slides.knit

# Carry trade and negative policy rates in Switzerland Low-lying fog or storm?
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### <a href="https://bttomio.github.io">Bruno Thiago Tomio</a> <a href="mailto:guillaume.vallet@univ-grenoble-alpes.fr">Guillaume Vallet</a>
### 23rd INFER Annual Conference
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---

# Motivation

- International spillovers of negative interest rate policy (NIRP) is a **`very recent`** strand in the literature (e.g. Arteta, Kose, Stocker and Taskin 20161)

- Twofold interest in the Swiss franc:

1. In times of turmoil, it is a major **`safe haven currency`**. Overall, also a **`funding currency`** of carry trade activities.

2. Due to the "interest rate bonus" (Kugler and Weder 20022) and the NIRP, the impacts of the Swiss National Bank's actions resonate **`far beyond`** Switzerland

.footnote[
[1] Arteta, Carlos, Ayhan Kose, Marc Stocker, and Temel Taskin. 2016. “Negative Interest Rate Policies: Sources and Implications.” *Policy Research Working Paper Series* 7791. The World Bank.
 [2] Kugler, Peter, and Beatrice Weder. 2002. “The Puzzle of the Swiss Interest Rate Island: Stylized Facts and a New Interpretation.” *Aussenwirtschafhet* 57 (01): 49–64.
]

- Lack of **`robust`** empirical papers analyzing the **`pervasive effects`** of the carry trade activity

???

> The carry trade is the name of the strategy of going  short  (betting  the  foreign  exchange value will fall) in a low-interest rate currency like  the  Japanese  yen,  while  simultaneously going  long  (betting  the  foreign  exchange value will rise) in a high-interest rate currency like the New Zealand dollar.

> --- Frankel (2008)

---

# What do we do?

In the context of the NIRP in Switzerland...

- We use data from hedge funds to **`investigate the behavior`** of the Swiss franc carry trade

+ Four major currencies: US dollar, euro, Japanese yen, and British pound
  
  + Disentangle the **`funding currency`** and **`safe haven`** effects
  
- Our Swiss franc carry trade proxy allows the investigation of different target currencies (**`bilateral analysis`**)

+ **`Volume`** approach using **`weekly`** CFTC data (**`non-commercial`** traders), based on Fong (2013)3
 
 + Uncovered interest rate parity (UIP), impact on asset prices, and systemic risk

.footnote[
[3] Fong, Wai Mun. 2013. “Footprints in the Market: Hedge Funds and the Carry Trade.” *Journal of International Money and Finance* 33 (March): 41–59.]

---

# What do we find?

Using **`all available data`** at the time (Dec 23, 2014 to Nov 24, 2020), excluding the sample-selection bias...

- Major findings:

+ Distinctive behavior for the Swiss franc as **`funding`** and **`safe have`** currency

+ The UIP is **`violated`** for the USD, EUR and JPY models
  
  + Hedge funds **`are able`** to move asset prices
  
  + An **`increased systemic risk`** is linked to a higher Swiss franc carry trade activity

