What option prices reveal about the ECB’s unconventional monetary policies
The decade because the Global Crisis has seen central banks hire a selection of monetary policy tools. This column draws two lessons from the unconventional monetary policy measures employed through the European sovereign debt crisis. First, central banks should communicate clearly – and with sufficient detail – in times of heightened market stress to lessen tail risk perceptions in financial markets. Second, policies targeted at changing the relative supply within different asset classes impact on perceived crash risk, while measures targeted at easing financing costs of commercial banks usually do not.
In the wake of the Global Crisis, policymakers ran into what, until then, had seemed a merely academic possibility – the effective lower bound (ELB) on interest levels. In response, major central banks resorted to unconventional monetary policies, which range from security market interventions to forward guidance and specific measures to aid distressed banks. A decade after the start of Global Crisis, it really is worth taking stock of central banks’ accumulated experience with these innovations, also to acquire the lessons it could provide for the look and conduct of policy in the years ahead.
From this background, it really is key to comprehend whether and how unconventional measures have impacted market sentiment. We concentrate on the extent to which unconventional ECB policy measures have reduced the perception of crash risk in the Eurodollar exchange rate. We define tail risk as the chance that the euro weakens significantly against the dollar. We pick the exchange rate for just two reasons. First, euro area breakup risk was a genuine market fear through the European sovereign debt crisis. As such, crash risk perceptions in the exchange rate certainly are a good instrument to fully capture markets’ judgement of an additional escalation of the crisis (Farhi et al. 2009). Second, the exchange rate can be an important transmission channel of monetary policy (Arteta et al. 2018).
To answer this question, we utilize the information embedded in option prices to derive a way of measuring tail risk perceptions. Currency options will be the most liquid options and so are therefore more likely to capture changes in risk perceptions timely and adequately. The analysis is founded on daily data from January 2009 to December 2018 and differentiates between two types of unconventional monetary policy: measures that target the ECB’s monetary stance, and measures that target the monetary transmission channel given the monetary stance (Table 1).
Table 1 Characterisation of ECB’s unconventional monetary policy measures
Note: MS identifies monetary stance; MTC identifies monetary transmission.
Option prices contain information on the perception of tail risk by investors
We proceed in three steps to extract information regarding crash risk from (out-of-the-money) Eurodollar option prices. First, we look at so-called risk reversals. Risk reversals certainly are a measure of the expense of hedging against downside risk by capturing the extent to which put options (that offer downside protection) are more costly than call options (that offer upside protection). Risk reversals can therefore serve as a proxy for capturing the extent to that your return distribution is asymmetric (i.e. skewed, see Figure 1).
Figure 1 Risk reversals σ (y-axis) reflect the implied volatility, δ may be the option delta (x-axis)
We then examine the complete distribution of future exchange rates (probability density function) using the Black-Scholes solution to investigate all moments of the distribution (mean, variance, kurtosis, and skewness). This enables for more descriptive measures of the distribution. That is important when, for example, the variance or the kurtosis of the distribution is volatile as the skewness of the distribution remains the same. When the former may be the case, the results predicated on the probability density functions varies from the chance reversals. From the estimated distribution, we are able to calculate the likelihood of a particular drop – say, 10% or 20% – in the exchange rate in the coming month (Figure 2).
Figure 2 Risk-neutral probability density-based time group of a 10% and 20% crash
Note: Figure 2 shows the crash probabilities thought as a drop of 10% and 20% produced from the RNPD predicated on 1-month options. The y-axis is in percentage points, x-axis in years. Red dotted lines represent (from left to right) the first announcement of the SMP, the first announcement of the TLTRO programme, technical top features of the OMT, the announcement to lessen the DFR below 0 and the announcement of the PSPP.
As several assumptions of the Black-Scholes method (Black and Scholes 1973) are violated the truth is, we also apply a way which allows for instantaneous jump risk to fully capture the number of perceived crash risk in foreign currency markets. More specifically, the Black-Scholes method revolves around the assumption of constant volatility. So as to work for this assumption, we use an explicit mixed jump diffusion risk model as outlined in Kou (2002). An advantage of the Kou model is that it generally does not use strict assumptions for modelling the tails of the distribution (i.e. so-called endpoint clamping), the most crucial part for the determination of crash risk perceptions. More specifically, this mixed jump diffusion model permits fat-tailed distributions.
