CENTRAL BANK INTERVENTION IN THE ROMANIAN FOREIGN EXCHANGE MARKET. ESTIMATING A REACTION FUNCTION

CENTRAL BANK INTERVENTION IN THE ROMANIAN FOREIGN EXCHANGE MARKET. ESTIMATING A REACTION FUNCTION

M.Sc. Student: Bogdan RadulescuSupervisor: Prof. Moisa Altar

ACADEMY OF ECONOMIC STUDIESDOCTORAL SCHOOL OF FINANCE AND BANKING

2/21

Contents Romanian FOREX market Model of optimal intervention Data and stylized facts Empirical study

GARCH model for conditional variance Structural breaks Estimated reaction function

o Linear reaction functiono Probit models and asymmetrieso Ordered probit reaction function

Conclusions

3/21

Romanian FOREX Market Managed float regime since 1997

‘USD market’ 1997 – 28 Feb 2003 ‘EUR market’ starting with 3 Mar 2003

Since 2002 NBR is following a trade weighted basket of EUR and USD Initially weights 60% EUR - 40% USD Updated to 75% EUR - 25% USD in 2004

Conflicting objectives for exchange rate policy Depreciation for external competitiveness Nominal anchor to fix inflation expectations

NBR systematically intervened to achieve exchange rate stability

4/21

Model of Optimal Intervention In most empirical papers the reaction function is assumed

rather than derived Almekinders and Eijffinger (1996), Frenkel and Stadtmann

(2001), Frenkel, Pierdzioch and Stadtmann (2002) and Ito and Yabo (2004) derive an optimal reaction function by minimizing the loss function of the central bank

We follow their approach to derive the reaction function; in addition to the exchange rate level target in these papers, we explicitly introduce a volatility target

0,0],)([)( 2211 bawithbhssaELossE t

TtttttLoss function

tVtVtt

ttttLtLtt

ZIhh

iidhZIss

1

1 )1,0(~,Exchange rate model

5/21

Model of Optimal Intervention (2) Optimal intervention is a function of the deviation from

target, conditional variance and other variables that impact the exchange rate

Exchange rate target (similar to Ito and Yabo (2004)) Short term target

Medium term target

Long term target

Optimal intervention

])()([1

1122*

tVVLLtVtTtL

VLt Zaahbssa

baI

1, 32131221 aaasasasas LTt

MAtt

Tt

21 tSTt ss

20

1

1 20

1

k

ktMAt ss

)365

1( 00

ttSS tgtt

LTt

tttLTtt

MAtttt ZhssssssI 113112211

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6/21

Data and Stylized Facts Daily data Intervention frequency decreased

60-80% of trading days for 1997-2001, 36% in 2002-Feb 2003 and 18% in Mar 2003 – Mar 2004

probability of continued intervention: 50-70% in 1997-2001, 18% in 2002-Feb 2003 and 2.33% in 2003 – 2004)

1997-1999 were influenced by some difficulties 1997-1998 were low liquidity years for the interbank market Aug 1998 - Apr 1999 was a period of fast depreciation related to

the Russian crises and anticipation of difficulties with the peak of external debt service in 1999 (ROL lost 70% against USD in less than 9 months)

In the second half of 1999 a peak of external debt service led to near depletion of NBR reserves and high risk of default

We restrict the study to Jan. 2000 – Mar. 2004

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Data and Stylized Facts (2)USDROL (Level)

5000

15000

25000

35000

USDROL (Return)

-0.03-0.02-0.01

00.010.020.030.040.050.060.07

EURROL (Level)

35000

36000

37000

38000

39000

40000

41000

42000

EURROL (Return)

