paradigms of trading strategies formulation

© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Paradigms of Trading Strategy FormulationHow and Why of A Trading Strategy Design

By

Shaurya Chandra

Faculty QuantInsti


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

Back-Testing & Optimization

Hypothesis Formulation

Coding Strategy in Trading Platform

Trading Live in the market

Simulator Testing


Designing a Trading Strategy

• 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

Choose your game!! Markets have place for everyone…


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:

• 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??

“Choose what pain you can live with, rather choosing what gain you want to make”


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




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


E-PAT Course Structure: Financial Computing & Technology

Core Content




Programming

Technology for Algorithmic Trading

Statistical Tools

Intro to Programming Language(s) Programming on Algorithmic

Trading Platforms Linear Regression

System Architecture Understanding an Algorithmic

Trading Platform Handling HFT Data

Excel & VBA Financial Modeling using R Using R & Excel for Back-testing


Core Content




Trading Strategies

Derivatives & Market Microstructure

Managing Algo Operations

Statistical Arbitrage Market Making Strategies Execution Strategies Forecasting & AI Based Strategies Machine readable News based Trend following Strategies

Option Pricing Model Time Structure of Volatility Dispersion Trading Volatility Forecasting & Interpretations Managing Risk using Greeks Position Analysis Order Book Dynamics Market Microstructure

Hardware & Network Regulatory Framework Exchange Infrastructure & Financial

Planning (Costing) Handling Risk Management in

Automated systems

E-PAT Course Structure: Financial Computing & Technology


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, 2013Last 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

http://www.quantinsti.com/importantdates.html

http://www.quantinsti.com/scholarships.html


Thanks!

THANK YOU

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paradigms of trading strategies formulation

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