Nomura FXI - When there was no trend

Global Foreign Exchange Research FIXED INCOME RESEARCH | EUROPE

FX Quant Insights

Any authors named on this report are research analysts unless otherwise indicated.

Please see analyst certifications and important disclosures starting on page 9.

N O M U R A I N T E R N A T I O N A L P L C

A U G U S T 1 8 , 2 0 1 0

When there was no trend1

Creating a simple metric for determining if the market is trending

The bane of any trend-following strategy is when the market becomes

range bound. In this article we look at a method for determining if the

market is trending or not, by looking at the gradient of moving averages.

The rationale is that moving averages tend to flatten during periods of

range-bound price action. We find that our gradient-based trading rule

outperforms simple moving-average crossovers, which suggests the

gradient-based approach adds value compared with simpler technical

indicators. We also show that filtering a simple moving average using a

gradient adds value.

Our trading basket based on these ideas has a historical information

ratio of 1.12 and annualised returns of 2.74%.

Introduction

We have written at length about various technical strategies in the past,

in particular trend-following strategies. One issue with trend-following

strategies is that they perform poorly during ranging markets. During

range-bound markets typical momentum-based indicators end up

getting whipsawed, repeatedly flipping their signals. The result is that in

range-bound environments a trend following model can often end up

buying high and selling low. This can severely affect returns, erasing

gains from strongly trending periods of price action.

We have in the past used several approaches to alleviate this problem,

which largely revolve around creating a regime switch for flipping

between trending and ranging markets. One was the creation of our

proprietary TrendMonitor2

indicator. It uses inputs from FX,

commodities, equities and rates markets, which are then combined

together to create a final TrendMonitor signal. Rising values of

TrendMonitor are indicative of building trends, while falling values tend

to be representative of diminishing trends. Essentially, TrendMonitor

gives an overall view of whether capital markets are trending or ranging,

rather than looking at trends on an asset-by-asset basis. Typically, the

indicator is mean-reverting over long periods, reflecting that market

trends do not last indefinitely.

1 I happened to come along in the music business when there was no trend – Elvis Presley

2 FX Quant Insights: Trying to be Trendy – May 28 2009 –

http://www.nomura.com/research/GetPub.aspx?pid=324706

Saeed Amen

+44 20 7103 7119

[email protected]

www.nomura.com/research Bloomberg: NRE


mailto:[email protected]

Global Foreign Exchange Research

Nomura International 2 August 18, 2010

Exhibit 1. Characteristics of a trend (examining EUR/USD during the

Lehman collapse)

Source: Bloomberg, Nomura

In a more recent paper3, we discussed the use of a currency cross-

specific regime filter, rather than using a market wide indicator such as

TrendMonitor, to create a mean-reversion trading model. In the model,

bounces lower from top Bollinger band would trigger sell signals.

Conversely, bounces upwards from a lower Bollinger band would trigger

buy signals. When rolling returns were poor for this trading strategy

specific currency cross, it was an indication that the price action in that

cross was trending. In this case, the model would exit a position. When

rolling returns picked up, the model would re-enter the mean-reversion

position.

In this paper, we shall also take a cross-specific approach. However, in

this case, we shall use an indicator based on the gradient of a simple

moving average, rather than using a filter based on rolling returns. The

rationale for using the gradient is that during ranging markets the simple

moving average essentially becomes flat. These are precisely the

periods when whipsawing signals can be particularly prevalent and loss

making. We note that during strong trends whipsawing tends on the

whole not to be as punitive on returns (see Exhibit 1).

We shall calculate the gradient4 by looking at the 10D percentage

returns of both short term and medium-term simple moving averages

(SMA) 5. We define the following trend regimes (illustrated in Exhibit 2):

When the short term and medium-term moving averages are

upwards sloping6 we are trending higher

When the short term and medium-term moving averages are

downwards sloping7 we are trending lower

When there is negligible slope8, then we are in a neutral trend

Historically, around half the time crosses9 are in a neutral state, with the

rest split below trending higher and low.

