People’s Republic of China–Hong Kong Special Administrative Region: Financial Sector Assessment Program-Stress Testing the Banking Sector-Technical Note

International Monetary Fund. Monetary and Capital Markets Department

doi:10.5089/9781498322638.002.A001

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People’s Republic of China–Hong Kong Special Administrative Region

Financial Sector Assessment Program-Stress Testing the Banking Sector-Technical Note

Author: International Monetary Fund. Monetary and Capital Markets Department

Publication Date:: 16 Jul 2014

eISBN:: 9781498322638

Language:: English

Keywords:: ISCR; CR; banking sector; put option; capital ratio; price index; asset swap; commercial bank; credit risk; Hong Kong SAR; cash inflow; sample bank; banking group; classified loan

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This Technical Note on Stress Testing the Banking Supervision was prepared in the context of the Financial Sector Assessment Program (FSAP) for the People’s Republic of China–Hong Kong Special Administrative Region (HKSAR). Bank liquidity tests focus on sudden, sizable withdrawals of funding and the sufficiency of existing assets to withstand those shocks under stressed conditions. The stress test results confirm a high degree of resilience of the sector. This reflects the strength of the banks at the starting position, which reduces their fundamental vulnerability to shocks. Banks in HKSAR hold very high levels of capital, are very profitable, and have a low level of asset impairments amid stable funding profiles. The Hong Kong Monetary Authority is encouraged to continue its integration of risk-based supervision in the development of stress test scenarios for macroprudential policy and surveillance. Banking supervisors routinely conduct stress tests and, from time to time, modify relevant assumptions in order to support thematic reviews of identified vulnerabilities against emerging risks.

Abstract

Introduction¹

A. Background and Objective

1. The stress testing exercise of the FSAP for HKSAR comprises a comprehensive vulnerability analysis of the banking sector.² The stress test exercise—as part of the FSAP mission’s analysis of financial stability—determined the capacity of the banking sector to absorb realization of key macro-financial risks based on the assessment of capital adequacy and sufficiency of liquidity under stress. It was aimed at examining the system-wide resilience to shocks over the medium-term, uncovering vulnerabilities to any rapid deterioration in the macroeconomic environment and, more generally, identifying potential threats to financial stability.

2. This note presents the methodology and results of a detailed examination of solvency and liquidity risks. It follows a multi-pronged approach, reflecting a critical assessment of a large variety of possible vulnerabilities that can affect the viability of individual institutions and system-wide risks in the sector. In this context, different stress tests are combined into a comprehensive analysis of the sector’s vulnerability to a considerable economic contraction, including a substantial rise in unemployment, a sharp depreciation of real estate prices, and rising funding pressures. The objective of these tests is to determine the capacity of the banking sector—using mid-2013 financial data—to absorb any realization of key macro-financial risks. Solvency tests consist of a BU stress test by the selected local banks and a cross-validation through several TD tests, undertaken jointly by staff of the HKMA and the FSAP team.

3. Solvency tests are complemented by TD liquidity stress tests using supervisory data and parameters specified by both the HKMA and the FSAP team in the context of different approaches (Figure 1). These liquidity stress tests cover both the local banks and the largest foreign branches in the sector. The analysis relies on the prudential assumption that sufficiently high individual capital levels and liquidity buffers lower systemic risk. Given that institutional viability might be insufficient to maintain financial stability during times of extreme stress, one of the stress tests also considered the impact of joint tail risks on system-wide solvency conditions. Overall, the various stress tests conducted for FSAP cover around 50 to around 70 percent of the banking sector’s total assets—depending on the type of analysis—accounting for up to 78 percent of total deposits and 66 of total loans). The two TD solvency stress tests cover more than 99 percent of all locally incorporated licensed banks (“local banks”) (Table 9).

Table 1.

Hong Kong SAR: Risk Assessment Matrix

Table 1.

Hong Kong SAR: Risk Assessment Matrix

Source of Main Threats	Likelihood of Realization of Threats in the next 1-3 Years	Expected Impact on Financial Stability of Threat if Realized
Protracted economic and financial volatility, triggered by prospective exit from unconventional monetary policies in advanced economies, particularly the United States, and resulting in increased risk premia and interest rates.	High (short-term)	Medium This could lead to capital outflows and a tightening of liquidity. Higher interest rates would require borrowers to allocate an increasing proportion of their income to service debt obligations, and encourage banks to tighten credit standards. The resulting contraction in financial intermediation and investment would adversely affect economic growth.
Sharp slowdown in growth in Mainland China, in the context of the increasing integration between HKSAR and Mainland China	Medium (medium-term)	Medium to High Economic growth in HKSAR would weaken significantly as a result of a sharp economic slowdown in Mainland China. This would have severe consequences for the Hong Kong financial sector. The quality of Hong Kong banks’ assets would deteriorate as lower growth adversely affect borrowers’—both Hong Kong and Mainland—capacity to repay. This pressure would be further aggravated by uncertainty about the recovery of collateral in Mainland China. Liquidity in the offshore renminbi market would be negatively affected by a tightening of liquidity in Mainland China.
Significant decline in property prices	Medium (short to medium-term)	Medium to High This would reduce the collateral value of mortgages, which would curtain the ability of households and small firms to borrow. In the context of a tightening of banks lending standards, this could have severe macroeconomic consequences and adversely affect banks.
Financial stress in the euro area re-emerges	Medium (short-term)	Low Again, depending on the impact on economic growth in HKSAR, this may also translate into some deterioration of banks’ earnings, asset quality, and, possibly, funding costs.

Table 1.

