## wpiea2021268-print-pdf - References 21

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### I. Introduction and rationale for an onshore FX futures market
- Since 2016, the People’s Bank of China has withdrawn from daily interventions and significantly enhanced RMB exchange rate flexibility; further increasing flexibility and ultimately establishing a floating exchange rate regime is in China’s interest to support capital market opening and RMB internationalization.
- Greater exchange rate flexibility may increase profits volatility for exporters/importers and vulnerability of firms with large foreign debt exposures.
- A sufficiently deep and liquid FX derivatives market is crucial to move toward a floating exchange rate while ensuring economic and financial stability.
- China’s OTC FX derivatives market exists (forwards, swaps, options) but lacks an onshore FX futures market, which:
  - Limits participation by SMEs and retail traders due to high transaction costs in the OTC market.
  - Reduces centralized price discovery, market transparency, and accessibility of low-cost standardized hedging tools.
- Advantages of an onshore FX futures market:
  - Standardized, low-cost products; centralized market with greater transparency; lower credit risk; more effective supervision.
  - Better service to a broader range of market participants, improving the economy’s resilience to external shocks and reducing the balance-sheet effect of exchange rate fluctuations.
- Concerns about speculative amplification of volatility exist in theory; policy should focus on conditions and regulatory practices to manage risks.

### II. Empirical study: design and data
- Objective: examine whether establishment of FX futures markets among BRICS (country-specific focus on India, Russia, South Africa) increases spot FX volatility.
- Currency pairs used (daily closing values from Bloomberg): USDINR, USDRUB, USDZAR.
- Cutoff dates identifying the beginning of a stable rise in currency futures trading:
  - India: January 2009
  - Russia: January 2006
  - South Africa: January 2008
- Pre-cutoff-period and Post-cutoff-period lengths: two years before and after the cutoff date.
- Return calculation: daily rate of return = natural logarithm of the ratio of present day’s index level to previous day’s index level.
- Unit root testing: ADF methods; presence of ARCH effect assessed by LM test.
- Volatility modeled with GARCH(1,1):
  - Mean: yt = vt + εt
  - Variance: σt^2 = α0 + α1 εt−1^2 + β σt−1^2
  - Parameter constraints: α0 > 0; α1 > 0; β ≥ 0; α1 + β < 1.

### III. Empirical results — country findings and key statistics

- India (USDINR)
  - Descriptive statistics:
    - Pre (Obs 507): Mean -0.0001923; Std. Dev. 0.0047907; Min -0.024074; Max 0.0189109
    - Post (Obs 485): Mean 0.0001808; Std. Dev. 0.0053458; Min -0.0170301; Max 0.0302912
  - ADF test: Pre statistic -14.669 (Obs 507, P value 0.0000); Post statistic -16.165 (Obs 485, P value 0.0000) — series stationary at 1%.
  - LM test: ARCH effect significant (zero probability).
  - GARCH(1,1) results:
    - Pre-Derivative: Intercept (α0) 5.40e-07; ARCH (α1) 0.1595126; GARCH (β1) 0.8292628; α1+β1 0.9887754; P values 0.000 across coefficients.
    - Post-Derivative: Intercept (α0) 3.08e-06; ARCH (α1) 0.1259465; GARCH (β1) 0.7386511; α1+β1 0.8645976; P values 0.000 across coefficients.
  - Unconditional variance (Varεt = α0 / (1 − (α1 + β1))):
    - Pre-period: 0.00004810862
    - Post-period: 0.00002274701
  - Main finding: persistence of volatility decreased in the Post-period; introduction of FX futures markets did not increase spot volatility in India and is associated with decreased volatility.

