## 1.  Between 2006 and 2012, the BCB tried to stem appreciation pressures on therealand strong

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### FX intervention instruments and history
- Between 2006 and 2012 the BCB accumulated FX reserves of almost 400 USD billion, equal to about 18 percent of GDP, and kept this level stable throughout the period of analysis.
- From 2013 onward FX intervention was conducted primarily in the derivative market via FX swaps that settle in reais.
- Key observed dynamics:
  - The stock of FX swaps started to increase sharply in 2013; swaps increased to almost 120 billion USD in 2015, then declined rapidly in 2016, and rose again in May 2018.
  - Auction features (May 31, 2013–Feb 28, 2019): maturity varies from a few days to a year and a half, with an average of 7 months; average value of FX swaps sold in a given auction is 200 million USD (some auctions reached a few billion USD); auction size can be negative (reducing outstanding stock).
- Swap mechanics (per-auction): BCB sells a swap pledging repayment of 50,000 USD at maturity converted in BRL at the spot exchange rate of the previous day; bidders offer a discounted value (the bid cupom cambial) and pay the accumulated Selic rate between settlement and maturity.
- Net USD revenues on a swap are given by (equation presented in source):  
  50,000 [ e_{S-1} / e_{T-1} * ∏_{t=S}^{T-1} (1 + i_t) / (1 + c_A) − 1 ]  
  (where e_t = BRL per USD, subscripts A,S,T denote auction, settlement, maturity; i_t = daily Selic; c_A = bid cupom cambial)

### Profitability of FX swaps (realized vs expected)
- Realized (ex-post) performance (May 2013–Sep 2018):
  - Cumulative losses of about 7.3 billion USD, peaking to 25.6 billion USD in April 2015.
  - Realized returns stopped being computed after Sep 2018 because many swaps matured in the future relative to writing.
- Expected (ex-ante) performance (using Market Expectations System on auction dates, horizon up to 18 months):
  - Cumulative expected profits reached 19.8 billion USD at the end of February 2019.
  - Hybrid calculation using realized exchange rates with market Selic expectations yielded losses of about 8.4 billion USD, indicating realized losses mainly driven by the BRL depreciating more than expected.
- Interpretation:
  - Ex-ante profitability suggests the BCB intervened against deviations from UIP equilibrium conditions (leaning against excessive movements).
  - Ex-post losses reflect unanticipated depreciation beyond expectations.

### Summary statistics on expected returns (preserving source tables)
- Table 1 (Average expected profitability of FX swaps, annualized, percent)
  - Full sample (all swaps): 5.6
  - Core sample (excluding pre-announced and rollover swaps): 9.8
- Table 2 (Average expected profitability using later surveys, annualized, percent)
  - Using surveys collected after auction by one week / two weeks / three weeks / four weeks:
    - Full sample: 3.3, 2.0, 1.7, 1.1
    - Core sample: 4.5, 1.9, 1.1, -0.1
  - Even using forecasts up to four weeks after auction, swaps remain profitable in expectation in many specifications.
- Average BRL expected excess return over USD (from equation 2):
  - On average 4.7 and 4.2 percent at the 6 and 9 month horizons, confirming a significant BRL premium.
  - Expected returns on swap sales (6–10 percent) exceed this average premium.

