Covered Interest Rate Parity Research Articles

Whether SORF Is a More Effective Substitute for LIBOR in the Market?

This paper examines the transition from LIBOR to SOFR and its impact on financial markets. LIBOR, once a key benchmark rate, has faced credibility issues, leading to the proposal of new benchmark rates like SOFR. The study investigates whether SOFR is a suitable LIBOR replacement and analyzes its effects on financial markets. Using statistical analysis, including covered interest rate parity theory and hypothesis testing, the study compares the accuracy of SOFR and LIBOR in determining the risk-free rate. The findings support the hypothesis that SOFR calculations more accurately reflect real market data compared to LIBOR. However, the study is limited in its focus on the US dollar market, which may limit its generalizability. Future research could explore the transition to alternative benchmark rates in other currencies and regions. Additionally, incorporating real-time data could provide more current insights into SOFR's effectiveness as a LIBOR replacement. Overall, the transition from LIBOR to SOFR represents a significant change in financial markets. Further research is needed to fully understand its implications. Addressing these limitations and exploring future research directions can enhance our understanding of the transition's impact on the global financial system.

Arbitraging Covered Interest rate Parity Deviations and Bank Lending

I propose and test a new channel through which covered interest rate parity (CIP) deviations can affect bank lending in emerging economies. I argue that when CIP deviations exist, banks attempt to arbitrage them. To do so, banks must borrow in a particular currency. When this currency is scarce, bank lending in the currency required to arbitrage decreases, while they use this currency in their arbitrage activities. I test this channel by exploiting differences in the abilities of Peruvian banks to arbitrage CIP deviations. I find evidence that supports the proposed channel. (JEL F31, G01, G13, G21, O16)

The price discovery in the renminbi/USD market: Two spot, two swap, and three forward FX rates

This paper employs the vector error correction model (VECM) to measure the contribution of the onshore renminbi spot foreign exchange (CNY) rate to the price discovery of the offshore one (CNH). The VECM incorporates the covered interest rate parity condition by introducing the forward swap rate. Each rate has onshore and offshore markets, and the VECM encompasses the seven variables. This rich VECM challenges the small VECM with only two CNH and CNY rates, revealing an overstatement of the CNH's contribution. Additionally, CNY and CNH are the main contributors to the price discovery of the forward exchange rates. When the central parity is set to be weaker than the previous day's closing of the CNY, the CNY is dominant over the CNH in terms of the information share in the spot FX rate. This effect is amplified after the month of sluggish Chinese exports.

The Term Structure of Covered Interest Rate Parity Violations

ABSTRACTWe quantify the impact of risk‐based and nonrisk‐based intermediary constraints (IC) on the term structure of covered interest rate parity (CIP) violations. Using a stochastic discount factor (SDF) inferred from interest rate swaps, we value currency derivatives. The wedge between model‐implied and observed derivative prices reflects the impact of nonrisk‐based IC because our SDF incorporates risk‐based IC. There is no wedge at short horizons, while the wedge accounts for 40% of long‐term CIP violations. Consistent with IC theory, the wedge correlates with the shadow cost of intermediary capital, and the SDF‐implied interest rate is a weighted average of collateralized and uncollateralized interest rates.

Analysis of Long-Term Bond Yields Using Deviations from Covered Interest Rate Parity

Analysis of Long-Term Bond Yields Using Deviations from Covered Interest Rate Parity

Original sin redux and deviations from covered interest parity

Emerging markets (EMs) have increasingly turned to international capital borrowing in their local currencies (LC), leading to considerable LC external debts, particularly after the 2007 global financial crisis. Our study shows that this rise in LC external debts results in more significant deviations from the covered interest rate parity (CIP) between EMs and the US. This phenomenon is primarily attributed to a shift of currency mismatch risk and specific transaction costs from EM borrowers to international investors. As a result, EMs encounter elevated funding costs in comparison to the US, since investors seek higher returns to offset the added risks and expenses linked to LC external debts. Our analysis further underscores that the influence of LC external debts on amplifying CIP deviations is especially notable in EMs marked by substantial currency mismatch risks, such as those with floating exchange rate systems, heightened inflation risks, and significant currency depreciations. Moreover, the presence of stringent capital controls and limited debt market liquidity, which signify high transaction costs, intensify these effects.