Hong Kong SAR: Risk Assessment Matrix

Source of Main Threats	Likelihood of Realization of Threats in the next 1-3 Years	Expected Impact on Financial Stability of Threat if Realized
Protracted economic and financial volatility, triggered by prospective exit from unconventional monetary policies in advanced economies, particularly the United States, and resulting in increased risk premia and interest rates.	High (short-term)	Medium This could lead to capital outflows and a tightening of liquidity. Higher interest rates would require borrowers to allocate an increasing proportion of their income to service debt obligations, and encourage banks to tighten credit standards. The resulting contraction in financial intermediation and investment would adversely affect economic growth.
Sharp slowdown in growth in Mainland China, in the context of the increasing integration between HKSAR and Mainland China	Medium (medium-term)	Medium to High Economic growth in HKSAR would weaken significantly as a result of a sharp economic slowdown in Mainland China. This would have severe consequences for the Hong Kong financial sector. The quality of Hong Kong banks’ assets would deteriorate as lower growth adversely affect borrowers’—both Hong Kong and Mainland—capacity to repay. This pressure would be further aggravated by uncertainty about the recovery of collateral in Mainland China. Liquidity in the offshore renminbi market would be negatively affected by a tightening of liquidity in Mainland China.
Significant decline in property prices	Medium (short to medium-term)	Medium to High This would reduce the collateral value of mortgages, which would curtain the ability of households and small firms to borrow. In the context of a tightening of banks lending standards, this could have severe macroeconomic consequences and adversely affect banks.
Financial stress in the euro area re-emerges	Medium (short-term)	Low Again, depending on the impact on economic growth in HKSAR, this may also translate into some deterioration of banks’ earnings, asset quality, and, possibly, funding costs.

Table 2.

Hong Kong SAR: Stress Test Matrix (STeM) for the Banking Sector—Liquidity

Table 2.

Hong Kong SAR: Stress Test Matrix (STeM) for the Banking Sector—Liquidity

Domain		Assumptions
Domain		Top-down by FSAP Team (with data input from HKMA)	Top-down by HKMA
1. Institutional Perimeter	Institutions included	All large locally incorporated, licensed banks (19) and selected foreign branches (8).	All large locally incorporated, licensed banks (19) and selected foreign branches (8) [for HKMA 7-day test/LOLR analysis (7-day) and (ELST)]. Selected locally incorporated, licensed banks and foreign branches [for Basel III standard measures LCR and NSFR (B3)]. All large locally incorporated, licensed banks (17) (all Group 1 banks but without separate treatment of Nanyang Commercial Bank Ltd. and Chiyu Banking Corporation Ltd., which are consolidated under Bank of China (HK)) [for credit-liquidity interaction (Wong-Hui, 2009) (WH)].
	Market share	70.9 percent of total banking sector assets	70.9 percent of total banking sector assets [for 7-day and ELST]. About 60 percent of total banking sector assets [for B3]. 63.0 percent of total banking sector assets [for WH].
	Data and baseline date	Source: supervisory data from liquidity reporting. Date: end-June 2013. Scope: solo basis; only unencumbered liquid assets (generating cash inflows), i.e., that can be sold or used as a collateral to receive funding (with the exception of cash/cash-equivalents) are included in the test (“liquidity scope”).	Source: supervisory data from liquidity reporting for 7-day and ELST, individual banks’ data for B3 and WH. Date: end-June 2013. Scope: solo basis (with the exception of consolidated/combined basis for selected locally incorporated, licensed banks for B3 and consolidated basis for WH); only unencumbered liquid assets (generating cash inflows), i.e., that can be sold or used as a collateral to receive funding (with the exception of cash/cash-equivalents) are included in the test (“liquidity scope”).
2. Channels of Risk Propagation	Methodology	Calculation of FSAP team’s 5-day ICF test (cumulative) and 30-day ICF test (non-cumulative), with focus on the sudden, sizeable withdrawal of funding (liabilities) and the sufficiency of existing assets to withstand those shocks under stressed conditions; also maturity mismatch analysis (both local and foreign currencies).	Calculation of 7-day and ELST, with focus on the sudden, sizeable withdrawal of funding (liabilities) and the sufficiency of existing assets to withstand those shocks under stressed conditions. Calculation of standard measures for liquidity risk as per Basel Committee on Banking Supervision (BCBS) guidance: definition of LCR as per revised guidance published on January 2013 (BCBS, 2013a) (including assessment of haircuts on liquid assets, assumption on expected and contingent cash in- and outflows), with exception of a higher outflow rate (5 percent instead of a reduced level of 3 percent) for retail “stable deposits” and retail term deposits with tenors beyond 30 days; NSFR based on latest guidance (BCBS, 2010c).³⁹ Calculation of expected first cash shortage time, probability of cash shortage), expected default time due to liquidity problems, and PD due to liquidity problems according to the model by Wong and Hui (2009).
3. Risks and Buffers	Risks Buffers	Market liquidity risk (asset amortization, liquidity and encumbrance). Market funding risk (liabilities run-off). Maturity-mismatch, rollover risk, and foreign exchange (FX) funding risk [for mismatch analysis]. Constant funding structure; no counterbalancing capacity. Ability to respond to withdrawals and funding needs with access to HKMA/central bank facilities only via collateralized funding.	Market liquidity risk (asset amortization, liquidity and encumbrance). Market funding risk (liabilities run-off). Maturity-mismatch and rollover risk [for NSFR]. Constant funding structure; no counterbalancing capacity. Ability to respond to withdrawals and funding needs with access to HKMA/central bank facilities only via collateralized funding
4. Tail Shocks	Size of the shock	Bank run and dry up of retail/wholesale funding markets, taking into account valuation haircuts to liquid assets, amortization of outstanding assets, related party lending, and contingent claims/liabilities. Very low expected/potential net cash inflows related to credit extension/funding, (i) without liquid financial assets, (ii) with liquid securities and bank loans, (iii) derivatives (excl. credit derivatives), and (iv) committed/uncommitted credit lines to/from related and third parties. One alternative scenario [for both 5-day and 30-day test], which assumes the absence of a retail deposit run.	7-day: Bank run, taking into account haircuts to liquid assets. ELST: Bank run and dry up of retail/wholesale funding markets, taking into account haircuts to liquid assets, related party lending/borrowing. One alternative scenario [for ELST], which assumes the absence of a retail deposit run.
5. Regulatory and Market-based Standards and Parameters	Regulatory standards	n.a. (but cash flow monitoring part of the Basel III liquidity risk framework)	Basel III ratios: LCR and NSFR.
6. Reporting Format for Results	Output presentation	Hurdle metrics: distribution of ratios, number of failed banks (i.e., ratio < 100%), liquidity shortfall relative to unencumbered assets.	Hurdle metrics: distribution of ratios, number of failed banks (i.e., ratio < 100%), liquidity shortfall relative to unencumbered assets.