### Determinants of FX intervention (regression evidence)
- Sample:
  - About 2,900 swap auctions (May 31, 2013–Feb 28, 2019); core sample ≈ 800 auctions (about 36 percent of total notional).
- Key regression findings (Table 3 and discussion):
  - Positive and highly significant correlation between swap sales (million USD; negative = purchases) and expected swap returns (annualized percent).
  - Coefficient magnitude increases for the core sample (excluding pre-announced and rollover swaps).
  - Controls included: BRL depreciation over prior day and prior ten days; gap between cupom cambial and USD rate (6-month horizon); lags of swap sales; financial variables (sovereign spreads, CDS, stock returns).
  - Gap between cupom cambial and USD rate: swap sales negatively correlated with this gap (interpreted as BCB absorbing currency risk when on-shore USD rate weakens).
  - Quantitative impacts: one-standard-deviation shocks to:
    - swap expected return affect swap issuance by 135 million USD,
    - exchange rate depreciation over prior ten days affect swap issuance by 21 million USD,
    - cupom cambial gap affect swap issuance by 51 million USD.
  - Robustness: results persist after winsorizing 1 percent outliers and adding financial controls.
- Aggregate daily analysis (Table 4):
  - Regressions of total daily swap sales on expected BRL excess return at 6 and 9 month horizons show strong positive correlations (example coefficients: 19.99*** for 6-month, 34.75*** for 9-month in baseline).
  - Results hold when including days with zero swap issuance and controlling for BRL depreciation and cupom cambial gap.

### Role of uncertainty and asymmetries in intervention
- Measure of uncertainty:
  - Market Expectations System provides dispersion measure (coefficient of variation, CV) of exchange rate forecasts.
  - Method: predict CV as function of forecast horizon and survey fixed effects; compute gap between actual CV for a swap and its predicted CV (horizon-corrected uncertainty).
- Findings (Table 5 and discussion):
  - Swap sales are negatively correlated with forecast uncertainty: BCB sold more swaps (i.e., intervened more to prop up BRL) when forecast uncertainty was lower.
  - Interaction: expected swap profitability × forecast uncertainty is negative and significant, implying stronger intervention against UIP deviations when uncertainty was low.
  - Alternative measure using unconditional 6-month CV confirms results.
  - Swap purchases sample small; uncertainty coefficients not statistically significant for purchases.
- Asymmetry (Table 6):
  - BCB response is asymmetric: swap sales react more strongly when the expected swap return is negative (i.e., when BRL is overvalued) than when positive.
  - Interpreted as BCB being more vigorous in repurchasing swaps (shortening BRL exposure) when currency appears overvalued; less eager to sell swaps when BRL undervalued, consistent with reluctance to shorten USD position or sell reserves.

### Conclusions and policy questions
- Primary conclusions:
  - FX intervention in Brazil (via FX swaps) was profitable in expectation and tailored to lean against deviations from UIP equilibrium conditions: BCB went long in BRL when undervalued and shortened BRL when overvalued.
  - Intervention intensity correlated strongly with expected swap profitability and with deviations in covered interest parity (cupom cambial vs USD rates).
  - BCB intervened more decisively when exchange rate forecasts were less uncertain and showed asymmetry toward stronger responses to overvaluation.
- Open policy questions raised by the analysis:
  - Should central banks explicitly monitor expected profitability and UIP deviations in real time (using survey forecasts) to guide FX intervention and provide market clarity?
  - Given that FX swaps can be profitable when used to smooth excessive exchange rate movements, are concerns about swap sustainability (absent large FX reserves) potentially overstated? Could swap-based intervention be viable for countries without large reserve cushions?

### Appendix A: Pre-announced and rollover swaps
- Core sample exclusion rule:
  - The core sample of analysis excludes pre-announced and rollover swaps.
- Identifying pre-announced swaps:
  - Pre-announced swaps are identified based on the BCB press releases in 2013 and 2014.
  - The BCB provided some indications regarding future swap sales also in 2018, but the statements were more vague, making it hard to identify specific auctions as pre-announced.
  - Experiments removing some 2018 auctions from the core sample produced results that were broadly unchanged.
- Table 7: Identifying pre-announced swap auctions (press release dates, descriptions, and Number of pre-announced auctions):
  - August 22, 2013 — Swap auctions of $500 million will take place every Monday, Tuesday, Wednesday and Thursday, from August 23 to at least December 31. — 97
  - December 18, 2013 — Swap auctions of $200 million per day will take place from Monday to Friday, starting from January 2 to at least June 30, 2014. — 183
  - June 14, 2014 — Swap auctions of $200 million per day will take place from Monday to Friday, starting from July 1 to at least December 31, 2014. — 227
  - December 30, 2014 — Swap auctions of $100 million per day will take place from Monday to Friday, starting from July 1 to at least March 31, 2015. — 113
- Identifying rollover swaps:
  - Method: compute the total amount of swaps that settle and that mature in a given day. If the difference between the two is less than 0.5 billion USD, code the swaps that settle that day as rollover swaps and exclude them from the core sample of analysis.
  - Example: during the month of October 2018 the BCB held 46 swap sales with settlement date on November 1st, 2018 for a total of 8,026.5 million USD. Since on November 1st 2018 a similar amount of swaps came to maturity for 8,026.7 USD million, we consider the swaps sold in October 2018 as rollover ones.

