Download A study on Foreign Exchange Rate Volatility in India and Use of

A study on Foreign Exchange Rate Volatility in
India and Use of Technical Analysis in
Hedging the Exposure
Prof. R. Nagendran1
Abstract
International trade is riskier than the domestic trade, due to many reasons. The most
important risk is the exchange rate risk and the resultant exposure. Any risk management
tool like hedging is costlier often, if all the transaction exposures are hedged. The importers
have to hedge only when the local currency depreciates, and the exporters when it appreciates
otherwise hedging cost is an added burden and will be substantial, and will erode the profit.
In India, the volatilities of the Foreign Exchange rates of major currencies are very high, for
example, the Euro depreciated 9.59% during 2000 but appreciated by 14.69% during 2003,
and GB Pound depreciated 3.42% during 2005, appreciated by 4.28% during 2006 and again
depreciated by 0.16% by August 2007. These volatilities are due to many factors like
fluctuations in FII, FDI, interest rate differentials between the countries, inflation rates etc.
The need of the hour is the forecasting accuracy of the exchange rates to decide what to hedge
and what not; when to hedge and when not. This paper deals with the Foreign Exchange rate
movements in India for the major currencies like US dollar, GB Pound Sterling, Euro and
Japanese Yen from 1999 to August 2007 and attempts to give solutions to this exchange rate
challenge using Technical Analysis.
Introduction
Glo bali zati on
o ffers
many
opportunities to our Indian traders,
manufacturers and investors like raising
capital with lower interest rates through
ECBs, FCCBs, FDI inward, extended market
through exports, FDI outwards, ADRs GDRs
etc., as well as challenges like cheap
imports / dumping of goods from foreign
nation s wi th bette r i nfrastru ctural
facilities and modern technologies. Due to
INR appreciation, even the highly efficient
company like Infosys Technologies Ltd.
achieved a reduced earnings of Rs. 3773
crore than the guidance of Rs.3896 – 3913
crores [63] during last fiscal. This has been
in spite of higher USD revenue of USD 928
million than the guidance of 904 -908. The
total revenue is US$3090 million for the
year ended 31.3.2007. Indian total Current
Account shows a debit balance of US$
1. Chief Functional Consultant, J Soft Technologies, P. Ltd., Bangalore.
E-mail:[email protected], [email protected]
Journal of Contemporary Research in Management, January - March 2008
33
255,862 millions and credit balance of US$
246,253 millions for the year 2006-07 [65].
Trade between India and UK is poised to
reach 1.5 billion pounds from the current
level of 900 million pounds [61] and with
Japan US$ 20 billion by 2010 [62]. The above
volume of foreign exchange in India reveals
the need and importance for good foreign
exchange management.
When considering challenges
confronted by our Indian players, though
there remain many, this paper considers
the exchange rate risk and exposure as
the most important challenge faced by them.
1. Exchange Rate Risk and
Exchange Rate Exposure
Foreign exchange risk is the amount
of change in the foreign exchange rate in
the opposite direction of our expectation.
For example, the EUR appreciated from
Rs.49.50 on 3.9.2003 to Rs. 57.90 on
13.1.2004, within 4 months and 10 days. If
a trader has already imported the raw
material / goods on 3.9.2003 and has to pay
say EUR (€) 1,00,000 on 13.1.2004, he/she
has to pay an extra amount of Rs.8.40 per
Euro, which is the risk involved. The
transaction exposure is the total loss
amounting to Rs. 8,40,000.
The loss is of the order of 16.97% of
the transaction value, for no mistake of
him; his entire profit margin may wipe off.
The Table No.1 and Charts No.1 below
reveal the high volatility in exchange rates.