-0.015

-0.01

-0.005

0

0.005

0.01

0.015

NBR Net Purchase

-100-80-60-40-20

020406080

100

-7000

-5000

-3000

-1000

1000

3000

5000

7000

Daily Level Cumulated

Clients' Net Purchase

-80

-60

-40

-20

0

20

40

60

80

-2500-2000-1500-1000-50005001000150020002500

Daily level Cumulated

8/21

GARCH Model of VolatilityDependent variable: RUSD Dependent variable: REUR

Variable Coefficient Probability Variable Coefficient Probability

C 0.018932 0.0015 C -0.04547 0.0138

RUSD(-1) 0.205151 0.0000 REUR(-1) 0.211182 0.0000

RUSD(-2) 0.099797 0.0031 MA(4) 0.184343 0.0025

RUSD(-5) 0.309043 0.0000 INT 0.009862 0.0000

RUSD(-10) 0.194000 0.0000 CL 0.006336 0.0000

INT -0.00062 0.0027 REU 0.301495 0.0000

INT(-1) 0.001129 0.0000

CL 0.000643 0.0259

D02*REU -0.11656 0.0000

Conditional variance equation Conditional variance equation

C 0.000201 0.0000 C 0.007292 0.0061

ARCH(1) 0.156963 0.0000 ARCH(1) 0.097295 0.0000

GARCH(1) 0.79079 0.0000 GARCH(1) 0.715332 0.0000

INT -0.000021 0.0021 INT 0.000395 0.0000

INT(-1) 0.000025 0.0003

D02*REU2 0.010289 0.0003

9/21

GARCH Model of Volatility (2)

Statistic USD equation EUR equation

No. observations 812 271

R-squared 0.0072 0.5280

Box-Pierce Q for residuals [probability]

Q[1] 3.0153 [0.082] 0.4634 [0.496]

Q[5] 4.4132 [0.492] 2.8096 [0.590]

Q[10] 8.5909 [0.571] 13.511 [0.141]

Box-Pierce Q for squared residuals [probability]

Q[1] 2.0224 [0.155] 1.3577 [0.244]

Q[5] 2.1848 [0.823] 2.4546 [0.653]

Q[10] 3.3864 [0.971] 10.659 [0.300]

ARCH – LM test [probability]

LM[1] 2.013742 [0.1559] 0.086551 [0.7686]

LM[5] 2.296514 [0.8068] 2.677791 [0.7495]

USD variance

0

0.1

0.2

0.3

0.4

0.5

0.6

EUR variance

00.020.040.060.080.1

0.120.140.16

10/21

Structural Breaks

We use the Andrews (1993) Sup(Wald(t)) test to search for an unknown structural break over 2000 - Feb 2003

The structural break is identified on 27 Feb 2001

0

5

10

15

20

25

30

35

40

45

Wald 1% critical values

Below, all models are estimated for four samples: full USD sample (2000 – Feb 2003) pre-Feb 2001 (2000 – 27 Feb 2001) post-Feb 2001 (28 Feb 2001 – 28 Feb 2003) full EUR sample (Mar 2003 – Mar 2004)

Structural change on 28 Feb/ 3 Mar 2003 (the interbank market switched from trading USD to trading EUR)

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Linear Reaction Function

Full USD sample Pre-Feb 2001 Post-Feb 2001 Full EUR sample

Intercept 5.683759 [0.0000] 2.003236 [0.3714] 5.682659 [0.0001] 3.170819 [0.3166]

DTGT 0.462773 [0.0533] 0.473455 [0.1562] 0.545104 [0.0540] 0.438580 [0.0244]

DMA 2.018289 [0.0109] -1.083671 [0.4372] 2.826393 [0.0318] 4.259066 [0.0129]

RUSD/REUR -14.76290 [0.0000] -25.54292 [0.0047] -12.84341 [0.0000] -10.42077 [0.0016]

VOL -10.48182 [0.4942] 57.00400 [0.3629] -15.32803 [0.3663] -63.22980 [0.3227]

VOL*DUP 1.580189 [0.9208] - 6.013609 [0.7419] 103.3733 [0.0687]

CL -0.553072 [0.0000] -0.890303 [0.0000] -0.436131 [0.0000] -0.329649 [0.0007]

