QuantTrendSeriesSLV20150512

Page | 1 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
MCI (P) 020/11/2014
Ref. No.: US2015_0014
QUANT ideas: Trend-following series
Optimizing an N-day breakout on the SLV
GLOBAL | EQUITIES| QUANTITATIVE ANALYSIS
6 April 2015
On the back of our previous report on GLD, Quant ideas: Optimizing an N-day breakout on
the GLD, dated 13 Apr 2015, we continue our series and backtest the n-day breakout
strategy on SLV.
Main Observations:
 SLV has increased shorter-term volatility, and intermediate moves tend to stretch a
further percentage as compared to the GLD. Most short-term parameters (<10) are
loss-making. But it is worth our while to identify the major monthly movements.
 At transaction costs per trade at 0.18%, the optimized parameters would have
resulted in a 16.9% gain without leverage.
 The strategy is unattractive on shorter-term parameters (<10) due to volatility.
 However, being able to identify monthly movements can be rewarding.
 Investors are cautioned that profit/loss swings are higher than the GLD strategy.
 Bottoming and flattening price markets tend to cause losses with this strategy
 We think that in the next year, the SLV will be in a bottoming process. This strategy
is not as effective in such conditions, hence, we recommend applying this strategy
after the current consolidation is complete.
Strategy: 18 Day High with 14 Day Low (mark-to-market results)
Trading
Results (Geo)
Long Gold
Results yoy
Number of
Trades Average ATR
SD of Daily
Returns No.of Gaps
No.of Traded
Gaps
2006 - 3.58% - 7.25% 6 0.414 0.026 82 4
2007 - 27.76% + 17.03% 11 0.315 0.016 116 8
2008 + 69.96% - 26.22% 6 0.584 0.034 120 5
2009 + 38.99% + 44.95% 7 0.450 0.021 131 3
2010 - 17.39% + 75.16% 11 0.524 0.019 113 11
2011 + 39.59% - 10.14% 9 1.291 0.030 142 5
2012 + 11.22% + 1.87% 10 0.735 0.017 106 9
2013 + 47.88% - 37.47% 6 0.547 0.021 128 4
2014 + 0.36% - 21.68% 8 0.323 0.014 121 3
2015 - 14.53% + 4.37% 3 0.366 0.017 21 3
Total + 149.79% + 15.93% Geometric gain
Annual + 16.93% + 1.68% Geometric gain
Commissions: 0.18%, Slippage: 0.05
Source: PSR
Kenneth Koh (+65 6531 1791)
kennethkohwk@phillip.com.sg

