keng goh january 2020 in practice - state street corporation...5 ‘value and momentum everywhere’...
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1
FX Factors and Media
Abstract
In October 2018, through our partnership with MKT MediaStats, we
introduced our suite of FX Macro Media Indicators that track media
coverage of currencies. Based on an extensive body of research by
MKT’s founding partners, Professor Ronnie Sadka of Boston College,
Professor Emeritus Ken Froot of Harvard Business School, and Gideon
Ozik, affiliate professor at École EDHEC Business School, these
indicators parse tens of thousands of news publications on a daily basis
to gather information about market sentiment and its potential impact on
foreign exchange. This near real-time pulse of broad media sentiment
enables investors to evaluate the impact of online chatter, including the
impact of unusual media coverage and the degree of disagreement in
opinion.
In this In Practice issue, we introduce a simple approach of combining
FX Macro Media Indicators with traditional FX factors such as
Momentum, Value and Carry to improve the risk-adjusted performance
of these standard currency factors. In our analysis, the excess returns
achieved by incorporating Media is +2.5% per year for Momentum,
+2.5% per year for Value, and +1.8% per year for Carry in G10 markets
above their respective stand-alone factors. In Emerging Markets, the
excess return is +1.8% per year for Momentum, +1.3% per year in Value,
and +0.1% in Carry. These performance improvements are broad-based
when media is taken into account, with most currencies within a factor
outperforming their stand-alone counterparts. Finally, these gains are
accompanied by lower returns volatility and drawdowns, suggesting
increased diversification benefits from incorporating media, whilst also
preserving the original factor attribute. By combining traditional FX
factors with media, we are capturing a currency’s factor desirability with
what people are saying about the currency in the media.
In Practice Series
State Street Associates’ research
agenda is rooted in financial theory
yet recognizes that theory must bend
to real-world complexities. Our In
Practice series provides investment
practitioners with concrete insights
into how our indicators and tools can
be applied.
State Street Associates
State Street’s research partnership
with renowned academics, State
Street Associates, offers a full
spectrum of indicators and advisory
research services.
MKT MediaStats
MKT MediaStats LLC is a pioneer in
extracting financial markets insights
from large sets of unstructured data.
Through our partnership with MKT
MediaStats, State Street offers a full
spectrum of media-based indicators
for companies, global equity indices
and foreign exchange.
Keng Goh January 2020 State Street Associates
In Practice
This paper is not intended for trading purposes. The paper is not appropriate for the purposes of making a decision to carry out a transaction or trade. Nor does it provide any form of advice
(investment, tax, legal) amounting to investment advice, or make any recommendations regarding particular financial instruments, investments or products. State Street MediaStats may
discontinue or change the paper content at any time, without notice. State Street MediaStats does not guarantee or warrant the accuracy, completeness or timeliness of the paper. For more
detailed disclaimer, please refer to the Disclaimers and Important Risk Information in back cover of this document. 2906950.1.1.GBL.
Information Classification: General 2906950.1.1.GBL State Street Corporation 2
IN PRACTICE: FX FACTORS AND MEDIA
Contents
Introduction p. 3
State Street MediaStats FX Indicators p. 3
FX Factors p. 5
Combining FX Factors and Media p. 8
Conclusions p. 12
References p. 13
Appendix p. 14
Information Classification: General 2906950.1.1.GBL State Street Corporation 3
IN PRACTICE: FX FACTORS AND MEDIA
Our In Practice series provides practitioners with concrete insights into how they can incorporate State Street
indicators and tools into their investment process. In this issue, we introduce a simple framework of combining our
FX Macro Media Indicators with traditional FX factors such as Momentum, Value and Carry.
1. Introduction
Currency management styles or factors are now firmly part of the active currency management landscape. Rule-
based active currency factors such as Momentum, Value and Carry have been shown to generate positive risk-
adjusted returns over the long term1, though their performance can be sensitive through time. In October 2018, we
introduced media as a new source of alternative data2 and the three distinct measures of media coverage called
Sentiment, Disagreement and Intensity – each producing investment strategies that can be, in general, orthogonal
and uncorrelated to traditional currency management strategies. In this issue, we introduce a simple framework of
combining these measures of media with traditional FX factors such as Momentum, Value and Carry, to help
enhance returns, reduce risk, and improve risk-adjusted performance.