TABLE No.1
Percentage Change in Exchange Rates
USD ($)
GBP (£)
EUR (€)
JPY (¥) (100)
Mean
Range %
Mean
Range %
Mean
Range % Mean
Range %
1999
43.08
2.83
69.67
8.24
45.89
15.33
38.04
22.65
2000
44.95
7.59
68.06
11.97
41.49
15.24
41.73
10.39
2001
47.19
4.22
67.99
10.19
42.29
12.24
38.87
12.01
2002
48.60
2.26
73.03
12.22
45.94
18.89
38.88
16.07
2003
46.56
5.91
76.15
12.27
52.69
14.82
40.22
10.89
2004
45.33
6.77
83.06
9.81
56.36
13.56
41.90
10.09
2005
44.11
6.87
80.22
10.76
54.86
12.43
40.08
14.67
2006
45.33
6.35
83.65
14.29
57.01
12.70
39.02
11.10
*2007
42.11
10.38
83.52
9.02
56.39
8.09
35.15
16.42
* Up to 31st August 2007
34
Journal of Contemporary Research in Management, January - March 2008
The above figures indicate that the
exchange rates fluctuate most of the time
in double digits. Normally the Foreign
Exchange market rates quoted in four
decimal points as the volume of dealing is
high. In this situation, one can imagine
the high volatility and risk involved by our
foreign exchange users. The foreign
exchange rates referred are trading rates
in Indian Rupee (INR) for one foreign
currency USD / EUR / GBP and for
Japanese Yen (JPY) it is for 100 JPY.
Whenever it is JPY, the rates quoted only
for 100 no. of JPY.
Chart No. 1
Daily Exchange Rates Mid Quotes from 1999 to 2007
1.1 Types of Exposures
Though the above example called
transaction exposure, there remain other
types known as Translation exposure and
Economic exposure, which are balance
sheet related and future cash flows of the
firm due to its activities.
1.1.1 Transaction exposure – arises
due to the cost or proceeds of settlements
of future payments or receipts.
1.1.2 Translation exposure – arises
due to change in the values of assets and
liabilities of the firm.
1.1.3 Economic exposure – arises due
to the future cash flows of the firm due to
its activities.
1.2 Exposure Management
Th ese expo sure s are no rmal ly
managed either by Financial Contracts or
by Operational techniques.
Journal of Contemporary Research in Management, January - March 2008
35
1.2.1 Financial Contracts
Forward Market Hedge, Money Market
Hedge, Option Market Hedge and Swap
Market Hedge
1.2.2 Operational Techniques
Choice of invoice currency, Lead / lag
strategies and Netting
2. Hedging Decision
This paper deals first with the need
for a hedge, whether to hedge or not, when
to hedge and when not. An exporter need
not hedge if he/she feels that the home
currency (INR) is depreciating and expects
the same trend to continue in future also.
Still he/she have to watch keenly any new
de velo pmen t, w hich may cau se the
directional change. Nevertheless, in this
situation, an importer has necessarily
hedge if the expected depreciation is
considerable. If home currency appreciates,
the reverse is true that an exporter has to
hedge. However, how one can forecast
about the direction of the exchange rate?
This is an important decision for any
trader. In management, the decision has
to be taken rationally, using analytical and
conceptual manner. The approaches used
for this purpose are broadly classified into
a) Fundamental b) Technical
3. Fundamental Analysis
This involves an extensive analysis of
the economy of the two nations whose
currencies are under study, the flow of the
cu rren cies between the cou ntri es
concerned, and the factors affecting the
future Currency flo ws. Balance of
36
Paymen ts, the relative pri ce l evel s,
interest rates, FII and FDI etc are a few
important factors that affect the exchange
rate. There are man y co ncepts and
theories like Purchasing Power Parity (PPP)
Theory, Interest Rate Parity Theory, Fisher
Effect and International Fisher Effect, and
Expectation Theory that are a few worth
mentioning. This type of analysis is
important but little bit difficult to get the
data and monitoring the changes of them.