*Source — content unit "wpiea2020090-print-pdf - 1.  Between 2006 and 2012, the BCB tried to stem appreciation pressures on therealand strong" (extracted text provided).*

### 1.  Between 2006 and 2012, the BCB tried to stem appreciation pressures on therealand strong

### 1.  Between 2006 and 2012, the BCB tried to stem appreciation pressures on therealand strong

### FX intervention instruments and history
- Between 2006 and 2012 the BCB accumulated FX reserves of almost 400 USD billion, equal to about 18 percent of GDP, and kept this level stable throughout the period of analysis.
- From 2013 onward FX intervention was conducted primarily in the derivative market via FX swaps that settle in reais.
- Key observed dynamics:
  - The stock of FX swaps started to increase sharply in 2013; swaps increased to almost 120 billion USD in 2015, then declined rapidly in 2016, and rose again in May 2018.
  - Auction features (May 31, 2013–Feb 28, 2019): maturity varies from a few days to a year and a half, with an average of 7 months; average value of FX swaps sold in a given auction is 200 million USD (some auctions reached a few billion USD); auction size can be negative (reducing outstanding stock).
- Swap mechanics (per-auction): BCB sells a swap pledging repayment of 50,000 USD at maturity converted in BRL at the spot exchange rate of the previous day; bidders offer a discounted value (the bid cupom cambial) and pay the accumulated Selic rate between settlement and maturity.
- Net USD revenues on a swap are given by (equation presented in source):  
  50,000 [ e_{S-1} / e_{T-1} * ∏_{t=S}^{T-1} (1 + i_t) / (1 + c_A) − 1 ]  
  (where e_t = BRL per USD, subscripts A,S,T denote auction, settlement, maturity; i_t = daily Selic; c_A = bid cupom cambial)

### Profitability of FX swaps (realized vs expected)
- Realized (ex-post) performance (May 2013–Sep 2018): cumulative losses of about 7.3 billion USD, peaking to 25.6 billion USD in April 2015. (Realized returns stopped being computed after Sep 2018 because many swaps matured in the future relative to writing.)
- Expected (ex-ante) performance (using Market Expectations System on auction dates, horizon up to 18 months):
  - Cumulative expected profits reached 19.8 billion USD at the end of February 2019.
  - Hybrid calculation using realized exchange rates with market Selic expectations yielded losses of about 8.4 billion USD, indicating realized losses mainly driven by the BRL depreciating more than expected.
- Interpretation: ex-ante profitability suggests the BCB intervened against deviations from UIP equilibrium conditions (leaning against excessive movements), while ex-post losses reflect unanticipated depreciation beyond expectations.

### Summary statistics on expected returns (preserving source tables)
- Table 1 (Average expected profitability of FX swaps, annualized, percent)
  - Full sample (all swaps): 5.6
  - Core sample (excluding pre-announced and rollover swaps): 9.8
  - (Table separates swap sales and swap purchases but core numbers cited above)
- Table 2 (Average expected profitability using later surveys, annualized, percent)
  - Using surveys collected after auction by one week / two weeks / three weeks / four weeks:
    - Full sample: 3.3, 2.0, 1.7, 1.1
    - Core sample: 4.5, 1.9, 1.1, -0.1
  - Even using forecasts up to four weeks after auction, swaps remain profitable in expectation in many specifications.