INT(-1) 0.074527 [0.0179] 0.053387 [0.3141] 0.055978 [0.1847] -

INT(-3) - - - 0.173438 [0.0130]

REU - - - -4.532524 [0.0028]

No. observations 801 295 505 254

R-squared [Adjusted] 0.2657 [0.2593] 0.4955 [0.4850] 0.1941 [0.1828] 0.2526 [0.2281]

Log likelihood -3116.459 -1071.867 -2006.518 -1028.964

BG serial corr. LM(1) 2.480461 [0.1153] 3.533897 [0.1708] 0.945211 [0.3309] 0.256490 [0.6125]

LM(5) 7.854545 [0.1644] 8.322209 [0.1393] 3.086386 [0.6867] 1.869896 [0.8668]

White heteroscedasticity 29.15172 [0.0100] 21.85852 [0.0391] 15.46979 [0.3468] 28.54144 [0.0272]

12111211131211 * ttttttttt INTCLDUPVOLVOLDTGTDMARINT

* White covariance matrix when the White test rejects the null of no heteroscedasticity

12/21

Linear Reaction Function (2)

LR test for the null of no structural break in Feb 2001 is 76.148 (8 df) - rejection of the null at 1%

The weights of different horizons in the overall target can be recovered from the estimated

parameters

LTt

MAtt

Tt sasasas 31221

3,2,1,321

ia ii

USDROL market EURROL market

Full sample Pre-Feb 2001 Post-Feb 2001 Full sample

DTGT 2.68% [0.39] - 3.36% [0.39] 2.90% [0.39]

DMA 11.71% [0.27] - 17.43% [0.18] 28.17% [0.08]

RUSD/REUR 85.61% [0.00] 100% 79.21% [0.00] 68.93% [0.00]

* Where the coefficient in the reaction function is insignificant, weight has been restricted to zero

* Standard errors computed with the ‘delta’ method

13/21

Probit Reaction Functions Estimation of the reaction function as a discrete choice

model is recommended because intervention is a ‘zero inflated’ process

Some researchers estimate separate probit models for ‘buy interventions’ and ‘sell interventions’ to search for possible asymmetries (Frenkel and Stadtmann (2001), Frenkel, Pierdzioch and Stadtmann (2002), Kim and Sheen (2000))

We assume the decision to intervene can be written:

LR test for the null of no structural break in Feb 2001 Buy interventions: 49.159 (8 df) – significance level 0.00 Sell interventions: 41.861 (8 df) – significance level 0.00

0,1

0,0*

*

t

tt

I

IINTBUY

0,1

0,0*

*

t

tt

I

IINTSELL

14/21

Probit for ‘Buy Interventions’Full USD sample Pre-Feb 2001 Post-Feb 2001 Full EUR sample

Constant -0.6417 [0.0000] -0.0027 [0.9934] -0.7559 [0.0000] -2.2643 [0.0004]

DTGT 0.0235 [0.3576] 0.1550 [0.0032] 0.0130 [0.6722] 0.1008 [0.0162]

DMA -0.2728 [0.0026] -0.2260 [0.3761] -0.3334 [0.0171] 0.2252 [0.3040]

RUSD/REUR -1.0867 [0.0004] -4.9484 [0.0004] -0.8583 [0.0065] -0.5968 [0.2167]

GARCH -1.1138 [0.4779] -10.8969 [0.3826] -0.1220 [0.9419] 4.0349 [0.7076]

GARCH*DUP -0.4005 [0.8136] - -1.1129 [0.5456] -3.3417 [0.7262]

CL -0.0475 [0.0000] -0.1057 [0.0000] -0.0326 [0.0000] -2.7E-08 [0.0170]

INTBUY[-1] 0.5800 [0.0000] - 0.5875 [0.0000] -

INTBUY[-2] 0.2051 [0.0434] - 0.3853 [0.0024] -

INTBUY[-3] - - - 0.8686 [0.0063]

REU - - - -0.2788 [0.0688]

REU2 - - - 0.2724 [0.0324]