- Russia (USDRUB)
  - Descriptive statistics:
    - Pre (Obs 522): Mean 0.0000331; Std. Dev. 0.0019555; Min -0.006682; Max 0.006992
    - Post (Obs 521): Mean 0.0002986; Std. Dev. 0.0021288; Min -0.0073153; Max 0.0098162
  - ADF test: Pre statistic -21.517 (Obs 520, P value 0.0000); Post statistic -22.323 (Obs 520, P value 0.0000) — series stationary at 1%.
  - LM test: ARCH effect exists.
  - GARCH(1,1) results:
    - Pre-Derivative: Intercept (α0) 8.60e-08; ARCH (α1) 0.1023693; GARCH (β1) 0.881888; α1+β1 0.9842581; P values 0.000 across coefficients.
    - Post-Derivative: Intercept (α0) 4.71e-08; ARCH (α1) 0.0329523; GARCH (β1) 0.9573649; α1+β1 0.9968879; P values: Intercept 0.281, ARCH 0.017, GARCH 0.000, α1+β1 0.000.
  - Unconditional variance:
    - Pre-period: 0.00000546285
    - Post-period: 0.0000048643
  - Main finding: ARCH coefficient decreased while GARCH coefficient increased; overall unconditional variance decreased slightly after introduction of FX futures.

- South Africa (USDZAR)
  - Descriptive statistics:
    - Pre (Obs 521): Mean -0.0001554; Std. Dev. 0.0096418; Min -0.032557; Max 0.0277545
    - Post (Obs 523): Mean -0.0001437; Std. Dev. 0.0163603; Min -0.154965; Max 0.0662992
  - ADF test: Pre statistic -23.344 (Obs 520, P value 0.0000); Post statistic -23.688 (Obs 520, P value 0.0000) — series stationary at 1%.
  - LM test: ARCH effect exists.
  - GARCH(1,1) results:
    - Pre-Derivative: Intercept (α0) 4.01e-06; ARCH (α1) 0.0322642; GARCH (β1) 0.9247918; α1+β1 0.957056; P values: Intercept 0.250; ARCH 0.098; GARCH 0.000; α1+β1 0.098.
    - Post-Derivative: Intercept (α0) 5.00e-06; ARCH (α1) 0.1492664; GARCH (β1) 0.8454004; α1+β1 0.9946668; P values: Intercept 0.164; ARCH 0.000; GARCH 0.000; α1+β1 0.000.
  - Main observation: ARCH coefficients increased and GARCH coefficients decreased, indicating more volatility from new information and less from persistent old information; overall unconditional variance of returns increased in the Post-period.
  - Contextual factor: South Africa’s Post-period coincides with the 2008 global financial crisis, which plausibly contributed to increased volatility.

### IV. Robustness checks: controlling for the financial crisis
- Introduced dummy variable “financial crisis” (DF) for September–December 2008 (DF = 1 for crisis period, 0 otherwise) based on Libor–OIS spread evidence.
- Modified variance equation: σt^2 = α0 + α1 εt−1^2 + β σt−1^2 + δ DF
- South Africa (with DF):
  - Post-Derivative (with DF): Intercept (α0) 0.000275; ARCH (α1) 0.0720019; GARCH (β1) 0.8662979; α1+β1 0.9382998; δ 1.876881; P value for δ 0.000.
  - Result: after controlling for the crisis, ARCH increases and GARCH decreases, and overall unconditional variance decreases — supporting that the 2008 crisis drove the observed volatility rise; introduction of futures reduced overall volatility when crisis effects are controlled.
- India (with DF):
  - Pre-Derivative (with DF): Intercept (α0) -14.02913; ARCH (α1) 0.1438344; GARCH (β1) 0.8035084; α1+β1 0.9473428; δ 2.168283; P values 0.000 across entries.
  - Result: results for India hold after introducing financial crisis dummy — introduction of futures market reduced overall volatility.

### V. Main empirical conclusion
- Across the studied emerging markets (India, Russia, South Africa), establishment of FX futures markets did not increase spot-market volatility; in some cases unconditional volatility decreased.
- For South Africa, observed post-introduction volatility rise is largely attributable to the global financial crisis; after controlling for it, futures introduction is associated with reduced volatility.
- Empirical implication: in emerging market contexts, FX futures markets tend to act as stabilizers rather than volatility amplifiers, possibly because diversified participants help the exchange rate return faster to equilibrium by “buying low and selling high.”