Table 2.

Hong Kong SAR: Stress Test Matrix (STeM) for the Banking Sector—Liquidity

Domain		Assumptions
Domain		Top-down by FSAP Team (with data input from HKMA)	Top-down by HKMA
1. Institutional Perimeter	Institutions included	All large locally incorporated, licensed banks (19) and selected foreign branches (8).	All large locally incorporated, licensed banks (19) and selected foreign branches (8) [for HKMA 7-day test/LOLR analysis (7-day) and (ELST)]. Selected locally incorporated, licensed banks and foreign branches [for Basel III standard measures LCR and NSFR (B3)]. All large locally incorporated, licensed banks (17) (all Group 1 banks but without separate treatment of Nanyang Commercial Bank Ltd. and Chiyu Banking Corporation Ltd., which are consolidated under Bank of China (HK)) [for credit-liquidity interaction (Wong-Hui, 2009) (WH)].
	Market share	70.9 percent of total banking sector assets	70.9 percent of total banking sector assets [for 7-day and ELST]. About 60 percent of total banking sector assets [for B3]. 63.0 percent of total banking sector assets [for WH].
	Data and baseline date	Source: supervisory data from liquidity reporting. Date: end-June 2013. Scope: solo basis; only unencumbered liquid assets (generating cash inflows), i.e., that can be sold or used as a collateral to receive funding (with the exception of cash/cash-equivalents) are included in the test (“liquidity scope”).	Source: supervisory data from liquidity reporting for 7-day and ELST, individual banks’ data for B3 and WH. Date: end-June 2013. Scope: solo basis (with the exception of consolidated/combined basis for selected locally incorporated, licensed banks for B3 and consolidated basis for WH); only unencumbered liquid assets (generating cash inflows), i.e., that can be sold or used as a collateral to receive funding (with the exception of cash/cash-equivalents) are included in the test (“liquidity scope”).
2. Channels of Risk Propagation	Methodology	Calculation of FSAP team’s 5-day ICF test (cumulative) and 30-day ICF test (non-cumulative), with focus on the sudden, sizeable withdrawal of funding (liabilities) and the sufficiency of existing assets to withstand those shocks under stressed conditions; also maturity mismatch analysis (both local and foreign currencies).	Calculation of 7-day and ELST, with focus on the sudden, sizeable withdrawal of funding (liabilities) and the sufficiency of existing assets to withstand those shocks under stressed conditions. Calculation of standard measures for liquidity risk as per Basel Committee on Banking Supervision (BCBS) guidance: definition of LCR as per revised guidance published on January 2013 (BCBS, 2013a) (including assessment of haircuts on liquid assets, assumption on expected and contingent cash in- and outflows), with exception of a higher outflow rate (5 percent instead of a reduced level of 3 percent) for retail “stable deposits” and retail term deposits with tenors beyond 30 days; NSFR based on latest guidance (BCBS, 2010c).³⁹ Calculation of expected first cash shortage time, probability of cash shortage), expected default time due to liquidity problems, and PD due to liquidity problems according to the model by Wong and Hui (2009).
3. Risks and Buffers	Risks Buffers	Market liquidity risk (asset amortization, liquidity and encumbrance). Market funding risk (liabilities run-off). Maturity-mismatch, rollover risk, and foreign exchange (FX) funding risk [for mismatch analysis]. Constant funding structure; no counterbalancing capacity. Ability to respond to withdrawals and funding needs with access to HKMA/central bank facilities only via collateralized funding.	Market liquidity risk (asset amortization, liquidity and encumbrance). Market funding risk (liabilities run-off). Maturity-mismatch and rollover risk [for NSFR]. Constant funding structure; no counterbalancing capacity. Ability to respond to withdrawals and funding needs with access to HKMA/central bank facilities only via collateralized funding
4. Tail Shocks	Size of the shock	Bank run and dry up of retail/wholesale funding markets, taking into account valuation haircuts to liquid assets, amortization of outstanding assets, related party lending, and contingent claims/liabilities. Very low expected/potential net cash inflows related to credit extension/funding, (i) without liquid financial assets, (ii) with liquid securities and bank loans, (iii) derivatives (excl. credit derivatives), and (iv) committed/uncommitted credit lines to/from related and third parties. One alternative scenario [for both 5-day and 30-day test], which assumes the absence of a retail deposit run.	7-day: Bank run, taking into account haircuts to liquid assets. ELST: Bank run and dry up of retail/wholesale funding markets, taking into account haircuts to liquid assets, related party lending/borrowing. One alternative scenario [for ELST], which assumes the absence of a retail deposit run.
5. Regulatory and Market-based Standards and Parameters	Regulatory standards	n.a. (but cash flow monitoring part of the Basel III liquidity risk framework)	Basel III ratios: LCR and NSFR.
6. Reporting Format for Results	Output presentation	Hurdle metrics: distribution of ratios, number of failed banks (i.e., ratio < 100%), liquidity shortfall relative to unencumbered assets.	Hurdle metrics: distribution of ratios, number of failed banks (i.e., ratio < 100%), liquidity shortfall relative to unencumbered assets.

