1. Accumulation of Foreign Currency Reserves and Risk Taking
Rasmus Fatum*
University of Alberta School of Business
James Yetman
Bank for International Settlements
Hitotsubashi University November 2017

2.
What Do We Do?
We assess whether reserve accumulation in the Asia-Pacific region is systematically associated with risk taking
We carry out a country-specific daily data event study analysis of whether official announcements of reserve stocks influence various proxy measures of risk taking

3.
What Do We Find?
Our baseline results do not suggest that reserve accumulation asserts a strong influence on risk-taking
Only when we extend our analysis to consider the effects of reserve accumulation on an estimated measure of the surprise component of reserve stock news do we find some weak indications of a systematic link between reserves and risk taking
Overall, our findings suggest that the effects of reserve accumulation on risk-taking are negligible

4. Outline Background Motivation Empirical Analysis Data Specific Tests
Outline
Background
Motivation
Empirical Analysis
Data
Specific Tests
Results
Extensions
Robustness
Conclusions

5.
Background (1)
The massive accumulation of reserves across EMEs and economies in the Asia-Pacific region is well-known
Reserves in the Asia-Pacific region are large, in both absolute and relative terms
Reserves exceed 20% of GDP for eight regional economies, and exceed 80% of GDP for Singapore and Hong Kong

6.
Background (2)

7.
Background (3)
Accumulation of reserves is a key factor in accounting for changes in the overall size of central bank balance sheets
For many Asian economies, the growth of reserves accounts for virtually all of the increase in the size of the balance sheet over the past decade

8.
Background (4)

9.
Motivation (1)
Possible costs and associated risks of holding large reserves include:
Sterilization costs
Difficulties in implementing monetary policy
Inflationary pressures
Capital losses
Asset bubbles
Overinvestment
Increased risk taking

10. Motivation (2) Reserve accumulation and increased risk taking:
Motivation (2)
Reserve accumulation and increased risk taking:
If reserves are seen as providing insurance in the event of financial stress, an increase in reserves may lead to moral hazard effects in the form of increased risk taking in anticipation of the ability (and willingness) of the monetary authority to serve as lender of last resort

11.
Motivation (3)
For example, market participants may view reserves as providing a form of insurance since reserves can be used in attempts to off-set pressure to depreciate the relative value of the domestic currency
This may increase the willingness of market participants to take on unhedged currency risks

12.
Motivation (4)
Reserves may seem particularly likely to increase risk-taking where monetary authorities have previously used reserves as a last resort provider of foreign currency liquidity – i.e. past use of reserves for such purposes may increase expectations that reserves are used for similar purposes in the future
For example, several central banks used either own reserves or the proceeds of swaps with the US Federal Reserve or other central banks during the crisis to reduce foreign currency mis-matches

13.
Motivation (5)
Literature on accumulation of reserves and risk taking is surprisingly sparse:
Reserve accumulation increases currency risk in the corporate sector in Latin America (Sengupta 2010)
Increase in reserves is associated with less sovereign CDS trading (Ismailescu and Phillips 2015)

14.
Empirical Analysis (1)
To address whether the accumulation of reserves influences risk taking we employ an event study methodology similar to the one used in Fatum (2000) and Fatum and Hutchison (2003, 2006)

15. Empirical Analysis (2)
An event study allows for a very general test of a very specific hypothesis without reliance on specification and estimation of time-series models of the risk taking proxies we consider
This is a particularly appealing aspect in our context of studying movements at relatively high (daily) frequency in variables that are volatile and influenced by numerous factors, including forward-looking variables that are unobservable at the daily frequency

16.
Empirical Analysis (3)
The starting point for an event study is to define the events of interest and to identify the time-periods (the event windows) during which the response variables of interest are examined
The events in our context are the recurring announcements of the stock of foreign currency reserves held by the respective economies considered in our study

17.
Empirical Analysis (4)
The event windows capture the movement of the response variable of interest before and after the event, and during the pre- and post-event windows
For our baseline analysis we set the event window length to two days and include in the two-day post-event window the event day itself
We subsequently vary the length of the event windows from one to three days and we vary whether the event day is included in the post-event window