- Average BRL expected excess return over USD (from equation 2): on average 4.7 and 4.2 percent at the 6 and 9 month horizons, confirming a significant BRL premium; expected returns on swap sales (6–10 percent) exceed this average premium.

### Determinants of FX intervention (regression evidence)
- Sample: about 2,900 swap auctions (May 31, 2013–Feb 28, 2019); core sample ≈ 800 auctions (about 36 percent of total notional).
- Key regression findings (Table 3 and discussion):
  - Positive and highly significant correlation between swap sales (million USD; negative = purchases) and expected swap returns (annualized percent).
  - Coefficient magnitude increases for the core sample (excluding pre-announced and rollover swaps).
  - Controls included: BRL depreciation over prior day and prior ten days; gap between cupom cambial and USD rate (6-month horizon); lags of swap sales; financial variables (sovereign spreads, CDS, stock returns).
  - Gap between cupom cambial and USD rate: swap sales negatively correlated with this gap (interpreted as BCB absorbing currency risk when on-shore USD rate weakens).
  - Quantitative impacts: one-standard-deviation shocks to (i) swap expected return, (ii) exchange rate depreciation over prior ten days, and (iii) cupom cambial gap affect swap issuance by 135, 21 and 51 million USD, respectively.
  - Robustness: results persist after winsorizing 1 percent outliers and adding financial controls.

- Aggregate daily analysis (Table 4):
  - Regressions of total daily swap sales on expected BRL excess return at 6 and 9 month horizons show strong positive correlations (coefficients: e.g., 19.99*** for 6-month, 34.75*** for 9-month in baseline).
  - Results hold when including days with zero swap issuance and controlling for BRL depreciation and cupom cambial gap.

### Role of uncertainty and asymmetries in intervention
- Market Expectations System provides dispersion measure (coefficient of variation, CV) of exchange rate forecasts.
- Method: predict CV as function of forecast horizon and survey fixed effects; compute gap between actual CV for a swap and its predicted CV (horizon-corrected uncertainty).
- Findings (Table 5 and discussion):
  - Swap sales are negatively correlated with forecast uncertainty: BCB sold more swaps (i.e., intervened more to prop up BRL) when forecast uncertainty was lower.
  - Interaction: expected swap profitability × forecast uncertainty is negative and significant, implying stronger intervention against UIP deviations when uncertainty was low.
  - Alternative measure using unconditional 6-month CV confirms results.
  - Swap purchases sample small; uncertainty coefficients not statistically significant for purchases.
- Asymmetry (Table 6):
  - BCB response is asymmetric: swap sales react more strongly when the expected swap return is negative (i.e., when BRL is overvalued) than when positive.
  - Interpreted as BCB being more vigorous in repurchasing swaps (shortening BRL exposure) when currency appears overvalued; less eager to sell swaps when BRL undervalued, consistent with reluctance to shorten USD position or sell reserves.

### Conclusions and policy questions
- Primary conclusions:
  - FX intervention in Brazil (via FX swaps) was profitable in expectation and tailored to lean against deviations from UIP equilibrium conditions: BCB went long in BRL when undervalued and shortened BRL when overvalued.
  - Intervention intensity correlated strongly with expected swap profitability and with deviations in covered interest parity (cupom cambial vs USD rates).
  - BCB intervened more decisively when exchange rate forecasts were less uncertain and showed asymmetry toward stronger responses to overvaluation.
- Open policy questions raised by the analysis:
  - Should central banks explicitly monitor expected profitability and UIP deviations in real time (using survey forecasts) to guide FX intervention and provide market clarity?
  - Given that FX swaps can be profitable when used to smooth excessive exchange rate movements, are concerns about swap sustainability (absent large FX reserves) potentially overstated? Could swap-based intervention be viable for countries without large reserve cushions?

