This chapter focuses on the results obtained based on the empirical analyses conducted to test the research objectives. The descriptive statistics calculated for the sample are provided in the sections that follow. That is, the data pertaining to the variables included in the study, as collected by the questionnaire is summarised by means of calculation of descriptive measures. In this manner, the properties of the observed data clearly emerge and an overall picture thereof is obtained.
The descriptive and inferential statistics generated for the conjectured relationships are presented and discussed. STATEMENT OF THE PROBLEM: The problem with bank liquidity management is that when banks get it wrong, there can be drastic consequences for the economy. This can be seen today from the continuing effects of what started in 2007. The economy is still in a rut and although Gross Domestic Product (GDP) has once again begun to pick up, unemployment remains at the extremely high level of 9.7% according to the most recent Bureau of Labour Statistics Report (Bureau of Labour Statistics, 2010). A key issue to ensure progress has to be how to make sure banks successfully balance their liquidity management in order to be stable and still provide the market with liquidity. Public policy makers will aim to continue strong national economic growth while keeping low unemployment and inflation. Banks themselves have a motive to ensure stability and also increase profits. Economies for years have struggled with liquidity risk.
The sheer size and complexity of the modern economy increases the importance of this issue and this is all the more reason it needs to be carefully considered. 4.1 RESPONDENT CHARACTERISTICS A total of 70 completed questionnaires were received from the banks, representing a 51.9% response rate. The majority of respondents, 87% of whom were male and 13% were female as shown in Table 4.1. (N=70) Gender Frequency Percentage Male 61 87% Female 09 13% Table 4.1: Gender Distribution of Respondents The chart below here shows the gender distribution of respondents. Ten respondents were between 25 and 30, remaining 50 respondents were between 31-35 years of age and the remaining respondents were older than 35. Age Frequency Percentage 25-30 years 10 14% 31-35 years 50 72% >35 years 10 14% Table 4.2: Age of Respondents The chart below here shows the age of respondents. 4.2. RESPONDENT ANSWERS: 4.2.1. Liquidity risk breaks the silo – based approach: Liquidity risk break the silo – based approach to manage risk as Basel 3 is the best opportunity to break down.
That starts with the senior management establishing a detailed, clearly defined definition of the overall risk appetite of the bank. This ensures that shareholders, deposit holders and other stakeholders have a clear understanding of the business strategy. From there, a number of steps should be taken to ensure that the bank truly takes ownership of the risks it is running at the group level, as well as at lower business or division levels. Systems should be developed based on common data inputs to drive market, credit and liquidity risk. A single data load with all the attributes required for market, counterparty credit risk, RWA, economic capital and liquidity risk should be extracted from source systems.
Since this data would be shared across risk types, data reconciliation requirements would be automatically met. At the same time, there should be consistent calculation engines that share common models and provide coherent measures across risk types. For example, cash flow generation for liquidity risk should use the same cash flow generation routines common to market risk and counterparty credit risk. There should also be integrated reporting across risk types to give senior managers and investors a consistent view across the enterprise of the impact of different types of risk. Meanwhile, systems should be designed that allow both for large volume, enterprise-wide batch runs and also interactive ‘what-if’ analysis. This will also enable consistent stress testing across market, credit and liquidity risks, as they will all be driven by common risk factors. The implementation of such measures would allow the interplay between capital and liquidity to be fully tested.
With this breaking down of risk silos, senior management will be able to view a ‘dashboard’ of risk indicators that give them a true picture of their group balance sheet and variances from the stated risk appetite. This will mean that senior managers will once again, like the days before the emergence of complex banking, take ownership of the bank portfolio balance sheet at the legal entity level, in turn allowing them to take a harder line if they feel they have to. As Basel 3 progresses it is crucial that the interconnected nature of the risks on the balance sheet is properly assessed, while taking account of regulations and accounting standards. It is, therefore, time to break down those silos. 4.2.2. Misunderstanding how liquidity risk and capital are connected By viewing capital as a primary mitigant of liquidity risk, we fail to understand the nature of that risk. Capital mitigates unexpected losses, but not cash flow imbalances, such as funding liquidity risk. Liquidity risk is crystallized when a bank has to undertake a last minute fire sale of assets to meet its obligations. In short, if an institution has a liquidity problem, then it needs cash, not capital.