18.
Empirical Analysis (5)
The response variables in our context are various proxy measures of risk taking
We use the cost of insuring against exchange rate changes vis-à-vis the USD as our baseline measure of risk taking. (Four measures: the implied volatility of one- and 12-month call and put options)
We also consider for each of the countries in our sample CDS spreads for US denominated debts and equity prices as other proxy measures of risk taking

19.
Data: Events (1)

20.
Data: Events (2)
Events are defined as the reserves announcements relative to:
Previous announcement (baseline)
Predicted reserves from simple projection model
Survey expectations (CN only)

21. Specific Tests (1) Direction criterion:
Specific Tests (1)
Direction criterion:
Does the response variable move in the direction consistent with the announcement during the post-event window?
H0: movement is random
HA: increased reserves increases risk-taking

22. Specific Tests (2) Reversal criterion:
Specific Tests (2)
Reversal criterion:
Does the response variable move in the direction consistent with the announcement during the post-event window in cases where it was moving in the opposite direction before?
H0: probability of changes in direction following events is the same as when there are no events
HA: probability of changes in the direction predicted by the event is greater than for non-events
from
non-events

23. Specific Tests (3) Smoothing criterion:
Specific Tests (3)
Smoothing criterion:
Does the event fulfill the Direction criterion or, if not, does the rate of change in the response variable during the pre-event window exceed that of the post-event window?
H0: probability of “smoothing” following events is the same as following non-events
HA: probability of “smoothing” following events is greater than following non-events

24. Specific Tests (4) Information criterion:
Specific Tests (4)
Information criterion:
Are changes in the post-event window larger than in the pre-event window?
H0:
HA:

25.
Results (1)
Baseline results: Hong Kong; implied volatility, 2-day windows
Implied vol
1 month call
1 month put
12 month call
12 month put
Test
Events
Non 1
Yes 73 68 76 No 62 60
p-val
0.20
0.53
0.10 2 37
1199
1202 31
1160 33
1169 30
1358 34
1355 43
1397 38
1388
0.11
0.23
0.76
0.49 3 56
1808 52
1801 59
1784
1795 11
449 19
464 15
470
463
0.30
0.92
0.52
0.62 4 72 67 75 80 71
0.25
0.88
0.40

26. Results (2) Overall baseline results:
Results (2)
Overall baseline results:
0 rejections: CN, HK, ID, JP, MY, PH, SG
1 rejection: AU, TH
3 rejections: KR
Across all tests/economies: 3% rejection rate at 5% significance
Next: 6 alternatives (baseline + 5):
1,2,3 day windows; event in post-event window or excluded
96 tests per economy (except 32 for TH)

27. Results (3) 01.08.2018 Implied volatility meta-analysis results
1m call
1m put
12m call
12m put
Test
Australia
China 1 2 3 4
Hong Kong
Indonesia
Japan
Korea
Malaysia
Philippines
Singapore
Thailand

28. Extensions CDS swaps (for USD denominated sovereign debt):
Extensions
CDS swaps (for USD denominated sovereign debt):
Some evidence (13% rejection rate at 5% level)
Equity indices: 8% rejection at 5% level
Reserves relative to expectations (for CN):
Opposite hypothesis:
Similar overall rejection rate for opposite hypothesis (7%) as for main hypothesis (6%)
Test
1m call
1m put
12m call
12m put
CDS
Equity 1 2 5 3 4

29. Robustness Post-IFC sample (2010–):
Robustness
Post-IFC sample (2010–):
Fewer significant rejections (4% overall)
Reserves relative to projections:
Similar overall result (6% rejection rate)
Reserves increases vs decreases for Test 1:
No discernible difference
Event regressions (to allow for magnitude effects):
No evidence that reserves influence risk taking

30.
Conclusion
Little or no evidence that accumulation of reserves influences risk-taking
Policy implications: Increased risk taking is not a concern when accumulating reserves. Symmetric implications for decumulation of reserves?
Caveats:
Imperfect proxies for risk-taking?
Effects at sectoral/industry level?
Daily frequency too high/too low?