"Build Effective Risk Management on Top of Your Trading Strategy" by Danielle Jiang, the Founder and CEO of Hedga Technology

Build Effective Risk Management
on Top of Your Trading Strategy
© 2016 Hedga Technology. All Rights Reserved.
Presented by
Danielle Jiang, FRM
QuantCon SG 2016

A Quant Fanatic and A Game Changer
Danielle Jiang, FRM
1
06 - 11
11 - 12
10
14 - 15
•  Bachelor of Science in Quantitative Finance, First Class Honours
•  Bachelor of Business Administration, Second Upper Class Honours
•  GTO - Capital Market – Business Analyst
•  Forex Exposure Management System
•  Senior Business Consultant
•  Commodity Repo Hedging, Receivable Finance Optimization
12 - 14
•  Senior Quantitative Analyst
•  Portfolio Risk Management, Portfolio Optimization, Performance Evaluation,
Back Testing, Stress Testing, Portfolio Simulation, Multi-Currency Hedging

The Smart Investment Decision Maker
About Hedga Technology
2
Strategy Research and Development
We develop quantitative strategies for institutions to subscribe.
Consulting - Portfolio and Risk Management
We access risk and optimise portfolios based on advanced quantitative
models.
Robot Advisor
China-focused robot advisor with customisation.

The Mystery of Risk
A Different View from Quants
Market Changes,
Your Risk Doesn’t
Build Risk Management

The Bias and The Truth
Why Risk Management?
1
“Don’t tell me how to manage risk, tell me how to make money.”
“Opportunity can’t stand alone without Risk.”

1
“Risk management is boring. Profitable Strategy is exciting.”
“Risk management can make my strategy perform better.”

1
“Risk management is important…
only when the market is bad.”
“Risk management is important all the time.
It’s nothing to do with the market condition.
It’s all about you.”

1
“Risk managers do not know how to make money.”
“Well…We survive through the storm.”

The Mystery
What is Risk?
2
Uncertainty
Fluctuation
Volatility
Unpredictable
Loss
Pain
Negative Impact
Disaster
Black Swan
Unknown
Instability
Over-LeveragedCrash
Drop
Holy Crap
Unexpected

A Recent Story
Do They Have the Same Risk?
3

A Recent Story
Do They Have the Same Risk?
3
Portfolio
No
YTD
Return
Mean
Return
Volatility
Downside
Volatility
Max
Drawdown
Sharpe
Ratio
Sortino
Ratio
Calmar
Ratio
1 3.86% 4.95% 2.61% 1.85% 1.88% 1.89 2.67 2.63
2 4.60% 5.88% 2.80% 1.97% 2.01% 2.10 2.98 2.92
3 5.08% 6.49% 3.10% 2.18% 2.27% 2.09 2.98 2.86
4 5.67% 7.22% 3.43% 2.41% 2.52% 2.10 2.99 2.86
5 6.25% 7.95% 3.76% 2.65% 2.78% 2.11 3.00 2.86
6 6.84% 8.68% 4.10% 2.88% 3.04% 2.12 3.01 2.86
7 7.42% 9.41% 4.43% 3.11% 3.39% 2.12 3.02 2.86
8 7.84% 9.92% 4.72% 3.32% 3.50% 2.10 2.99 2.83
9 8.17% 10.33% 5.00% 3.51% 3.68% 2.07 2.94 2.81
10 8.48% 10.72% 5.27% 3.70% 3.85% 2.03 2.90 2.78

Risk Analytics
How do we measure risk?
4
Volatility?
@ http://www.businessinsider.sg/

Risk Analytics
4
Drawdown?

Risk Analytics
4
VaR?
CVaR?

The Mystery of Risk
A Different View from Quants
Market Changes,
Your Risk Doesn’t

How about you?
The Three Views
1
View 1: Reward is everything.
20% a year is absolutely better than 10%.
View 2: Separate View on Risk and Reward.
We look at ratios: Sharpe, Sortino, Calmar…
We compare risk-adjusted returns.
View 3: Return only is everything.
Return, as a random variable

as a random variable
Look at the Return ONLY
2

Stochastic Dominance
How to compare?
3
First order Stochastic Dominance
For any outcome x, A gives at least as high a probability of
receiving at least x as does B. For some x, A gives a higher probability
of receiving at least x.
Second-order Stochastic Dominance
A has a higher or equal mean and is more predictable than B

How to compare?
3
First order Stochastic Dominance
Second-order Stochastic Dominance

How to compare?
3
How about A & C?
They have different styles!