### VI. Regulatory design and policy recommendations for China
- Phase out requirement of underlying exposure gradually:
  - Requirement once served to inform regulators of trade-based FX demand but has become counterproductive, limiting market scale, liquidity, depth, and preemptive hedging.
  - International experience (e.g., India) shows relaxing the requirement with the introduction of futures is feasible; OTC restrictions can be removed in a phased manner.
- Adopt market-based regulatory tools instead of underlying-exposure documentation:
  - Margin requirement (leverage ratio):
    - Cross-country margins in emerging markets: within 5%–10% (implying leverage ratios 10–20).
    - Suggested initial margin for China: 5% (allowing 20 times leverage) for most customers; 10% (allowing 10 times leverage) for higher-risk customers; adjust over time and gradually decrease as market matures.
    - Reference margins in developed markets: CME USD/CNH Futures between 1.5% and 2.4%; Hong Kong Stock Exchange ~2%; Singapore Exchange ~1%.
  - Limitations on margin/net financial assets:
    - Prohibit borrowed margin payments; cap margin of traders as a percentage of net financial assets with differentiated levels by scale and orientation.
  - Position limits:
    - To prevent manipulation and concentration; example: India sets gross open position limits of clients and members to 6% and 15% of total open interests respectively; China could set dynamic limits with warnings beyond thresholds.
  - Settlement choice:
    - Cash settlement (local-currency-denominated) appropriate initially given incomplete RMB capital account convertibility; cash settlement reduces cross-border pressures and suits speculators and liquidity.
    - Physical delivery more suitable when currency is fully convertible.
  - Daily price bands:
    - Most developed and developing countries do not set daily price bands; India and Hungary are exceptions.
    - Price bands can impede price discovery and attract speculation; given reduced central bank interventions, little need for daily bands in China; central bank should retain right to intervene under disorderly conditions.
  - Role of central banks and supervisory authorities:
    - Joint oversight by central bank and securities regulator; central bank responsibility: market access guidance, monitoring financing sources, dynamic trading parameters (margins, limits), direct market participation and intervention as needed.
    - Securities regulatory commission: enforce regulations and standards for supervised market participants.
    - Effective coordination indispensable.
  - Encourage broader use of derivatives tools and hedge accounting:
    - Hedge accounting reduces profit volatility from derivatives mark-to-market; regulators should educate firms and investors to adopt risk-neutral perspectives focused on core business.
  - Platform selection and liquidity considerations:
    - Given China’s inter-bank participants’ dominance, consider establishing FX futures in the inter-bank market initially to mobilize banks, improve liquidity, and encourage complementarity between forward and futures markets.
    - Allow all types of market participants access at inception; electronic platform to cross geographical boundaries; permit commercial banks and institutions to act as market makers and arbitrageurs.

### VII. Conclusion
- International experience and the paper’s empirical analysis indicate FX futures markets are important complements to spot and OTC markets by serving many investors and improving price discovery.
- Empirical evidence from the studied emerging markets suggests that the FX futures market functions more like a “stabilizer” than a “risk amplifier.”
- Policy recommendation: accelerate establishment of a FX futures market in China while transitioning to market-based regulation to ensure stability and sustainability of the market.

*Source: wpiea2021268-print-pdf - References 21*

### References 21

### wpiea2021268-print-pdf - References 21

### I. Introduction and rationale for an onshore FX futures market
- Since 2016, the People’s Bank of China has withdrawn from daily interventions and significantly enhanced RMB exchange rate flexibility; further increasing flexibility and ultimately establishing a floating exchange rate regime is in China’s interest to support capital market opening and RMB internationalization.
- Greater exchange rate flexibility may increase profits volatility for exporters/importers and vulnerability of firms with large foreign debt exposures, contributing to some emerging markets’ reluctance to float.
- A sufficiently deep and liquid FX derivatives market is crucial to move toward a floating exchange rate while ensuring economic and financial stability.
- China’s OTC FX derivatives market exists (forwards, swaps, options) but lacks an onshore FX futures market, which:
  - Limits participation by SMEs and retail traders due to high transaction costs in the OTC market.
  - Reduces centralized price discovery, market transparency, and accessibility of low-cost standardized hedging tools.
- Advantages of an onshore FX futures market (as contrasted with an OTC market):
  - Standardized, low-cost products; centralized market with greater transparency; lower credit risk; more effective supervision.
  - Better service to a broader range of market participants, improving the economy’s resilience to external shocks and reducing the balance-sheet effect of exchange rate fluctuations.
- Concerns about speculative amplification of volatility exist in theory, but practical inability to distinguish hedgers from speculators means policy must focus on conditions and regulatory practices to manage risks.