3 FX Quant Insights: Know what I mean (revert) – April 9 2010 –

http://www.nomura.com/research/GetPub.aspx?pid=366424 4 What we refer to as the gradient is often referred to as ROC (rate-of-change).

5 We have taken gradient of the simple moving average, rather than of spot, given that it is less noisy.

6 Gradient of short term and long-term SMA are greater than +25bp

7 Gradient of short term and long-term SMA are lower than -25bp

8 Gradient of short term and long-term SMA are between -25 and +25bp

9 As an example since 2002, using our metric, EUR/USD spot has been trending lower roughly 16% of

the time and trending higher around 31% of the time. It has been a neutral for close to 52% of the time.

1.2

1.25

1.3

1.35

1.4

1.45

1.5

1.55

1.6

Jan 2008 Apr 2008 Jul 2008 Oct 2008

Spot 20D SMA 55D SMA

strong trends are characterisedby a rapid increase in the gradeint

of moving averages

whipsawing during strong trendsdoes not impact returns as much

as whipsawing during ranging periods




Exhibit 2. EUR/USD spot with moving averages and trend filter


Creating a trading rule around moving average gradients

We shall create a relatively straightforward trading rule, using our

moving average gradient, where we

buy spot when our gradient is upwards sloping

sell spot when our gradient is downwards sloping

stay flat otherwise

We shall construct historical returns using this trading strategy from

2002 – present. In all case we include both transaction costs and carry.

We compare our gradient-based trading rule against a simple moving-

average trading rule10

. We shall also be using the gradient as a filter for

simple moving-average crossovers (and label this strategy filtered

SMA), thus, we:

buy spot when our gradient is upwards sloping and the spot is

above the simple moving average

bell spot when our gradient is downwards sloping and the

spot is below the simple moving average

go flat otherwise11

We present our results for all three strategies in Exhibit 3. We find that

on the whole gradient and filtered SMAs have the highest information

ratios, compared to the SMA. This suggests that the gradient of simple

moving averages does add value to standard momentum-based trading

rules.

We note that the highest information ratios are present in the gradient

and filtered SMA rules, with the lowest in the SMA case. This suggests

that looking at the slope of SMA does add value when compared with

simply using an SMA on its own. The best performing crosses (by

information ratio) include EUR/USD, NZD/USD, AUD/USD, USD/TRY

and EUR/PLN. The worst performing crosses are USD/CHF, EUR/AUD

and EUR/NZD. On the whole, the CHF crosses generally underperform

when traded using our technical trading rules.

10

SMA trading rule involves buying spot, when spot is above the SMA and selling spot, when spot is below the SMA. 11

Given that such a strategy is likely to generate more signals, when we get a signal change, we spread the trade over two days. Hence, we enter half the notional on the first day of a signal change and the rest on the next day. This approach should reduce the problem of repeated signal flipping.

However, in the event of hitting stop losses or take profits we exit the whole trade immediately.

-1

0

1

1.2

1.25

1.3

1.35

1.4

1.45

1.5

1.55

1.6

Jan 2010 Apr 2010 Jul 2010

Spot

20D SMA

55D SMA

Trend (Higher/Neutral/Lower)

flatter moving averagesindicativeof a lack of trend



Exhibit 3. Information ratios for gradient rule, filtered SMA and SMA


Adding stops and take profits

In this section we have applied stops and take profit points to each of

our technical trading rules. We present the information ratios in Exhibit

4.

We note that the addition of stops and take profit points improves

information ratios significantly. This is consistent with the results from

previous papers on technicals. We have found that with the majority

technical indicators, the addition of stops often reduces drawdowns (see

Appendix for breakdown of drawdowns). In NZD/JPY for example

drawdowns are cut by half when using the gradient and filtered SMA

rules.