---

# Data and SVAR model

---

<table class="table" style="width: auto !important; margin-left: auto; margin-right: auto;">
<caption>Table 1. Description of variables</caption>
 <thead>
 <tr>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> Variable </th>
 <th style="text-align:left;text-align: center;color: white !important;background-color: black !important;"> Definition </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> Source </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:center;"> $IRD_i$ </td>
 <td style="text-align:left;"> Interest rate differential using the 12-Month London Interbank Offered Rate (LIBOR) and spot (LIBOR) rates for target currencies (USD, EUR, JPY, and GBP) </td>
 <td style="text-align:center;"> FRED </td>
 </tr>
 <tr>
 <td style="text-align:center;"> $VIX^{*}$ </td>
 <td style="text-align:left;"> Market sentiment: CBOE DJIA Volatility Index </td>
 <td style="text-align:center;"> FRED </td>
 </tr>
 <tr>
 <td style="text-align:center;"> $CT_i$ </td>
 <td style="text-align:left;"> Net position of Swiss franc-funded carry trade by target currencies, following Fong (2013) </td>
 <td style="text-align:center;"> CFTC </td>
 </tr>
 <tr>
 <td style="text-align:center;"> $SM^{*}$ </td>
 <td style="text-align:left;"> Domestic stock market: Swiss Market Index ^SSMI </td>
 <td style="text-align:center;"> BIS </td>
 </tr>
 <tr>
 <td style="text-align:center;"> $ER_i^{*}$ </td>
 <td style="text-align:left;"> Nominal exchange rates (cross rates): USD/CHF, EUR/CHF, CHF/JPY, GBP/CHF </td>
 <td style="text-align:center;"> Yahoo Finance </td>
 </tr>
 <tr>
 <td style="text-align:center;"> $FSM_i^{*}$ </td>
 <td style="text-align:left;"> Foreign stock markets: USD - S&amp;P 500 (^GSPC), EUR - EURONEXT 100 (^N100), JPY - Nikkei 225 (^N225), GBP - FTSE 100 (^FTSE) </td>
 <td style="text-align:center;"> Yahoo Finance </td>
 </tr>
</tbody>
</table>

`$*$` In logarithmic form.

- Yahoo Finance data was obtained and checked/cleaned with <svg viewBox="0 0 581 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"></path></svg> packages `quantmod` and `BatchGetSymbols`. Overall, the problem with this source is related to individual stocks, **`not indices`**.

---

# CFTC data

- Some **`caveats`**:

> I. Bias in the classification of the traders

> II. Trades identified as speculative may not result from carry trades

> III. Only a small proportion of foreign exchange market activity is executed through exchanges (mostly OTC)

> --- Galati, Heath and McGuire (2007)3

- As mentioned by **`market participants`**, CFTC data tends to be indicative of the **`trend`** of carry trade activity (Bank for International Settlements 2015)4.

.footnote[
[3] Galati, G., A. Heath and P. McGuire (2007), ‘Evidence of carry trade activity’, *BIS Quarterly Review*.
[4] Bank for International Settlements (2015), *Currency Carry Trades in Latin America*, Bank for International Settlements.
]

---

# Econometric model

- Structural vector-autoregressive (**`SVAR`**) model with Cholesky identification

+ Ordering: `$IRD_{i}$` `$\rightarrow$` `$VIX$` `$\rightarrow$` `$CT_{i}$` `$\rightarrow$` `$ER_{i}$` `$\rightarrow$` `$FSM_{i}$` `$\rightarrow$` `$SM$` 
 
--

- Toda-Yamamoto approach to capture **`long-term effects`** (non-stationary variables stay in **`levels`**)

<table class="table" style="font-size: 16px; width: auto !important; margin-left: auto; margin-right: auto;">
<caption style="font-size: initial !important;">Table 2. Exogenous variables for each model</caption>
 <thead>
 <tr>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> Model </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> VAR lag length ($p)$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> Exogenous variables </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:center;"> USD </td>
 <td style="text-align:center;"> 2 </td>
 <td style="text-align:center;"> $VIX_{t-3}$, $CT_{USD,t-3}$,
 $ER_{USD,t-3}$, $FSM_{USD,t-3}$,
 $SM_{t-3}$ </td>
 </tr>
 <tr>
 <td style="text-align:center;"> EUR </td>
 <td style="text-align:center;"> 2 </td>
 <td style="text-align:center;"> $VIX_{t-3}$, $CT_{EUR, t-3}$,
 $ER_{EUR, t-4}$, $FSM_{EUR, t-3}$,
 $SM_{t-3}$ </td>
 </tr>
 <tr>
 <td style="text-align:center;"> JPY </td>
 <td style="text-align:center;"> 1 </td>
 <td style="text-align:center;"> $VIX_{t-2}$, $CT_{JPY,t-2}$,
 $ER_{JPY,t-2}$, $FSM_{JPY,t-2}$,
 $SM_{t-2}$ </td>
 </tr>
 <tr>
 <td style="text-align:center;"> GBP </td>
 <td style="text-align:center;"> 1 </td>
 <td style="text-align:center;"> $VIX_{t-2}$, $CT_{GBP,t-2}$,
 $SM_{t-2}$ </td>
 </tr>
</tbody>
</table>