### II. Empirical study: design and data
- Objective: examine whether establishment of FX futures markets among BRICS (country-specific focus on India, Russia, South Africa) increases spot FX volatility.
- Currency pairs used (daily closing values from Bloomberg): USDINR, USDRUB, USDZAR.
- Cutoff dates identifying the beginning of a stable rise in currency futures trading:
  - India: January 2009
  - Russia: January 2006
  - South Africa: January 2008
- Pre-cutoff-period and Post-cutoff-period lengths: two years before and after the cutoff date.
- Return calculation: daily rate of return = natural logarithm of the ratio of present day’s index level to previous day’s index level.
- Unit root testing: ADF methods; presence of ARCH effect assessed by LM test.
- Volatility modeled with GARCH(1,1):
  - Mean: yt = vt + εt
  - Variance: σt^2 = α0 + α1 εt−1^2 + β σt−1^2
  - Parameter constraints: α0 > 0; α1 > 0; β ≥ 0; α1 + β < 1.

### III. Empirical results — country findings and key statistics

- India (USDINR)
  - Descriptive statistics (Table 1):
    - Pre (Obs 507): Mean -0.0001923; Std. Dev. 0.0047907; Min -0.024074; Max 0.0189109
    - Post (Obs 485): Mean 0.0001808; Std. Dev. 0.0053458; Min -0.0170301; Max 0.0302912
  - ADF test (Table 2): Pre statistic -14.669 (Obs 507, P value 0.0000); Post statistic -16.165 (Obs 485, P value 0.0000) — series stationary at 1%.
  - LM test: ARCH effect significant (zero probability).
  - GARCH(1,1) results (Table 3):
    - Pre-Derivative: Intercept (α0) 5.40e-07; ARCH (α1) 0.1595126; GARCH (β1) 0.8292628; α1+β1 0.9887754; P values 0.000 across coefficients.
    - Post-Derivative: Intercept (α0) 3.08e-06; ARCH (α1) 0.1259465; GARCH (β1) 0.7386511; α1+β1 0.8645976; P values 0.000 across coefficients.
  - Unconditional variance (Varεt = α0 / (1 − (α1 + β1))):
    - Pre-period: 0.00004810862
    - Post-period: 0.00002274701
  - Main finding: persistence of volatility decreased in the Post-period; introduction of FX futures markets did not increase spot volatility in India and is associated with decreased volatility.

- Russia (USDRUB)
  - Descriptive statistics (Table 4):
    - Pre (Obs 522): Mean 0.0000331; Std. Dev. 0.0019555; Min -0.006682; Max 0.006992
    - Post (Obs 521): Mean 0.0002986; Std. Dev. 0.0021288; Min -0.0073153; Max 0.0098162
  - ADF test (Table 5): Pre statistic -21.517 (Obs 520, P value 0.0000); Post statistic -22.323 (Obs 520, P value 0.0000) — series stationary at 1%.
  - LM test: ARCH effect exists.
  - GARCH(1,1) results (Table 6):
    - Pre-Derivative: Intercept (α0) 8.60e-08; ARCH (α1) 0.1023693; GARCH (β1) 0.881888; α1+β1 0.9842581; P values 0.000 across coefficients.
    - Post-Derivative: Intercept (α0) 4.71e-08; ARCH (α1) 0.0329523; GARCH (β1) 0.9573649; α1+β1 0.9968879; P values: Intercept 0.281, ARCH 0.017, GARCH 0.000, α1+β1 0.000.
  - Unconditional variance:
    - Pre-period: 0.00000546285
    - Post-period: 0.0000048643
  - Main finding: ARCH coefficient decreased while GARCH coefficient increased; overall unconditional variance decreased slightly after introduction of FX futures.