4. Technical Analysis
This analysis uses the historical data
of the exchange rates and the charts
compiled with those data. The analysts are
also called as chartists. They believe that
trends persists for quite some time and the
shift in demand and supply are gradual and
technical analysis can detect these shifts
rather early and hence provides clues to
future price movements. The Efficient
Marke t Theory (EMT) i s against the
Technical Analysis, which says that future
rates cannot be predicted. Inefficiency of
the market like slow information spread
rather than instantaneo us, not all
investors / traders are having the same
efficiency and knowledge, different tax
structures, transaction costs etc., results
in the predictability of the future exchange
rates, with reasonable accuracy. Many
empirical studies proved that future prices
could be predicted. This paper is a try in
this direction and many of the time, the
exchange rates were predictable using the
charts. This paper used charts like EMA,
ROC, and MACD. However, didn’t use
Stochastic, RSI and Williams % R charts,
as daily high and low rates are not
available, only the closing prices are
available.
Journal of Contemporary Research in Management, January - March 2008
5. Methodology
MACDA (n) =
5.1 Data
The exchange rates for US Dollar ($),
Euro (€), GB Pound (£) and Japanese Yen
(¥) from 1.1.1999 to 31.08.2007 are collected
from Reserve Bank of India website [65].
As only the mid quotes are available, the
same is used in our study. There are 2019
rates for each foreign currency totaling to
8076 rates.
MACD (n-1) +
[k * (MACD (n)
MACD (n-1)

where n is the current period

k is a smoothing constant

and 9 is the number of MACD data
points used to calculate the MACDA
Though there are many combinations
of MACD, in our study 12 DEMA and 26
DEMA are used.
5.2 Techniques
5.2.1 Exponential Moving Averages
Exponential Moving Averages (EMA) are
calculated using ordinary moving averages
method by adding the latest data and
eliminating oldest data and the exponent
is calculated by dividing two by the length of
the period of Moving Average (MA).
The selection of the period depends
upon the cycle and the variable and no
single solution is available as on now. 12,
13, 21, 50, 89, 150 and 200 days are some
of the lengths of the MAs that are used in
this study. About 56,532 Exponential
Moving Averages have been calculated. For
each EMA about 6 steps are performed
making the total calculations more than
3, 39,000.
5.2.2 Moving Average Convergence and
Divergence
Moving Average Convergence and
Divergence (MACD) is calculated by
subtracting 26 DEMA from 12DEMA. The
smo othe ned tren d li ne o f above is
calculated by the following formula
5.2.3 Rate of Change
Rate of Change (ROC) is one of the
leading indicators and is calculated by
dividing the current rate by the exchange
rate of the predetermined time span. It is
an oscillator without boundaries. In our
study, 12 day ROC and 25 day ROCs are
used. The trend line of ROC is estimated
and plotted to identify the signal.
5.3 Signals
Buy and Sell signals are generated
using the above methods and the direction
of the future exchange rates are predicted.
Buy signal means the home currency is
expected to depreciate against the other
referred currency say USD / EUR / GBP /
JPY. This means that one has to give more
home currency (INR) to buy a foreign
currency in future dates. If you buy a USD
/ EUR / GBP / JPY now you can sell it at a
higher rate in future. (This study ignores
spread between the buying rate and selling
rate as our study is for hedging only). Thus
buying is profitable. The importers with
credit purchase have to hedge and the
exporters of credit sales are happy. On the
Journal of Contemporary Research in Management, January - March 2008
37
contrary, the Sell signal is generated when
the techniques predict the home currency
is expected to appreciate in future. Thus,
the credit exporters have to hedge.
The sample signals are shown in the
Chart Nos. 2 & 3 below, as the page limitation does not allow showing all the
Charts.
Chart No. 2
EMA Chart for the Exchange Rates of US $ from 1999 to 2007
Chart No. 3
USD Charts from 16.05.07 to 30.08.07
38
Journal of Contemporary Research in Management, January - March 2008
5.4 Testing Method
Payoff is defined as the difference
between the foreign exchange rates at the
time of first SELL signal and at the time of
first BUY signal. A sample of the signals
obtained by various techniques is given in
Annexure I. The number of signals
obtained by different methods always
varies. The number of signals obtained by
13 DEMA is higher than the 21 DEMA,
which is more than the 200 DEMA. The
signal obtained by ROC is normally higher
than the MACD signals, which can be
easily observed by the Chart No. 3 shown
in the above page.