Exhibit 4. Information ratios for gradient rule, filtered SMA and SMA with stop loss and take profits


-1.00

-0.50

0.00

0.50

1.00

EU

RU

SD

US

DJP

Y

GB

PU

SD

AU

DU

SD

US

DC

AD

US

DC

HF

NZ

DU

SD

EU

RS

EK

EU

RN

OK

AU

DJP

Y

NZ

DJP

Y

GB

PJP

Y

EU

RJP

Y

EU

RC

HF

EU

RA

UD

EU

RN

ZD

EU

RG

BP

EU

RC

AD

AU

DC

HF

NZ

DC

HF

CA

DC

HF

GB

PC

HF

US

DS

EK

US

DN

OK

AU

DN

ZD

US

DT

RY

US

DIL

S

US

DZ

AR

EU

RP

LN

EU

RH

UF

EU

RC

ZK

US

DM

XN

Grad Filt 55D SMA 55D SMAIR

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

1.25

EU

RU

SD

US

DJP

Y

GB

PU

SD

AU

DU

SD

US

DC

AD

US

DC

HF

NZ

DU

SD

EU

RS

EK

EU

RN

OK

AU

DJP

Y

NZ

DJP

Y

GB

PJP

Y

EU

RJP

Y

EU

RC

HF

EU

RA

UD

EU

RN

ZD

EU

RG

BP

EU

RC

AD

AU

DC

HF

NZ

DC

HF

CA

DC

HF

GB

PC

HF

US

DS

EK

US

DN

OK

AU

DN

ZD

US

DT

RY

US

DIL

S

US

DZ

AR

EU

RP

LN

EU

RH

UF

EU

RC

ZK

US

DM

XN

Grad SL Filt 55D SMA SL 55D SMA SLIR



Creating a technical basket

Using the filtered SMA rule (with stops and take profits), we have

created a trading basket of liquid deliverable crosses in G10 and EM.

We have excluded those crosses with particularly low12

information

ratios. Our final combined trading basket has an information ratio of

1.12 and annualised returns of 2.74%. The maximum drawdowns are

3.28%.

We have also created baskets specifically for G10 and EM. A leveraged

basket is also included, which increases the basket leverage when it is

underinvested by up to 2 times or if the leveraged basket is 100%

invested. Applying the leverage filter slightly reduces the information

ratio and increases the drawdowns as we would expect, but adds about

2% to returns.

As a comparison, we have used a generic G10 carry basket13

as a

benchmark. Historically returns from G10 carry are higher than our

technical based basket, but this comes at a cost of much higher

drawdowns and much higher volatility. Hence, the information ratio of

our G10 carry basket is much lower14

. The best year for our technical

basket was 2008, when there were particularly strong trends within the

market following the bankruptcy of Lehman Brothers.

Exhibit 5. Gradient technicals basket compared with a generic carry basket

cumulative returns (top) and year-on-year returns (bottom)


12

We have used 0.2 as our information ratio threshold. 13

We buy the three highest yielding currencies in G10 and sell the three lowest-yielding currencies in G10. 14

Typically we would use techniques such as introducing a risk filter (such as Nomura’s GRAM+) to

mitigate returns associated with carry baskets.

95

115

135

155

175

195

215

2002 2003 2004 2005 2006 2007 2008 2009 2010

G10 Portfolio Ret=2.46% Vol=2.81% IR=0.87 Draw=-3.93%

EM Portfolio Ret=3.73% Vol=3.3% IR=1.13 Draw=-5.46%

Combined Portfolio Ret=2.74% Vol=2.45% IR=1.12 Draw=-3.28%

Leveraged Portfolio Ret=4.58% Vol=4.45% IR=1.03 Draw=-6.49%

G10 Carry Ret=4.42% Vol=11.85% IR=0.37 Draw=-35.7%

-40%

-30%

-20%

-10%

0%

10%

20%

2002 2003 2004 2005 2006 2007 2008 2009 2010

Technical

Carry



Conclusion

We have discussed how using the gradient of simple moving averages

can be a useful addition to the array of indicators used by technical

traders. The rationale is that range-bound trading environments, where

trend following trading rules underperform, tend to be characterised by

a flattening of SMA.

We have seen how either using a gradient-based approach or creating

a filtered SMA can outperform using an SMA on its own.

We have also created a trading basket to demonstrate the filtered SMA

trading rule. Our technical trading basket has a historical information

ratio of 1.12 and annualised returns of 2.74%. Peak-to-trough

drawdowns are comparatively low at 3.28%.