Indeed, should a liquidity situation arise and the bank begins using reserves set aside to guard against liquidity risk in order to absorb losses and meet obligations, then the value of the company and thus the value of the capital are also likely to decline, since the bank will start to be perceived as “riskier”. Liquidity risk and capital are therefore inextricably linked. This linkage has not been recognized by the Basel Committee’s primary response to liquidity risk, the liquidity coverage ratio (LCR), and the net stable funding ratio (NSFR).As with previous compartmentalized approaches to risk management, these ratios more or less view liquidity risk as a stand-alone risk silo. As such, the implementation of the current approach does not effectively address the flawed silo-based approach. The LCR requires that banks hold enough liquid assets to offset the sum of all cash outflows expected over the next 30 days. It tries to ensure the bank owns liquid resources to such an amount that short-term cash obligations will be fulfilled even under severe stress. The NSFR focuses on the structural balance between maturities of bank assets versus liabilities. Through the application of a one-year term horizon, it aims to prevent banks from exposing themselves to extreme maturity transformation risks through funding medium and long-term assets with very short-term liabilities. The prescriptive nature of these ratios is not helpful, as it does not allow the tailoring of a liquidity risk buffer to the needs of the specific institution.
Under a top-down, holistic risk management model, the senior management of the bank would decide on the size of the liquidity buffer and what survival horizon is appropriate for it, based on a careful assessment of the bank’s overall risk appetite. This is important from a best practice governance perspective, because if an institution is holding more than the needed amount of liquid assets, then the part of the liquidity buffer that is not needed has an opportunity cost associated with it; that money could be deployed elsewhere to make a higher return for shareholders. If the institution holds less than is necessary to maintain stability, then the bank risks bankruptcy. 4.2.3. Nature of the liquidity risk: Liquidity risk originates from the mismatch between the timings of cash inflows and outflows. As such, it is fundamentally inherent to the banking business.
Indeed, one of the key social functions of the banking industry is the provision of intermediation so as to facilitate the reallocation of financial resources from the liquid sectors of the economy – those that have excess financial resources to invest – to the illiquid ones. The consequence of this is that the banking industry is necessarily exposed to maturity mismatch. Typically, the terms on which liquid operators are ready to invest their liquidity are shorter than that on which illiquid operators are willing to borrow. While reallocating financial resources from one sector to the other, the banking system bears such mismatch of maturities in the form of liquidity risk. A further natural consequence is that the banking industry is leveraged – banks inherently work on deposits and other funding.
Obviously, a high degree of leverage boosts the impact of any liquidity problem, both on an individual and a systemic basis. In Basel 1 and Basel 2, liquidity risk received limited attention, with the regulations focused on the asset side of the balance sheet. Under Basel 2, risks arising from the liability side – including liquidity risk and interest rate risk in the banking book – are not subject to Pillar 1 minimum regulatory capital requirement. They are instead disciplined under pillar 2, with banks required to calculate the amount of capital they deem sufficient to support all their risks, which includes liquidity risk. However, after years of sterile debate on the possible methodologies for calculating the ‘internal capital’ requirement for liquidity risk, it was generally accepted that capital alone was not a suitable mitigant for liquidity risk. As a result, the current Basel 2 framework does not effectively address liquidity risk. At the root of the Basel 2 framework is the fundamental assumption that a bank will always be creditworthy as long as asset quality is preserved. In other words, consensus thinking before the credit crisis was that as long as the quality of assets was good enough, then the bank would always finance assets at fair prices for virtually any amount. However, this assumption failed to materialize when the crisis erupted and entire liquidity channels suddenly dried up, to the extent that even institutions with high ratings and excellent quality of assets collapsed or were threatened by collapse as a result of liquidity mismatches.
The phenomenon grew to systemic proportions because many in the industry were massively leveraging maturity mismatches between assets and liabilities as a key component of their business model. Clearly, regulators cannot aim to remove liquidity risk from the system. Their best hope is to force banks to build liquid reserves such that, while not matching outflows in terms of maturities, there is an assurance that should a stress event occur then banks can withstand funding imbalances until the situation returns to normal. 4.3. QUALITY ASPECTS OF LIQUIDITY RISK MANAGEMENT: Most of the respondents (83%) answers that the bank maintains a strategy for the liquidity risk management approved by the management. Even though a strategy is maintained, the strategy is not in a revised manner by the bank’s risk management. It is a draw of the bank’s risk management. 4.4 STUDY OF LIQUIDITY RISK In the causes of liquidity risk model, we divide the causes of liquidity risk into bank-specific, supervisory and macroeconomic factors. The model is estimated through fixed effects regression. In the bank liquidity risk and performance model, we regard liquidity risk as an endogenous determinant of bank performance, and apply panel data instrumental variables regression to estimate this model. We also consider another factors affect bank performance besides liquidity risk.
