Systems TradingATAA Presentation 19th November 2014

Bruce Vanstone

Bruce Vanstone 2

This material is presented for educational purposes only.

I am not a financial advisor, and this material is not advice.

In many cases, the material represents ongoing research findings.

Disclaimer

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Dr. Bruce Vanstone◦ PhD in Computational Finance

Academic◦ Teach at Bond University (

http://apps.bond.edu.au/staff/profile.asp?s_id=257)◦ Publish internationally (search http://epublications.bond.edu.au)◦ Systems Trading Courses (www.vanstonetrading.com)

Trader◦ My own accounts◦ Porter Capital (www.portercapital.com.au)◦ Research and Investment (www.researchandinvestment.com)

Bruce Vanstone

Introduction

Firstly◦ Please feel free to shout out and ask questions as

we go along!

Secondly◦ If we have time, I have a few areas I would like to

cover Approach: Systems Trading, Quant, DNA approach Specific examples:

Stylized facts Making Indicators ‘better’ Money Management Q & A

Overview

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…just means defining rules to trade◦ Entry rules, exit rules, money management rules

and risk related rules

Has a number of distinct benefits!◦ Removes subjectivity,◦ makes skills “transferable”, ◦ allows for building a model

... what's often referred to as a Quant

Systems Trading

To ‘succeed’ in trading, I believe you need skills in:◦ IT

Coding Deployment

◦ Statistics How else do you know what you’re doing is

worthwhile? Are you improving what you’re doing?

◦ A “little” finance/econometrics Basic understanding of ‘stylized facts’ and how to test

for them

Quant

If you approach the markets with the idea that anything can (and probably will) happen then you should just stop trading

If you approach the markets with a sense that there is an underlying character to price movement then you are going in the right direction◦ DNA approach just means (initially) thinking about

‘character’ rather than ‘rules’ What is the ‘character’ of the data/system?... Not, what

are the ‘rules’... Beginners seem to get focused on ‘rules’

DNA approach

Its your key to actually learning something about the markets!◦ The markets do have an underlying character and its

important to understand what that looks like

This approach moves your thinking away from the infinite number of monkeys approach to one where you can reason about the types of systems/ideas that will work given consideration of your markets and timeframes◦ You need a framework for scientific thinking!

Why?

... are the Quant's (read: maths and stats) way of assessing that character and providing that framework

Stylized facts refers to empirical findings that are so consistent (for example, across a wide range of instruments, markets and time periods) that they are accepted as truths

Part 1 - Stylized Facts

There are quite a few!◦ We actually know quite a bit about market

character! ... So I thought that tonight it would be

better to focus on just one stylized fact, explain it, show how it is measured, and what it means, and then investigate its character in a trading system context

Stylized Facts

Autocorrelation !◦ Similar to the idea of normal correlation

We say X and Y are correlated if there is a measurable relationship between them Example: as X increases Y increases It also gives us a scale (-1 to +1) of the ‘strength’ of the

relationship Note this is not the same as saying X causes Y

(correlation doesn’t say that) Example: As trading prowess increases, wealth

increases!

◦ OK, back to autocorrelation

Tonight’s Stylized Fact

In autocorrelation, we still have the idea of a relationship between X and Y◦ HOWEVER, the important difference is that X and Y

are the same data, just shifted in time (forward or backward)

◦ Example: As X increases Y increases. X is the price history up till today. Y is the same data

as X but every observation is shifted backwards 1 day. Now we can do some testing about how previous

prices affect future prices... Or in this specific example, how yesterdays price movement affects todays.... Or how todays price movement affects tomorrows....

Autocorrelation

Remember the DNA approach... We are interested in learning about the character of the markets /stocks / instruments

The autocorrelation idea can be measured in many timeframes.

Lets imagine I measured it in monthly timeframe◦ You use returns, not prices for this

Autocorrelation

If we do this across the constituents of the ASX200 for the last 14 years, we would find there is positive autocorrelation in the results◦ The ‘average’ autocorrelation would be about

+0.0157 So what?

◦ Well... As X increases Y increases◦ The X and Y are returns ... The change in price...◦ Interpretation: positive (previous) changes are a

little more likely to lead to positive (future) changes than negative future changes

Autocorrelation

positive (previous) changes are a little more likely to lead to positive (future) changes than negative future changes

Positive previous changes means the price has been going up... What we are really saying is that stocks whose price have been going up in the past are more likely to continue to go up than stocks whose price hasn’t been going up

How would I investigate this?

To put it more accurately:◦ if X increases Y increases also implies that ◦ if X decreases Y also decreases

So a nice way to explore the character of this result would be to compare

A – stocks which have been going up historically, to

B – stocks that have been going down historically

Or...

Our expectation is that if we buy stocks that have been going up in the past, we should be much better off than those bottom-fishers that try to buy stocks that have been going down in the past

All we need is a credible definition of ‘going up’ and ‘going down’◦ For the analysis that follows, I used whether the

stock has hit a 200 day high (going up) or 200 day low (going down)

Expectations

Remember what I said earlier... Its not about the rules, its about defining the character of what you are looking for◦ Any sensible technical analysis definition of ‘going

up’ and ‘going down’ would have a similar outcome

◦ Its not about the rules! Its important to keep this in mind. We need rules to

actually produce the result, but once we confirm the result, we can then speculate about many systems and indicators and ways to trade that would exploit this result

Once you understand why, you can start on the how!

Important

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Equity Curve

Buy 200d High Sell 200d Low Buy 200d Low Sell 200d Low

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Performance: Comparison 1

Buy 200d High Sell 200d Low Buy 200d Low Sell 200d High

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Performance Comparison 2

Buy 200d High Sell 200d Low Buy 200d Low Sell 200d High

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Performance Comparison 3

Buy 200d High Sell 200d Low Buy 200d Low Sell 200d High

OK, so now we have confirmed our stylized fact◦ We now know a few more things about the

character of our market than we knew before◦ We can distill a few thoughts from this exercise...

Bottom-fishers aren’t going anywhere (and have little/no chance of long-term success)

Buying strength (in equity markets in this kind of timeframe) seems much more viable

What does this mean?

Once we know this, we can think about trading rules, setups, money management methods, etc that are consistent with this approach◦ So...

Trend trading.... Breakout trading... Pyramiding etc all have a place and a sensible use (within this kind of market and timeframe)

Some things don’t... How does this thinking relate to using stops?

Remember: Stylized facts are dependant on type of market and timeframe◦ In this case ASX200 equity and monthly timeframe

Further thoughts