To test th e effectiven ess of the
techniques used, the following payoffs are
measured:
1. The payoffs obtained by buying a foreign
currency on 1.11.1999 and selling the
same on 31.08.2007 for all the above
four currencies.
Journal of Contemporary Research in Management, January - March 2008
39
2.
The payoffs of the different signals
obtained by 12 DEMA, 13 DEMA,
21
DEMA, 26 DEMA, 50 DEMA, 89 DEMA,
150 DEMA and 200 DEMA have been
measured and totaled.
3.
Similarly, payoffs of 12 D ROC, 25 D
ROC, and MACD (12 – 26) have been
measured and totaled.
4.
5.
Payoff is calculated assuming of
buying one foreign currency at the
price of first “BUY” signal and selling
the same at the pri ce o f ne xt
immediate “SELL” signal for the period
1.11.1999 until 31.08.2007.
If the foreign exchange rate at the
time of SELL signal is higher than the
rate at the time of BUY signal then the
payoff is positive and if otherwise, it
is negative.
6.
If the signal is wrong, the resultant
negative payoffs are deducted from the
positive payoffs by the correct signals
and totaled.
The resultant payoffs are tabulated in
the Table No.6 in the next Chapter.
6. Predictions
The number of signals obtained by
various methods are more than 3000 for
the above period of study and so explaining
all the signals individually are tedious and
out of scope. Hence, the results are
consolidated, analyzed and tabulated below
for better understanding.
Table No. 2
No. of Positive Payoffs and negative Payoffs generated by the
Signals produced by various Technical Analysis Methods
12 DEMA USD
GBP
EUR
JPY
13 DEMA USD
GBP
EUR
JPY
21 DEMA USD
GBP
EUR
JPY
40
Positive
Payoffs
Negative
Payoffs
Zero
Payoff
No. of
Signals
No.
%
No.
%
No.
%
No.
%
37
42
39
47
36
37
34
43
23
33
26
36
24.18
26.58
23.49
27.98
24.83
24.83
21.79
26.88
23.47
28.70
20.63
29.75
104
115
126
118
98
111
120
115
71
81
98
84
67.97
72.78
75.90
70.24
67.59
74.50
76.92
71.88
72.45
70.43
77.78
69.42
12
1
1
3
11
1
2
2
4
1
2
1
7.84
0.63
0.60
1.79
7.59
0.67
1.28
1.25
4.08
0.87
1.59
0.83
153
158
166
168
145
149
156
160
98
115
126
121
100
100
100
100
100
100
100
100
100
100
100
100
Journal of Contemporary Research in Management, January - March 2008
Positive
Payoffs
Negative
Payoffs
Zero
Payoff
No. of
Signals
No.
%
No.
%
No.
%
No.
