratio)
• Average Profit per Trade
• Average Loss Per Trade
• Maximum Drawdown
• Maximum Consecutive losses
• Volatility of Returns
• Sharpe Ratio : Excess returns (over risk free rate)
versus Volatility of returns

Trade-offs in the market:
“Choose what pain you can live with, rather choosing what
gain you want to make”
• Returns vs Risk
– How high the risk you want to take?
– Is low risk arbitrage for you or the high risk trend following is
your cup of tea?
• Hit Ratio Vs Average Returns Per trade
– Can you handle the string of losses before you see the light of
dawn?
• Quick Returns vs Maximum Drawdown
– Do you want big returns (by leveraging your position) and
susceptible to big draw downs, or smooth curve of returns??

A sample strategy
• Sample Hypothesis: If the daily closing price
closes above 60-day moving average, then, it’s
a buy and if it closes below, then the trade is
Sell.
• Back-testing particulars:
– Daily Nifty Data for 3-Jan-2000 to 31-Dec-2010
– Almost all kind of market scenario considered.

Sample Results
Total Returns 279.0%
Average Annual Returns 25%
Total Number of Positive trades 33
Total Number of Negative trades 69
Hit Ratio 32%
Average Profitable Trade 12.8%
Average Loss Making Trade -4.4%
Avg profit/Avg Loss Making 2.94
Volatility of Returns 11.4%

Quick Returns vs Drawdown
Equity Curve with Leverage 1- Maximum Drawdown -21%

Why you want to Trade?
• Want to prove right or you want to make
money?
• Getting the right tool and skill set is most
important!!
• One Mantra and only one key to success in
Trading :- “Improve Everyday”
• Diligently improve, improve on your mistake,
commit new ones and improve on them.

E-PAT course structure
Core Content
Statistics and
Econometrics
Financial Computing &
Technology
Algorithmic &
Quantitative Trading

E-PAT Course Structure: Statistics and
Econometrics
Core Content
Statistics and Econometrics
Technology
Algorithmic & Quantitative
Trading
Basic Statistics
 Probability and Distribution
 Statistical Inference
 Linear Regression
Advanced Statistics
 Correlation vs. Co-integration
 ARIMA, ARCH-GARCH Models
 Multiple Regression
Time Series Analysis
 Stochastic Math
 Causality
 Forecasting

E-PAT Course Structure: Financial Computing
& Technology
Core Content
Technology
Trading
Programming
 Intro to Programming Language(s)
 Programming on Algorithmic
Trading Platforms
 Linear Regression
Technology for Algorithmic
Trading
 System Architecture
 Understanding an Algorithmic
Trading Platform
 Handling HFT Data
Statistical Tools
 Excel & VBA
 Financial Modeling using R
 Using R & Excel for Back-testing

E-PAT Course Structure: Financial Computing
Core Content
& Technology
Technology
Trading
Trading Strategies
 Statistical Arbitrage
 Market Making Strategies
 Execution Strategies
 Forecasting & AI Based Strategies
 Machine readable News based
 Trend following Strategies
Derivatives & Market
Microstructure
 Option Pricing Model
 Time Structure of Volatility
 Dispersion Trading
 Volatility Forecasting & Interpretations
 Managing Risk using Greeks
 Position Analysis
 Order Book Dynamics
 Market Microstructure
Managing Algo Operations
 Hardware & Network
 Regulatory Framework
 Exchange Infrastructure & Financial
Planning (Costing)
 Handling Risk Management in
Automated systems

Program Delivery
• Weekends only program
– 3 hrs sessions on Saturday & Sunday both days
– 4 months long program
– Practical Oriented
– 100 contact hours including practical sessions
• Convenience – Conducted online
• Open Source
• Virtual Classroom integration
• Student Portal

Going beyond the curriculum
• Faculty supervision
• Placement assistance

Important dates
Date Event Venue
5th December, 2013
Last date for Early bird registration for
18th batch of EPAT*
Online
4th January, 2014 Classes for EPAT batch 18th start Online & offline
http://www.quantinsti.com/importantdates.html
*Scholarships: http://www.quantinsti.com/scholarships.html

Thanks!
THANK YOU
Contact us at:
Email: contact@quantinsti.com or sales@quantinsti.com
Phone: +91-22-61691400, +91-9920448877

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