N-day breakout strategy results
1 May 2006 - 10 Apr 2015
Results Table with gaps (0.18 % comissions, 0.05 slippage per trade) Days High
15 16 17 18 19 20 21 22 23 24 25
9 7.4% 8.2% 9.7% 14.0% 10.5% 10.3% 7.5% 5.2% 2.7% 6.0% 4.8%
10 2.0% 2.9% 4.0% 7.1% 4.6% 4.4% 2.4% 0.7% -1.1% 1.8% 0.9%
11 0.5% 3.3% 5.7% 9.2% 6.4% 3.0% 1.1% -0.4% -2.1% 1.1% 0.4%
12 3.9% 7.5% 4.2% 7.4% 4.8% 1.7% 0.0% -1.3% -2.9% -2.0% -2.2%
13 9.4% 14.3% 9.8% 15.7% 11.9% 7.4% 5.1% 3.1% 0.9% 2.6% 2.3%
14 10.4% 15.5% 10.7% 16.9% 13.0% 8.3% 6.3% 4.1% 1.8% 5.1% 4.8%
15 7.5% 12.1% 7.9% 13.3% 9.8% 5.7% 4.1% 2.2% 0.1% 3.2% 2.9%
16 4.6% 10.4% 6.5% 11.6% 8.3% 4.6% 3.3% 1.5% -0.5% 2.5% 2.2%
17 -2.1% 1.8% 0.3% 3.6% 1.4% -1.0% -1.9% -3.1% -4.3% -2.4% -2.0%
18 -1.9% 3.5% 1.8% 5.5% 3.1% 0.3% -0.7% -2.0% -3.5% -0.9% -0.5%
19 -3.0% 1.8% 0.2% 3.5% 1.4% -1.1% -2.0% -3.1% -4.4% -2.0% -1.5%
20 1.5% 8.8% 6.6% 11.8% 8.4% 4.6% 5.2% 3.2% 1.2% 2.2% 3.1%
Days low
1 Jan 2006 - 10 Apr 2015
Results Table with gaps (0.18% commissions, 0.05USD slippage per trade) Days High
1 2 3 4 5 6 7 8 9 10 15
1 -11.3% -11.3% -11.3% -11.3% -11.2% -11.1% -10.8% -10.6% -10.5% -10.4% -9.8%
2 -11.3% -11.2% -11.2% -11.2% -11.1% -11.0% -10.6% -10.6% -10.5% -10.4% -9.9%
3 -11.2% -11.2% -11.2% -11.2% -11.0% -10.9% -10.2% -10.2% -10.1% -9.8% -9.2%
4 -11.1% -11.1% -11.0% -11.0% -10.9% -10.7% -10.1% -10.2% -9.9% -9.7% -8.7%
5 -10.9% -10.6% -10.5% -10.5% -10.2% -10.2% -9.2% -9.1% -9.3% -8.9% -6.4%
6 -10.7% -10.2% -10.4% -10.3% -10.3% -10.2% -8.9% -8.8% -8.8% -8.4% -5.5%
7 -10.4% -9.2% -9.7% -9.5% -9.5% -9.4% -7.4% -7.2% -7.0% -7.4% -4.3%
8 -9.3% -7.3% -7.9% -7.7% -7.4% -7.5% -3.6% -2.6% -3.7% -5.0% -0.3%
9 -8.8% -6.8% -7.4% -6.9% -6.4% -6.3% -1.5% 0.2% -1.7% -2.9% 7.4%
10 -8.0% -5.2% -6.3% -6.4% -6.5% -6.1% -1.0% 0.7% -1.1% -2.3% 2.0%
15 -3.1% -0.4% -2.3% 0.1% 0.0% -1.2% 5.4% 7.2% 3.2% 4.0% 7.5%
Days low
Source: PSR
Because of the increased volatility of SLV, it is more challenging to be profitable using a simple
trend following system. Shorter parameters can led to heavy losses. However, the successful
parameter window (17-19, 13-16) corroborates that it can be rewarding if one can capture
longer movements without being whipsawed out.
Sweet Spot

Quant section
Technical Analysis: It helps, if used correctly.
There is a growing body of evidence that technical analysis, when used appropriately, and not
in isolation, can increase profit performance. For instance, during high-sentiment periods,
hedge funds using technical analysis exhibit higher returns, lower risk, and superior market-
timing ability than those non users [Smith, Wang, Wang and Zychowicz (2014)]. Additionally,
Han, Yang and Zhou (2011), show that an application of an appropriate trend following
strategy of technical analysis to certain high volatility portfolios often outperform buy-and-
hold strategies substantially.
Unfortunately, there is much subjectivity in the world of technical analysis. What can seem
like a reversal pattern could turn into a continuation pattern, a posteriori. Subjective TA, at
first blush, seem to convey knowledge. However, when examined critically, lacks in
knowledge precision.
The purpose for this backtesting series is to help clients to bridge the subjectivity gap of
technical analysis to get closer to justified true belief rooted in objectivity, which is a useful
definition of “knowledge”.
Methodology: N-day breakout – a trend following strategy
 At every current daily price, let Days High be the maximum high of prior n- Days Low
be the minimum low of prior m-days. Define n and m.
 When today’s price moves higher than Days High within the day, buy/long the asset
immediately. If price gaps above Days High at the start of the day, buy/long the asset
immediate at opening.
 When today’s price moves lower than Days Low within the day, sell/short the asset
immediately. If price gaps below Days Low at the start of the day, sell/short the asset
immediately at opening.
5
7
9
11
13
15
17
19
21
23
5
7
9
11
13
15
17
19
21
23
02Jan08
09Jan08
16Jan08
24Jan08
31Jan08
07Feb08
14Feb08
22Feb08
29Feb08
07Mar08
14Mar08
24Mar08
31Mar08
07Apr08
14Apr08
21Apr08
28Apr08
05May08
12May08
19May08
27May08
03Jun08
10Jun08
17Jun08
24Jun08
01Jul08
09Jul08
16Jul08
23Jul08
30Jul08
06Aug08
13Aug08
20Aug08
27Aug08
04Sep08
11Sep08
18Sep08
25Sep08
02Oct08
09Oct08
16Oct08
23Oct08
30Oct08
06Nov08
13Nov08
20Nov08
28Nov08
05Dec08
12Dec08
19Dec08
29Dec08
SLV Price with Trading Channel Signals
Previous 18 Days High Previous 14 Days Low
Signal Buy Price Signal Sell Price
18 Day High with 14 Day Low
For this illustrative example, using the above SLV price chart and 18 day high, 14 day low
parameters (18,14) as channel signals from 01 Jan 2008 to 29 Feb 2008, you can see there
were 3 buy signals and 3 sell signals (excluding the buy signal that occurred before 1 Jan
2008).