Table 3.

Hong Kong SAR: Stress Test Matrix (STeM) for the Banking Sector—Solvency

Table 3.

Hong Kong SAR: Stress Test Matrix (STeM) for the Banking Sector—Solvency

Domain		Assumptions
Domain		Bottom-up by Banks (with guidelines by FSAP Team)	Top-down by FSAP Team (balance sheet-based)	Top-down by HKMA (balance sheet-based)	Top-down by FSAP Team (market-based, ‘Systemic CCA’)
BANKING SECTOR: SOLVENCY RISK
1. Institutional Perimeter	Institutions included	Selected local banks.	All large locally incorporated licensed banks (16), excluding those which are subsidiaries of another licensed bank.	All large locally incorporated licensed banks (19).	9 publicly listed, locally incorporated licensed banks.
	Market share	About 50 percent of total banking sector assets on a consolidated basis (as of end-June 2013).	63.0 percent of total banking sector assets on a consolidated basis (as of end-June 2013).	58.0 percent of total banking sector assets on a combined basis (as of end-June 2013).	53.8 percent of total banking sector assets on a consolidated basis (as of end-June 2013).
	Data and baseline date	Source: institutions’ own granular data. Date: end-June 2013 (projected to end-2013). Scope: consolidated banking group.	Source: institutions’ own granular data. Date: end-June 2013 (projected to end-2013). Scope: consolidated banking group.	Source: supervisory data. Date: end-June 2013 (projected to end-2013). Scope: combined basis.	Source: institutions’ own granular data and capital market data. Scope: consolidated banking group.
2. Channels of Risk Propagation	Measurement Satellite Models for Macro-Financial linkages	Banks’ internal models BU guidance (IMF, 2011a, 2012a and 2013b). Valuation haircut model for sovereign risk (Jobst and others, forthcoming; IMF, 2013b). Macro-financial linkages estimated based on firm’s internal models to forecast the profitability components (interest income, interest expenses, fee/commissions income, trading income and operating expenses) as well as the flow of asset impairments and charge-offs; each material loan category includes an increase of loss-givendefaults (LGDs) under stress according to the increase of default risk (PD), after controlling down-cycle LGDs that are based on a long-term average, i.e., “through the cycle.” Key macroeconomic and financial variables include GDP (nominal and real), household income, unemployment, inflation, interest rates/asset swap rates (short-term and long-term), equity prices, commercial property price index, real estate price index, and credit growth, and were projected using the HKMA’s macro model and IMF staff estimates based on G20MOD model⁴⁰. Cross-border effects are considered in all macro scenarios: IMF staff provided estimates for real GDP growth rates consistent with the macroeconomic forecast for HKSAR under both baseline and adverse scenarios for all relevant countries (Mainland China, Australia, France, Germany, India, Japan, South Korea, Singapore, the United Kingdom, and the United States) Sovereign risk assessed by applying valuation haircuts on all direct and indirect net exposures to sovereign risk (including home country) and financial bonds (i.e., bonded debt issued by financial institutions) in trading book as well as available-for-sale (AfS) and hold-to-maturity (HtM) assets over the entire time horizon; cash at central banks as well as repos or asset swaps where there is no economic interest in the security (for instance, instruments held against assets pledged to the HKMA) are excluded.	Balance sheet-based model (IMF, 2010, 2011 and 2012). Valuation haircut model for sovereign risk (Jobst and others, forthcoming; IMF, 2013b). Macro-financial linkages estimated based on dynamic 2SLS panel data regression (using GMM with orthogonal deviations over quarterly observations between 1996: Q1 and 2013: Q2) to forecast the profitability components (interest income, interest expenses, fee/ commissions income, and operating expenses) as well as the flow of asset impairments and charge-offs; each material loan category includes an increase of LGDs under stress according to the increase of default risk (PD), after controlling down-cycle LGDs that are based on a long-term average, i.e., “through the cycle”; the change in trading income was mapped to nominal GDP growth Key macroeconomic and financial variables include GDP (nominal and real), household income, unemployment, inflation, interest rates/asset swap rates (short-term and long-term), equity prices, commercial property price index, real estate price index, and credit growth, and were projected using the HKMA’s macro model and IMF staff estimates based on G20MOD model. Cross-border effects are considered in all macro scenarios: IMF staff provided estimates for real GDP growth rates consistent with the macroeconomic forecast for HKSAR under both baseline and adverse scenarios for all relevant countries (Mainland China, Australia, France, Germany, India, Japan, South Korea, Singapore, the United Kingdom, and the United States). Sovereign risk assessed by applying valuation haircuts on all direct and indirect net exposures to sovereign risk (including home country) and financial bonds (i.e., bonded debt issued by financial institutions) in trading book as well as AfS and HtM assets over the entire time horizon; cash at central banks as well as repos or asset swaps where there is no economic interest in the security (for instance, instruments held against assets pledged to the HKMA) are excluded; assumption of exposureweighted average duration of three years	Balance sheet-based model (HKMA, 2013). Macro-financial linkages estimated for asset impairments/charge-offs for certain loan categories (“Nonbank Mainland China Exposures (NBMCE)”, other loans (excl. residential mortgages, property investment loans, and credit card lending), and off-balance sheet credit exposures derived from their historical sensitivity to changes in real GDP at specified statistical confidence level; other shocks to default probabilities (for stock-related lending, credit card lending, off-balance sheet derivatives exposures, debt securities) and asset prices by means of statistical mapping to specified historical severity (90^th or 99^th percentile); expert judgment on other risk factors (interest rate shocks, floors on asset impairments/charge-offs, procyclical impact on credit RWA). Aggregation of single factor shocks. Key macroeconomic and financial variables included real GDP for HKSAR and Mainland China, interest rates, equity prices, commercial and residential property price index. Cross-border effects are considered in relation to Mainland China: real GDP growth rate for Mainland China is incorporated in projections of loan losses. Sovereign risk assessed as part of the general credit risk shock to debt securities (securitized and non-securitized).	