Programa Nacional de Desarrollo Urbano y Ordenación del Territorio

It is very important for banks to model their liquidity risk. Wylie (2012) says that one of the lessons that institutions learned from the global financial crisis in 2007- 2008 is the need for better integration of liquidity risk management into the overall risk management process. By having a full picture of funding liquidity risk, this will help to ensure that the banks have a good understanding of how much liquid assets they may require. Global liquidity indicators may be useful to help the bank know when they might want to increase their liquid asset holding but the modelling will help them assess by how much.

Funding liquidity risk modelling is different to credit risk modelling. Adalsteins- son (2015) notes that credit risk is well identified, with good historic data and estab- lished correlation to macro-factors. While for funding liquidity risk, Adalsteinsson (2015) notes that data is limited, as each experience is different and difficult to assess. Therefore a variety of approaches will be needed to assess funding liquidity risk.

Fiedler (2011) highlights the basic components that need to be modelled. He suggests that banks model their forward liquidity exposure and assess this compared to their counter balance capacity. The counter balance capacity can be thought of as the bank’s ability to raise liquidity. BCBS and Prudential Regulation Authority (PRA) have set out what they expect to see in the modelling. Generally they set out that all liquidity risk should be captured in the models. We will look at the different model approaches in this section rather than the details of how to model and what should be assessed.

In one approach Matz (2006b) says banks carry out stress testing to assess their liquidity needs. As part of this banks will perform scenario and sensitivity testing. For scenario testing, the bank will look at historical events and hypothetical cases.

For sensitivities, the bank will vary the key assumptions to quantity the impact. Historical events are past experiences of liquidity events. Examples of historical liquidity events are the Asian crisis in 1997 and the Russian default in 1998. Matz (2006b) lists 12 different liquidity events during a 15 year period between 1987 and 2002. Matz (2006b) notes that each liquidity event is quite different to the previous event. Therefore, investigating just previous liquidity events might not prepare you for the next liquidity event.

Banks must look at hypothetical cases since each liquidity event is different. This allows the bank to create their own stress scenarios and help them identify key risks to their liquidity needs. They are not bound by previous events. Historical events can be used as a starting point and can be amended to allow for develop- ments. Hypothetical cases are therefore very useful for stress testing. However, Matz (2006b) notes that the main disadvantage is that they are subjective so will require appropriate judgement and skill.

One method suggested by Matz (2006b) is to assess liquidity risk by looking at deterministic scenarios. This can be very useful as both historical and hypothetical cases can be applied. This will allow the bank to identify its key risks to their liquidity and assess the impact of different events. The downside of this approach is that it does not provide a probability of occurrence.

Another method, specified by Matz (2006b), that can be used is where Value at Risk (VAR) is considered. VAR looks at the loss at a selected confidence level, often 99% confidence level is used. This method can assign a probability to the likelihood of loss. However, this method is based on historical data so the results may be misleading if future events are different from past situations.

Matz (2006b) also suggests Monte Carlo simulation can be used to assess liquidity risk. This can be used to provide a probability of events. Matz (2006b) notes that it can be difficult to estimate parameters. If parameters are estimated from historical data, then this is implicitly assuming that liquidity crisis will be the same as before and will not allow for any structural changes.

sensitivity testing. This will allow the bank to see how sensitive the results are to each of the assumptions and help the bank understand its key drives for its liquidity needs.

FSA (2009) requires banks to look at three scenarios for stress testing. One scenario is to look at a bank specific event that can last up to 14 days. Another scenario is a market wide stress event that can last up to 3 months. The final scenario is a combination of the first and second scenarios. Similarly, BCBS (2008b) states that banks should look at ‘what-if’ scenarios taking into account bank specific and market related factors. The PRA replaced the Financial Services Authority (FSA) legislation with Basel III so this is the only legislation requirement from 1 October 2015 (PRA, 2015).

BCBS (2000) notes these stress tests can be viewed in terms of maturity ladders and should be carried out for each major currency the bank operates in. BCBS (2013b) requires this to be done for contractual maturities of inflows and outflows. In addition, the bank can look at cashflow summary reports and sufficiency reports. Matz (2007) gives an example of a cashflow summary report and this is shown in Table 2.2.2. Table 2.2.2 shows the ratio of income to outflow of cash each month and is checked to see if it is above a certain level. If it is below the level, the bank will need to take action. Matz (2007) also gives an example of a sufficiency report and this is shown in Table 2.2.3. Banks want to know how long they can survive with their current liquid asset holding under different scenarios. They will monitor this expectation and check it is above their target survival period. If expected survival is less than the target survival period, the bank will take action to increase the survival period.

Table 2.2.2: Cashflow summary report from Matz (2007)

March April May

Ordinary course of business scenario actual 1.24:1 1.27:1 1.21:1

limit 1.20:1 1.20:1 1.20:1

Bank-specific scenario, stress level 1 actual 1.16:1 1.11:1 1.12:1

limit 1.10:1 1.10:1 1.10:1

Bank-specific scenario, stress level 2 actual 1.02:1 0.94:1 1.04:1

guidance minimum 1.00:1 1.00:1 1.00:1

Table 2.2.3: Sufficiency report from Matz (2007)

Forecast number of months before negative cashflows consume the standby liquid assets

Required minimum number of time

periods Normal course of business scenario 24 12

Bank-specific funding scenario

Stress level 1 18 12

Stress level 2 2 4

Systemic-funding scenario

Stress level 1 15 12

Stress level 2 8 9

All these scenarios helps the bank understand its liquidity needs especially in times of crisis. As Brunnermeier and Pedersen (2009) note liquidity crisis can happen quickly and can impact across assets so it is important to have a plan in place so it can react quickly.

Liquidity risk modelling cannot be carried in isolation. Gea-Carrasco and Little (2013) note that considering liquidity risk without other risk leads to underesti- mating solvency risk. To effectively manage liquidity risk, Gea-Carrasco and Little (2013) say there is a need to address exposure in the following areas:

• Market liquidity risk;

• Funding liquidity risk;

• Liquidity stress testing; and

• Contingency planning.

As such liquidity risk modelling needs to be taken into consideration with Asset Liability Modelling (ALM). Wylie (2013) notes that the ALM team traditionally concentrates on interest rate risk. However, it has now become responsible for:

• Liquidity;

• FTP;

• Capital management; and

Kunghehian (2010) assesses the main tools used for ALM. These are:

• Gap analysis;

• Net interest income simulation;

• Market value sensitivity measures; and

• Earning at risk.

Information about these methods can be found in Wylie (2013) and Crouhy et al. (2006). Kunghehian (2010) lists the pros and cons of each method.

BCBS (2008b) notes a range of measurements and metrics are needed to be used as no single number can adequately quantify liquidity risk. The different approaches have their pros and cons but by carrying out multiple approaches this will assist the bank with their understanding of funding liquidity risk. BCBS (2008b) states that stress testing helps banks identify potential liquidity risk and the results can be used to develop their contingency plan.