## Appendix 4: Coefficients on error correction terms; hourly data

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---

### Major findings: NDF market size and structure
- Asia accounts for three of the top four NDF currencies by volume: INR, KRW, and TWD together accounted for 55% of total daily global NDF turnover of USD258 bn as of April 2019.
- London accounts for close to half of all trading (45%), followed by the US (16%), Singapore (16%), and Hong Kong SAR (12%).
- NDF trading growth since 2016: INR rose 204%, TWD rose 168%, KRW rose 100%.
- IDR monthly NDF turnover exceeds USD100 bn based on DTCC data; DTCC data likely substantially understates total NDF trading (BIS data larger by a factor of 2 to 4 where both available).
- KRW NDF daily turnover around USD 60bn according to the BIS (KRW is the world’s largest and most liquid NDF market).
- CNY accounted for another 5% of global NDF turnover in the BIS breakdown.

### Policy approaches to NDFs across Asia
- Korea: few restrictions on onshore financial institutions’ participation in NDF markets; close integration between offshore and onshore markets.
- Taiwan POC: Taiwanese banks can participate in NDF market up to 20% of their net open FX positions; partial integration.
- Malaysia: Bank Negara Malaysia enforced an attestation/ban in November 2016 limiting offshore MYR NDF activity; onshore FX market deepening measures followed; sum of onshore turnover and NDFs remains substantially below pre-November 2016 levels.
- Indonesia: introduced a domestic net-settled DNDF in November 2018 (settled in IDR) primarily as a monetary policy tool; DNDFs largely in primary market with 1 and 3-month tenors.
- China: segmented markets with onshore deliverable (CNY), offshore NDF (CNY NDF), and offshore deliverable (CNH); CNH has gradually replaced CNY NDF activity.
- India: Reserve Bank of India commissioned a Task Force and allowed onshore banks to participate in the NDF market from June 2020.

### Volatility and pricing patterns
- Median volatility: Asian NDFs have higher median 1-month realized volatility than corresponding onshore deliverable forwards over 2013–April 2020.
- Maximum realized volatility: lower in NDFs than onshore forwards for IDR, INR, KRW, and TWD.
- Pricing differences (onshore forward implied yield less offshore NDF implied yield) are close to zero on average for most currencies, indicating eventual arbitrage, but can be very large during stress episodes:
  - Indonesia experienced interest rate differentials of +/-50% at times.
  - Substantial pricing deviations also occurred in MYR, PHP, and INR, often to the downside (NDF priced higher implied interest rates / depreciation pressure).
- Stress episode patterns:
  - 2013 taper tantrum: large dislocations for IDR and INR with offshore markets pricing large depreciations.
  - 2015 episode: large dislocations in MYR NDF pricing (overshooting behavior).
  - 2018 sell-offs: IDR most affected among sample.
  - COVID-19 pandemic: implied interest rates spiked in IDR, INR, MYR, and PHP; TWD NDF implied interest rates declined far below onshore rates (offshore pricing more appreciation).
- KRW: small deviations due to active arbitrage and domestic participation.
- TWD: intermediate deviations consistent with partial integration.