Systemic CCA model (Gray and Jobst, 2010; Jobst and Gray, 2013). Valuation haircut model for sovereign risk (Jobst and others, forthcoming; IMF, 2013b). Macro-financial linkages estimated based on dynamic 2SLS panel data regression (→ other TD test by FSAP team) Key macroeconomic and financial variables include GDP (nominal and real), household income, unemployment, inflation, interest rates/asset swap rates (short-term and long-term), equity prices, commercial property price index, and real estate price index, and were projected using the HKMA’s macro model and IMF staff estimates based on G20MOD model. Cross-border effects are not explicitly considered in any macro scenario but are implicit in estimated dependence between market-implied expected losses and their impact on capital adequacy.
	Stress test horizon	2014–2018 (five years).	2014–2018 (five years).	2014–2015 (two years) but single-period set-up.	2014–2018 (five years).
3. Tail Shocks	Scenario analysis	Three different macroeconomic scenarios: (i) a baseline scenario with projections in line with the World Economic Outlook (April 2013); (ii) a “slow growth” scenario, underpinned by a broad-based slowdown of global growth triggered by markets’ accelerated view on the pace of tightening in U.S. monetary policy; and (iii) a “severe adverse” scenario, where the contraction of economic activity (ii) is further aggravated by a severe intensification of capital outflows in emerging market countries, impacting Hong Kong’s major trading partners. Under the two adverse scenarios, economic growth in HKSAR deteriorates to 2.6 and 2.0 percent on average relative to baseline expectations of average annual growth of 4.4 percent (which is slightly above the long-term (30-year) annual growth rate of 4.1 percent). Overall, the magnitude of these shocks—at cumulative negative deviations of about 9.1 and 12.1 percentage points in real GDP, which equate to about 1.6 and 2.1 standard deviations of the average cumulative two-year growth rate over the last 30 years, respectively—is in line with the spectrum of economic adversity considered in the context of other stress testing exercises.		Three different macroeconomic scenarios: (i) a baseline scenario with projections and risk parameters in line with those used for the TD solvency by the FSAP team, (ii) Scenario A (“Severe”), and (iii) Scenario B (“More Severe”), which include single factor shocks to credit losses, market risk (interest rates, equity prices), profitability (net interest income and non-interest income), asset risk-weighting, and interest in land & buildings at the 90 percent (Scenario A) and 99 percent (Scenario B) statistical confidence levels (Table 6).	Same three macroeconomic scenarios as for the BU and TD tests (→ other TD test by FSAP team).
	Sensitivity analysis	FX shock: shock to FX net open positions (both through the P&L and on RWAs): Chinese renminbi, euro, Japanese yen, pound sterling, Singapore dollar, and other material currencies for the firm vis-à-vis the U.S. dollar; for each currency should be four times the maximum deviation of the annualized FX volatility during the 2008-11 period from the long-term FX volatility (>10 years) for the adverse scenarios (not baseline) and impact the trading book in 2014 (100 percent) and 2015 (50 percent) only.		RWAs increase not only for derivatives but all credit risk-sensitive exposures.	Variability of statistical confidence level of risk measure. Quantification of contribution of individual banks to systemic risk
4. Risk Factors	Risks/factors assessed	Credit risk (households and corporates, domestic and foreign exposures, local currency and FX). Counterparty risk of off-balance sheet exposures in the banking book.⁴¹ Sovereign risk of all government bonds, indirect sovereign exposure as well as all financial bonds. Funding risk (additional add-on to interest expenses, contingent on Tier 1 capitalization). Market risk: interest rates and FX. Tax rate: 16.5 percent.		Credit risk (loans and advances (incl. NBMCE, residential mortgages and property investment loans, credit card lending, stock-related lending, other loans, off-balance sheet exposures) and debt securities (non-securitization/securitization). Market risk: interest rates and equity prices.	Same three macroeconomic scenarios as for the BU and TD tests (→ other TD test by FSAP team).
	Balance sheet assumption	Static balance sheet with constant credit growth (i.e., lending and funding increases in line with nominal GDP (if positive)) without changes in the funding structure, subject to a “deleveraging rule” (i.e., credit growth decreases by 2 percentage points for each decrease in Tier 1 capital by 1 percentage point once the buffer is less than 2.5 percentage points; no asset disposals/divestments after cut-off date; defaulted loans are not replenished.		Static balance sheet without any adjustments.	Static balance sheet without any adjustments.
	Treatment of Dividends	Dividend payout is limited if the firm reports profits over the past year (and exhibits sufficient Tier 1 capitalization) but falls below 10.5 percent (which reflects the magnitude of the CAR and “capital conservation buffer” under Basel III); however, firms that are not capital constrained will have to pay out at least 40 percent of earnings after tax each year.	Dividend payout is limited if the firm reports profits over the past year (and exhibits sufficient Tier 1 capitalization) but CAR falls below a certain threshold (which reflects the average Pillar 2 minimum CAR requirement imposed by the HKMA on the local banks under Basel III and the historical capital buffer of local banks over that requirement (3.2 percent)). Firms that are not capital constrained will have to pay out at least 45 percent of earnings after tax each year. The payout ratio declines by 10 percentage points for each 0.5 percentage point decline in the capital buffer; 100 percent retention if capital buffer is lower than the threshold.		Dividend payout: discounted from the current share price when deriving implied asset values.
