Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 2 https://isni.org/isni/0000000404811396, International Monetary Fund

References

  • Behera, H. K. (2011). Onshore and offshore market for Indian rupee: recent evidence on volatility and shock spillover. Macroeconomics and Finance in Emerging Market Economies, 4 (1), 4355.

    • Search Google Scholar
    • Export Citation
  • BIS (2019). Triennial Central Bank Survey of Foreign Exchange and Over-the-counter (OTC) Derivatives Markets in 2019.

  • Cadarajat, Y. & Lubis, A. (2012). Offshore and onshore IDR market: an evidence on information spillover. Bulletin of Monetary Economics and Banking, April, pp 32347.

    • Search Google Scholar
    • Export Citation
  • Du, W., Tepper, A., & Verdelhan, A. (2018). Deviations from covered interest rate parity. The Journal of Finance, 73 (3), 915957.

  • Garcia, M., & Volpon, T. (2014). DNDFs: a more efficient way to intervene in FX markets? (Texto para discussão, No. 621, Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia, Rio de Janeiro.

    • Search Google Scholar
    • Export Citation
  • Goyal, R., R. Jain & S. Tewari (2013). Non deliverable forward and onshore Indian rupee market: a study on inter-linkages. Reserve Bank of India Working Paper Series, 11/2013, December.

    • Search Google Scholar
    • Export Citation
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 424438.

  • International Monetary Fund (2019). Malaysia: Staff Report for the 2019 Article IV Consultation. IMF Country Report No. 19/71

  • International Monetary Fund (2020). Malaysia: Staff Report for the 2020 Article IV Consultation. IMF Country Report No. 20/57

  • Ishii, S., Ötker-Robe, I., & Cui, L. (2001). Measures to limit the offshore use of currencies: pros and cons. International Monetary Fund WP/01/43.

    • Search Google Scholar
    • Export Citation
  • Ma, G., Ho, C., & McCauley, R. N. (2004). The markets for non-deliverable forwards in Asian currencies. BIS Quarterly Review, June.

  • McCauley, R. N., Shu, C., & Ma, G. (2014). Non-deliverable forwards: 2013 and beyond. BIS Quarterly Review, March.

  • McCauley, R. N., & Shu, C. (2016). Non-deliverable forwards: impact of currency internationalisation and derivatives reform. BIS Quarterly Review December.

    • Search Google Scholar
    • Export Citation
  • McCauley, R. N., & Shu, C. (2019). Recent renminbi policy and currency co-movements. Journal of International Money and Finance, 95, 444456.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Misra, S., & Behera, H. (2006). Non deliverable foreign exchange forward market: An overview. Reserve Bank of India Occasional Papers, 27 (3), 2555.

    • Search Google Scholar
    • Export Citation
  • Packer, F., A. Schrimpf and V. Sushko (2019): “Renminbi turnover tilts onshore”, BIS Quarterly Review, December.

  • Park, J. (2001). Information flows between non-deliverable forward (NDF) and spot markets: Evidence from Korean currency. Pacific-Basin Finance Journal, 9 (4), 363377.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Patel, N., & Xia, F. D. (2019). Offshore markets drive trading of emerging market currencies. BIS Quarterly Review, December.

  • RBI Reserve Bank of India (2019). Report of the task force on offshore rupee markets, July.

  • Shleifer, A., & Vishny, R. W. (1997). The limits of arbitrage. The Journal of Finance, 52 (1), 3555.

Appendix 1: Realized volatility of onshore forwards and NDFs

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Sources: Bloomberg, IMF staff estimates.

Appendix 2: Coefficients and intercepts for the long-run cointegration regressions

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Note: Presented results are from regressions in log levels of (1) spot on NDF (local time); (2) onshore forward on NDF (local Asia time); (3) spot on NDF at NY close; (4) onshore forward on NDF at NY close. All regressions include an intercept.Source: IMF staff estimates.

Appendix 3: Coefficients on error correction terms; daily data Period: 2012 – Apr 2020

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Note: Coefficients are γfrom equations (1) and (2) in section V. Column headings (spot/NDF.NY/NDF) identify the dependent variable. NDF.NY is the NDF quote at the New York close. NDF is the NDF quote at local Asia time.Source: IMF staff estimates.