### Empirical analysis of price linkages (VECM and Granger causality)
- Data and methods:
  - Dataset: NDF, spot, and onshore deliverable forward prices for IDR, INR, KRW, MYR, PHP, and TWD from Bloomberg (BFIX); daily and hourly data used.
  - Time-matching innovation: NDF and onshore quotes are exactly time-matched to control for time-zone induced spillovers.
  - Tests: ADF unit root tests (series non-stationary in levels, I(1)); Johansen cointegration tests (cointegrating relationships found for all currencies); Vector Error Correction Models estimated; Granger causality tests based on joint significance of lagged independent variables.
- Long-run equilibrium:
  - Cointegrating regressions: intercepts close to zero, coefficients on dependent variables close to one — onshore and offshore prices close to equal in the long run.
  - Error correction coefficients: generally statistically significant with correct sign (converging to equilibrium) except for MYR (NDF dependent regressions) and INR (NDF dependent regressions) in some cases.
- Directional spillovers (daily data using NDF at New York close):
  - Changes in NDF prices Granger cause changes in onshore spot and forward FX prices in all cases.
  - One-directional NDF → onshore observed for spot in IDR, KRW, PHP, and TWD; and for onshore forward in IDR, MYR, and PHP.
  - Two-way influences for INR (spot and forward), MYR (spot), and TWD (forward).
  - Caveat: Using NDF quotes at New York close can produce apparent one-way NDF → onshore influence due to information being priced in different trading hours (time-zone effect).
- Directional spillovers (daily data using time-matched NDF at Asia trading hours):
  - Most currencies show bi-directional influences between NDFs and onshore markets when quotes are time-matched (price discovery runs in both markets).
  - Exceptions:
    - KRW: one-directional NDF → onshore forward (consistent with close integration and domestic arbitrage).
    - MYR: Granger causality runs only from onshore forwards to NDF; for MYR spot the direction switched from NDF → onshore before November 2016 measures to onshore → NDF after measures.
    - TWD: no significant lead-lag relations in daily time-matched tests.
- High-frequency crisis analysis (COVID-19: Jan 20 to Apr 30 2020; hourly time-matched data):
  - Hourly data used to increase observations for crisis period analysis.
  - Error correction term: expected-sign and significant at 10% for most regressions; IDR NDF regressions show no convergence (likely due to sustained dislocation).
  - Lagged independent variables (Granger causality):
    - Evidence that during COVID-19 NDF markets led onshore forward markets for IDR and INR (both under depreciation pressure).
    - For other currencies either bi-directional relations or no association in high-frequency data.
    - TWD: direction from NDF → spot, but from onshore forward → NDF.
  - Note: at a 10% significance level there is no significant spillover from NDF to spot for IDR and from spot to NDF for INR (sensitivity noted in source).

### Domestic NDFs (DNDFs): design, use, and Indonesian experience
- DNDF definition: net-settled in local currency and traded onshore; distinct from USD-settled offshore NDFs and from deliverable onshore forwards (full notional exchange).
- Motivations for central banks to issue DNDFs:
  - Intervention without affecting foreign exchange reserves (DNDFs settled in local currency).
  - Dampening spot or deliverable forward USD demand by providing alternative hedging instruments.
  - Provide an FX intervention tool for price signals.
- Risks and limitations:
  - Large short-USD DNDF positions can be risky if counterparties demand USD instead of rolling positions, potentially exacerbating depreciation pressures.
  - Losses on DNDFs can impair central bank capital.
  - DNDFs may be imperfect substitutes for deliverable instruments or NDFs for corporates and foreign investors (actual USD delivery needs; convertibility risk).
  - Historical Brazil case: large discounts on DNDFs relative to NDFs amid convertibility concerns.
- Indonesia (Bank Indonesia) DNDF specifics:
  - Introduced November 2018; mostly used as monetary policy tool; primary market focus with daily 1-month and 3-month DNDFs (3-month introduced February 2019).
  - Counterparties: mostly domestic banks and offshore subsidiaries of global banks with presence in Indonesia.
  - Outstanding DNDFs prior to COVID-19 estimated in the source to be in the range of USD1 to 4 bn.
  - Starting in February 2020 BI increased DNDF sales to close to USD 8 bn.
  - Comparison with portfolio flows: net portfolio outflows of USD 2.4 bn in February and USD 7.9 bn in March 2020.
  - DNDF pricing: BI fixes IDR rate using the Jakarta Interbank Spot Dollar Rate; DNDF typically priced below NDF but during COVID-19 the DNDF – NDF spread reached record levels with NDF pricing more depreciation; DNDFs priced more depreciation than onshore deliverable forwards during COVID-19 (BI possibly set DNDF pricing to bridge NDF and onshore forward markets).
  - DNDF liquidity remains limited; BI measures in 2020 to increase DNDF liquidity include expanding eligible underlying transactions and allowing DNDFs in net open FX position calculations.
- Philippines (BSP):
  - Currency Rate Risk Protection Program (CRRP) is a DNDF-like standing facility net-settled in pesos for domestic banks acting as intermediaries for eligible hedging needs.
  - CRRP reactivated September 2018; uptake has been very limited.