5. Regulatory and Market-based Standards and Parameters	Calibration of risk parameters	PDs and LGDs: internal models for point-in time-PDs and down-cycle LGDs (or adjustment to long-term average LGDs); in absence of an internal model, LGDs increase under stress according to the following specification: LGD(under stress)=0.3502+2.3408*PD. In case of over-collateralization (or supervisory LGDs below the intercept value), the increase of LGDs is limited to the trend coefficient (beta) of the LGD elasticity to PDs, which allows banks to calibrate the LGD at the starting point to their own LGD estimate. RWAs were estimated in accordance with IRB method under Basel III using through-the-cycle PDs, plus adjustments for loan portfolio concentration and changes in default risk.	PDs and LGDs: PDs (not LGDs) change over time; through-the-cycle PDs based on prudential data and stressed PDs based on the change in the stock of NPLs (via satellite model) while provisioning levels at the start of the forecast horizon are maintained. RWAs were estimated in accordance with AIRB method under Basel III, plus adjustments for loan portfolio concentration and changes in default risk (i.e., RWAs for credit risk are reduced by the RWAs of defaulted exposures, which are assumed to be 2.5 times the average RWAs for non-defaulted exposures (accounting for the fact that risk-weights for defaulted exposures were higher prior to default)).	Credit loss rates, PDs and LGDs: change in response to shock (either based on estimated sensitivity to macro-financial variables (in the case of NBMCE, residential mortgages, property investment loans, and other loans) or historical loss at specified statistical confidence level (for credit card lending, stock related lending, debt securities)). RWAs for derivatives remain constant under the baseline scenario but increase by 30 and 50 percent under the “severe” and “more severe” scenario, respectively. Increase in IRB credit RWAs based on IRB banks’ historical data and stress test estimates, external data and internal analysis.	Market-implied expected losses (with endogenously determined PD and LGD) inform the amount of capital shortfall (if any) for each firm and jointly for the entire sample.
	Regulatory/Accounting and Market-based Standards	Full Basel III transition schedule. Capital definition according to the Basel III framework; includes phase-in of capital deductions and the phase-out of non-eligible forms of capital, without consideration of grandfathering, during the forecast horizon: Phase-in of adjustments to common CET1 capital: reduction of CET1 capital (such as goodwill, deferred tax assets and minority interests that exceed the permissible limit) deducted at a rate of 20 percent p.a. between 2014 and 2018; in the BU exercise, firms must document deductions if the total amount is less than 20.1 percent (which is the average value for Group 2 (small banks) according to the results from the latest Basel III monitoring exercise as of 30 June 2012 (BCBS, 2013b)). Phase-out of non-Tier 1 and Tier 2 capital elements: the higher of either (i) 10 percent (per annum) of the amount of capital to be phased-out based on results of the quantitative impact study (QIS) (BCBS, 2010) at 16.6 percent (≈1.7 percent p.a.) or (ii) the amount of capital maturing each year of the stress test horizon between 2014 and 2018 (BCBS, 2010a). RWAs: RWAs for operational risk remain constant throughout the forecast period. RWAs for credit risk and market risk are sensitive to the regulatory impact due to Basel III based on firm’s own data; in addition, credit RWAs are subject to the Basel I floor and sensitive both changes in PDs and portfolio concentration: (a) nonlinear effect of changes in PDs and (b) concentration risk impact on RWAs. RWA impact of defaulted loans: The risk-weights for credit risk are subsequently reduced by the RWAs of defaulted exposures, which are calculated by banks’ internal models or approximated by taking 2.5 times the average RWAs for non-defaulted exposures (accounting for the fact that risk-weights for defaulted exposures were higher prior to default).		Basel III hurdle rate for 2015. Capital definition according to the Basel III framework, including phase-in of adjustments to common CET1 capital and phase-out of non-eligible forms of capital, without consideration of grandfathering, during the forecast horizon (same as “Bottom-up by Banks”). RWAs: RWAs for operational and market risk remain constant throughout the forecast period. RWAs for credit risk are sensitive to the regulatory impact due to Basel III and are subject to the Basel I floor. RWA impact of defaulted loans: no replenishment of loan portfolio. Risk-weighted assets (RWAs): RWAs for market and operational risk remain constant throughout the forecast period. RWAs for credit risk change due to higher PD and LGD for the major asset classes under the IRB approach, and the counterparty risk valuation of OTC derivatives and Regulatory impact due to Basel III based on HKMA’s own data.	Full Basel III transition schedule. Capital definition according to the Basel III framework. RWAs: not applicable; however, under the concept of market-implied capital adequacy (MCAR) of the Systemic CCA model, the implied asset value of a firm corresponds to Pillar 1 RWAs.
6. Reporting Format for Results	Output presentation	Basel III (Common Equity Tier 1, Tier 1, Total Capital, plus conservation buffer) for each year of the risk horizon. Firms reported capital adequacy for each year over the forecast horizon based on an output template. In case of a capital shortfall, firms calculated the recapitalization needs. Firms reported the major risk drivers (profitability, credit/trading losses, RWAs) and showed the impact of including (i) haircuts on sovereign debt holdings, and (ii) capital phase-in/phase-out according to Basel III	Basel III (Common Equity Tier 1, Tier 1, Total Capital, plus conservation buffer) for each year of the risk horizon. Staff determined capital adequacy for each year over the forecast horizon. In case of a capital shortfall, recapitalization needs were calculated. The major risk drivers (profitability, haircuts on sovereign debt holdings, capital phase-in/phase-out and increases of RWAs according to Basel III) were identified.		Basel III (Common Equity Tier 1, Tier 1, Total Capital, plus conservation buffer) for each year of the risk horizon.