Besides, we divide these factors into bank-specific factors, market structure factors, supervisory factors, and macroeconomic conditions. The contribution of this study is to use alternative liquidity risk measures instead of liquidity ratio, and we are the first study to investigate the causes of liquidity risk. Furthermore, we find that liquidity risk is an endogenous determinant of bank performance. The analyses in subsample, we further classify countries as bank-based or market-based system, and investigate the different causes of liquidity risk in different financial systems. We also investigate the effect of liquidity risk on bank performance in different financial systems. We find that liquidity risk is the endogenous determinant of bank performance. The causes of liquidity risk include components of liquid assets and dependence on external funding, supervisory and regulatory factors and macroeconomic factors.
Besides, we also find that liquidity risk may lower bank profitability (ROAA and ROAE). Banks with larger gap lack stable and cheap fund, and thus they have to use liquid assets or much external funding to meet the demand of fund, increase bank’s cost of funding. It consequently decreases bank’s profitability. However, liquidity risk will increase bank’s net interest margins (NIM). It indicates that banks with high levels of illiquid assets in loans may receive higher net interest income. The financing behaviour is very different between bank-based and market-based financial system. In our study, we classify countries as bank-based or market-based system, and investigate the difference of causes of liquidity risk in different financial systems.
The empirical results indicated that the bank-specific variable has the same effect on bank liquidity risk in two financial systems. About supervision and regulation, it provides that greater official power; higher activity restrictiveness will diminish bank liquidity risk in market-based financial system. However, we find that greater regulatory empowerment of private monitoring of banks will increase bank liquidity risk in market-based financial system. Regarding macroeconomic environment, the results indicates that boom economy make banks run down their liquidity buffer in market-based financial system, but macroeconomic has no effect on bank liquidity risk in bank-based financial system.
Besides, we further investigate bank liquidity risk and performance in different financial systems. We find that liquidity risk has different effects on bank performance in different financial systems. Liquidity risk is negatively related to bank performance in market-based financial system; however, it has no effect on bank performance in bank-based financial system. Finally, we check the robustness of our results using alternative liquidity risk measures, net loans to customer and short term funding. We find that the results are almost same as the model using financing gap to total assets ratio (FGAPR). Table No.1 Opinion about the financial banking system needed to function in a proper and effective manner S. No. Opinion No. of Respondents Percentage 1. Efficient Transfer of funds between lenders to borrowers 18 36 2. Efficient and correct pricing of financial assets 10 20 3. Secure and efficient payments resulting in liquidity 22 44 Total 50 100 The above table shows that majority 44% of the respondents stated that the financial banking system needed to function in a proper and effective manner with secure and efficient payments resulting in liquidity, 36 indicates efficient transfer of funds between lenders to borrowers and the remaining 20% expressed efficient and correct pricing of financial assets. Table No.2 Awareness of Basel Core Principles S. No. Opinion No. of Respondents Percentage 1. Preconditions for effective banking supervision 41 82 2. Licensing and structure 27 54 3. Prudential regulations and requirements 38 76 4. Methods of ongoing banking supervision 29 58 5. Information requirements 43 86 6. Formal powers of supervision 34 68 7. Cross border banking 36 72 The above tables reveals that majority (86%) of the respondents are aware about the information requirements in basel core principles, 82% are aware about the preconditions for effective banking supervision, 76% are aware about the prudential regulations and requirements, 68% of the respondents are aware about the formal powers and supervision, 58% are aware about the methods of ongoing banking supervision and the remaining 54% are aware about the licensing and structure. Table No.3 Parties considered for financing by the Basel 2 committee S. No. Opinion No. of Respondents Percentage 1. Retail SME’s 48 96 2. Factories 33 66 3. Commercial Real Estates 37 74 The above tables shows that majority (96%) of the parties considered to finance by the Basel 2 Committee are Retail SMEs, 74% of the respondents are aware that the beneficiaries are commercial real estates and the rest 66% of them are aware the factories are the beneficiaries towards the Basel 2 Committee finance. Table No.4 Awareness about the retail loan segment hindering during the retail loan distribution Sl. No. Opinion No. of Respondents Percentage 1. Yes 46 92 2. No 4 8 Total 50 100 The above table shows that majorities (92%) of the respondents are aware about the retail loan segment hindering