Monetary stance policies appear to be far better in downplaying crash risk than policies targeted at restoring the transmission channel
An overarching conclusion is that policies targeted at changing the relative supply within different asset classes impact on perceived crash risk, while measures targeted at easing financing costs usually do not. Our paper thereby emphasises the need for tail risk indicators, since kurtosis and skewness indicators sometimes tell a different story compared to the central tendency (i.e. the mean) of a particular distribution. More specifically, in this column we reveal two of the primary findings that emerge from our analysis (Olijslagers et al. 2019). First, we find that the Securities Markets Program (SMP) – which centered on supporting monetary transmission by intervening specifically markets for sovereign debt – actually resulted in higher tail risk perceptions in the Eurodollar market. Second, we document that announcing policies generally terms, without precisely describing just what they entail, didn’t instantly move asset markets. Occasionally, this even moved them in the incorrect direction.
All crash risk measures indicate a rise in tail risk perceptions surrounding the SMP programme
Not absolutely all unconventional monetary policies conducted by the ECB have already been successful with regard to diminishing crash risk perceptions in the euro area. We find that the SMP programme actually resulted in higher downside risk perceptions. Specifically, the programme didn’t really lower tail risk perceptions, and in line with the jump-diffusion risk model it actually resulted in significantly higher risk perceptions. A possible explanation is that the SMP lacks conditionality and will in the long run result in more fragmentation (which plays a part in the perception of crash risk). Reis (2017) provides another explanation because of this result by indicating that mismatches between your composition of asset purchases and the administrative centre key of the ECB governing its distribution of dividends signal ultimately unsustainable redistribution. According to the theory, the asset purchases might, for a while, relax markets (and lower tail risk perceptions), however in the future – because of their unsustainable nature – result in higher tail risk perceptions because they possibly increase crash risk (by a rise in redenomination risk).
The OMT programme resulted in lower tail risk perceptions only once the details were clarified enough
Amid the European sovereign debt crisis, Draghi tried to calm market fears by assuring that the ECB would do “whatever it takes" to preserve the euro. Although this speech is often thought to have downplayed market fears, Figure 3 demonstrates Draghi’s speech initially didn’t deliver upon market expectations (actually it shows a jump in tail-risk perceptions in the times after Draghi’s statement). More specifically, tail risk in the Eurodollar increased substantially afterwards (i.e. less risk reversal implies an increased tail risk). Seemingly, investors thought the statement contained inadequate information to reduce their hedging of downside risks in the Eurodollar exchange rate. The finding is a lot more remarkable as the cost of the euro against the dollar jumped by 1.1% following the speech. So, the worthiness of the euro (which reflects the mean price) did increase, but this increase didn’t bring about lower crash risk perceptions.
Figure 3 Risk reversals surrounding the OMT programme announcements
Note: Figure 3 displays the 10 and 25 delta risk reversal (RR = IVcall – IVput for same delta) predicated on 1-month options from July-October 2012. The dotted lines represent the announcement days (from left to right) of the “Whatever needs doing” speech, further hints on OMT, and the launch of the OMT.
The marketplace view changed when Draghi announced that the ECB was exploring options to aid sovereign debt markets. This occurred when the ultimate framework of the OMT programme was published in September 2012. In the times following this announcement, the chance reversal moved near zero, signalling a nearly identical possibility of the euro upgrading or down. These findings are underlined by our jump-diffusion risk model (Figure 4) and in addition occurred – although less extreme – following the announcement of the general public Sector Purchase Program. Concurrently, these observations substantiate our main conclusion that unconventional monetary policy only directly moves security markets when the relevant details are announced.
Figure 4 Jump risk model points to diminished crash risk perceptions following the full OMT announcement
Note: Figure 4 shows the estimated jump intensities. The blue line represents the intensity prior to the announcement and the red line the intensity following the announcement of the OMT completely detail (6-9-2012). On the x-axis the potential size of a crash is given. The (risk-neutral) possibility of a drop bigger than x% within twelve months may be the area below the intensity curve left of point x%.
Authors’ note: The views expressed are those of the authors and don’t necessarily reflect those of the Eurosystem or De Nederlandsche Bank.
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