# OTC Derivatives and Global Economic Activity: An Empirical Analysis

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## Abstract

**:**

## 1. Introduction

So it comes as no surprise that, based on the survey of global business of Bodnar et al. (2011), firms report that protection from price surprises is the most important reason for using OTC derivatives:“Why do we see this great success of financial futures and the financial futures industry? The reasons are the same as the reasons for the successful growth of any other industry: The industry is offering a product that people want. To show that they want it, they are willing to pay for it. What is the product that the world seems to want and that is so much in demand? The answer is insurance. The world wants insurance against price risk.”

Rating of Importance | ||

Objective | Very Important | Not Important |

Avoid losses from price surprises | 50% | 3% |

Expectations from shareholders | 41% | 3% |

Increase expected future cash flows | 38% | 3% |

Source: Bodnar et al. (2011). |

- to address the mismatch in interest-rate sensitivities in firms’ balance sheets
- to protect lenders from borrowers’ defaults.

“... Historically, securitization has played a valuable role in housing finance. By allowing interest rate and credit risks to be allocated efficiently among investors with varying risk appetites, it expanded access to credit for many credit-qualified Americans. ...”2

## 2. The Evolution of Global OTC Derivatives

## 3. Empirical Analysis

#### 3.1. Measurement

Counterparties $(i)$ | |||||

Non-Financial | Other Financial | Dealers | |||

Instruments $(j)$ | Foreign Exchange | Currency Swaps | ${D}_{11}$ | ${D}_{21}$ | ${D}_{31}$ |

Options | ${D}_{12}$ | ${D}_{22}$ | ${D}_{32}$ | ||

Interest Rate | Interest Rate Swaps | ${D}_{13}$ | ${D}_{23}$ | ${D}_{33}$ | |

Options | ${D}_{14}$ | ${D}_{24}$ | ${D}_{34}$ | ||

FRAs | ${D}_{15}$ | ${D}_{25}$ | ${D}_{35}$ | ||

Equity Linked | Forwards and Swaps | ${D}_{16}$ | ${D}_{26}$ | ${D}_{36}$ | |

Options | ${D}_{17}$ | ${D}_{27}$ | ${D}_{37}$ |

**Cash-Flow Equivalents**Because movements in the notional values of swaps and forwards have a net present value of zero, one could argue that sole reliance on these notional values is not ideal for examining the interdependencies between OTC derivatives and economic activity. Thus, for these instruments, we adjust their notional values to get their cash-flow equivalent as the product of notional values for swaps and forwards and a 5-year moving average of the 5-year swap rate ($R$, as a fraction).14 The resulting data matrix becomes:

Counterparties $(i)$ | |||||

Non-Financial | Other Financial | Dealers | |||

Instruments $(j)$ | Foreign Exchange | Currency Swaps | ${D}_{11}\xb7R$ | ${D}_{21}\xb7R$ | ${D}_{31}\xb7R$ |

Options | ${D}_{12}$ | ${D}_{22}$ | ${D}_{32}$ | ||

Interest Rate | Interest Rate Swaps | ${D}_{13}\xb7R$ | ${D}_{23}\xb7R$ | ${D}_{33}\xb7R$ | |

Options | ${D}_{14}$ | ${D}_{24}$ | ${D}_{34}$ | ||

FRAs | ${D}_{15}$ | ${D}_{25}$ | ${D}_{35}$ | ||

Equity Linked | Forwards and Swaps | ${D}_{16}\xb7R$ | ${D}_{26}\xb7R$ | ${D}_{36}\xb7R$ | |

Options | ${D}_{17}$ | ${D}_{27}$ | ${D}_{37}$ |

By Counterparty | ||

Non-financial | ${D}_{nf}^{c}{=(D}_{11}{+D}_{13}{+D}_{16}{)\xb7R+D}_{12}{+D}_{14}{+D}_{15}{+D}_{17}$ | |

Other financial | ${D}_{of}^{c}{=(D}_{21}{+D}_{23}{+D}_{26}{)\xb7R+D}_{22}{+D}_{24}{+D}_{25}{+D}_{27}$ | |

Dealer | ${D}_{d}^{c}{=(D}_{31}{+D}_{33}{+D}_{36}{)\xb7R+D}_{32}{+D}_{34}{+D}_{35}{+D}_{37}$ | |

By Instrument | ||

Foreign exchange | ${D}_{fx}^{c}{=(D}_{11}{+D}_{21}{+D}_{31}{)\xb7R+D}_{12}{+D}_{22}{+D}_{32}$ | |

Interest-rate | ${D}_{ir}^{c}{=(D}_{13}{+D}_{23}{+D}_{33}{)\xb7R+D}_{14}{+D}_{15}{+D}_{24}{+D}_{25}{+D}_{34}{+D}_{35}$ | |