### Policy implications and conclusions
- NDF markets in major Asian currencies are large and often have higher trading volumes than onshore FX markets.
- NDFs are generally more volatile than onshore counterparts; during stress NDF pricing often diverges and initially prices more depreciation than onshore markets.
- Large NDF pricing deviations can have real effects by making hedging expensive and prompting foreign investors to sell local assets.
- Empirically:
  - Long-term equilibrium relations exist between NDFs and onshore markets with cointegration in all cases studied.
  - Both NDFs and onshore markets typically adjust back toward equilibrium after perturbations.
  - When time-matching quotes, price discovery tends to run in both directions for most currencies (bi-directional spillovers); apparent unidirectional NDF → onshore findings in prior literature are often due to using NDF quotes from outside Asian trading hours.
  - During COVID-19 there is evidence for increased one-directional influence from NDF to onshore for IDR and INR.
- Policy tradeoffs:
  - Countries choose different approaches reflecting priorities: control and limiting offshore price discovery (Malaysia), close integration and market depth (Korea), segmented onshore/offshore arrangements (China/CNH), and onshore net-settled instruments for intervention (Indonesia DNDF).
  - Policymakers weigh control, market depth, spillovers, attractiveness to nonresident investors, real economy impacts, and prudential considerations.
- Outlook:
  - For most emerging market currencies, NDF markets are likely to continue to flourish as long as full convertibility is not established.

### Appendix highlights: Cointegration regressions (selected periods)
- Periods and coefficients (Onshore Forward / NDF) by currency

  - Taper Tantrum May 13 - Aug 13
    - IDR: 0.45 / 0.75
    - MYR: 0.47 / 0.52
    - PHP: 0.37 / 0.43
    - INR: 0.62 / 0.75
    - KRW: 0.52 / 0.51
    - TWD: 0.28 / 0.34

  - EM Sell Off (1) May 15 - Jan 16
    - IDR: 0.43 / 0.66
    - MYR: 0.62 / 0.71
    - PHP: 0.25 / 0.32
    - INR: 0.32 / 0.36
    - KRW: 0.56 / 0.53
    - TWD: 0.33 / 0.42

  - China Slowdown/ RMB Weakness Feb 16 - Dec 16
    - IDR: 0.41 / 0.60
    - MYR: 0.56 / 0.76
    - PHP: 0.30 / 0.40
    - INR: 0.27 / 0.35
    - KRW: 0.64 / 0.63
    - TWD: 0.27 / 0.46

  - EM Sell Off (2) Jan 18 - Dec 18
    - IDR: 0.30 / 0.52
    - MYR: 0.19 / 0.34
    - PHP: 0.24 / 0.34
    - INR: 0.37 / 0.41
    - KRW: 0.44 / 0.49
    - TWD: 0.19 / 0.31

  - COVID-19 Jan 20 - Apr 20
    - IDR: 0.62 / 1.09
    - MYR: 0.39 / 0.59
    - PHP: 0.26 / 0.33
    - INR: 0.37 / 0.52
    - KRW: 0.66 / 0.61
    - TWD: 0.26 / 0.35

  - Entire Sample Period 2013 - Apr-20
    - IDR: 0.35 / 0.51
    - MYR: 0.30 / 0.39
    - PHP: 0.27 / 0.32
    - INR: 0.32 / 0.38
    - KRW: 0.46 / 0.48
    - TWD: 0.20 / 0.30

### Appendix 4: Coefficients on error correction terms; hourly data (20 Jan 2020 to 30 Apr 2020)
- Note: Coefficients are 훾 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.
- Coefficients and Standard Errors (grouped as presented)