A Quantity-Driven Theory of Term Premia and Exchange Rates

AbstractWe develop a model in which specialized bond investors must absorb shocks to the supply and demand for long-term bonds in two currencies. Since long-term bonds and foreign exchange are both exposed to unexpected movements in short-term interest rates, a shift in the supply of long-term bonds in one currency influences the foreign exchange rate between the two currencies, as well as bond term premia in both currencies. Our model matches several important empirical patterns, including the comovement between exchange rates and term premia, and the finding that central banks’ quantitative easing policies affect exchange rates. An extension of our model links spot exchange rates to the persistent deviations from covered interest rate parity that have emerged since 2008.

Currency carry trades and global funding risk

We measure funding constraints in currency markets by deviations in the covered interest rate parity and funding risk by the standard deviation of the magnitude of the funding constraints. Empirically, funding risk is driven by financial sector conditions in the low interest rate countries, oil price, and the actions of the main central banks. Since 2008, funding risk has affected currency carry trading activity, carry trade returns, correlation between carry trade long and short currencies, relative equity returns, and the economic growth in the carry trade long and short countries. We develop a theory of currency markets under funding constraints to explain the phenomena. The model has additional testable implications: For instance, as funding constraints start to bind, it predicts that both the investment and the funding currencies crash relative to a safe asset. This result is observable empirically when we use gold to proxy for the safe asset.

The US Dollar and Covered Interest Rate Parity Deviations: Oil Price Channel

The US Dollar and Covered Interest Rate Parity Deviations: Oil Price Channel

Why exchange rate pass-through matters in forward exchange markets

Persistent deviations from a covered interest rate parity (CIRP) have been observed between the United States (US) and the United Kingdom (UK) from January 2002 to August 2020. This study argues that the CIRP does not hold because even if income from domestic and foreign investments is equalized, foreign investment's utility could be higher than that of domestic investment depending on the exchange rate pass-through (ERPT) into import price. Theoretically, the deviations of observed forward exchange rates from CIRP conditions are attributed to changes in importable goods prices and ERPT. A change in net capital flow affects import price volatilities and deviations from the CIRP. Therefore, the forward exchange rate depends not only on the interest rate differential between countries but also on ERPT into the import price. Using a logarithmic utility function, this study derives a utility-equalizing forward rate (UEFR). An increase in net capital outflow and the ERPT into the import price reduces the UEFR. Our empirical evidence shows that from December 2011 to June 2020, the UEFR estimates trace the actual US−UK forward exchange rates better than CIRP.

Covered interest rate parity deviations in the Asia-Pacific

Recent evidence has documented a failure in the covered interest rate parity (CIP) condition post Global Financial Crisis (post-GFC). Using a model which incorporates the transaction costs embedded in the bid-ask spread, we find evidence that while raw deviations from this relation have increased, market makers spreads have also widened, resulting in a decreasing trend in both the magnitude and duration of CIP deviations after adjusting for transaction costs. This finding, however, is highly market specific and varies considerably between developed and emerging market countries. These conclusions are robust to the post-GFC period and trading strategies designed to exploit these deviations were found to generally perform poorly.

A New Testable Theory on Deviations from Covered Interest Rate Parity

A New Testable Theory on Deviations from Covered Interest Rate Parity

The Term Structure of Covered Interest Rate Parity Violations

The Term Structure of Covered Interest Rate Parity Violations

Mind the Violation of Covered Interest Rate Parity, an Emerging Market Perspective

Mind the Violation of Covered Interest Rate Parity, an Emerging Market Perspective

Deviations from the covered interest parity: The role of fundamentals, financial and political turmoil, and market frictions

Recent studies of mature markets on covered interest parity suggest that deviations are mean-reverting, but persistent, particularly after the 2008 crisis (Du et al., 2018). Our study contributes to the literature by modeling the deviations from covered interest rate parity (CIP) of an important emerging-market economy. We focus on Brazilian data, given the importance of its derivative market. One of the strengths of our study is the use of an agnostic approach, based on an automatic model-selection technique that is robust to structural change, the Autometrics algorithm (Hendry and Doornik, 2014), to unveil the possible determinants of CIP deviations from a wide information data set. We show that CIP deviations are highly sensitive to changes in Brazilian federal government total debt, level of reserves, inflation, and degree of trade openness. We also document the existence of instability in the model due to financial and political turmoil. We reach these conclusions based on the algorithm’s intercept correction, which can be seen as a byproduct of our methodology. Finally, we find evidence that, even after correction for fundamentals and instability points, CIP deviations still have persistence, suggesting that market frictions play an important role in the dynamics of CIP deviations.