2. State Street MediaStats FX Indicators
State Street MediaStats’ Indicators® provide a timely measure of media sentiment drawn from hundreds of
thousands of curated, unstructured data sources. Over the past six years, we have found that this source of data
can generate timely insights into the performance of foreign currencies. This near real-time pulse of broad media
sentiment enables investors to evaluate the impact of online chatter, including the impact of unusual media
coverage and the degree of disagreement in opinion. Tone, volume and dispersion of media news are the three
dimensions we measure which we call Sentiment, Intensity and Disagreement.
Sentiment
The Sentiment indicator is designed to measure the tone of media coverage on a currency each day. We start by
applying sentiment analysis scoring for each article in the set. As a general rule, the scoring process works such
that detailed articles, which are highly relevant to country finances and that express consistent views (either
optimistic or pessimistic) tend to receive high absolute sentiment scores (positive or negative) .
As documented in the literature, articles exhibiting clusters of positive or negative terms are typically associated
with high absolute sentiment scores across a variety of sentiment scoring techniques (including ours). Our
approach is holistic and contextual, examining an article at its entirety. A distinction between sentiment scoring of
currency and other assets is that the former requires attention to trading conventions. An article about the strength
of the Yen might refer to the strength of “JPY” or the weakness of the “USDJPY pair.” Our system adjusts
accordingly. Once article scoring is completed, one has to adjust for the fixed effects (e.g. EUR tends to receive
negative coverage on average; China tends to be covered negatively on Mondays). Our adjusted sentiment scores
1 “Currency Management Style through the Ages” by James Binny, The Journal of Alternative Investments Winter 2005, 8 (3) 52-59 2 “In Practice – Media Coverage and Foreign Exchange Returns”, by Michael Guidi, State Street Associates In Practice series, October 2018
Information Classification: General 2906950.1.1.GBL State Street Corporation 4
IN PRACTICE: FX FACTORS AND MEDIA
represent the difference between the measured sentiment and the expected sentiment for a country’s currency
each day.
Our studies3 have shown, unsurprisingly, that high sentiment tends to lead positive currency returns.
Intensity
The Intensity indicator is designed to measure the abnormal quantity of media coverage on a currency each day.
We document several fixed effects; For example, on average, some currencies tend to receive more media
coverage than other currencies. Additionally, some media sources tend to cover specific currencies on the same
day-of-the-week. The Financial Times may cover Russia every Tuesday and China every Thursday. Our system
controls for such effects and the distributed indicators represent the abnormal coverage beyond predictable
patterns.
In our studies3, high intensity of media coverage is associated with lower future currency returns. The intuition for
these findings follow the theoretical work of Merton (1987). In his model, some investors are not aware of the
opportunity of investing in certain assets (these are the neglected assets)—and therefore will not include them in
their optimal portfolios. In equilibrium, the neglected assets are under‐invested, thereby resulting in a low expected
return for better‐known assets relative to less‐known assets. Using media coverage intensity of a currency to proxy
for how well investors are familiar with it, we find evidence consistent with predictions, that is, high‐intensity
currencies tend to underperform in the short term.
Disagreement
As articles are collected from thousands of different sources, they may naturally express different opinions with
respect to a country’s currency. The Disagreement indicator measures the degree to which these opinions vary.
The sentiment scores of articles covering a given country's currency are pooled and Disagreement measures the
standard deviation of sentiment across the pooled distribution.
Our analysis3 show that high disagreement currencies tend to outperform those with low levels of media
disagreement, on average. The intuition for this follows the traditional risk‐return trade-off assertion that currencies
for which there is high disagreement about fundamental value are riskier, and, therefore, should be low‐priced and
earn high expected return.
3 “In Practice – Media Coverage and Foreign Exchange Returns”, by Michael Guidi, State Street Associates In Practice series, October 2018
Information Classification: General 2906950.1.1.GBL State Street Corporation 5
IN PRACTICE: FX FACTORS AND MEDIA
3. FX Factors
In this issue, we look at three standard FX Factors – Momentum, Value, and Carry. For completeness, we also
include a ‘Media’ factor which is formed by taking Sentiment + Disagreement – Intensity measures into a single
media composite score as described in our previous In Practice publication (“In Practice – Media Coverage and
Foreign Exchange Returns”, October 2018). Briefly, Sentiment and Disagreement were shown to be positively
correlated to a currency’s return, while Intensity tended to negatively predict a currency’s future return (hence the
‘-‘ sign in the composite score).