Our specific backtest specifications:
1) We went long on the buy signal. However, on the sell signal, we not only sold off our
entire position but went further to a net short position.
2) We will only have 1 active trade at the time. A long position will stay long until a
short signal is generated and vice versa.
3) Every trading position size was all of our trading capital at the time
4) We are always in the market, either long or short.
5) We started in 1 Jan 2006 with a buy.
The Results
1st
Screen Observations (refer to Appendix 1)
Our first matrix of results are data tables tabulating the theoretical gains by backtesting actual
GLD price data from 1 May 2006 to 10 Apr 2015. We vary n (days high) and m (days low) and
calculate the returns for commission rates of 0.18% with a fixed slippage amount (the actual
traded buy price is higher than the buy signal price and vice versa for selling) of 0.05USD per
trade.
18 day high, 14 day low trading results analysis
The anatomy of trading results with market movements
0
10
20
30
40
50
60
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
SLV Price with Strategy MTM Returns
Annual strategy returns:
Total strategy returns:
SLV Total Returns:
- 14.5%- 3.6% - 27.8% + 70.0% + 39.0% - 17.4% + 39.6% + 11.2% + 47.9% + 0.4%
+ 155.99%
+ 15.9%
Source: PSR
Note: Strategy returns are marked–to-market.
The above chart shows the actual SLV price chart from Jan 2006 to Apr 2015. The bottom
numbers are the yearly returns for the 18, 14 strategy. We note the following observations:
 Out of ten years, it was unprofitable for 4 of them.
 The parameters are close to monthly timeframes. Understandably, unprofitable
regions were characterized by whipsaws that led to no large trends in terms of
magnitude and time. We include the trade signals in the biggest lost making year
(2007), and the trade signals in the biggest winning year (2008) below.
 Although the biggest single loss was only -15% in 2006, the maximum cumulative loss
was a hefty 57% that ended in Aug 2010.
 Longer term trend-following strategies tend to have bigger drawdowns during
whipsaw regions as compared to shorter term trend-following strategies, but the
reward is bigger if there is a major market move.
Results Summary Table
Buy Breakout Period 18
Sell Breakout Period 14
Arithmatic Returns + 144.12%
Geometric Returns + 155.99% (realized)
Total Long Signals 38
Total Short Signals 38
Profitable Trades 28
Loss Making Trades 48
Total Trades 76
Average Days per trade 29.6
Average Annual Gain Arth + 16.29%
Average Annual Gain Geo + 11.21%
Sharpe Ratio (Strategy) 0.47
Sharpe Ratio (Buy and hold) -0.03
Sortino Ratio (Strategy) 1.68
Sortino Ratio (Buy and hold) -0.07
Risk-free rate 2.50%
Trades Data
% Profitable trade 37%
Stdev 12.3%
Average 1.90%
Average profitable trade + 13.71%
Average losing trade - 5.00%
Single Biggest Profit + 53.14% 13/1/2011
Single Biggest Loss - 15.46% 1/6/2006
Max Cumulative Profit (MTM) + 408.48% 5/11/2014
Max Cumulative Loss (MTM) - 57.19% 11/8/2010
Max Cumulative Profit (Realized) + 365.11% 25/11/2014
Max Cumulative Loss (Realized) - 53.26% 2/8/2010