How to compare?
3
They are similar in Style

The Steps
1
Step One:
Know Your
Strategy
Step Two:
Know Your
Preference
Step Three:
Know Your
Limit
Step Four:
Control
Trade Level
Risk

It Has Personality
Step One: Know Your Strategy
1
A systematic trading strategy follows certain sets of rules
1. Market Entry Rules
2. Market Exit Rules
Statistics from Backtesting ( Use One Unit of Position Size)
1. Basics: Win Rate, Average Profit, Average Loss
Win Rate * Average Profit + (1 - Win Rate)* Average Loss
2. Advance: Fit the simulated trades to a distribution

1 It Has Personality
0
Strategy 1Strategy 2

It Has Personality
1
Two Different Strategies
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Strategy 1 70% $50 -$30 $26
Strategy 2 30% $121.67 -$15 $26

It Has Personality
1
Assume Every Trade Signal is Independent
Make sure the probability for the worse case to happen is very
small.
e is a very small number,
n is the maximum losses you can have down the road in the
extreme case with a probability equals e

It Has Personality
1
(e = 10^-6)
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Worse Case
Losses
Strategy 1 70% $50 -$30 $26 12
Strategy 2 30% $121.67 -$15 $26 39

People stays rational until the real thing starts
Are you patient enough when consecutive losses happen?
Are you sticking to the rule? (Yes, your algorithm does)
Do you feel greedy when consecutive wins happen?
Can you tolerance many losses?
Do you doubt about your strategy when it seems not performing?
Why preference matters? Trading is a process.
Your Psychology and Emotion Matters
Step Two: Know Your Preference
2

Your Psychology and Emotion Matters
Step Two: Know Your Preference
2
Which One Do You Prefer?
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Strategy 1 70% $50 -$30 $26
Strategy 2 30% $121.67 -$15 $26

How much can you lose?
Step Three: Know Your Limit
3
Set a limit:
In worse case,
I can mostly lose 10% of my capital.

Calculate how much risk you will take for every signal
Step Four: Control Trade Level Risk
4
(e = 10^-6, RiskLimit = 10%, Capital = $100,000)
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Worse Case
Losses
Loss Per
Trade
Strategy 1 70% $50 -$30 $26 12 -$874
Strategy 2 30% $121.67 -$15 $26 39 -$270

Calculate how much risk you will take for every signal
Step Four: Control Trade Level Risk
4
Position Size is decided by Risk Management.
Derive the average position size: Strategy 1 = 29, Strategy 2 = 18
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Worse Case
Losses
Loss Per
Trade
Strategy 1 70% $50 -$30 $26 12 -$874
Strategy 2 30% $121.67 -$15 $26 39 -$270

Market Changes
Heteroskedasticity
1

Not You
Market Affects Your Strategy
2
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Worse Case
Losses
Loss Per
Trade
Strategy 1 70% $50 -$30 $26 12 -$874
Strategy 1* 70% $100 -$60 $52 12 -$874
You should decrease your position size by 50%

Case Study
A Mean Reverting Strategy
3
The General Idea:
1. Detect Abnormal Price Levels.
2. Go against the trend and take profit when the price is back to
mean.
3. Decide the stop loss price Level for the case of trend continuation

Case Study
3
Betting Same Lot Size

Case Study
3
Betting Different Lot Sizes, But Fix the Risk Exposure
The Average Lot Size here is the same as the previous case)

Case Study
3
Win Rate
Average
Profit
Average
Loss
Expected
Profit
Max
Drawdown
Profit
Factor
Fixed
Sizing
43.07% 2.81% 2.02% 0.0603% 32.05% 1.05
Floating
Sizing
43.07% 1.45% 0.97% 0.0723% 14.82% 1.13

In Hedga…
Extension
4
1. Not just “Average Loss”, but how the loss distributed.
2. Think in Conditional Distributions. (Things may not be independent)
— use GARCH
3. Combine model and reality:
New limit = Original limit - Realised loss

The Full Picture
Extension
4
1. Not just Average Loss, but how the loss distributed.
2. Think in Conditional Distributions, for time series.
3. Combine model and reality:
New limit = Original limit - Realised loss

Master Risk Management
The Ending
5
Think in probabilities
A risk manager knows the chance of losing money, and how much it can lose…
he/she also knows the opposite.
The risk of going long is the opportunity of going short.
But wait, you got to be consistent.
Market Changes, You Don’t.

Q&A

"Build Effective Risk Management on Top of Your Trading Strategy" by Danielle Jiang, the Founder and CEO of Hedga Technology

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