- South Africa (USDZAR)
  - Descriptive statistics (Table 7):
    - Pre (Obs 521): Mean -0.0001554; Std. Dev. 0.0096418; Min -0.032557; Max 0.0277545
    - Post (Obs 523): Mean -0.0001437; Std. Dev. 0.0163603; Min -0.154965; Max 0.0662992
  - ADF test (Table 8): Pre statistic -23.344 (Obs 520, P value 0.0000); Post statistic -23.688 (Obs 520, P value 0.0000) — series stationary at 1%.
  - LM test: ARCH effect exists.
  - GARCH(1,1) results (Table 9):
    - Pre-Derivative: Intercept (α0) 4.01e-06; ARCH (α1) 0.0322642; GARCH (β1) 0.9247918; α1+β1 0.957056; P values: Intercept 0.250; ARCH 0.098; GARCH 0.000; α1+β1 0.098.
    - Post-Derivative: Intercept (α0) 5.00e-06; ARCH (α1) 0.1492664; GARCH (β1) 0.8454004; α1+β1 0.9946668; P values: Intercept 0.164; ARCH 0.000; GARCH 0.000; α1+β1 0.000.
  - Main observation: ARCH coefficients increased and GARCH coefficients decreased, indicating more volatility from new information and less from persistent old information; overall unconditional variance of returns increased in the Post-period.
  - Contextual factor: South Africa’s Post-period coincides with the 2008 global financial crisis, which plausibly contributed to increased volatility.

### IV. Robustness checks: controlling for the financial crisis
- Method: introduced a dummy variable “financial crisis” (DF) for September–December 2008 (binary 1 for crisis period, 0 otherwise) based on Libor–OIS spread evidence (6-month Libor–OIS spread stayed above 200 basis points from September to December 2008).
- Modified variance equation: σt^2 = α0 + α1 εt−1^2 + β σt−1^2 + δ DF
- South Africa (Table 10) — impact controlled:
  - Pre-Derivative: Intercept (α0) 4.01e-06; ARCH (α1) 0.0322642; GARCH (β1) 0.9247918; α1+β1 0.957056; P values as before.
  - Post-Derivative (with DF): Intercept (α0) 0.000275; ARCH (α1) 0.0720019; GARCH (β1) 0.8662979; α1+β1 0.9382998; δ 1.876881; P value for δ 0.000.
  - Result: after controlling for the crisis, ARCH increases and GARCH decreases, and overall unconditional variance decreases — supporting that the 2008 crisis drove the observed volatility rise; introduction of futures reduced overall volatility when crisis effects are controlled.
- India (Table 11) — impact controlled:
  - Pre-Derivative (with DF): Intercept (α0) -14.02913; ARCH (α1) 0.1438344; GARCH (β1) 0.8035084; α1+β1 0.9473428; δ 2.168283; P values 0.000 across entries.
  - Post-Derivative: Intercept (α0) 3.08e-06; ARCH (α1) 0.1259465; GARCH (β1) 0.7386511; α1+β1 0.8645976; P values 0.000.
  - Result: results for India hold after introducing financial crisis dummy — introduction of futures market reduced overall volatility.

### V. Main empirical conclusion
- Across the studied emerging markets (India, Russia, South Africa), establishment of FX futures markets did not increase spot-market volatility; in some cases unconditional volatility decreased.
- For South Africa, observed post-introduction volatility rise is largely attributable to the global financial crisis; after controlling for it, futures introduction is associated with reduced volatility.
- Empirical implication: in emerging market contexts, FX futures markets tend to act as stabilizers rather than volatility amplifiers, possibly because diversified participants (including speculators) help the exchange rate return faster to equilibrium by “buying low and selling high.”