  - Block 1 (Spot NDF.NY / Spot NDF.NY / Onshore Forward NDF.NY / Onshore Forward NDF.NY)
    - IDR: -0.0608 / 0.0523 / 0.0100 / 0.0149  -0.1195 / 0.0719 / 0.0152 / 0.0196
    - INR: -0.0400 / 0.0545 / 0.0215 / 0.0267  -0.0746 / 0.0679 / 0.0289 / 0.0363
    - KRW: -0.1934 / 0.1126 / 0.0303 / 0.0345  -0.7411 / 0.2536 / 0.0345 / 0.0402
    - MYR: -0.3077 / -0.0165 / 0.0300 / 0.0454  -0.3232 / 0.0255 / 0.0335 / 0.0505
    - PHP: -0.2411 / 0.1823 / 0.0225 / 0.0263  -0.2575 / 0.2077 / 0.0254 / 0.0299
    - TWD: -0.2068 / 0.1218 / 0.0197 / 0.0270  -0.1556 / 0.1214 / 0.0157 / 0.0202

  - Block 2 (Spot NDF / Spot NDF / Onshore Forward NDF / Onshore Forward NDF)
    - IDR: -0.0511 / 0.0472 / 0.0107 / 0.0149  -0.0918 / 0.0660 / 0.0165 / 0.0197
    - INR: 0.0112 / 0.0430 / 0.0244 / 0.0260  -0.0061 / 0.0404 / 0.0337 / 0.0362
    - KRW: -0.0945 / 0.1505 / 0.0367 / 0.0368  -0.6206 / 0.3815 / 0.1168 / 0.1165
    - MYR: -0.1493 / -0.0006 / 0.0378 / 0.0424  -0.1418 / 0.0043 / 0.0462 / 0.0512
    - PHP: -0.1988 / 0.1959 / 0.0234 / 0.0252  -0.1646 / 0.1756 / 0.0293 / 0.0318
    - TWD: -0.2306 / 0.2614 / 0.0314 / 0.0405  -0.2089 / 0.1757 / 0.0272 / 0.0357

  - Block 3 (Spot NDF / Spot NDF / Onshore Forward NDF / Onshore Forward NDF)
    - IDR: -0.0914 / 0.0167 / 0.0130 / 0.0181  -0.0902 / 0.0185 / 0.0126 / 0.0177
    - INR: -0.1163 / 0.0767 / 0.0215 / 0.0290  -0.1366 / 0.0978 / 0.0216 / 0.0300
    - KRW: -0.3698 / 0.2349 / 0.0487 / 0.0467  -0.6011 / 0.1820 / 0.0963 / 0.0993
    - MYR: -0.1817 / 0.1760 / 0.0204 / 0.0253  -0.2112 / 0.1665 / 0.0229 / 0.0282
    - PHP: -0.1297 / 0.0671 / 0.0264 / 0.0323  -0.2406 / 0.0876 / 0.0357 / 0.0433
    - TWD: -0.0514 / 0.0932 / 0.0178 / 0.0206  -0.0653 / 0.1015 / 0.0178 / 0.0221

*Source: IMF staff report (Appendix 4: Coefficients on error correction terms; hourly data) from wpiea2020179-print-pdf.*

### References .............................................................................................................

### References ............................................................................................................................... 25

### Appendices
- Appendix 1: Realized volatility of onshore forwards and NDFs ............................................ 27
- Appendix 2: Coefficients and intercepts for the long-run cointegration regressions ............. 27
- Appendix 3: Coefficients on error correction terms; daily data ............................................. 28

*Source: wpiea2020179-print-pdf - References ............................................................................................................. — https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020179-print-pdf.pdf*

### Appendix 4: Coefficients on error correction terms; hourly data ........................................... 28

### Appendix 4: Coefficients on error correction terms; hourly data

### Major findings: NDF market size and structure
- Asia accounts for three of the top four NDF currencies by volume: INR, KRW, and TWD together accounted for 55% of total daily global NDF turnover of USD258 bn as of April 2019.
- London accounts for close to half of all trading (45%), followed by the US (16%), Singapore (16%), and Hong Kong SAR (12%).
- NDF trading growth since 2016: INR rose 204%, TWD rose 168%, KRW rose 100%.
- IDR monthly NDF turnover exceeds USD100 bn based on DTCC data; DTCC data likely substantially understates total NDF trading (BIS data larger by a factor of 2 to 4 where both available).
- KRW NDF daily turnover around USD 60bn according to the BIS (KRW is the world’s largest and most liquid NDF market).
- CNY accounted for another 5% of global NDF turnover in the BIS breakdown.