*Italic: Source — content unit "wpiea2020090-print-pdf - 1.  Between 2006 and 2012, the BCB tried to stem appreciation pressures on therealand strong" (extracted text provided).*

### References

### References

### Cited works
- Adler, Gustavo, and Camilo E. Tovar Mora.2011. “Foreign Exchange Intervention:  A Shield against Appreciation Winds?”IMF Working Paper 11/165.
- Adler, Gustavo, and Rui C Mano.2019. “The cost of foreign exchange intervention: concepts and measurement.”Journal of Macroeconomics.
- Adler,  Gustavo,  Noemie  Lisack,  and Rui  Mano.2015.  “Unveiling the  Effects of  Foreign  Ex-change Intervention; A Panel Approach.”IMF Working Paper 15/310.
- Blanchard, Olivier, Gustavo Adler, and Irineu Filho de Carvalho.2015. “Can foreign exchange intervention stem exchange rate pressures from global capital flow shocks?”NBER Working Paper 21427.
- Calvo, Guillermo A, and Carmen M Reinhart.2002. “Fear of floating.”The Quarterly Journal of Economics, 117(2): 379–408.
- Cavallino, Paolo, and Damiano Sandri.2018. “The Expansionary Lower Bound: Monetary Easing and the Trilemma.”IMF Working Paper.
- Chamon, Marcos, Márcio Garcia, and Laura Souza.2017. “FX interventions in Brazil:  a synthetic control approach.”Journal of International Economics, 108: 157–168.
- Chang, Robert.2018. “Foreign Exchange Intervention Redux.”NBER Working Paper No. 24463.
- Chinn, Menzie D, and Jeffrey A Frankel.2019. “A Third Century of Currency Expectations Data: The Carry Trade and the Risk Premium.” working paper.
- Daude, Christian, Eduardo Levy Yeyati, and Arne J Nagengast.2016. “On the effectiveness of exchange rate interventions in emerging markets.”Journal of International Money and Finance, 64: 239–261.
- Dominguez, Kathryn M. E.2019. “Emerging Market Exchange Rate Policies: Stabilizing or Manipulation?”
- Dominguez,  Kathryn M. E.,  and Jeffrey Frankel.1993. “Does foreign-exchange intervention matter? The portfolio effect.”American Economic Review, 83(5): 1356–69.
- Dominguez, Kathryn M. E., Fatum R., and Vacek P.2013. “Do sales of foreign exchange reserves lead to currency appreciation?”Journal of Money, Credit and Banking, 45(5): 867–890.
- Du, Wenxin, Alexander Tepper, and Adrien Verdelhan.2018. “Deviations from Covered Interest Rate Parity.”Journal of Finance, 73(3): 915–957.
- Fanelli, S., and L. Straub.2018. “A theory of foreign exchange interventions.”Harvard working paper.
- Fatum, Rasmus, and Michael M. Hutchison.2003. “Is sterilised foreign exchange intervention effective after all? An event study approach.”The Economic Journal, 113(487): 390–411.
- Flood,  Robert,  and  Nancy  Marion.2001.  “Holding  International  Reserves  in  an  Era  of  High Capital Mobility.” 1–68.
- Fratzscher,  Marcel,  Oliver Gloede,  Lukas Menkhoff,  Lucio Sarno,  and Tobias Stöhr.2019. “When Is Foreign Exchange Intervention Effective?   Evidence from 33 Countries.”American Economic Journal: Macroeconomics, 11(1): 132–56.
- Friedman,  Milton.1953.  “The  Case  for  Flexible  Exchange  Rates.”  InEssays  in  Positive Economics. 157–203. The University of Chicago Press.
- Gabaix, Xavier, and Matteo Maggiori.2015. “International Liquidity and Exchange Rate Dynamics.”Quarterly Journal of Economics, 130(3): 1369–1420.
- Garcia, Márcio, and Tony Volpon.2014. “DNDFs: a more efficient way to intervene in FX markets?” PUC-Rio Discussion Paper No. 621.
- Garcia, Márcio, Marcelo Medeiros, and Francisco Santos.2014. “Price discovery in Brazilian FX markets.” PUC-Rio Discussion Paper No. 622.
- Gilmore, Stephen, and Fumio Hayashi.2011. “Emerging market currency excess returns.”American Economic Journal: Macroeconomics, 3(4): 85–111.
- Hauner,  David.2006.  “A  fiscal  price  tag  for  international  reserves.”International  Finance, 9(2): 169–195.
- Jacobson, Laurence R.1983. “Calculations of profitability for US dollar-deutsche mark intervention.”Staff Studies No. 131.
- Jeanne, Olivier, and Damiano Sandri.2018. “The global financial cycle and liquidity management.”Working Paper.
- Kohlscheen, Emanuel, and Sandro C. Andrade.2014. “Official FX interventions through derivatives.”Journal of International Money and Finance, 47: 202–216.
- Nedeljkovic, Milan, and Christian Saborowski.2019. “The Relative Effectiveness of Spot and Derivatives-Based Intervention.”Journal of Money, Credit and Banking.
- Neely, Christopher J.1998. “Technical analysis and the profitability of US foreign exchange intervention.”Federal Reserve Bank of St. Louis Review, 80(4): 3.
- Rodrik, Dani.2006. “The social cost of foreign exchange reserves.”International Economic Journal, 20(3): 253–266.
- Sarno, Lucio, and Mark P Taylor.2001. “Official intervention in the foreign exchange market: is it effective and, if so, how does it work?”journal of Economic Literature, 39(3): 839–868.
- Sweeney, Richard J.1997. “Do central banks lose on foreign-exchange intervention?  A review article.”Journal of Banking & Finance, 21(11-12): 1667–1684.
- Taylor, Dean.1982. “Official intervention in the foreign exchange market, or, bet against the central bank.”Journal of Political Economy, 90(2): 356–368.
- Yeyati, Eduardo Levy.2008. “The cost of reserves.”Economics Letters, 100(1): 39–42.