### VI. Regulatory design and policy recommendations for China
- Phase out requirement of underlying exposure gradually:
  - The requirement once served to inform regulators of trade-based FX demand but has become counterproductive, limiting market scale, liquidity, depth, and preemptive hedging.
  - International experience (e.g., India) shows relaxing the requirement with the introduction of futures is feasible; OTC restrictions can be removed in a phased manner.
- Adopt market-based regulatory tools instead of underlying-exposure documentation:
  - Margin requirement (leverage ratio):
    - Cross-country margins in emerging markets: within 5%–10% (implying leverage ratios 10–20).
    - Suggested initial margin for China: 5% (allowing 20 times leverage) for most customers; 10% (allowing 10 times leverage) for higher-risk customers; adjust over time and gradually decrease as market matures.
    - Reference margins in developed markets: CME USD/CNH Futures between 1.5% and 2.4%; Hong Kong Stock Exchange ~2%; Singapore Exchange ~1%.
  - Limitations on margin/net financial assets:
    - Prohibit borrowed margin payments; cap margin of traders as a percentage of net financial assets with differentiated levels by scale and orientation.
  - Position limits:
    - To prevent manipulation and concentration; example: India sets gross open position limits of clients and members to 6% and 15% of total open interests respectively; China could set dynamic limits with warnings beyond thresholds.
  - Settlement choice:
    - Cash settlement (local-currency-denominated) appropriate initially given incomplete RMB capital account convertibility; cash settlement reduces cross-border pressures and suits speculators and liquidity.
    - Physical delivery more suitable when currency is fully convertible.
  - Daily price bands:
    - Most developed and developing countries do not set daily price bands; India and Hungary are exceptions.
    - Price bands can impede price discovery and attract speculation; given reduced central bank interventions, little need for daily bands in China; central bank should retain right to intervene under disorderly conditions.
  - Role of central banks and supervisory authorities:
    - Joint oversight by central bank and securities regulator; central bank responsibility: market access guidance, monitoring financing sources, dynamic trading parameters (margins, limits), direct market participation and intervention as needed.
    - Securities regulatory commission: enforce regulations and standards for supervised market participants.
    - Effective coordination indispensable.
  - Encourage broader use of derivatives tools and hedge accounting:
    - Hedge accounting reduces profit volatility from derivatives mark-to-market; regulators should educate firms and investors to adopt risk-neutral perspectives focused on core business.
  - Platform selection and liquidity considerations:
    - Exchange-traded markets historically common but face early-stage liquidity challenges.
    - Given China’s inter-bank participants’ dominance, consider establishing FX futures in the inter-bank market initially to mobilize banks, improve liquidity, and encourage complementarity between forward and futures markets.
    - Allow all types of market participants access at inception; electronic platform to cross geographical boundaries; permit commercial banks and institutions to act as market makers and arbitrageurs.

### VII. Conclusion
- International experience and the paper’s empirical analysis indicate FX futures markets are important complements to spot and OTC markets by serving many investors and improving price discovery.
- Empirical evidence from the studied emerging markets suggests that the FX futures market functions more like a “stabilizer” than a “risk amplifier.”
- Policy recommendation: accelerate establishment of a FX futures market in China while transitioning to market-based regulation to ensure stability and sustainability of the market.

*Source: wpiea2021268-print-pdf - References 21*

### REFERENCES

### REFERENCES

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- 22
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- Prakash, A., 2012, Major episodes of volatility in the Indian FX market in the last two decades (1993-2013): Central Bank’s Response. Reserve Bank of India Occasional Papers, 33(1 & 2). 
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- Shastri, K., Sultan, J., and Tandon, K., 1996, The impact of the listing of options in the FX market. Journal of International Money and Finance, 15: 37–64.  
- Stein, J., 1987, Informational externalities and welfare reducing speculation. Journal of Political Economy, 95: 1123–45.  
- Stoll, H., and Whaley, R., 1988, Volatility and futures: Message versus messenger. Journal of Portfolio Management, 14(2): 20–2.

*Source: wpiea2021268-print-pdf - REFERENCES*

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_Source: https://www.imf.org/-/media/files/publications/wp/2021/english/wpiea2021268-print-pdf.pdf_