- Selection of the VAR lag length follows a **`step-wise approach`**: unit-root tests and Lagrange-multiplier (LM) test for residual autocorrelation

+ **`Robustness checks`**: **`(1)`** different ordering, based on Granger causality tests, **`(2)`** non-stationary model, **`(3)`** model with time dummies, and **`(4)`** model excluding the carry trade proxy

---

# Results for the Impulse Response Functions (IRFs)

---

**Swiss franc carry trade activity `is impacted`...**
<img src="./gALL_COIRF20_RESP20.png" width="6000" />
.center[Figure 1. Cumulative structural carry trade (*CT*) responses to variables impulses in each model]

<table class="table table-condensed" style="font-size: 12px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> Target currency </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $IRD_i$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $VIX$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $ER_i$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $FSM_i$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $SM$ </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:center;font-weight: bold;"> USD </td>
 <td style="text-align:center;font-weight: bold;"> </td>
 <td style="text-align:center;font-weight: bold;"> </td>
 <td style="text-align:center;font-weight: bold;"> + </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> </td>
 </tr>
 <tr>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> EUR </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> + </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> + </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 </tr>
 <tr>
 <td style="text-align:center;font-weight: bold;"> JPY </td>
 <td style="text-align:center;font-weight: bold;"> </td>
 <td style="text-align:center;font-weight: bold;"> </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 </tr>
 <tr>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> GBP </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 </tr>
</tbody>
</table>

---

**`An increased` Swiss franc carry trade activity...**
<img src="./gALL_COIRF20.png" width="6000" />
.center[Figure 2. Cumulative structural variables responses to carry trade (*CT*) impulses in each model]

<table class="table table-condensed" style="font-size: 12px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> Target currency </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $IRD_i$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $VIX$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $ER_i$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $FSM_i$ </th>
 <th style="text-align:center;text-align: center;color: white !important;background-color: black !important;"> $SM$ </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:center;font-weight: bold;"> USD </td>
 <td style="text-align:center;font-weight: bold;"> + </td>
 <td style="text-align:center;font-weight: bold;"> + </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 </tr>
 <tr>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> EUR </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> + </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 </tr>
 <tr>
 <td style="text-align:center;font-weight: bold;"> JPY </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> + </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 <td style="text-align:center;font-weight: bold;"> - </td>
 </tr>
 <tr>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> GBP </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> + </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 <td style="text-align:center;background-color: #E5E5E5 !important;font-weight: bold;"> - </td>
 </tr>
</tbody>
</table>

---

# Results for the Granger causality tests using the Toda-Yamamoto approach

---

**Swiss franc carry trade activity `is Granger-caused by`...**
<table class="table" style="font-size: 16px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:left;color: white !important;background-color: black !important;"> </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $CT_{USD}$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $CT_{EUR}$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $CT_{JPY}$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $CT_{GBP}$ </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:left;"> $IRD_i$ </td>
 <td style="text-align:center;"> 0.0483** </td>
 <td style="text-align:center;"> 0.7511 </td>
 <td style="text-align:center;"> 0.9286 </td>
 <td style="text-align:center;"> 0.0558* </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $VIX$ </td>
 <td style="text-align:center;"> 0.9823 </td>
 <td style="text-align:center;"> 0.2604 </td>
 <td style="text-align:center;"> 0.4740 </td>
 <td style="text-align:center;"> 0.5320 </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $ER_i$ </td>
 <td style="text-align:center;"> 0.0015*** </td>
 <td style="text-align:center;"> 0.1818 </td>
 <td style="text-align:center;"> 0.0241** </td>
 <td style="text-align:center;"> 0.0002*** </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $FSM$ </td>
 <td style="text-align:center;"> 0.8945 </td>
 <td style="text-align:center;"> 0.3664 </td>
 <td style="text-align:center;"> 0.1994 </td>
 <td style="text-align:center;"> 0.0034*** </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $SM$ </td>
 <td style="text-align:center;"> 0.9624 </td>
 <td style="text-align:center;"> 0.3845 </td>
 <td style="text-align:center;"> 0.0787* </td>
 <td style="text-align:center;"> 0.2506 </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $All$ $variables$ </td>
 <td style="text-align:center;"> 0.0311** </td>
 <td style="text-align:center;"> 0.5404 </td>
 <td style="text-align:center;"> 0.3112 </td>
 <td style="text-align:center;"> 0.0097*** </td>
 </tr>
</tbody>
</table>