Appendix

In this section we present more detailed returns statistics for our various

trading rules. In Exhibit 6, we present the full returns statistics for our

trading rules in the absence of stops and take profits.

Exhibit 6. Returns statistics for trading rules without stops and take profits


In Exhibit 7, presents returns statistics for our trading rules with the

addition of stop losses and take profits.

Gradient Filt 55D SMA 55D SMA

Ret Vol IR Draw Ret Vol IR Draw Ret Vol IR Draw

EURUSD 4.5% 8.1% 0.56 -14.8% 4.4% 8.0% 0.55 -14.3% 4.0% 10.9% 0.36 -18.5%

USDJPY 0.6% 8.6% 0.08 -16.8% 1.2% 8.4% 0.14 -14.9% 0.6% 11.2% 0.06 -23.2%

GBPUSD -0.5% 8.3% -0.06 -21.6% -1.1% 8.0% -0.13 -23.3% 1.2% 11.1% 0.11 -34.1%

AUDUSD 3.0% 12.6% 0.24 -26.9% 2.3% 12.4% 0.18 -27.8% 4.0% 15.3% 0.26 -37.4%

USDCAD 1.7% 8.2% 0.20 -20.2% 0.5% 7.9% 0.06 -24.6% -3.5% 11.0% -0.32 -42.6%

USDCHF -2.3% 8.2% -0.28 -34.0% -2.4% 8.0% -0.30 -32.7% -0.3% 11.6% -0.03 -29.2%

NZDUSD 6.1% 12.5% 0.49 -18.3% 5.0% 12.2% 0.41 -20.4% 4.2% 15.4% 0.27 -27.4%

EURSEK -0.7% 4.7% -0.14 -12.3% -0.5% 4.6% -0.11 -10.4% -3.1% 7.1% -0.44 -30.8%

EURNOK -0.3% 5.9% -0.05 -18.9% -0.3% 5.7% -0.05 -19.1% 1.3% 7.9% 0.17 -14.6%

AUDJPY 0.3% 17.1% 0.02 -33.4% 0.3% 16.7% 0.02 -31.1% 4.6% 19.7% 0.23 -39.9%

NZDJPY 1.9% 16.1% 0.12 -27.4% 2.8% 15.7% 0.18 -25.2% 7.7% 19.4% 0.40 -40.4%

GBPJPY 2.7% 12.5% 0.22 -17.0% 2.6% 12.2% 0.21 -21.7% -0.1% 15.0% -0.01 -43.8%

EURJPY 1.2% 10.4% 0.11 -20.4% 0.6% 10.2% 0.06 -20.9% -4.5% 13.3% -0.34 -43.3%

EURCHF 0.4% 3.7% 0.12 -9.9% 0.2% 3.6% 0.07 -11.0% -1.4% 5.4% -0.26 -17.4%

EURAUD -2.4% 9.2% -0.26 -36.1% -2.2% 9.0% -0.25 -35.4% -1.9% 11.8% -0.16 -33.7%

EURNZD -2.1% 9.0% -0.23 -34.4% -1.8% 8.7% -0.21 -31.2% 0.1% 12.0% 0.01 -36.9%

EURGBP 1.7% 5.9% 0.30 -16.7% 1.8% 5.8% 0.31 -15.9% -5.4% 8.4% -0.64 -45.9%

EURCAD 1.1% 7.6% 0.15 -18.6% 0.4% 7.4% 0.06 -20.6% -2.8% 10.5% -0.27 -40.3%

AUDCHF -1.6% 12.0% -0.13 -32.8% -2.6% 11.6% -0.22 -33.3% -0.8% 14.4% -0.06 -28.0%

NZDCHF 0.8% 11.7% 0.07 -22.5% 1.4% 11.4% 0.12 -18.7% 2.4% 14.2% 0.17 -27.0%

CADCHF 0.1% 9.1% 0.01 -21.2% 0.0% 8.9% 0.00 -21.4% -0.9% 12.2% -0.08 -33.2%