Equity-linked | ${D}_{el}^{c}{=(D}_{16}{+D}_{26}{+D}_{36}{)\xb7R+D}_{17}{+D}_{27}{+D}_{37}$ | |

Aggregate | ${D}^{c}{=D}_{nf}^{c}{+D}_{of}^{c}{+D}_{d}^{c}{=D}_{fx}^{c}{+D}_{ir}^{c}{+D}_{el}^{c}$ |

**Expressing Derivatives in Real Terms**To characterize empirically the interdependencies between economic activities and OTC derivatives, we need to express the ${D}^{c}s$ in real terms. To this end, we deflate the cash-flow adjusted dollar value of derivatives by the OECD’s GDP deflator expressed in US dollars:

#### 3.2. Unconditional Correlations

- 2 measures of economic activity “a” (Real GDP and Real Exports of goods and services)
- 4 alternative counterparties (Non-Financial, Other Financial, Dealers, and Aggregate)
- 2 instruments: (Foreign-Exchange derivatives and Interest-Rate derivatives).

- OTC derivatives aggregated across counterparties against either GDP or exports
- OTC derivatives aggregated across instruments against either GDP or exports
- OTC derivatives by instrument and counterparty against either GDP or exports.

#### 3.3. Econometric Formulation

#### 3.4. Cointegration Tests

#### 3.4.1. Implementation

- 2 measures of economic activity ($a)$: Real GDP and Real Exports of goods and services
- 3 counterparties and their aggregate: Non-Financial, Other Financial, Dealers, and Aggregate
- 2 instruments: Foreign-Exchange derivatives and Interest-Rate derivatives17
- lags varying from 3 to 8 semesters.

#### 3.4.2. Results

#### 3.4.3. Statistical Reliability

#### 3.4.4. Model Fit

#### 3.4.5. Residuals’ Properties

#### 3.4.6. Dynamic Stability

#### 3.4.7. Parameter Constancy

## 4. Applications

#### 4.1. Estimating the Effects of Regulations

#### 4.2. Estimating Speculative Trades

...In the run-up to the financial crisis, OTC derivatives markets grew rapidly, with interest rate and credit derivatives growing the fastest, as shown in the chart below. While these derivatives provide an important vehicle for hedging economic risks, recent academic literature has argued that market participants also use these markets to take speculative directional exposures....

## 5. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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1. | Key features of OTC derivatives: Contracts are tailored to counterparties’ needs, counterparties do not post margins, contracts are not regulated: Only periodic disclosure required; no rules on who can hold derivatives; no limits on holdings. See the explanations provided by the Bank of International Settlements (BIS): https://www.bis.org/statistics/about_derivatives_stats.htm?m=6%7C32%7C639. |

2. | Dr. Michael Stegman before a Bipartisan Policy Center Panel “Reigniting the Private Label Mortgage-backed Securities Market” http://www.treasury.gov/press-center/press-releases/Pages/jl2634.aspx (accessed on 15 September 2014). |

3. | |

4. | (Smithson 1998, p. 229) and Merton (1973) relax the assumption of a constant interest rate in the Black-Scholes model. However, Merton did not endogenize the interest rate as a function of the aggregate derivative contracts. |

5. | Specifically, it is not enough to say that firms may use a forecast of GDP or interest rates. What is of interest is how those forecasts will react to changes in policies or other shocks. In addition, if they do and the associated forecast revision leads to a change in the hedging strategy, then it will represent the effect of economic activity on derivatives. |

6. | Interest in the finance-growth link is not new. What is new here is the focus on OTC derivatives. |

7. | |

8. | |

9. | |

10. | |

11. | The BIS’ Macroeconomic Assessment Group on Derivatives published a report (BIS 2013) finding that regulations on derivatives will have a minimal effect on economic activity (BIS 2013, p. 4). However, these calculations do not recognize the feedback effect from GDP to derivatives. BIS (2013) empirical work relies on models that treat the effect of income on derivatives as given. The idea is that deriviatives affect the cost of capital and therefore investment and therefore GDP. But again this work assumes that one can treat economic activity as not mattering for derivatives. |

12. | Thanks to Denis Pêtre from the BIS for clarifying the source of the unallocated derivatives. |

13. | Our data do not include Credit Default Swaps. The BIS treats this category separately and are a small fraction of the total; see http://www.bis.org/publ/otc_hy1705.pdf. |

14. | As one of the referees points out, further work is needed in this area. Importantly, there is no universally accepted method for converting notional values into cash-flow equivalents. We examined, however, the alternative of using the notional values as reported. The statistical properties of the associated models violate key assumptions such as residuals being white noise. Finding that ignoring adjustments leads to poor reliability does not automatically imply that our adjustment is correct but, we argue, it is better than the alternative. Specifically, given that the swap interest rate is influenced by economic fundamentals, we expect the movements in the adjusted series to embody economic information. |