### Policy approaches to NDFs across Asia
- Policy approaches vary widely: examples include
  - Korea: few restrictions on onshore financial institutions’ participation in NDF markets; close integration between offshore and onshore markets.
  - Taiwan POC: Taiwanese banks can participate in NDF market up to 20% of their net open FX positions; partial integration.
  - Malaysia: Bank Negara Malaysia enforced an attestation/ban in November 2016 limiting offshore MYR NDF activity; onshore FX market deepening measures followed; sum of onshore turnover and NDFs remains substantially below pre-November 2016 levels.
  - Indonesia: introduced a domestic net-settled DNDF in November 2018 (settled in IDR) primarily as a monetary policy tool; DNDFs largely in primary market with 1 and 3-month tenors.
  - China: segmented markets with onshore deliverable (CNY), offshore NDF (CNY NDF), and offshore deliverable (CNH); CNH has gradually replaced CNY NDF activity.
  - India: Reserve Bank of India commissioned a Task Force and allowed onshore banks to participate in the NDF market from June 2020.

### Volatility and pricing patterns
- Median volatility: Asian NDFs have higher median 1-month realized volatility than corresponding onshore deliverable forwards over 2013–April 2020.
- Maximum realized volatility: lower in NDFs than onshore forwards for IDR, INR, KRW, and TWD.
- Pricing differences (onshore forward implied yield less offshore NDF implied yield) are close to zero on average for most currencies, indicating eventual arbitrage, but can be very large during stress episodes:
  - Indonesia experienced interest rate differentials of +/-50% at times.
  - Substantial pricing deviations also occurred in MYR, PHP, and INR, often to the downside (NDF priced higher implied interest rates / depreciation pressure).
- Stress episode patterns:
  - 2013 taper tantrum: large dislocations for IDR and INR with offshore markets pricing large depreciations.
  - 2015 episode: large dislocations in MYR NDF pricing (overshooting behavior).
  - 2018 sell-offs: IDR most affected among sample.
  - COVID-19 pandemic: implied interest rates spiked in IDR, INR, MYR, and PHP; TWD NDF implied interest rates declined far below onshore rates (offshore pricing more appreciation).
- KRW: small deviations due to active arbitrage and domestic participation.
- TWD: intermediate deviations consistent with partial integration.