Observations 802 296 506 257

% 0s/ % 1s 51.62%/ 48.38% 40.88%/ 59.12% 57.91%/ 42.09% 89.49%/ 10.51%

LogL -452.5329 -141.3202 -289.4118 -65.9744

LogL0 -555.4825 -200.2182 -344.3817 -86.3667

Chi-square [probability] 205.8992 [0.0000] 117.7961 [0000] 109.9399 [0.0000] 40.7846 [0.0000]

McFadden LRI 0.1853 0.2942 0.1596 0.2361

Cramer 0.2310 0.3466 0.2001 0.2037

* Marginal effects have the same signs as estimated coefficients

15/21

Probit for ‘Sell Interventions’Full USD sample Pre-Feb 2001 Post-Feb 2001 Full EUR sample

Constant -1.3460 [0.0000] -0.1602 [0.6445] -1.8350 [0.0000] -2.0564 [0.0153]

DTGT -0.1162 [0.0012] -0.1863 [0.0017] -0.0556 [0.2690] -0.1042 [0.0513]

DMA -0.4372 [0.0011] 0.2506 [0.3528] -0.8022 [0.0061] -1.0251 [0.0139]

RUSD/REUR 1.5560 [0.0020] 2.9098 [0.0449] 1.2776 [0.0176] 2.2400 [0.0037]

GARCH -12.6403 [0.0685] -21.3422 [0.0465] 0.0188 [0.9971] -145.1330 [1.0000]

GARCH*DUP 7.4653 [0.2767] - -3.4556 [0.5363] 120.2473 [1.0000]

CL 0.0509 [0.0000] 0.1262 [0.0000] 0.0251 [0.0073] 3.84E-08 [0.0366]

INTSELL[-1] 0.4068 [0.0107] - 0.5235 [0.0429] -

REU - - - 1.0570 [0.0176]

REU2 - - - -0.3371 [0.3604]


% 0s/ % 1s 86.53%/ 13.47% 76.69%/ 23.31% 92.29%/ 7.71% 95.33%/ 4.67%

LogL -240.5946 -106.8997 -113.9940 -28.8274

LogL0 -316.9154 -160.7294 -137.4129 -48.4854

Chi-square [probability] 152.6416 [0.0000] 107.6594 [0.0000] 46.83772 [0.0000] 39.3160 [0.0000]

McFadden LRI 0.2408 0.3349 0.1704 0.4054

Cramer 0.2191 0.3537 0.1123 0.2725


16/21

Predictions from probit modelsFull USD sample Pre-Feb 2001 Post-Feb 2001 Full EUR sample

Buy interventions

Actual/ Predicted 0 1 0 1 0 1 0 1

0 301 113 83 38 226 67 229 1

1 114 274 31 144 86 127 22 5

% correct 72.53% 70.80% 72.81% 79.12% 72.44% 65.46% 91.24% 83.33%

% of interventions predicted 70.62% 82.29% 59.62% 18.52%

% of no interventions predicted 72.71% 68.59% 77.13% 99.56%

Sell interventions

0 679 15 214 13 466 1 244 1

1 88 20 34 35 37 2 9 3

% correct 88.53% 57.14% 86.29% 72.92% 92.64% 66.67% 96.44% 75.00%

% of interventions predicted 18.52% 50.72% 5.13% 25.00%

% of no interventions predicted 97.84% 94.27% 99.79% 99.59%

Gain over naïve prediction

Naïve predictions 802 0 0 296 506 0 257 0

% naïve correct 51.62% 59.12% 57.91% 89.49%

% buy correct 71.70% 76.69% 69.76% 91.05%

% buy gain 20.07% 17.57% 11.86% 1.56%

% sell correct 87.16% 84.12% 92.49% 96.11%

% sell gain 0.62% 7.43% 0.20% 0.78%

17/21

Ordered Probit Reaction Function

We assume that NBR compares benefits of reducing loss of no intervention to fixed costs of intervention and intervenes only when benefits are higher than costs

gives a neutral band of no intervention

2*

2*

1

1*

,2

,1

,0

t

t

t

t

I

I

I

INTORD

],[ 21

18/21

Ordered Probit Reaction Function (2)