Trading signals for 2008 (Best year)
5
7
9
11
13
15
17
19
21
23
5
7
9
11
13
15
17
19
21
23
02Jan08
09Jan08
16Jan08
24Jan08
31Jan08
07Feb08
14Feb08
22Feb08
29Feb08
07Mar08
14Mar08
24Mar08
31Mar08
07Apr08
14Apr08
21Apr08
28Apr08
05May08
12May08
19May08
27May08
03Jun08
10Jun08
17Jun08
24Jun08
01Jul08
09Jul08
16Jul08
23Jul08
30Jul08
06Aug08
13Aug08
20Aug08
27Aug08
04Sep08
11Sep08
18Sep08
25Sep08
02Oct08
09Oct08
16Oct08
23Oct08
30Oct08
06Nov08
13Nov08
20Nov08
28Nov08
05Dec08
12Dec08
19Dec08
29Dec08
Trading signals for 2007 (Worst Year)
5
7
9
11
13
15
17
5
7
9
11
13
15
17
03Jan07
10Jan07
18Jan07
25Jan07
01Feb07
08Feb07
15Feb07
23Feb07
02Mar07
09Mar07
16Mar07
23Mar07
30Mar07
09Apr07
16Apr07
23Apr07
30Apr07
07May07
14May07
21May07
29May07
05Jun07
12Jun07
19Jun07
26Jun07
03Jul07
11Jul07
18Jul07
25Jul07
01Aug07
08Aug07
15Aug07
22Aug07
29Aug07
06Sep07
13Sep07
20Sep07
27Sep07
04Oct07
11Oct07
18Oct07
25Oct07
01Nov07
08Nov07
15Nov07
23Nov07
30Nov07
07Dec07
14Dec07
21Dec07
31Dec07
Source: PSR

0
50
100
150
200
250
300
350
400
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
SLV Price with Equity Curve (Rebased)
SLV price (Rebased) Equity Curve (Rebased)18 Day High with 14 Day
Low
Factors affecting performance
Number of gaps traded. Gaps can occur in the SLV when there is excessive movement in the
futures market during the non-trading hours. The COMEX silver market operates from Sunday
to Friday, 6pm – 5:15pm. The typical NYSE trading hours are from 9:30pm – 4:00pm. If the
gap occurs that triggers a trading signal in our strategy, our traded price will not be as
favorable if it were triggered without a gap. Hence, the more gaps that are traded, the less
likely we will be profitable.
Number of trades. Higher number of trades in a year imply that traded trends tended to be
shorter, decreasing profitability. In addition, there were also more transaction costs.
Regions of minor cycling with no big moves. A look at the trade signals for 2007 show the
type of price movement that led to whipsaws. The longer the prices go into a bottoming or
drifting pattern without bigger moves in either direction, the more likely whipsaws will occur.