Table 3.

Hong Kong SAR: Stress Test Matrix (STeM) for the Banking Sector—Solvency

Domain		Assumptions
Domain		Bottom-up by Banks (with guidelines by FSAP Team)	Top-down by FSAP Team (balance sheet-based)	Top-down by HKMA (balance sheet-based)	Top-down by FSAP Team (market-based, ‘Systemic CCA’)
BANKING SECTOR: SOLVENCY RISK
1. Institutional Perimeter	Institutions included	Selected local banks.	All large locally incorporated licensed banks (16), excluding those which are subsidiaries of another licensed bank.	All large locally incorporated licensed banks (19).	9 publicly listed, locally incorporated licensed banks.
	Market share	About 50 percent of total banking sector assets on a consolidated basis (as of end-June 2013).	63.0 percent of total banking sector assets on a consolidated basis (as of end-June 2013).	58.0 percent of total banking sector assets on a combined basis (as of end-June 2013).	53.8 percent of total banking sector assets on a consolidated basis (as of end-June 2013).
	Data and baseline date	Source: institutions’ own granular data. Date: end-June 2013 (projected to end-2013). Scope: consolidated banking group.	Source: institutions’ own granular data. Date: end-June 2013 (projected to end-2013). Scope: consolidated banking group.	Source: supervisory data. Date: end-June 2013 (projected to end-2013). Scope: combined basis.	Source: institutions’ own granular data and capital market data. Scope: consolidated banking group.
2. Channels of Risk Propagation	Measurement Satellite Models for Macro-Financial linkages	Banks’ internal models BU guidance (IMF, 2011a, 2012a and 2013b). Valuation haircut model for sovereign risk (Jobst and others, forthcoming; IMF, 2013b). Macro-financial linkages estimated based on firm’s internal models to forecast the profitability components (interest income, interest expenses, fee/commissions income, trading income and operating expenses) as well as the flow of asset impairments and charge-offs; each material loan category includes an increase of loss-givendefaults (LGDs) under stress according to the increase of default risk (PD), after controlling down-cycle LGDs that are based on a long-term average, i.e., “through the cycle.” Key macroeconomic and financial variables include GDP (nominal and real), household income, unemployment, inflation, interest rates/asset swap rates (short-term and long-term), equity prices, commercial property price index, real estate price index, and credit growth, and were projected using the HKMA’s macro model and IMF staff estimates based on G20MOD model⁴⁰. Cross-border effects are considered in all macro scenarios: IMF staff provided estimates for real GDP growth rates consistent with the macroeconomic forecast for HKSAR under both baseline and adverse scenarios for all relevant countries (Mainland China, Australia, France, Germany, India, Japan, South Korea, Singapore, the United Kingdom, and the United States) Sovereign risk assessed by applying valuation haircuts on all direct and indirect net exposures to sovereign risk (including home country) and financial bonds (i.e., bonded debt issued by financial institutions) in trading book as well as available-for-sale (AfS) and hold-to-maturity (HtM) assets over the entire time horizon; cash at central banks as well as repos or asset swaps where there is no economic interest in the security (for instance, instruments held against assets pledged to the HKMA) are excluded.	Balance sheet-based model (IMF, 2010, 2011 and 2012). Valuation haircut model for sovereign risk (Jobst and others, forthcoming; IMF, 2013b). Macro-financial linkages estimated based on dynamic 2SLS panel data regression (using GMM with orthogonal deviations over quarterly observations between 1996: Q1 and 2013: Q2) to forecast the profitability components (interest income, interest expenses, fee/ commissions income, and operating expenses) as well as the flow of asset impairments and charge-offs; each material loan category includes an increase of LGDs under stress according to the increase of default risk (PD), after controlling down-cycle LGDs that are based on a long-term average, i.e., “through the cycle”; the change in trading income was mapped to nominal GDP growth Key macroeconomic and financial variables include GDP (nominal and real), household income, unemployment, inflation, interest rates/asset swap rates (short-term and long-term), equity prices, commercial property price index, real estate price index, and credit growth, and were projected using the HKMA’s macro model and IMF staff estimates based on G20MOD model. Cross-border effects are considered in all macro scenarios: IMF staff provided estimates for real GDP growth rates consistent with the macroeconomic forecast for HKSAR under both baseline and adverse scenarios for all relevant countries (Mainland China, Australia, France, Germany, India, Japan, South Korea, Singapore, the United Kingdom, and the United States). Sovereign risk assessed by applying valuation haircuts on all direct and indirect net exposures to sovereign risk (including home country) and financial bonds (i.e., bonded debt issued by financial institutions) in trading book as well as AfS and HtM assets over the entire time horizon; cash at central banks as well as repos or asset swaps where there is no economic interest in the security (for instance, instruments held against assets pledged to the HKMA) are excluded; assumption of exposureweighted average duration of three years	Balance sheet-based model (HKMA, 2013). Macro-financial linkages estimated for asset impairments/charge-offs for certain loan categories (“Nonbank Mainland China Exposures (NBMCE)”, other loans (excl. residential mortgages, property investment loans, and credit card lending), and off-balance sheet credit exposures derived from their historical sensitivity to changes in real GDP at specified statistical confidence level; other shocks to default probabilities (for stock-related lending, credit card lending, off-balance sheet derivatives exposures, debt securities) and asset prices by means of statistical mapping to specified historical severity (90^th or 99^th percentile); expert judgment on other risk factors (interest rate shocks, floors on asset impairments/charge-offs, procyclical impact on credit RWA). Aggregation of single factor shocks. Key macroeconomic and financial variables included real GDP for HKSAR and Mainland China, interest rates, equity prices, commercial and residential property price index. Cross-border effects are considered in relation to Mainland China: real GDP growth rate for Mainland China is incorporated in projections of loan losses. Sovereign risk assessed as part of the general credit risk shock to debt securities (securitized and non-securitized).	Systemic CCA model (Gray and Jobst, 2010; Jobst and Gray, 2013). Valuation haircut model for sovereign risk (Jobst and others, forthcoming; IMF, 2013b). Macro-financial linkages estimated based on dynamic 2SLS panel data regression (→ other TD test by FSAP team) Key macroeconomic and financial variables include GDP (nominal and real), household income, unemployment, inflation, interest rates/asset swap rates (short-term and long-term), equity prices, commercial property price index, and real estate price index, and were projected using the HKMA’s macro model and IMF staff estimates based on G20MOD model. Cross-border effects are not explicitly considered in any macro scenario but are implicit in estimated dependence between market-implied expected losses and their impact on capital adequacy.