1

2


DTGT 0.0337 [0.1103] 0.1630 [0.0007] 0.0177 [0.4880] 0.0921 [0.0014]

DMA -0.0110 [0.8838] -0.2891 [0.1988] -0.0897 [0.4468] 0.3465 [0.0449]

RUSD/REUR -0.9321 [0.0002] -3.7258 [0.0018] -0.8623 [0.0012] -0.9526 [0.0090]

GARCH -1.0873 [0.4291] 12.2069 [0.2028] -0.5431 [0.7212] 6.4894 [0.4425]

GARCH*DUP 0.9606 [0.5058] - 0.2618 [0.8735] 1.5873 [0.8305]

CL -0.0420 [0.0000] -0.1004 [0.0000] -0.0267 [0.0000] -0.0300 [0.0006]

CL[-1] - -0.0297 [0.0064] - -

INTORD[-1] 0.3671 [0.0000] - 0.4641 [0.0000] -

INTORD[-2] - - 0.1861 [0.0393] -

REU - - - -0.4203 [0.0018]

REU2 - - - 0.1769 [0.1398]

Lower limit -0.7177 [0.0000] -0.2932 [0.3445] -0.6800 [0.0004] -1.4630 [0.0009]

Higher limit 0.6175 [0.0000] 0.4497 [0.1482] 1.1407 [0.0000] 2.2253 [0.0000]


% 0s / % 1s / %2s 13.4% / 38.1% / 48.3% 23.3% / 17.5% / 59.1% 7.7% / 50.1% / 42% 4.6% / 84.8% / 10.5%

LogL -701.1833 -209.5040 -412.0492 -104.2750

LogL0 -791.0948 -281.4290 -457.7557 -133.4862

Chi-square [probability] 179.8230 [0.0000] 143.8499 [0.0000] 91.4131 [0.0000] 58.4223 [0.0000]

McFadden LRI 0.1137 0.2556 0.0998 0.2189


19/21

Ordered Probit Reaction Function (3) LR test for no structural break in Feb 2001 is 146.914 (9 df) The weights of different horizons in the overall target

Predictions of ordered probit reaction function


DTGT - 4.19% [0.39] - 6.62% [0.38]

DMA - - - 24.91% [0.14]

RUSD/REUR 100% 95.81% [0.00] 100% 68.47% [0.00]

Actual 0 1 2 % correct% interventions

correctly predicted

Full USD sample

0 15 11 1 55.56%

63.10%1 61 146 89 49.32%

2 32 149 298 61.95%

Pre-Feb 2001

0 49 16 12 63.64%

86.89%1 0 0 0 -

2 20 36 163 73.76%

Post-Feb 2001

0 0 1 0 0.00%

52.78%1 32 198 80 63.87%

2 7 55 133 67.51%

Full EUR sample

0 0 0 0 -

0.00%1 12 218 27 84.82%

2 0 0 0 0.00%

20/21

Conclusions The exchange rate level target had a highly

significant effect on NBR interventions NBR intervened mainly to smooth out exchange rate

fluctuations (“leaning-against-the-wind”) Short sighted – focused on daily fluctuations Monthly fluctuations gained importance in the last year

NBR also pursued a nominal depreciation policy, but depreciation had a small weight in its objectives

Volatility had an insignificant effect on interventions Net purchases of clients from the banks had a

significant impact on interventions; NBR used interventions to cover a part of the FX market’s deficit with clients

Asymmetry between buying interventions and selling interventions

21/21

Future Developments

Further study of the influence of costs on intervention behavior

Objective of building foreign exchange reserves

Links to money market and NBR’s sterilization operations

Documents

CENTRAL BANK INTERVENTION IN THE ROMANIAN FOREIGN EXCHANGE MARKET. ESTIMATING A REACTION FUNCTION