Appendix 4: Coefficients on error correction terms; hourly data Period: 20 Jan 2020 to 30 Apr 2020

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Note: Coefficients are γ from equations (1) and (2) in section V. Column headings (spot/NDF.NY/NDF) identify the dependent variable. NDF is the NDF quote at local Asia time.Source: IMF staff estimates.
1

We thank Reda Cherif, Nada Choueiri, Dimitris Drakopoulos, Anna Ilyina, Rajeev de Mello, and Evan Papageorgiou for helpful comments and Elise Toh for help with word processing.

2

London accounts for close to half of all trading (45%), followed by the US (16%), Singapore (16%), and Hong Kong SAR (12%) (Patel & Xia 2019).

3

Policymakers can impose limits on domestic actors’ involvement in NDF markets. They can also attempt to forbid facilitation of NDF transactions by foreigners through attestations of non-participation in the market as a precondition for domestic market access.

4

Market contacts pointed out the link between hedging costs and bond holdings. Empirically, hedge costs and flows into local currency bonds are correlated, but many factors including global risk aversion are driving this correlation.

5

Directional influence in this paper refers to an asset price significantly affecting another asset price in the sense of Granger (1969). See section V for technical details.

6

We do not include CNY in the analysis given that the offshore Chinese yuan (CNH) market is increasingly replacing CNY NDF trading as discussed in section III.

7

In addition to CNY, INR, KRW, and TWD for which NDF markets exist, the BIS reports data on other FX instruments for these Asian currencies: AUD, HKD, JPY, NZD, SGD.

8

DTCC data likely substantially understates total NDF trading. For currencies where both DTCC and BIS data is available, BIS data is larger by a factor of 2 to 4.

9

Historically, the Bank of Thailand also enforced a ban on NDF quotation by international banks that had business activity in Thailand, similar to Bank Negara Malaysia.

10

Convertibility is the ease with which a currency can be converted into another currency.

11

Convertibility risk refers to the risk of loss arising from an inability to convert local currency into a fully convertible currency and/or to repatriate convertible currency back to a home country as a result of exchange controls.

12

The requirement not to engage in the NDF market was longstanding but not strictly enforced. In November 2016, BNM required an attestation from banks to certify that they did not engage in the NDF market. In December 2016, BNM introduced a requirement for conversion of 75 percent of export proceeds into MYR and a measure limiting investment in FX assets by residents with domestic ringgit borrowing was extended to exporters.

13

Some market participants indicated a preference for NDFs at the time due to convenience. Restrictions on currency positions without underlying asset exposures in onshore markets were an additional concern.

14

Since April 2017 registered nonresident investors are allowed to hedge up to 100 percent of their MYR exposures, up from 25 percent, and take additional 25 percent MYR exposure on top of their underlying asset.

15

This is unsurprising since a large share of trading in NDFs is without underlying asset positions which is not permissible in the Malaysian onshore market.

16

Since the GFC, violations of covered interest rate parity in the pricing of forwards are common. See, for example, Du, Tepper, and Verdelhan 2018.

17

During the taper tantrum India and Indonesia were labeled the “fragile five” by Morgan Stanley along with Brazil, South Africa, and Turkey.

18

To illustrate this, consider for simplicity the case where θ0 is zero and γ1 is 1 (the actual coefficients in our data are close to this case). Then St-1 – Ft-1 = et-1, where et-1 is the deviation from the long-run equilibrium at time t-1 (error correction term). The error correction term is a function of both St-1 and Ft-1. It follows that the coefficient on the error correction term in equations (1) and (2), γ, could be driven by a perturbation to St-1 or Ft-1 or both.

19

One exception are KRW onshore forwards.

20

Our result of two-way spillovers for INR, in line with the literature, could be due to the Indian trading day having more overlap with the European and US trading day than is the case for East Asia.

21

To our knowledge, we are the first to move to higher frequency data than daily to analyze NDF and onshore market relationships.

22

For the 2015/16 and 2018 EM sell-off episodes we also find some evidence for one-way spillovers from NDFs to onshore markets, but many results are not statistically significant.

23

DNDFs could also help reduce selling pressure by foreign investors in the bond market. As shown in section IV, NDF implied interest rates tend to spike in stress episodes which makes hedging of currency risk for bond investors expensive, in turn leading them to liquidate bond positions.

24

The 3-month contract was introduced in February 2019.

25

The underlying asset requirement for DNDF use was waived for transaction below USD 5mn in April 2019.