### Empirical analysis of price linkages (VECM and Granger causality)
- Data and methods:
  - Dataset: NDF, spot, and onshore deliverable forward prices for IDR, INR, KRW, MYR, PHP, and TWD from Bloomberg (BFIX); daily and hourly data used.
  - Time-matching innovation: NDF and onshore quotes are exactly time-matched to control for time-zone induced spillovers.
  - Tests: ADF unit root tests (series non-stationary in levels, I(1)); Johansen cointegration tests (cointegrating relationships found for all currencies); Vector Error Correction Models estimated; Granger causality tests based on joint significance of lagged independent variables.
- Long-run equilibrium:
  - Cointegrating regressions: intercepts close to zero, coefficients on dependent variables close to one — onshore and offshore prices close to equal in the long run.
  - Error correction coefficients: generally statistically significant with correct sign (converging to equilibrium) except for MYR (NDF dependent regressions) and INR (NDF dependent regressions) in some cases.
- Directional spillovers (daily data using NDF at New York close):
  - Changes in NDF prices Granger cause changes in onshore spot and forward FX prices in all cases (Table 1 summary in source).
  - One-directional NDF → onshore observed for spot in IDR, KRW, PHP, and TWD; and for onshore forward in IDR, MYR, and PHP.
  - Two-way influences for INR (spot and forward), MYR (spot), and TWD (forward).
  - Caveat: Using NDF quotes at New York close can produce apparent one-way NDF → onshore influence due to information being priced in different trading hours (time-zone effect).
- Directional spillovers (daily data using time-matched NDF at Asia trading hours):
  - Most currencies show bi-directional influences between NDFs and onshore markets when quotes are time-matched (price discovery runs in both markets).
  - Exceptions:
    - KRW: one-directional NDF → onshore forward (consistent with close integration and domestic arbitrage).
    - MYR: Granger causality runs only from onshore forwards to NDF; for MYR spot the direction switched from NDF → onshore before November 2016 measures to onshore → NDF after measures.
    - TWD: no significant lead-lag relations in daily time-matched tests.
- High-frequency crisis analysis (COVID-19: Jan 20 to Apr 30 2020; hourly time-matched data):
  - Hourly data used to increase observations for crisis period analysis.
  - Error correction term: expected-sign and significant at 10% for most regressions; IDR NDF regressions show no convergence (likely due to sustained dislocation).
  - Lagged independent variables (Granger causality):
    - Evidence that during COVID-19 NDF markets led onshore forward markets for IDR and INR (both under depreciation pressure).
    - For other currencies either bi-directional relations or no association in high-frequency data.
    - TWD: direction from NDF → spot, but from onshore forward → NDF.
  - Note: at a 10% significance level there is no significant spillover from NDF to spot for IDR and from spot to NDF for INR (sensitivity noted in source).

### Domestic NDFs (DNDFs): design, use, and Indonesian experience
- DNDF definition: net-settled in local currency and traded onshore; distinct from USD-settled offshore NDFs and from deliverable onshore forwards (full notional exchange).
- Motivations for central banks to issue DNDFs:
  - Intervention without affecting foreign exchange reserves (DNDFs settled in local currency).
  - Dampening spot or deliverable forward USD demand by providing alternative hedging instruments.
  - Provide an FX intervention tool for price signals.
- Risks and limitations:
  - Large short-USD DNDF positions can be risky if counterparties demand USD instead of rolling positions, potentially exacerbating depreciation pressures.
  - Losses on DNDFs can impair central bank capital.
  - DNDFs may be imperfect substitutes for deliverable instruments or NDFs for corporates and foreign investors (actual USD delivery needs; convertibility risk).
  - Historical Brazil case: large discounts on DNDFs relative to NDFs amid convertibility concerns.
- Indonesia (Bank Indonesia) DNDF specifics:
  - Introduced November 2018; mostly used as monetary policy tool; primary market focus with daily 1-month and 3-month DNDFs (3-month introduced February 2019).
  - Counterparties: mostly domestic banks and offshore subsidiaries of global banks with presence in Indonesia.
  - Outstanding DNDFs prior to COVID-19 estimated in the source to be in the range of USD1 to 4 bn.
  - Starting in February 2020 BI increased DNDF sales to close to USD 8 bn.
  - Comparison with portfolio flows: net portfolio outflows of USD 2.4 bn in February and USD 7.9 bn in March 2020.
  - DNDF pricing: BI fixes IDR rate using the Jakarta Interbank Spot Dollar Rate; DNDF typically priced below NDF but during COVID-19 the DNDF – NDF spread reached record levels with NDF pricing more depreciation; DNDFs priced more depreciation than onshore deliverable forwards during COVID-19 (BI possibly set DNDF pricing to bridge NDF and onshore forward markets).
  - DNDF liquidity remains limited; BI measures in 2020 to increase DNDF liquidity include expanding eligible underlying transactions and allowing DNDFs in net open FX position calculations.
- Philippines (BSP):
  - Currency Rate Risk Protection Program (CRRP) is a DNDF-like standing facility net-settled in pesos for domestic banks acting as intermediaries for eligible hedging needs.
  - CRRP reactivated September 2018; uptake has been very limited.