Factor Definition
Momentum – one month spot return from two months ago to one month ago4.
Value – five-year change in CPI (relative to US) minus the five-year FX return (relative to USD)5
Carry – short term interest rate of currency
Media – composite aggregate of Sentiment + Disagreement – Intensity6.
Each factor above is constructed as a long/short portfolio. Each day, we rank currencies by their factor scores as
defined above and construct long/short portfolios by taking the top/bottom terciles. Currencies in each long/short
portfolio are weighted equally and held for 20-days following the approach of Jegadeesh and Titman (1993)7.
Figures 1 and 2 illustrate the performance of each factor for G10 and EM markets respectively8. The FX factors
simulated here are not intended to be ‘optimal’ or to maximize profits. Rather, the objective is to demonstrate that
active strategies can be constructed to extract specific premia that exist in currency markets and they serve as
benchmarks for our analysis when we incorporate media information. As a stand-alone factor, we can see from
Figures 1(C) and 2(C) that Media is generally uncorrelated to the other FX factors.
4 ‘Currency Momentum Strategies’ by Menkhoff, Sarno, Schmeling, Schrimp, BIS Working Papers No 366, December 2011 5 ‘Value and Momentum Everywhere’ by C. Asness, T. Moskowitz, L. Pedersen, The Journal of Finance, Vol. 68, No. 3, June 2013 6 We use the 28-day lookback indicator version. 7 ‘Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency’ by N. Jegadeesh and S. Titman, The Journal of Finance Vol. 48, No. 1 (Mar., 1993), pp. 65-91 8 We measure factor performance from 2013 onwards to span the period for which we have media data.
Information Classification: General 2906950.1.1.GBL State Street Corporation 6
IN PRACTICE: FX FACTORS AND MEDIA
Figure 1: FX factors, G10 currencies
(A) Cumulative return
(B) Performance statistics
Statistics Momentum Value Carry Media
Return (Ann) -1.5% 0.9% 0.0% 3.3%
Volatility (Ann) 5.1% 5.4% 7.3% 4.2%
Sharpe Ratio -0.3 0.2 0.0 0.8
t-stat -0.8 0.4 0.0 2.0
Turnover 17x 4x 0x 16x
Maximum Drawdown 22.4% 12.5% 17.3% 4.2%
(C) Returns correlation
Momentum Value Carry Media
Momentum 100%
Value -8% 100%
Carry -19% -21% 100%
Media -1% -1% -18% 100%
Source: State Street Global Markets®. Mar’13-September 2019, G10 currencies: AUD, CAD, CHF, EUR, GBP, JPY, NOK, NZD, SEK, USD
0.80
0.85
0.90
0.95
1.00
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Cum
ulat
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Ret
urn
Inde
x
Momentum Value Carry Media
Information Classification: General 2906950.1.1.GBL State Street Corporation 7
IN PRACTICE: FX FACTORS AND MEDIA
Figure 2: FX factors, EM currencies
(A) Cumulative return
(B) Performance statistics
Momentum Value Carry Media
Return (Ann) 2.1% 2.3% 2.5% 2.5%
Volatility (Ann) 5.4% 6.1% 6.9% 4.0%
Sharpe Ratio 0.4 0.4 0.4 0.6
t-stat 1.0 1.0 0.9 1.6
Turnover 15x 3x 0x 15x
Maximum Drawdown 11.2% 12.8% 15.0% 8.7%
(C) Returns correlation
Momentum Value Carry Media
Momentum 100%
Value -23% 100%
Carry -32% 6% 100%
Media 21% -32% -19% 100%
Source: State Street Global Markets®. Mar’13-September 2019, EM currencies: BRL, CLP, CNY, COP, CZK, HUF, IDR, INR, KRW, MXN,
MYR, PEN, PHP, PLN, RUB, THB, TRY, TWD, ZAR
0.80
0.85
0.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
Mar
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Cum
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urn
Inde
x
EM
Momentum Value Carry Media
Information Classification: General 2906950.1.1.GBL State Street Corporation 8
IN PRACTICE: FX FACTORS AND MEDIA
4. Combining traditional FX factors with media
Data and methodology
In the below tests, we employ a framework of creating a multi-factor score for each currency by combining a
currency’s factor score with its media score. Each day, we calculate a composite score for each currency by
summing the cross-sectional factor z-score with the cross-sectional media z-score i.e. factor z-score + media z-
score. We then rank the currencies by this composite score, and evenly allocate the long portion of our portfolio
with the top tercile of currencies, and we evenly allocate the short portion of our portfolio with the bottom tercile.