%
26 DEMA USD
16
20.78
59
76.62
2
2.60
77
100
GBP
29
28.71
71
70.30
1
0.99
101
100
EUR
27
24.32
83
74.77
1
0.90
111
100
JPY
33
31.13
72
67.92
1
0.94
106
100
9
27.27
22
66.67
2
6.06
33
100
GBP
15
17.05
72
81.82
1
1.14
88
100
EUR
16
19.28
66
79.52
1
1.20
83
100
JPY
15
20.27
58
78.38
1
1.35
74
100
89 DEMA USD
6
30.00
13
65.00
1
5.00
20
100
GBP
9
14.52
52
83.87
1
1.61
62
100
EUR
12
17.65
55
80.88
1
1.47
68
100
JPY
8
13.56
49
83.05
2
3.39
59
100
150 DEMA USD
4
40.00
5
50.00
1
10.0
10
100
GBP
11
19.64
44
78.57
1
1.79
56
100
EUR
7
14.58
40
83.33
1
2.08
48
100
JPY
7
12.96
46
85.19
1
1.85
54
100
200 DEMA USD
4
26.67
10
66.67
1
6.67
15
100
GBP
6
13.64
37
84.09
1
2.27
44
100
EUR
6
15.00
33
82.50
1
2.50
40
100
JPY
6
13.04
39
84.78
1
2.17
46
100
USD
43
21.94
142
72.45
11
5.61
196
100
GBP
68
34.34
129
65.15
1
0.51
198
100
EUR
56
24.56
170
74.56
2
0.88
228
100
JPY
63
30.73
140
68.29
2
0.98
205
100
12D ROC USD
247
50.20
198
40.24
47
9.55
492
100
GBP
279
58.61
196
41.18
1
0.21
476
100
EUR
301
60.20
196
39.20
3
0.60
500
100
JPY
295
58.42
205
40.59
5
0.99
505
100
25D ROC USD
319
65.37
108
22.13
61
12.5
488
100
GBP
351
74.84
116
24.73
2
0.43
469
100
EUR
362
73.43
126
25.56
5
1.01
493
100
JPY
356
73.40
114
23.51
15
3.09
485
100
50 DEMA USD
MACD
Journal of Contemporary Research in Management, January - March 2008
41
It may be observed from the above table
that EMAs are not giving enough success
rates, as the Positive Payoffs is as low as
12.96 to 40% only in spite of about 2910
total signals. The method MACD is little
better as it varies from 21.94% to 34.34% .
The real fruitful method is ROC, which
gives a success rate ranging from 50.20%
to 74.84% . In particular, 25 day ROC has
been so great in predicting the directional
changes of the foreign exchange rates with
a minimum success rate of 65.37% and
maximum of 74.84% in spite of as high as
1935 signals generated by it. The sample
signals generated by ROC are already
shown in the Chart No.3 above.
Though EMA method has given least
success rate, it i s evide nt from the
following Table No. 3 and Table No. 4 that
the method still works and be useful in
getting better payoff than just buy and hold
strategy in a long run.
TABLE NO. 3
Comparison of Payoffs of various methods and the actual Payoffs
from 1.11.1999 to 31.08.07
USD($)
EUR(€)
GBP(£)
JPY(¥)
BUY & HOLD
AMOUNT
-2.4202
10.2311
11.2335
-6.3950
%
-5.61
22.23
15.75
-15.36
12 DEMA
AMOUNT
5.8687
5.1461
11.2580
-4.1801
%
13.60
11.18
15.79
-10.04
13 DEMA
AMOUNT
6.0800
5.8185
13.9372
-5.0153
%
14.09
12.64
19.54
-12.05
21 DEMA
AMOUNT
5.3530
7.2987
16.5171
-1.4444
%
12.41
15.86
23.16
-3.47
26 DEMA
AMOUNT
5.5045
8.5982
14.2874
0.3469
%
12.7565
18.6852
20.0338
0.8334
50 DEMA
AMOUNT
7.53
6.43
6.29
0.18
%
17.4448
13.9762
8.8217
0.4351
89 DEMA
AMOUNT
7.0698
4.8441
-0.0735
-5.1373
%
16.38
10.53
-0.10
-12.34
150 DEMA
AMOUNT
6.7298
5.6657
-2.0788
-8.0497
%
15.60
12.31
-2.91
-19.34
200 DEMA
AMOUNT
5.8498
5.5645
0.8878
-11.8052
%
13.56
12.09
1.24
-28.36
MACD 12-26
AMOUNT
0.4924
-11.0384
8.8558
-6.0213
%
1.14
-25.58
20.52
-13.95
12 D ROC
AMOUNT
-0.2256
16.7374
12.9001
8.6468
%
-0.52
38.79
29.90
20.04
25 D ROC
AMOUNT
18.3911
80.492
96.0514
61.0948
%
42.62
174.92
134.68
146.77
42
Journal of Contemporary Research in Management, January - March 2008
From the above Table No.3, it may be
observed that a person buying a US Dollar
on first November 1999 and hold it till
31.08.2007 and sell it at the market rate
might have lost Rs.2.42 and one with Euro
gained Rs.10.23, the GB Pound holder
earned the highest of payoff of Rs.11.23 and
the Japanese Yen holder lost Rs.6.40. On
the other hand, the Technical analyst
might have earned a positive payoff of Rs.