during the retail loan distribution and 8% of the respondents are not aware. Table No.5 Reasons aware about the hindrances S. No. Reasons No. of Respondents Percentage 1. Only SME’s are benefited from this distribution 23 50 2. All retail segments are not covered 12 26 3. Banks step towards self protection 11 24 Total 46 100 The above tables shows that half (50%) of the respondents are aware that only SMEs are benefited from this distribution, 26% of the respondents are aware all retail segments are not covered and the remaining 24% of the respondents are aware only banks step towards self protection. Table No.6 Impacts on SMEs or retail loan segment due to banks self protection S. No. Opinion No. of Respondents Percentage 1. Hindrance in growth of retail segment 12 24 2. Hindrance in growth of economy 38 76 Total 50 100 The above tables shows that majority (76%) of the respondents stated that the impact on SMEs or retail loan segment due to banks self protection hinders the growth of the economy and 24% considered the hindrance in growth of retail segment. Table No.7 Other Disadvantages Sl. No. Opinion No. of Respondents Percentage 1. Restricting retail segment to small business 15 30 2. Non-consideration higher business volume 35 70 Total 50 100 The above table shows that majority (70%) of the respondents considers other disadvantages as non-consideration higher business volume and 30% indicates that restricting retail segment to small business. Table No.8 Awareness about the three issues of risk addressed during the proposal Sl. No. Opinion No. of Respondents Percentage 1. Yes 35 70 2. No 15 30 Total 50 100 The above table shows that majority (70%) of the respondents is aware about the three issues of risk addressed during the proposal and 30% of the respondents are not aware. Table No.9 Impact of the risk considered very high Sl. No. Reasons No. of Respondents Percentage 1. Counter party credit risk 10 29 2. Credit derivatives 9 25 3. Operational risk 16 46 Total 35 100 The above tables shows that less than half (46%) of the respondents stated that operational risk impact is considered as very high, 29% considered counter party credit risk and the remaining 25% considered credit derivatives risk. Table No.10 Risk involved in counterparty credit risk Sl. No. Opinion No. of Respondents Percentage 1. Medium potential exposure measure and manage the credit risk 7 20 2. Loss given default rate is relatively high 28 80 Total 35 100 The above tables shows that majority (80%) of the respondents stated loss given default rate is relatively high which is the risk involved in counterparty credit risk and 20% of the respondents expressed medium potential exposure measure and mange the credit risk. Table No.11 Risk involved in credit Derivatives Sl. No. Opinion No. of Respondents Percentage 1. Substitution approach 18 51 2. Offset approach 17 49 Total 35 100 The above tables shows that more than half (51%) of the respondents stated that the substitution approach is the highest risk involved in credit derivatives and 49% opined offset approach as the risk factor involved in credit derivative risk. The disadvantages of substitutional approach and offset approach are Substitutional approach substitutes the risk weight of the protection seller in place of the risk weight of the reference credit. Offset approach reduces the amount of current exposure by the amount of protection provided by the credit derivatives Table No.12 Awareness about the major impact of double default Sl. No. Awareness No. of Respondents Percentage 1. Reference credit 34 68 2. Protection seller 16 32 Total 50 100 The above tables shows that most (68%) of the respondents are aware that the reference credit as the major impact of double default and 32% of the respondents are aware about the protection seller. Table No.13 Advantages in structure of Basel 2 Sl. No. Awareness High Medium Low Total 1. Fundamental safety and soundness banking principles 22 21 7 50 2. Reasonable trade off between enhanced risk sensitivity and implementation burden 36 8 4 50 3. Capital charges are stable over the economic cycle 31 12 7 50 4. Improvement in risk management practice 18 20 12 50 5. Greater Risk Sensitivity 46 2 2 50 6. Reflect and support sound risk management practices 39 6 5 50 7. Adapt to evolving markets and products 17 24 9 50 8. Promote and enhance a level playing field across international boundaries 11 15 24 50 The above tables shows that the advantages in the structure of Basel 2 are self explanatory, however, 46 (92%) of the respondents stated the greater risk sensitivity as high, 39 (78%) of the respondents indicated reflect and support sound risk management practices as high, 36 (72%) expressed reasonable trade off between enhanced risk sensitivity and implementation burden, 31 (62%) of the respondents opined capital charges are stable over the economic cycle and considered high, 24 (48%) of the respondents stated medium on the adapt to evolving markets and products and the remaining 24 (48%) stated low over the promotion and enhancement of level playing field across international boundaries.
A professional writer will make a clear, mistake-free paper for you!Get help with your assigment
Please check your inbox
I'm Chatbot Amy :)
I can help you save hours on your homework. Let's start by finding a writer.Find Writer