15. | Thanks to one of the referees for calling this point to our attention. |

16. | The test result that we report is the one that minimizes the Akaike’s Information Criteria. The critical values for the ADF test are 5%–1.95; 1%–2.65. |

17. | Contracts on equity-linked derivatives are negligible and they are excluded from the modeling work. Their values are, however, included in the computation of the aggregates for the various counterparties; Section 3.1 shows the data matrix that we use. |

18. | See Doornik and Hendry (2013) for the empirical implementation of this test. |

19. | We could not reject the view that the residuals from the Engle-Granger equation are stationary. |

20. | For normality we use the Jarque-Bera test. For serial independence we test the hypothesis that all of the coefficients of an AR(7) of the residuals are jointly equal to zero. For homoskedasticity we test whether the residuals exhibit an ARCH of order 1. These tests are explained in Doornik and Hendry (2013). |

21. | |

22. | However, the BIS calculations do not recognize the feedback effect from GDP to derivatives. BIS (2013) empirical work relies on models that treat the effect of income on derivatives as given. The idea is that deriviatives affect the cost of capital and therefore investment and therefore GDP. Our contribution lies on treating economic activity as responding to regulations of derivatives. |

**Figure 16.**Autocorrelation function for OTC derivatives by counterparty and instrument. The horizontal green lines are the critical values for the hypothesis that the autocorrelation is zero.

**Figure 17.**Autocorrelation Function forthe growth rates of OTC derivatives by counterparty and instrument. The horizontal green lines are the critical values for the hypothesis that the autocorrelation is zero.

**Figure 24.**Deviations of Derivatives from their long run value as predicted by the cointegration relation.

Counterparties | ||||
---|---|---|---|---|

Non-Financial | Other Financial | Dealers | Total | |

Instruments | ||||

Foreign Exchange | ${D}_{fx,nf}^{c}$ | ${D}_{fx,of}^{c}$ | ${D}_{fx,d}^{c}$ | ${D}_{fx}^{c}$ |

Interest Rate | ${D}_{ir,nf}^{c}$ | ${D}_{ir,of}^{c}$ | ${D}_{ir,d}^{c}$ | ${D}_{ir}^{c}$ |

Equity-linked | ${D}_{el,nf}^{c}$ | ${D}_{el,of}^{c}$ | ${D}_{el,d}^{c}$ | ${D}_{el}^{c}$ |

Total | ${D}_{nf}^{c}$ | ${D}_{of}^{c}$ | ${D}_{d}^{c}$ | ${D}^{c}$ |

Economic Activity $(\mathit{a})$ | Johansen | Engle-Granger *19 | ||||
---|---|---|---|---|---|---|

$\mathit{\beta}$ | ${\mathit{\alpha}}_{\mathit{d}}$ | ${\mathit{\alpha}}_{\mathit{y}}$ | ||||

GDP | $(se)$ | 4.98 | −1.15 | 0.0095 | 4.45 | |

(1.27) | (0.24) | (0.0176) | (1.34) | |||

$(se)$ | 4.696 | −1.12 | $-\u2020$ | |||

(1.269) | (0.229) | |||||

Exports | $(se)$ | 1.887 | −1.156 | 0.0689 | 1.23 | |

(0.304) | (0.24) | (0.076) | (0.598) | |||

$(se)$ | 1.8276 | −1.5347 | $-\u2020$ | |||

(0.304) | (0.241) |

Model | Null Hypothesis | ||
---|---|---|---|

Normality | Serial Ind. | Homosk. | |

Interest Rates | 0.639 | 0.074 | 0.475 |

and GDP | 0.816 | 0.084 | 0.274 |

Interest Rates | 0.077 | 0.172 | 0.309 |

and Exports | 0.639 | 0.074 | 0.475 |

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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**MDPI and ACS Style**

Bodnar, G.; Fortun, J.; Marquez, J.
OTC Derivatives and Global Economic Activity: An Empirical Analysis. *J. Risk Financial Manag.* **2017**, *10*, 13.
https://doi.org/10.3390/jrfm10020013

**AMA Style**

Bodnar G, Fortun J, Marquez J.
OTC Derivatives and Global Economic Activity: An Empirical Analysis. *Journal of Risk and Financial Management*. 2017; 10(2):13.
https://doi.org/10.3390/jrfm10020013

**Chicago/Turabian Style**

Bodnar, Gordon, Jonathan Fortun, and Jaime Marquez.
2017. "OTC Derivatives and Global Economic Activity: An Empirical Analysis" *Journal of Risk and Financial Management* 10, no. 2: 13.
https://doi.org/10.3390/jrfm10020013