Optimization of the (18,14) parameters
Backtest range: 1 May 2006 to 1 Apr 2015
Results Table with gaps (from 2005-2015), 18 days high, 14 days low, 0.05USD slippage per trade)
+ 10.31% 0% 50% 100% 150% 200% 250% 300% 350% 400% Leverage
0.00% 25.8% 38.5% 44.9% 42.9% 33.6% 20.6% 8.1% -1.4% -7.1%
0.05% 23.1% 33.1% 37.0% 33.4% 24.2% 12.9% 2.7% -4.5% -8.6%
0.10% 20.6% 28.3% 30.2% 25.6% 16.8% 7.0% -1.2% -6.6% -9.5%
0.15% 18.2% 24.1% 24.3% 19.1% 10.9% 2.5% -4.0% -8.1% -10.2%
0.20% 16.1% 20.3% 19.2% 13.8% 6.2% -0.8% -6.0% -9.1% -10.6%
0.25% 14.1% 16.8% 14.9% 9.3% 2.5% -3.4% -7.5% -9.8% -10.8%
0.30% 12.2% 13.8% 11.1% 5.7% -0.4% -5.4% -8.6% -10.3% -11.0%
Commission Rate
0.18% 16.9% 21.7% 21.1% 15.8% 8.0% 0.4% -5.3% -8.7% -10.4%
Backtest range: 1May 2006 to 1 Apr 2015
Results Table with gaps (from 2006-2015), 18 days high, 14 days low, 0.05USD slippage per trade, 2.75% annual finance costs
0% 50% 100% 150% 200% 250% 300% 350% 400% Leverage
0.00% 23.0% 34.4% 39.4% 36.0% 25.3% 11.0% -2.9% -13.7% -20.9%
0.05% 20.3% 29.0% 31.5% 26.6% 16.0% 3.3% -8.3% -16.8% -22.3%
0.10% 17.8% 24.2% 24.7% 18.7% 8.6% -2.6% -12.2% -19.0% -23.3%
0.15% 15.5% 19.9% 18.8% 12.2% 2.7% -7.1% -15.0% -20.5% -23.9%
0.20% 13.3% 16.1% 13.7% 6.9% -2.0% -10.5% -17.0% -21.5% -24.3%
0.25% 11.3% 12.7% 9.4% 2.5% -5.7% -13.0% -18.5% -22.2% -24.6%
0.30% 9.5% 9.7% 5.6% -1.2% -8.6% -15.0% -19.6% -22.7% -24.7%
Commission Rate
0.18% 14.2% 17.6% 15.6% 8.9% -0.3% -9.2% -16.3% -21.1% -24.2%
In the above table, we optimized the 18, 14 N-day breakout model with leverage versus
transaction costs.
Factoring in Financial Costs
Phillip CFD offers transaction costs of 1.8%, and an average finance cost of 2.75% annually, if
trading the SLV. Assuming CFDs are utilized to execute this strategy, we tabulate the
hypothetical performance below.
Assuming the usage of such CFDs inclusive of the 2.75% finance cost:
At 0.18% transaction costs:
No leverage: annual gain was 14.2% (16.9% - 2.75% x 1)
Suggested leverage of 0.5x: annual gain was 17.6% (21.7% - 2.75% x 1.5)
In summary, the above results factor in the transaction costs, slippage of 0.05USD, and
finance costs.

Final Thoughts
How well the strategy will work in the future is a matter of probabilities, but we hope that we
have made these probabilities a little clearer with some hindsight quantitative perspectives. It
is key to note that market conditions can change going forward, and that the best parameters
of last year may not yield the best results this year. However, there are a few key
observations we can broadly agree with:
1. SLV tends to trend more than it doesn’t. However, higher volatility than the GLD
causes shorter term signals to be more unprofitable, but rewards the strategy if the
major market move can be caught.
2. The backtested results show that the range of parameters 16-19 for highs and 13-16
for lows captured most of the bigger trends.
3. “Popular” parameters like 3,2 or 4,3 underperform on the SLV at all commission
should have been avoided.
4. At the least, seasoned technical analysts can utilize the statistical tendencies to
augment their trading decisions.
5. Bottoming and/or minor cycling, drifting price patterns tend to increase whipsaws
and losses.
6. We think that likely this year based on our other models, barring any crisis, SLV price
will be in an early stage bottoming process. Such patterns are not that beneficial for
profiting in this major move catching strategy. However, this strategy can be
considered once this bottoming process becomes maturity.
7. There are definitely other filters and tweaks to the strategy that can be done to
improve the strategy performance. Suggestions could be: momentum filters, serial
correlation filters, probit regressions that indicate coming bottoming or topping
patterns that can include technical, fundamental or economic variables. But we have
reached the limit of our objective for the report. We may address these
enhancements in the future.
Note: Past results do not guarantee future results.

References
Smith, M. David, Wang, N., Wang, Y., Zychowicz, E. J., (2014). Sentiment and the Effectiveness
of Technical Analysis: Evidence from the Hedge Fund Industry.
Han, Y., Yang, K., Zhou, G., (2011). A New Anomaly: The Cross-Sectional Profitability of
Technical Analysis.