**Swiss franc carry trade activity `Granger-causes`...**
<table class="table" style="font-size: 16px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:left;color: white !important;background-color: black !important;"> </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $IRD_i$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $VIX$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $ER_i$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $FSM_i$ </th>
 <th style="text-align:center;color: white !important;background-color: black !important;"> $SM$ </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:left;"> $CT_{USD}$ </td>
 <td style="text-align:center;"> 0.1881 </td>
 <td style="text-align:center;"> 0.0217** </td>
 <td style="text-align:center;"> 0.3625 </td>
 <td style="text-align:center;"> 0.0656* </td>
 <td style="text-align:center;"> 0.0442** </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $CT_{EUR}$ </td>
 <td style="text-align:center;"> 0.0810* </td>
 <td style="text-align:center;"> 0.0600* </td>
 <td style="text-align:center;"> 0.0648* </td>
 <td style="text-align:center;"> 0.0281** </td>
 <td style="text-align:center;"> 0.0169** </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $CT_{JPY}$ </td>
 <td style="text-align:center;"> 0.5202 </td>
 <td style="text-align:center;"> 0.0395** </td>
 <td style="text-align:center;"> 0.7120 </td>
 <td style="text-align:center;"> 0.0017*** </td>
 <td style="text-align:center;"> 0.0255** </td>
 </tr>
 <tr>
 <td style="text-align:left;"> $CT_{GBP}$ </td>
 <td style="text-align:center;"> 0.8517 </td>
 <td style="text-align:center;"> 0.0300** </td>
 <td style="text-align:center;"> 0.1296 </td>
 <td style="text-align:center;"> 0.0931* </td>
 <td style="text-align:center;"> 0.0442** </td>
 </tr>
</tbody>
</table>

Both tables show the p-value of the test for the `absence of Granger causality`. Null hypothesis is that one variable `does not` Granger-cause the other variable. \*\*\*, \*\*, and \* denote statistical significance at 1%, 5%, and 10%, respectively.

---

# Concluding remarks

---

- The paper extends the carry trade literature by investigating empirically the effects of the Swiss NIRP

- Swiss franc carry trade is explored with four target currencies ($, €, ¥, £)

- **`Funding`** currency

+ CHF depreciation increases CT (all models but GBP)
  + Higher FSM impacts positively CT (EUR)
  + UIP failure, where CT impacts ER (USD, EUR and JPY)
  + Higher CT appreciates the CHF (USD and EUR)

- **`Safe haven`** currency

+ Higher FSM impacts negatively CT (USD)
  + Higher SM impacts negatively CT (JPY and GBP)
  + Higher CT depreciates the CHF (JPY)
  + Higher CT increases VIX (all models)
  
--

- Notably, for **`all models`**, there is also evidence that CT **`increases systemic risk`** (higher CT increases VIX) and **`moves asset prices`** (higher CT increases FSM and SM)

- More importantly, results demonstrate that coordinated monetary policies are needed to tame these negative spillovers

---

Slides created with [`xaringan`](https://github.com/yihui/xaringan) and [`xaringanthemer`](https://github.com/gadenbuie/xaringanthemer).

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