### Policy implications and conclusions
- NDF markets in major Asian currencies are large and often have higher trading volumes than onshore FX markets.
- NDFs are generally more volatile than onshore counterparts; during stress NDF pricing often diverges and initially prices more depreciation than onshore markets.
- Large NDF pricing deviations can have real effects by making hedging expensive and prompting foreign investors to sell local assets.
- Empirically:
  - Long-term equilibrium relations exist between NDFs and onshore markets with cointegration in all cases studied.
  - Both NDFs and onshore markets typically adjust back toward equilibrium after perturbations.
  - When time-matching quotes, price discovery tends to run in both directions for most currencies (bi-directional spillovers); apparent unidirectional NDF → onshore findings in prior literature are often due to using NDF quotes from outside Asian trading hours.
  - During COVID-19 there is evidence for increased one-directional influence from NDF to onshore for IDR and INR.
- Policy tradeoffs:
  - Countries choose different approaches reflecting priorities: control and limiting offshore price discovery (Malaysia), close integration and market depth (Korea), segmented onshore/offshore arrangements (China/CNH), and onshore net-settled instruments for intervention (Indonesia DNDF).
  - Policymakers weigh control, market depth, spillovers, attractiveness to nonresident investors, real economy impacts, and prudential considerations.
- Outlook:
  - For most emerging market currencies, NDF markets are likely to continue to flourish as long as full convertibility is not established.

*Source: IMF staff report (Appendix 4: Coefficients on error correction terms; hourly data) from wpiea2020179-print-pdf.*

### References

### wpiea2020179-print-pdf - References

### References (selected)
- 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), 43-55.
- 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 323–47.
- Du, W., Tepper, A., & Verdelhan, A. (2018). Deviations from covered interest rate parity. The Journal of Finance, 73(3), 915-957.
- 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.
- 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.
- Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 424-438.
- 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.
- 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.
- McCauley, R. N., & Shu, C. (2019). Recent renminbi policy and currency co-movements. Journal of International Money and Finance, 95, 444-456.
- Misra, S., & Behera, H. (2006). Non deliverable foreign exchange forward market: An overview. Reserve Bank of India Occasional Papers, 27(3), 25-55.
- 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), 363-377.
- 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), 35-55.

### Appendix 1: Realized volatility of onshore forwards and NDFs
- Sources: Bloomberg, IMF staff estimates.

### Appendix 2: Coefficients and intercepts for the long-run cointegration regressions
- 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.
- Periods and coefficients (Onshore Forward / NDF) by currency

  - Taper Tantrum May 13 - Aug 13
    - IDR: 0.45 / 0.75
    - MYR: 0.47 / 0.52
    - PHP: 0.37 / 0.43
    - INR: 0.62 / 0.75
    - KRW: 0.52 / 0.51
    - TWD: 0.28 / 0.34

  - EM Sell Off (1) May 15 - Jan 16
    - IDR: 0.43 / 0.66
    - MYR: 0.62 / 0.71
    - PHP: 0.25 / 0.32
    - INR: 0.32 / 0.36
    - KRW: 0.56 / 0.53
    - TWD: 0.33 / 0.42

  - China Slowdown/ RMB Weakness Feb 16 - Dec 16
    - IDR: 0.41 / 0.60
    - MYR: 0.56 / 0.76
    - PHP: 0.30 / 0.40
    - INR: 0.27 / 0.35
    - KRW: 0.64 / 0.63
    - TWD: 0.27 / 0.46

  - EM Sell Off (2) Jan 18 - Dec 18
    - IDR: 0.30 / 0.52
    - MYR: 0.19 / 0.34
    - PHP: 0.24 / 0.34
    - INR: 0.37 / 0.41
    - KRW: 0.44 / 0.49
    - TWD: 0.19 / 0.31

  - COVID-19 Jan 20 - Apr 20
    - IDR: 0.62 / 1.09
    - MYR: 0.39 / 0.59
    - PHP: 0.26 / 0.33
    - INR: 0.37 / 0.52
    - KRW: 0.66 / 0.61
    - TWD: 0.26 / 0.35

  - Entire Sample Period 2013 - Apr-20
    - IDR: 0.35 / 0.51
    - MYR: 0.30 / 0.39
    - PHP: 0.27 / 0.32
    - INR: 0.32 / 0.38
    - KRW: 0.46 / 0.48
    - TWD: 0.20 / 0.30

### Appendix 3: Coefficients on error correction terms; daily data
- Period: 2012 - Apr 2020
- Note: Coefficients are 훾 from 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.
- (Table data not reproduced beyond note in source.)