QUANT IDEAS QUANTITATIVE ANALYSIS
Contact Information (Singapore Research Team)
Management
Chan Wai Chee
(CEO, Research - Special Opportunities)
yebo@phillip.com.sg
Research Operations Officer
Jaelyn Chin chinjn@phillip.com.sg
Macro | Equities Market Analyst | Equities US Equities
Soh Lin Sin sohls@phillip.com.sg Kenneth Koh kennethkohwk@phillip.com.sg Wong Yong Kai wongyk@phillip.com.sg
Bakhteyar
Osama
osama@phillip.com.sg
Finance | Offshore Marine Real Estate REITs
Benjamin
Ong benjaminongcw@phillip.com.sg
Caroline Tay carolinetayyy@phillip.com.sg Dehong Tan tandh@phillip.com.sg
Transport & Logistics Consumer
Richard
Leow, CFTe
richardleowwt@phillip.com.sg Shane Goh shanegohla@phillip.com.sg
Contact Information (Regional Member Companies)
SINGAPORE
Phillip Securities Pte Ltd
Raffles City Tower
250, North Bridge Road #06-00
Singapore 179101
Tel +65 6533 6001
Fax +65 6535 6631
Website: www.poems.com.sg
MALAYSIA
Phillip Capital Management Sdn Bhd
B-3-6 Block B Level 3 Megan Avenue II,
No. 12, Jalan Yap Kwan Seng, 50450
Kuala Lumpur
Tel +603 2162 8841
Fax +603 2166 5099
Website: www.poems.com.my
HONG KONG
Phillip Securities (HK) Ltd
11/F United Centre 95 Queensway
Hong Kong
Tel +852 2277 6600
Fax +852 2868 5307
Websites: www.phillip.com.hk
JAPAN
Phillip Securities Japan, Ltd.
4-2 Nihonbashi Kabuto-cho Chuo-ku,
Tokyo 103-0026
Tel +81-3 3666 2101
Fax +81-3 3666 6090
Website: www.phillip.co.jp
INDONESIA
PT Phillip Securities Indonesia
ANZ Tower Level 23B,
Jl Jend Sudirman Kav 33A
Jakarta 10220 – Indonesia
Tel +62-21 5790 0800
Fax +62-21 5790 0809
Website: www.phillip.co.id
CHINA
Phillip Financial Advisory (Shanghai) Co Ltd
No 550 Yan An East Road,
Ocean Tower Unit 2318,
Postal code 200001
Tel +86-21 5169 9200
Fax +86-21 6351 2940
Website: www.phillip.com.cn
THAILAND
Phillip Securities (Thailand) Public Co. Ltd
15th Floor, Vorawat Building,
849 Silom Road, Silom, Bangrak,
Bangkok 10500 Thailand
Tel +66-2 6351700 / 22680999
Fax +66-2 22680921
Website www.phillip.co.th
FRANCE
King & Shaxson Capital Limited
3rd Floor, 35 Rue de la Bienfaisance 75008
Paris France
Tel +33-1 45633100
Fax +33-1 45636017
Website: www.kingandshaxson.com
UNITED KINGDOM
King & Shaxson Capital Limited
6th Floor, Candlewick House,
120 Cannon Street,
London, EC4N 6AS
Tel +44-20 7426 5950
Fax +44-20 7626 1757
Website: www.kingandshaxson.com
UNITED STATES
Phillip Futures Inc
141 W Jackson Blvd Ste 3050
The Chicago Board of Trade Building
Chicago, IL 60604 USA
Tel +1-312 356 9000
Fax +1-312 356 9005
Website: www.phillipusa.com
AUSTRALIA
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Level 12, 15 William Street,
Melbourne, Victoria 3000, Australia
Tel +61-03 9629 8288
Fax +61-03 9629 8882
Website: www.phillipcapital.com.au
SRI LANKA
Asha Phillip Securities Limited
No-10 Prince Alfred Tower,
Alfred House Gardens,
Colombo 03, Sri Lanka
Tel: (94) 11 2429 100
Fax: (94) 11 2429 199
Website: www.ashaphillip.net
INDIA
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No.1, 18th Floor
Urmi Estate
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Maharashtra, India
Tel: +91-22-2300 2999 / Fax: +91-22-2300 2969
Website: www.phillipcapital.in
TURKEY
PhillipCapital Menkul Degerler
Dr. Cemil Bengü Cad. Hak Is Merkezi
No. 2 Kat. 6A Caglayan
34403 Istanbul, Turkey
Tel: 0212 296 84 84
Fax: 0212 233 69 29
Website: www.phillipcapital.com.tr
DUBAI
Phillip Futures DMCC
Member of the Dubai Gold and
Commodities Exchange (DGCX)
Unit No 601, Plot No 58, White Crown Bldg,
Sheikh Zayed Road, P.O.Box 212291
Dubai-UAE
Tel: +971-4-3325052 / Fax: + 971-4-3328895
Website: www.phillipcapital.in

QUANT IDEAS QUANTITATIVE ANALYSIS
Important Information
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