utrade forex summit (19 oct) part 3 · 2019. 10. 22. · pullback / scalping strategy (not every...

Gary YangGary Yang

How How Systematic Trading Systematic Trading

Can Improve Your TradingCan Improve Your Trading

So why do you trade?

Another source of income?

Mid career switch?

Fulltime trading?Retirement job?

Financial independence?

To become a To become a

consistently consistently

profitable Trader!profitable Trader!

Percentages of profitable and losing traders at major brokerages, Source: FM Intelligence

Over-risk (Trading Size)

Jumping from System to System

Poor Capitalization

Emotional Trading - Refuse to Cut Loss

Jumping into Trades (FOMO)

No Trading Plan

Following the Herd

Over-risk (Trading Size)

Jumping from System to System

Poor Capitalization

Emotional Trading - Refuse to Cut Loss

Jumping into Trades (FOMO)

No Trading Plan

Following the Herd

23

22

6

2

40

2

0

Over-risk (Trading Size)

Jumping from System to System

Poor Capitalization

Emotional Trading - Refuse to Cut Loss

Jumping into Trades (FOMO)

No Trading Plan

Following the Herd

23

22

6

2

40

2

0

Jumping from System to System

• Weak Risk Management

• Lack of long-term perspective

• No Rules

Over-risk (Trading Size)

Jumping into Trades (FOMO)22

23

40

• System that does not work

• Strategy that does not fit their personality type

• Lack of confident in the strategy

• Cannot deal with Losing streak

• Weak Risk Management

• Lack of long-term perspective

• Unrealistic Expectations

Systematic Approach to Trading.

Systematic Approach to Trading.

1. Test a strategy I found online2. Develop and improve on the strategy3. Develop understanding via statistics from backtesting

Jan 2008 Dec 2014 Dec 2018

In Sample (7 Years) Out of Sample (4 Years)

Total Data Available for Testing

Before we even start with the backtesting, we need to divide the entire pool of data available for out-of-sample

and in-sample testing. This process is also called ‘Walk Forward Optimising’

Original RulesOriginal RulesOriginal RulesOriginal Rules

RULES FOR LONG SET UP

1. Close Greater than 100-EMA

2. Close less than 5 EMA

3. 3 Lower Lows

4. Pend a Limit order below 3rd lower lows based on 0.5 times the 10 ATR

5. Exit if close is higher than entry price

6. SL based on 10% of balance

Rules for Short set up are the opposite of Long

Original RulesOriginal RulesOriginal RulesOriginal Rules

1111

2222

3333

Pend Pend Pend Pend

Buy Limit orderBuy Limit orderBuy Limit orderBuy Limit order

ATR Value: 17 pipsATR Value: 17 pipsATR Value: 17 pipsATR Value: 17 pips

5EMA5EMA5EMA5EMA 100EMA100EMA100EMA100EMA

In Sample testing 1 - Base on Original Rules

Jan 2008 to Dec 2014

Common sense revisions based on observation of 1Common sense revisions based on observation of 1Common sense revisions based on observation of 1Common sense revisions based on observation of 1stststst backtestbacktestbacktestbacktest

1.1.1.1. Close Greater than 200 SMAClose Greater than 200 SMAClose Greater than 200 SMAClose Greater than 200 SMA

2.2.2.2. Remove FAST MARemove FAST MARemove FAST MARemove FAST MA

3. 3 lower lows

4. Pend a Limit order below 3rd lower lows based

on 0.5 times the 10 ATR

5. Exit if close is higher than entry price

6. SL based on 5% of balance

1. Close Greater than 100 EMA

2. Close less than 5 EMA

3. 3 Lower Lows

4. Pend a Limit order below 3rd lower lows

based on 0.5 times the 10 ATR

5. Exit if close is higher than entry price

6. SL based on 10% of balance

OriginalOriginalOriginalOriginal Revised Revised Revised Revised

11112222

3333

Pend Pend Pend Pend

Buy Limit orderBuy Limit orderBuy Limit orderBuy Limit order

200SMA200SMA200SMA200SMA

ATR Value: 17 pipsATR Value: 17 pipsATR Value: 17 pipsATR Value: 17 pips

In Sample Testing 2

Jan 2008 to Dec 2014

In-sample Testing 1 In-sample Testing 2

Total Net Profits - $135.92 $2,023.83

Max DD 23.27% 10.16%

Profit Factor 0.99 1.34

No. of Trades 549 352

In-sample Testing 1

In-sample Testing 2

Next Test:

To find the optimal values for:

1)ATR Period and

2)Percentage of ATR for entry order

o ATR Period

Original ATR Value: 10 Periods

ATR Period Value To Test: 3 to 9 period / Step 1 (3,4,5..9 etc)

o Percentage of ATR for entry order

Original Percentage of ATR value: 0.5

To Test: 0.5 to 1.0 / Step 0.1 (e.g. 0.5,0.6,..1.0 etc)

11112222

3333

ATR Period: to test 3,4,5,6,7,8,9

(which ATR period is the most profitable settings for this strategy?)