### Appendix A: Pre-announced and rollover swaps
- Core sample exclusion rule:
  - The core sample of analysis excludes pre-announced and rollover swaps.
- Identifying pre-announced swaps:
  - Pre-announced swaps are identified based on the BCB press releases in 2013 and 2014.
  - The BCB provided some indications regarding future swap sales also in 2018, but the statements were more vague, making it hard to identify specific auctions as pre-announced.
  - Experiments removing some 2018 auctions from the core sample produced results that were broadly unchanged.
- Table 7: Identifying pre-announced swap auctions (press release dates, descriptions, and Number of pre-announced auctions):
  - August 22, 2013 — Swap auctions of $500 million will take place every Monday, Tuesday, Wednesday and Thursday, from August 23 to at least December 31. — 97
  - December 18, 2013 — Swap auctions of $200 million per day will take place from Monday to Friday, starting from January 2 to at least June 30, 2014. — 183
  - June 14, 2014 — Swap auctions of $200 million per day will take place from Monday to Friday, starting from July 1 to at least December 31, 2014. — 227
  - December 30, 2014 — Swap auctions of $100 million per day will take place from Monday to Friday, starting from July 1 to at least March 31, 2015. — 113
- Identifying rollover swaps:
  - Method: compute the total amount of swaps that settle and that mature in a given day. If the difference between the two is less than 0.5 billion USD, code the swaps that settle that day as rollover swaps and exclude them from the core sample of analysis.
  - Example: during the month of October 2018 the BCB held 46 swap sales with settlement date on November 1st, 2018 for a total of 8,026.5 million USD. Since on November 1st 2018 a similar amount of swaps came to maturity for 8,026.7 USD million, we consider the swaps sold in October 2018 as rollover ones.

*Source: wpiea2020090-print-pdf - References*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020090-print-pdf.pdf_