GBPCHF -0.1% 7.7% -0.01 -17.6% -0.8% 7.5% -0.11 -18.9% -7.4% 10.3% -0.72 -50.8%

USDSEK 3.4% 10.6% 0.32 -17.7% 3.8% 10.3% 0.37 -14.7% 1.0% 13.3% 0.08 -32.2%

USDNOK 2.9% 10.4% 0.28 -24.8% 2.6% 10.1% 0.26 -24.4% -4.7% 13.6% -0.35 -53.6%

AUDNZD 1.0% 5.4% 0.19 -10.7% 1.1% 5.3% 0.20 -11.8% 2.2% 7.7% 0.29 -17.6%

USDTRY 8.5% 13.2% 0.64 -21.5% 8.3% 12.8% 0.64 -23.0% 7.3% 16.1% 0.46 -27.3%

USDILS 0.8% 7.1% 0.11 -13.8% 1.1% 6.6% 0.17 -11.3% 3.9% 8.9% 0.43 -15.2%

USDZAR 0.7% 14.7% 0.05 -36.2% -0.1% 14.3% 0.00 -37.2% -2.3% 19.4% -0.12 -54.8%

EURPLN 3.4% 8.6% 0.40 -12.6% 4.2% 8.4% 0.50 -12.8% 5.5% 11.0% 0.50 -14.6%

EURHUF 1.6% 8.4% 0.19 -13.0% 0.7% 8.3% 0.08 -18.8% -2.6% 10.8% -0.24 -30.7%

EURCZK 1.1% 5.4% 0.21 -10.7% 1.0% 5.2% 0.19 -11.6% 1.1% 7.1% 0.16 -14.7%

USDMXN -1.5% 11.0% -0.14 -23.6% -2.6% 10.8% -0.24 -27.3% -2.7% 13.1% -0.21 -32.8%



Exhibit 7. Returns statistics for trading rules with stops and take profits


Gradient SL Filt 55D SMA SL 55D SMA SL

Ret Vol IR Draw Ret Vol IR Draw Ret Vol IR Draw

EURUSD 3.5% 5.9% 0.60 -11.0% 3.2% 5.8% 0.56 -10.7% 3.5% 8.0% 0.44 -17.7%

USDJPY 1.1% 7.2% 0.15 -14.0% 1.5% 7.0% 0.21 -13.8% 0.7% 8.8% 0.08 -16.2%

GBPUSD -3.2% 5.6% -0.57 -28.5% -2.2% 5.8% -0.38 -22.4% -1.6% 7.8% -0.20 -28.2%

AUDUSD 1.5% 6.7% 0.22 -14.5% 1.1% 6.6% 0.17 -16.6% 2.2% 8.4% 0.26 -27.4%

USDCAD 1.9% 5.9% 0.32 -11.6% 1.8% 5.8% 0.31 -9.0% -2.7% 8.3% -0.32 -30.0%

USDCHF -0.3% 6.5% -0.05 -16.6% -1.0% 6.6% -0.15 -19.8% -0.4% 9.2% -0.05 -25.4%

NZDUSD 3.5% 7.1% 0.50 -14.7% 3.1% 7.3% 0.43 -18.7% 2.2% 9.4% 0.24 -22.6%

EURSEK -0.1% 3.7% -0.03 -8.2% -0.6% 3.8% -0.16 -8.9% -4.2% 5.9% -0.71 -34.5%

EURNOK 1.7% 4.7% 0.35 -9.5% 1.2% 4.5% 0.27 -10.7% 2.1% 6.4% 0.33 -9.5%

AUDJPY -0.6% 9.1% -0.06 -19.6% 0.6% 8.8% 0.07 -18.3% 3.4% 9.1% 0.37 -17.2%

NZDJPY 3.8% 9.3% 0.41 -14.4% 4.7% 8.9% 0.53 -12.5% 6.6% 9.8% 0.67 -24.6%

GBPJPY 2.7% 7.0% 0.39 -15.5% 3.3% 7.0% 0.48 -12.2% -3.5% 8.7% -0.40 -32.3%

EURJPY -1.0% 7.1% -0.13 -20.1% -1.4% 7.0% -0.20 -21.3% -2.7% 9.4% -0.28 -30.8%

EURCHF 0.4% 2.9% 0.15 -5.8% 0.7% 3.0% 0.24 -5.6% -1.1% 4.6% -0.25 -11.7%

EURAUD -2.8% 6.3% -0.44 -34.2% -2.5% 6.1% -0.41 -32.6% -0.4% 8.2% -0.04 -21.6%