0.5, 0.6, 0.7, 0.8, 0.9, 1.0 x ATR

((((Which multiple of ATR is best value for pending order?)

Highest ProfitsCluster of Above Average Profits

Set 1: ATR 4 Period / 0.9

Set2: ATR 6 Period / 0.9

Revised Rules for in-Sample Testing 3 and 4

1. Closed above 200 SMA

2. 3 lower lows

3. Pend a Limit order below 3rd lower lows based on

(Set 1) 4 ATR / 0.9 times ATR

and

(Set 2) 6 ATR / 0.9 times ATR

In Sample Testing 3 (Set 1: ATR 4, 0.9)

Jan 2008 to Dec 2014

In Sample Testing 4 (Set 2: ATR 6, 0.9)

Jan 2008 to Dec 2014

In-sample

Testing 1

In-sample

Testing 2

In-sample

Testing 3 (Set 1)

In-sample

Testing 4 (set 2)

Total Net Profits - $135.92 $2,023.83 3,727.12 3,877.14

Max DD 23.27% 10.16% 9.89% 10.09%

Profit Factor 0.99 1.34 2.29 2.33

No. of trades 549 352 202 204

In-sample Testing 1

In-sample Testing 2

In-sample Testing 3 (Set 1)

Jan 2008 Dec 2014 Dec 2018

In Sample (7 Years) Out of Sample (4 Years)

Total Data Available for Testing

NEXT

Out of Sample Testing (Set 1: ATR 4 period / 0.9)

Jan 2015 to Dec 2018

Out of Sample

In Sample

Combined Testing (Set 1: ATR 4 period / 0.9)

Jan 2008 to Dec 2018

Total Net Profits 5,425.42

Max DD 9.89

Profit Factor 2.78

No. of Trades 277

Winning Percentage 95.31%

Shapre Ratio 0.1

Stagnation in days / % 939 / 23.39%

� 9/132 losing months

� 16/132 flat months

� 2/11 losing years

� 2 losing months in 2008, 2011, 2012

� No losing months in 2009, 2010,

2013, 2014, 2015

Additional Bonus of SystematicSystematic Trading

Set 1: ATR 4 Period / 0.9 Set2: ATR 6 Period / 0.9

Set 3: ATR 3 Period / 0.8

Mini Portfolio Based on 3 best settings using the same strategy?

Comparing results between Set 1 and Set 2Comparing results between Set 2 and Set 3Comparing results between Set 1 and Set 3

Set 1 Set 2 Set 3

Set 1 0.88 0.8

Set 2 0.88 0.71

Set3 0.8 0.71

Moderate: < 0.4

Moderate High: < 0.4 – 0.7

High: < 0.7 – 1.0

CONCLUSION

Out of Sample

In Sample

Long Set Up

1.Closed above 200 SMA

2.3 lower lows

3.Pend a Limit order below 3rd lower lows based on

•(Set 1) 4 ATR / 0.9 times ATR

•(Set 2) 6 ATR / 0.9 times ATR

4.Exit if close is higher than entry price

5.SL based on 5% of balance

Rules for Short set up are the opposite of Long

Stress Testing for Trading Strategy Robustness

•Data Re-sampling

•Randomly missing “x” percentage of trades

Jan 2004 Dec 2014 Dec 2018

In Sample (7 Years) Out of Sample

(4 Years)

Total Data Available for Testing

Forward Testing

� Pullback / scalping strategy (not every broker supports scalping)

� Developed a strategy that’s likely to work in future

� High win rates with many small profits

� Inverted risk : reward (majority wins with huge occasional losses)

� Infrequent trading opportunities

• Does this strategy fits your personality?

• Is this strategy effective?

• More likely stick to this strategy in a drawdown?

• More likely to stick to the same risk?

• Less likely to jump into any random trade?

Backtesting is a key component of effective trading system development. It is accomplished by reconstructing, with historical data, trades that would have occurred in the past using rules defined by a given strategy.

Backtesting is NOT the Holy Grail, but it provides an

objective way in using past statistics to gauge the

effectiveness of the strategy.

Make Sound Trading Decisions, Backed by Data.

Not Gut Feel. Not Baseless Assumptions. Not Hearsay.

“Victorious warriors win first and then go

to war, while defeated warriors go to war

first and then seek to win.” – Sun Tze

Thank you.Make Trading Decisions Based On Data.