This long/short portfolio is then held for 20 days following the approach of Jegadeesh and Titman (1993). By
combining standard FX factors with media, we are capturing a currency’s factor desirability with what people are
saying about the currency in the media.
Results
Figures 3, 4 and 5 illustrate the factor performances of Momentum, Value and Carry respectively when combined
with media in G10 markets. All three factors show incremental benefits when media data is incorporated into their
construction. Taking Momentum as an example, Figure 3(D) shows that by including media information into the
Momentum factor (i.e. Momentum+Media), an additional gain of +2.5% return per year is achieved above stand-
alone Momentum. In addition, volatility of the factor drops 50bps (from 5.1% to 4.6% risk) while the maximum
drawdown reduces notably from 22.4% to 12.0% as can be seen from Figure 3(B), suggesting that the media-
enhanced factor is taking on more diversified currencies. From Figure 3(C), we can see that the performance
improvement is broad-based with most currencies outperforming their respective stand-alone counterparts when
media is taken into account.
Figure 3(E) illustrates the returns correlation of Momentum, Momentum+Media and Media. We can see that
Momentum+Media largely preserves its factor attribute as can be shown from the high correlation between
Momentum+Media and stand-alone Momentum. This factor preservation is consistent across all factors in both
G10 and EM markets (results for EM in Appendix section).
Information Classification: General 2906950.1.1.GBL State Street Corporation 9
IN PRACTICE: FX FACTORS AND MEDIA
Figure 3: Momentum + Media, G10 currencies
(A) Cumulative return
(B) Volatility and maximum drawdown (C) Attribution
(D) Performance statistics (E) Returns correlation
Statistics Momentum Momentum + Media
Excess
Return (Ann) -1.5% 1.0% 2.5%
Volatility (Ann) 5.1% 4.6% 3.5%
Sharpe Ratio -0.3 0.2 0.7
t-stat -0.8 0.6 1.8
Turnover 17x 16x N/A
Max. Drawdown 22.4% 12.0% N/A
Momentum Media Momentum +
Media
Momentum 100%
Media -1% 100%
Momentum + Media 74% 55% 100%
Source: State Street Global Markets®. Mar’13-Sep’19, G10 currencies: AUD, CAD, CHF, EUR, GBP, JPY, NOK,NZD, SEK, USD
0.80
0.85
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Momentum Momentum+Media
5.1%
22.4%
4.6%
12.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Volatility, ann. Max Drawdown
Momentum Momentum+Media
-1.5%
-1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
AUD CAD CHF EUR GBP JPY NOK NZD SEK
Ret
urn,
ann
.
Momentum Momentum+Media Excess
Information Classification: General 2906950.1.1.GBL State Street Corporation 10
IN PRACTICE: FX FACTORS AND MEDIA
Figure 4: Value + Media, G10 currencies
(A) Cumulative return
(B) Volatility and maximum drawdown (C) Attribution
(D) Performance statistics (E) Returns correlation
Value Value + Media Excess
Return (Ann) 0.9% 3.4% 2.5%
Volatility (Ann) 5.4% 4.8% 3.8%
Sharpe Ratio 0.2 0.7 0.7
t-stat 0.4 1.8 1.7
Turnover 4x 11x N/A
Max. Drawdown 12.5% 6.7 N/A
Value Media Value + Media
Value 100%
Media -1% 100%
Value + Media 73% 53% 100%
Source: State Street Global Markets®. Mar’13-Sep’19, G10 currencies: AUD, CAD, CHF, EUR, GBP, JPY, NOK,NZD, SEK, USD
0.90
1.00
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1.20
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Value Value+Media
5.4%
12.5%
4.8%
6.7%
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
Volatility, ann. Max Drawdown
Value Value+Media
-2.0%-1.5%-1.0%-0.5%0.0%0.5%1.0%1.5%2.0%2.5%
AUD CAD CHF EUR GBP JPY NOK NZD SEK
retu
rn, a
nn.
