QuantTrendSeriesSLV20150512
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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) [email protected]
Page | 2 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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
Page | 3 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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
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b 0
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b 0
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b 0
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b 0
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r 0
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r 0
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r 0
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r 0
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n 0
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n 0
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n 0
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n 0
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l 08
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l 08
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l 08
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l 08
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l 08
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Au
g 0
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g 0
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g 0
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Au
g 0
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p 0
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p 0
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p 0
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p 0
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No
v 0
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v 0
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v 0
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No
v 0
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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).
Page | 4 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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
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SLV Price with Strategy MTM Returns
18 Day High with 14 Day Low
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
Page | 5 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
Trading signals for 2008 (Best year)
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Jan
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Fe
b 0
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b 0
8
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Fe
b 0
8
29
Fe
b 0
8
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Mar
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14
Mar
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24
Mar
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31
Mar
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07
Ap
r 0
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Ap
r 0
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Ap
r 0
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Ap
r 0
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May
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May
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19
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27
May
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03
Ju
n 0
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n 0
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n 0
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Ju
n 0
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Ju
l 08
09
Ju
l 08
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l 08
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Ju
l 08
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Ju
l 08
06
Au
g 0
8
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Au
g 0
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Au
g 0
8
27
Au
g 0
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Se
p 0
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Se
p 0
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Se
p 0
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25
Se
p 0
8
02
Oct
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09
Oct
08
16
Oct
08
23
Oct
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30
Oct
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No
v 0
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No
v 0
8
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No
v 0
8
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No
v 0
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Dec
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Dec
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19
Dec
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Dec
08
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
Trading signals for 2007 (Worst Year)
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b 0
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b 0
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b 0
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b 0
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Mar
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Ap
r 0
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r 0
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Ap
r 0
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Ap
r 0
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May
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May
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May
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Ju
n 0
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Ju
n 0
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Ju
n 0
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Ju
n 0
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Ju
l 07
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Ju
l 07
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Ju
l 07
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Ju
l 07
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Au
g 0
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Au
g 0
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Au
g 0
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Au
g 0
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Au
g 0
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p 0
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Se
p 0
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Se
p 0
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Se
p 0
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Oct
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Oct
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Oct
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Oct
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01
No
v 0
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08
No
v 0
7
15
No
v 0
7
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No
v 0
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No
v 0
7
07
Dec
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Dec
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Dec
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31
Dec
07
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
Source: PSR
Page | 6 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
0
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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.
Page | 7 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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.
Page | 8 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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.
Page | 9 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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.
Page | 10 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
QUANT IDEAS QUANTITATIVE ANALYSIS
Contact Information (Singapore Research Team) Management Chan Wai Chee (CEO, Research - Special Opportunities)
[email protected] Research Operations Officer Jaelyn Chin [email protected]
Macro | Equities Market Analyst | Equities US Equities Soh Lin Sin [email protected] Kenneth Koh [email protected] Wong Yong Kai [email protected] Bakhteyar Osama
Finance | Offshore Marine Real Estate REITs Benjamin Ong [email protected]
Caroline Tay [email protected] Dehong Tan [email protected]
Transport & Logistics Consumer Richard Leow, CFTe
[email protected] Shane Goh [email protected]
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 Phillip Capital Limited
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 PhillipCapital (India) Private Limited
No.1, 18th Floor Urmi Estate
95, Ganpatrao Kadam Marg Lower Parel West, Mumbai 400-013
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
Page | 11 | PHILLIP SECURITIES RESEARCH (SINGAPORE)
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