### Appendix 4: Coefficients on error correction terms; hourly data
- Period: 20 Jan 2020 to 30 Apr 2020
- Note: Coefficients are 훾 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.
- Coefficients and Standard Errors (grouped as presented)

  - Coefficients / Standard Errors block 1 (Spot NDF.NY / Spot NDF.NY / Onshore Forward NDF.NY / Onshore Forward NDF.NY)
    - IDR: -0.0608 / 0.0523 / 0.0100 / 0.0149  -0.1195 / 0.0719 / 0.0152 / 0.0196
    - INR: -0.0400 / 0.0545 / 0.0215 / 0.0267  -0.0746 / 0.0679 / 0.0289 / 0.0363
    - KRW: -0.1934 / 0.1126 / 0.0303 / 0.0345  -0.7411 / 0.2536 / 0.0345 / 0.0402
    - MYR: -0.3077 / -0.0165 / 0.0300 / 0.0454  -0.3232 / 0.0255 / 0.0335 / 0.0505
    - PHP: -0.2411 / 0.1823 / 0.0225 / 0.0263  -0.2575 / 0.2077 / 0.0254 / 0.0299
    - TWD: -0.2068 / 0.1218 / 0.0197 / 0.0270  -0.1556 / 0.1214 / 0.0157 / 0.0202

  - Coefficients / Standard Errors block 2 (Spot NDF / Spot NDF / Onshore Forward NDF / Onshore Forward NDF)
    - IDR: -0.0511 / 0.0472 / 0.0107 / 0.0149  -0.0918 / 0.0660 / 0.0165 / 0.0197
    - INR: 0.0112 / 0.0430 / 0.0244 / 0.0260  -0.0061 / 0.0404 / 0.0337 / 0.0362
    - KRW: -0.0945 / 0.1505 / 0.0367 / 0.0368  -0.6206 / 0.3815 / 0.1168 / 0.1165
    - MYR: -0.1493 / -0.0006 / 0.0378 / 0.0424  -0.1418 / 0.0043 / 0.0462 / 0.0512
    - PHP: -0.1988 / 0.1959 / 0.0234 / 0.0252  -0.1646 / 0.1756 / 0.0293 / 0.0318
    - TWD: -0.2306 / 0.2614 / 0.0314 / 0.0405  -0.2089 / 0.1757 / 0.0272 / 0.0357

  - Coefficients / Standard Errors block 3 (Spot NDF / Spot NDF / Onshore Forward NDF / Onshore Forward NDF)
    - IDR: -0.0914 / 0.0167 / 0.0130 / 0.0181  -0.0902 / 0.0185 / 0.0126 / 0.0177
    - INR: -0.1163 / 0.0767 / 0.0215 / 0.0290  -0.1366 / 0.0978 / 0.0216 / 0.0300
    - KRW: -0.3698 / 0.2349 / 0.0487 / 0.0467  -0.6011 / 0.1820 / 0.0963 / 0.0993
    - MYR: -0.1817 / 0.1760 / 0.0204 / 0.0253  -0.2112 / 0.1665 / 0.0229 / 0.0282
    - PHP: -0.1297 / 0.0671 / 0.0264 / 0.0323  -0.2406 / 0.0876 / 0.0357 / 0.0433
    - TWD: -0.0514 / 0.0932 / 0.0178 / 0.0206  -0.0653 / 0.1015 / 0.0178 / 0.0221

*Source: wpiea2020179-print-pdf (References and Appendices as provided).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020179-print-pdf.pdf_