Value Value+Media Excess
Information Classification: General 2906950.1.1.GBL State Street Corporation 11
IN PRACTICE: FX FACTORS AND MEDIA
Figure 5: Carry + Media, G10 currencies
(A) Cumulative return
(B) Volatility and maximum drawdown (C) Attribution
(D) Performance statistics (E) Returns correlation
Carry Carry + Media Excess
Return (Ann) 0.0% 1.7% 1.8%
Volatility (Ann) 7.3% 5.6% 4.4%
Sharpe Ratio 0.0 0.3 0.4
t-stat 0.0 0.8 1.0
Turnover 0x 11x N/A
Max. Drawdown 17.3% 8.4% N/A
Carry Media Carry + Media
Carry 100%
Media -18% 100%
Carry + Media 80% 29% 100%
Source: State Street Global Markets®. Mar’13-Sep’19, G10 currencies: AUD, CAD, CHF, EUR, GBP, JPY, NOK,NZD, SEK, USD
0.80
0.85
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Carry Carry+Media
7.3%
17.3%
5.6%
8.4%
0.0%
5.0%
10.0%
15.0%
20.0%
Volatility, ann. Max Drawdown
Carry Carry+Media
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
AUD CAD CHF EUR GBP JPY NOK NZD SEK
retu
rn, a
nn.
Carry Carry+Media Excess
Information Classification: General 2906950.1.1.GBL State Street Corporation 12
IN PRACTICE: FX FACTORS AND MEDIA
5. Conclusions
The results of our analysis show that media information can be used to improve the risk-adjusted performance of
standard currency factors like Momentum, Value and Carry. The excess returns achieved by incorporating Media
is +2.5% per year for Momentum, +2.5% per year for Value, and +1.8% per year for Carry in G10 markets above
their respective stand-alone factors. In Emerging Markets, the excess return is +1.8% per year for Momentum,
+1.3% per year in Value, and +0.1% in Carry. These performance improvements are broad-based when media is
taken into account, with most currencies within a factor outperforming their stand-alone counterparts. The media-
enhanced versions also preserve their original factor attribute as shown by the high returns correlations with their
respective stand-alone factors. Finally, these gains are accompanied by lower returns volatilities and drawdowns,
suggesting increased diversification benefits from incorporating media. By combining standard FX factors with
media, we are capturing a currency’s factor desirability with what people are saying about the currency in the
media. As a stand-alone factor, Media is broadly orthogonal and uncorrelated to traditional currency factors in
general.
Information Classification: General 2906950.1.1.GBL State Street Corporation 13
IN PRACTICE: FX FACTORS AND MEDIA
6. References
N. Jegadeesh and S. Titman, ‘Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency’, The Journal of Finance Vol. 48, No. 1 (Mar., 1993), pp. 65-91 J. Binny, "Currency Management Style through the Ages," Journal of Alternative Investments, Winter 2005, 8 (3) 52-59 L. Menkhoff, L. Sarno, M Schmeling, A. Schrimp, ‘Currency Momentum Strategies’, BIS Working Papers No 366, December 2011 C. Asness, T. Moskowitz, L. Pedersen, ‘Value and Momentum Everywhere’, The Journal of Finance, Vol. 68, No. 3, June 2013
Information Classification: General 2906950.1.1.GBL State Street Corporation 14
IN PRACTICE: FX FACTORS AND MEDIA
7. Appendix
Figure A1: Momentum + Media, EM currencies
Source: State Street Global Markets®. Mar’13-September 2019, EM currencies: BRL, CLP, CNY, COP, CZK, HUF, IDR, INR, KRW, MXN,
MYR, PEN, PHP, PLN, RUB, THB, TRY, TWD, ZAR
(A) Cumulative Return
(B) Volatility and maximum drawdown (C) Attribution
(D) Performance Statistics (E) Strategy Correlations Momentum Momentum
+ Media Excess
Return (Ann) 2.1% 4.0% 1.8%
Volatility (Ann) 5.4% 4.8% 2.9%
Sharpe Ratio 0.4 0.8 0.6
t-stat 1.0 2.1 1.6
Turnover 15x 15x N/A
Max. Drawdown 11.2% 6.4% N/A
Momentum Media Momentum +
Media
Momentum 100%
Media 21% 100%
Momentum + Media 84% 60% 100%
0.90
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Momentum Momentum+Media
5.4%
11.2%
4.8%
6.4%
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
Volatility, ann. Max. Drawdown
Momentum Momentum+Media
-0.6%-0.4%-0.2%0.0%0.2%0.4%0.6%0.8%1.0%
BR
LC
LPC
NY
CO
PC
ZK
HU
FID
RIN
RK
RW
MX
NM
YR
PE
NP
HP
PLN
RU
BT
HB
TR
YT
WD
ZA
R
Ret
urn,
ann
.