Arbitrage Capital of Global Banks

We show that the role of unsecured, short-term wholesale funding for global banks has changed significantly in the post-financial-crisis regulatory environment. Global banks mainly use such funding to finance liquid, near risk-free arbitrage positions—in particular, the interest on excess reserves arbitrage and the covered interest rate parity arbitrage. In this environment, we examine the response of global banks to a large negative wholesale funding shock as a result of the U.S. money market mutual fund reform implemented in 2016. In contrast to past episodes of wholesale funding dry-ups, we find that the primary response of global banks to the reform was a cutback in arbitrage positions that relied on unsecured funding, rather than a reduction in loan provision.

Volatility, intermediaries, and exchange rates

We propose and estimate a quantitative model of exchange rates in which participants in the foreign exchange market are intermediaries subject to value-at-risk (VaR) constraints. Higher volatility translates into tighter VaR constraints, and intermediaries require higher returns to hold foreign assets. Therefore, the foreign currency is expected to appreciate. The model quantitatively resolves the Backus–Smith puzzle, the forward premium puzzle, and the exchange rate volatility puzzle and explains deviations from the covered interest rate parity. Moreover, the model implies both contemporaneous and predictive relations between proxies of leverage constraint tightness and exchange rates. These implications are supported in the data.

Currency Carry Trades and Global Funding Risk

We measure funding constraints in international currency markets by deviations in the covered interest rate parity. Our measure of funding risk is the standard deviation of the magnitude of the funding constraints. This funding risk measure appears to be driven by conditions in the financial sector in the low interest rate, so called carry trade short countries, oil price volatility, as well as by the actions of the main central banks. Although funding risk has been present throughout our sample, it becomes only relevant in currency carry trading after 2008, suggesting that investors’ funding constraints start binding at that time. We document evidence that since 2008 funding risk has affected the magnitude of currency carry trading activity, carry trade returns, correlation between carry long and short currencies, relative equity returns in carry trade long vs. short countries, and the economies of carry trade long countries measured through changes in industrial production. We develop a theory of currency markets under funding constraints that has several testable implications. For instance, as funding constraints start to bind, our theory predicts that both the investment and funding currencies drop relative to a safe asset. This result is observable also in our empirical analysis, when we proxy for the safe asset with gold. In line with theory, funding risk forecasts currency crashes in the carry trade long and short countries.

Arbitraging Covered Interest Rate Parity Deviations and Bank Lending

In this paper, I propose and test a new channel that can affect bank lending in an emerging markets setting. This channel works as follows. When there are covered interest rate parity (CIP) deviations, banks attempt to arbitrage them. This requires banks to borrow in a particular currency. In the presence of borrowing frictions, banks either increase the rates paid for deposits to arbitrage or shift a portion of the resources used to lend to fund their arbitrage activities. Either case, bank lending in the currency required to arbitrage decreases. I test this channel by exploiting differences in the abilities of Peruvian banks to arbitrage CIP deviations. I show that banks that have greater ability to arbitrage reduce their lending in the currency they need to fund their CIP arbitrage. This is partly compensated by lending in a different currency. This evidence suggests that arbitraging CIP deviations can affect the currency composition of bank lending.

Deviations from Covered Interest Rate Parity: The Case of British Pound Sterling versus Euro

The authors find that the foreign exchange derivatives market for British pound sterling versus euro deviates from the covered interest rate parity (CIP). The resulting arbitrage opportunities seem to be persistent and vary systematically. They are driven not only by Brexit-related politics. The authors find a relation between the cross-currency basis and various factors. Furthermore, they discover nonlinearities that require the application of deep learning methods. The findings are important for arbitrage desks: They show when arbitrage opportunities will become large for international trade, when to look for better alternatives than hedging with forwards, and when corporate treasuries should procure currencies—that are about to become scarce—in advance. <b>TOPICS:</b>Big data/machine learning, currency, simulations <b>Key Findings</b> ▪ We focus on the investigation of deviations from covered interest rate parity on the British pound and the euro and include event-driven factors. ▪ Arbitrage opportunities seem to be persistent and vary systematically. We make the driving factors explicit. ▪ The presence of nonlinearities requires the application of methods from deep learning. It is shown that deep learning adds value. Equipped with better forecasts, arbitrage desks can prepare for days when there are large arbitrage gains. Corporates can punctually adapt their procurement of currencies that are about to become scarce.