Download Intra-day De-Mark Plus Order-Flow Indicator (Indempofi)

Intra-day De-Mark Plus Order-Flow Indicator
(Indempofi)
QuantCon Singapore 2016
Christopher Ting
http://mysmu.edu.sg/faculty/christophert/
k [email protected]
Lee Kong Chian School of Business
Singapore Management University
Novermber 11, 2016
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Quantitative Finance, SMU
November 11, 2016
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Table of Contents
1
Introduction
2
Tom DeMark’s Indicators
3
Order Flow
4
Back-Testing
5
Conclusions
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Introduction
Overview
Trading
Investment
Systematic
Discretionary
Statistical Arbitrage
Back-Testing
Money/Risk Management
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Introduction
Industry Trend
Trader
Algo
X Agency
Emotional
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X Principal
Quantitative Finance, SMU
Machine
Operational
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Introduction
Order Placement Strategies
Source: Domowitz, I. and Yegerman, H. (2011). Sample Period: Q4 2009 to Q4 2010 Q4
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Introduction
Aspects of An Algo
Data
Tests
Algorithm
Commission
KPI
Coding
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Introduction
Types of Trading Strategy
Risk
Mgmt
Hedging
Momentum
Spread
Neutral
Factors
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Trading
Strategy
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Directional
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Tom DeMark’s Indicators
Tom DeMark (TD)
Main Feature
• Market timing based
solely on prices
• Trend exhaustion
• Spotting market high
and market low
Source: Tom Demark May 2016
Basic Building Block
Closing price Pt today versus
the closing price 4 days earlier
Pt−4
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“Conventional indicators are
typically trend followers whereas
DeMark is designed specifically
to anticipate trend reversals.”
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Tom DeMark’s Indicators
Intra-Day TD Sequential: TD Setup (Buy)
Buy Setup: consecutive Pt < Pt−4 nine times
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Tom DeMark’s Indicators
Intra-Day TD Sequential: TD Setup (Sell)
Sell Setup: consecutive Pt > Pt−4 nine times
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Order Flow
Limit-Order Books
6E Mar16
Bid Qty Price Ask Qty
10907
54
10906
64
10905
49
10904
45
10903
10
8
10902
62
10901
46
10900
55
10899
38
10898
6E Jun16
Bid Qty Price Ask Qty
10938
12
10937
12
10936
14
10935
7
10934
1
1
10931
15
10930
14
10929
12
10928
52
10927
The back and front contracts of EUR/USD futures on December 17, 2015 7 PM EST.
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November 11, 2016
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Order Flow
Date
Time
Type
Price
Contracts
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
2016-02-08
9:45:55
9:45:55
9:45:55
9:45:55
9:45:55
9:45:55
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
9:45:56
B
A
T
A
T
A
B
A
B
A
B
A
T
T
A
B
A
B
A
B
A
T
16755
16760
16760
16760
16755
16760
16755
16760
16755
16760
16755
16760
16760
16755
16760
16755
16760
16755
16760
16755
16760
16760
210
144
1
143
1
150
209
149
219
149
213
149
3
2
146
211
146
212
146
212
146
2
Sign
Signed Volume
1
1
-1
-1
1
-1
3
-2
1
2
Data of Small Nikkei 16H Futures from Bloomberg
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Order Flow
Features of Intra-Day Trading
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Bid-Ask
Spread
buy at the ask and sell to the bid
Slippage
market depth, price impact
Seasonality
market “rush minutes”
Trading
Hours
curtailed time horizon
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Order Flow
Features of Intra-Day Trading
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Survivorship
no bias
Corporate
action
no direct impact
Macroeconomic
news
breakdown of TD?
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(cont’d)
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Order Flow
FBI’s Announcement Effect on 6J
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Order Flow
FBI’s Announcement Effect on ES
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Back-Testing
Performance Measures for Back-Testing
Winning Probability
A :=
number of positive P&L
number of round-trip trades
Reward-to-Risk Ratio
B :=
average gain
average loss
Trading Sharpe Ratio
C :=
Christopher Ting
average P&L
standard deviation of P&L
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Back-Testing
Performance Measures for Back-Testing
(cont’d)
t statistic
• Average P&L (after costs) from n trades (e.g. n = 81)
• Standard deviation of P&L (after costs)
• Formula for t statistic
t=
√
n×
average P&L
standard deviation of P&L
• If |t| is large (e.g. |t| > 2), then the average P&L is said to be
statistically significant.
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Back-Testing
Parameter Robustness
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Back-Testing
Data Partition
Past performance is not indicative of future performance.
In-Sample
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Out-ofSample
Paper
Trading
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Commission
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Conclusions
Concluding Remarks
• Applying TD in intraday trading requires the order flow threshold to
increase the probability of winning and the t statistics of P&L.
• Intra-day DeMark plus order flow indicator (Indempofi) has two
parameters: holding-period and order-flow threshold.
• It is important to separate in-sample data for “training” and
out-of-sample data for more realistic expectation of Indempofi’s
performance.
• Cross-sectional scaling rather than position scaling is less risky:
portfolio of indempofi (HPi , OFTi ).
• t stat is useful to gauge the effectiveness of an algo on the rolling
window basis.
• Use t statistics as the “weights” for allocating capitals to indempofi’s.
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