Momentum Momentum+Media Excess
Information Classification: General 2906950.1.1.GBL State Street Corporation 15
IN PRACTICE: FX FACTORS AND MEDIA
Figure A2: Value + Media, EM currencies
Source: State Street Global Markets®. Mar’13-September 2019, EM currencies: BRL, CLP, CNY, COP, CZK, HUF, IDR, INR, KRW, MXN,
MYR, PEN, PHP, PLN, RUB, THB, TRY, TWD, ZAR
(A) Cumulative Return
(B) Volatility and maximum drawdown (C) Attribution
(D) Performance statistics (E) Returns correlation
Value Value + Media Excess
Return (Ann) 2.3% 3.6% 1.3%
Volatility (Ann) 6.1% 4.6% 3.5%
Sharpe Ratio 0.4 0.8 0.4
t-stat 1.0 2.0 1.0
Turnover 3x 10x N/A
Max. Drawdown 12.8% 4.5% N/A
Value Media
Value + Media
Value 100%
Media -32% 100%
Value + Media 82% 11% 100%
0.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
Mar
'13
Jun'
13
Sep
'13
Dec
'13
Mar
'14
Jun'
14
Sep
'14
Dec
'14
Mar
'15
Jun'
15
Sep
'15
Dec
'15
Mar
'16
Jun'
16
Sep
'16
Dec
'16
Mar
'17
Jun'
17
Sep
'17
Dec
'17
Mar
'18
Jun'
18
Sep
'18
Dec
'18
Mar
'19
Jun'
19
Sep
'19
Value Value+Media
6.1%
12.8%
4.6% 4.5%
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
Volatility, ann. Max. Drawdown
Value Value+Media
-1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
BR
LC
LPC
NY
CO
PC
ZK
HU
FID
RIN
RK
RW
MX
NM
YR
PE
NP
HP
PLN
RU
BT
HB
TR
YT
WD
ZA
R
Ret
urn,
ann
.
Value Value+Media Excess
Information Classification: General 2906950.1.1.GBL State Street Corporation 16
IN PRACTICE: FX FACTORS AND MEDIA
Figure A3: Carry + Media, EM currencies
Source: State Street Global Markets®. Mar’13-September 2019, EM currencies: BRL, CLP, CNY, COP, CZK, HUF, IDR, INR, KRW, MXN,
MYR, PEN, PHP, PLN, RUB, THB, TRY, TWD, ZAR
(A) Cumulative Return
(B) Volatility and maximum drawdown (C) Attribution
(D) Performance statistics (E) Returns correlation
Carry Carry + Media Excess
Return (Ann) 2.5% 2.6% 0.1%
Volatility (Ann) 6.9% 5.2% 3.4%
Sharpe Ratio 0.4 0.5 0.0
t-stat 0.9 1.3 0.1
Turnover 0x 9x N/A
Max. Drawdown 15% 10.2% N/A
Carry Media Carry + Media
Carry 100%
Media -19% 100%
Carry + Media 88% 8% 100%
0.85
0.90
0.95
1.00
1.05
1.10
1.15
1.20
Mar
'13
Jun'
13
Sep
'13
Dec
'13
Mar
'14
Jun'
14
Sep
'14
Dec
'14
Mar
'15
Jun'
15
Sep
'15
Dec
'15
Mar
'16
Jun'
16
Sep
'16
Dec
'16
Mar
'17
Jun'
17
Sep
'17
Dec
'17
Mar
'18
Jun'
18
Sep
'18
Dec
'18
Mar
'19
Jun'
19
Sep
'19
Cum
ulat
ive
Ret
urn
Inde
x
Carry Carry+Media
6.9%
15.0%
5.2%
10.2%
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
Volatility, ann. Max. Drawdown
Carry Carry+Media
-1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
BR
LC
LPC
NY
CO
PC
ZK
HU
FID
RIN
RK
RW
MX
NM
YR
PE
NP
HP
PLN
RU
BT
HB
TR
YT
WD
ZA
R
Ret
urn,
ann
.
Carry Carry+Media Excess
Information Classification: General 2906950.1.1.GBL State Street Corporation 17
IN PRACTICE: FX FACTORS AND MEDIA
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Information Classification: General 2906950.1.1.GBL State Street Corporation 18
IN PRACTICE: FX FACTORS AND MEDIA
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