5.35 to 18.39 in USD market, which is more
by 42.62 % at the maximum payoff, in GB
Pound Sterling, he might have gained
around 134.68% and in the Japanese Yen
market, about 146.77% higher than the
non-technical person is. Contrarily the
Chartist might have lost about 15% in the
Euro Market. This is not the mistake of
the method but due to immature market
for EUR. (EUR was introduced to the world
fin anci al marke ts as an accounting
currency in 1999 and launched as physical
coins and banknotes in 2002). If we
consider EUR from January 2003 till
August 2007 almost all the EMAs give better
payoffs than the actual buy and hold policy
which is shown below in Table No. 4
Table No. 4
EUR (€)
BUY & HOLD
AMOUNT
5.6500
%
11.23
12 DEMA
AMOUNT
6.6100
50 DEMA
AMOUNT
7.67
%
13.14
%
15.2455
AMOUNT
7.0900
AMOUNT
7.0698
%
14.09
%
16.38
AMOUNT
7.0500
AMOUNT
6.7298
%
14.01
%
15.60
AMOUNT
7.6000
AMOUNT
5.8498
%
15.1063
%
13.56
13DEMA
21 DEMA
26 DEMA
89 DEMA
150 DEMA
200 DEMA
7. Conclusion
Many empirical studies conducted
abroad have been of the conclusion that
profit associated with using several of these
forecasts (Technical Analysis) seem too
good to be explained by chances. Some
important papers by Richard M. Levich
(1980) [50], Blume, Easley, and O’Hara
(1994) [9], De Long et al. (1991) [29], Beja
and Goldman (1980) [47], Schulmeister
(1988) [47] etc are in favour of Technical
Analysis. This study also opines the same
and concludes that using Technical
Journal of Contemporary Research in Management, January - March 2008
43
Analysis is really working in enhancing the
payoffs of the user. Exponential Moving
Averages have been unsuccessful many
times. In spite of it has increased the payoff
many folds than just buy and hold strategy
in all the samples and for all currencies
under study. Thus, the method is working
and profitable but may not be up to the
expectations. The reason being, it is a
lagging indicator. It can be combined with
other indicators to get better output than
this. Rate of Change technique has been
so early to predict the direction of the
foreign exchange rates and phenomenally
successful as it is an oscillator and a
momentum indicator.
Thus, it is happy to conclude that the
exporters and importers may use Technical
Analysis to decide what to hedge and when
to hedge. When a country like US sneezes,
Indians get cold and their sub-prime
mortgages problem and the rate cut by
Federal not only affects US Economy but
also foreign exchange flows to India
resulting our INR to appreciate heavily
against USD. The coming era of hot money
flow to India and RBI’s move towards fuller
convertibility will lead only to an increase
in the volatility of INR against major
currencies. Hence need of the our is a good
method to predi ct the direction al
movements of the foreign exchange rates
for which Technical Analysis is really an
useful method. By combining, a few more
methods of Tech nical An alysis w ill
definitively very useful.
This paper is not against the EMT; but
in real world, imperfection and inefficiency
do exit which makes the foreign exchange
44
rates predictable. Un til we achie ve
perfection and efficiency in our markets,
foreign exchange rate will continue to be
predictable.
References
1.
Achelis, Steven B., Technical Analysis
from A to Z, 2001, (McGraw Hill, Inc.,
New York, NewYork).
2.
Adrian Buckley, (2001), Multinational
Finance, New Delhi, Prentice-hall of
India Private Ltd. 3e.
3.
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