EURNZD 0.2% 7.5% 0.02 -18.2% -0.3% 7.7% -0.05 -18.0% 3.3% 9.3% 0.35 -23.5%

EURGBP 1.2% 4.6% 0.27 -16.7% 1.6% 4.5% 0.35 -15.9% -4.8% 6.5% -0.75 -39.2%

EURCAD 0.6% 5.9% 0.10 -12.0% 1.4% 5.8% 0.24 -13.0% -1.6% 8.9% -0.19 -23.0%

AUDCHF -3.1% 7.6% -0.41 -35.5% -3.0% 7.5% -0.40 -36.0% 0.9% 9.3% 0.10 -16.0%

NZDCHF 2.4% 7.8% 0.31 -14.9% 3.9% 8.5% 0.47 -11.9% 5.2% 8.9% 0.58 -12.5%

CADCHF 3.7% 6.7% 0.56 -12.2% 3.2% 6.7% 0.48 -12.7% -2.2% 8.9% -0.24 -31.3%

GBPCHF 0.2% 5.7% 0.04 -14.9% -0.1% 5.6% -0.02 -17.7% -7.0% 7.8% -0.91 -45.6%

USDSEK 3.2% 6.6% 0.48 -9.0% 4.3% 6.7% 0.64 -9.6% 2.4% 9.3% 0.26 -15.7%

USDNOK -0.1% 7.4% -0.01 -22.4% 0.1% 7.1% 0.01 -22.0% -3.6% 10.0% -0.36 -42.6%

AUDNZD 1.7% 4.4% 0.38 -10.7% 1.6% 4.3% 0.37 -11.8% 1.8% 6.4% 0.28 -12.8%

USDTRY 8.6% 8.3% 1.04 -12.5% 7.0% 7.9% 0.89 -11.5% 6.0% 10.4% 0.58 -13.0%

USDILS 3.5% 6.3% 0.55 -10.3% 3.5% 5.9% 0.59 -9.2% 5.2% 6.7% 0.77 -14.3%

USDZAR 2.2% 9.6% 0.23 -16.4% 1.7% 9.4% 0.18 -18.8% 0.6% 12.1% 0.05 -25.9%

EURPLN 1.1% 5.1% 0.22 -12.0% 3.1% 5.5% 0.57 -11.6% 3.4% 7.5% 0.46 -9.7%

EURHUF -0.1% 6.2% -0.01 -12.7% -1.2% 6.1% -0.20 -19.6% -2.4% 7.5% -0.31 -24.1%

EURCZK 1.6% 4.6% 0.35 -7.9% 1.8% 4.5% 0.40 -9.0% 1.6% 6.0% 0.27 -14.2%

USDMXN -2.6% 6.4% -0.41 -23.7% -3.3% 6.2% -0.52 -26.4% -1.7% 7.6% -0.22 -20.7%


Nomura 9 August 18, 2010

ANALYST CERTIFICATIONS

I, Saeed Amen, hereby certify (1) that the views expressed in this report accurately reflect my personal views about any or all of the subject securities or issuers referred to in this report, (2) no part of my compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this report and (3) no part of my compensation is tied to any specific investment banking transactions performed by Nomura Securities International, Inc., Nomura International plc or any other Nomura Group company.

Online availability of research and additional conflict-of-interest disclosures: Nomura Japanese Equity Research is available electronically for clients in the US on NOMURA.COM, REUTERS, BLOOMBERG and THOMSON ONE ANALYTICS. For clients in Europe, Japan and elsewhere in Asia it is available on NOMURA.COM, REUTERS and BLOOMBERG.

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