	Stress test horizon	2014–2018 (five years).	2014–2018 (five years).	2014–2015 (two years) but single-period set-up.	2014–2018 (five years).
3. Tail Shocks	Scenario analysis	Three different macroeconomic scenarios: (i) a baseline scenario with projections in line with the World Economic Outlook (April 2013); (ii) a “slow growth” scenario, underpinned by a broad-based slowdown of global growth triggered by markets’ accelerated view on the pace of tightening in U.S. monetary policy; and (iii) a “severe adverse” scenario, where the contraction of economic activity (ii) is further aggravated by a severe intensification of capital outflows in emerging market countries, impacting Hong Kong’s major trading partners. Under the two adverse scenarios, economic growth in HKSAR deteriorates to 2.6 and 2.0 percent on average relative to baseline expectations of average annual growth of 4.4 percent (which is slightly above the long-term (30-year) annual growth rate of 4.1 percent). Overall, the magnitude of these shocks—at cumulative negative deviations of about 9.1 and 12.1 percentage points in real GDP, which equate to about 1.6 and 2.1 standard deviations of the average cumulative two-year growth rate over the last 30 years, respectively—is in line with the spectrum of economic adversity considered in the context of other stress testing exercises.		Three different macroeconomic scenarios: (i) a baseline scenario with projections and risk parameters in line with those used for the TD solvency by the FSAP team, (ii) Scenario A (“Severe”), and (iii) Scenario B (“More Severe”), which include single factor shocks to credit losses, market risk (interest rates, equity prices), profitability (net interest income and non-interest income), asset risk-weighting, and interest in land & buildings at the 90 percent (Scenario A) and 99 percent (Scenario B) statistical confidence levels (Table 6).	Same three macroeconomic scenarios as for the BU and TD tests (→ other TD test by FSAP team).
	Sensitivity analysis	FX shock: shock to FX net open positions (both through the P&L and on RWAs): Chinese renminbi, euro, Japanese yen, pound sterling, Singapore dollar, and other material currencies for the firm vis-à-vis the U.S. dollar; for each currency should be four times the maximum deviation of the annualized FX volatility during the 2008-11 period from the long-term FX volatility (>10 years) for the adverse scenarios (not baseline) and impact the trading book in 2014 (100 percent) and 2015 (50 percent) only.		RWAs increase not only for derivatives but all credit risk-sensitive exposures.	Variability of statistical confidence level of risk measure. Quantification of contribution of individual banks to systemic risk
4. Risk Factors	Risks/factors assessed	Credit risk (households and corporates, domestic and foreign exposures, local currency and FX). Counterparty risk of off-balance sheet exposures in the banking book.⁴¹ Sovereign risk of all government bonds, indirect sovereign exposure as well as all financial bonds. Funding risk (additional add-on to interest expenses, contingent on Tier 1 capitalization). Market risk: interest rates and FX. Tax rate: 16.5 percent.		Credit risk (loans and advances (incl. NBMCE, residential mortgages and property investment loans, credit card lending, stock-related lending, other loans, off-balance sheet exposures) and debt securities (non-securitization/securitization). Market risk: interest rates and equity prices.	Same three macroeconomic scenarios as for the BU and TD tests (→ other TD test by FSAP team).
	Balance sheet assumption	Static balance sheet with constant credit growth (i.e., lending and funding increases in line with nominal GDP (if positive)) without changes in the funding structure, subject to a “deleveraging rule” (i.e., credit growth decreases by 2 percentage points for each decrease in Tier 1 capital by 1 percentage point once the buffer is less than 2.5 percentage points; no asset disposals/divestments after cut-off date; defaulted loans are not replenished.		Static balance sheet without any adjustments.	Static balance sheet without any adjustments.
	Treatment of Dividends	Dividend payout is limited if the firm reports profits over the past year (and exhibits sufficient Tier 1 capitalization) but falls below 10.5 percent (which reflects the magnitude of the CAR and “capital conservation buffer” under Basel III); however, firms that are not capital constrained will have to pay out at least 40 percent of earnings after tax each year.	Dividend payout is limited if the firm reports profits over the past year (and exhibits sufficient Tier 1 capitalization) but CAR falls below a certain threshold (which reflects the average Pillar 2 minimum CAR requirement imposed by the HKMA on the local banks under Basel III and the historical capital buffer of local banks over that requirement (3.2 percent)). Firms that are not capital constrained will have to pay out at least 45 percent of earnings after tax each year. The payout ratio declines by 10 percentage points for each 0.5 percentage point decline in the capital buffer; 100 percent retention if capital buffer is lower than the threshold.		Dividend payout: discounted from the current share price when deriving implied asset values.
5. Regulatory and Market-based Standards and Parameters	Calibration of risk parameters	PDs and LGDs: internal models for point-in time-PDs and down-cycle LGDs (or adjustment to long-term average LGDs); in absence of an internal model, LGDs increase under stress according to the following specification: LGD(under stress)=0.3502+2.3408*PD. In case of over-collateralization (or supervisory LGDs below the intercept value), the increase of LGDs is limited to the trend coefficient (beta) of the LGD elasticity to PDs, which allows banks to calibrate the LGD at the starting point to their own LGD estimate. RWAs were estimated in accordance with IRB method under Basel III using through-the-cycle PDs, plus adjustments for loan portfolio concentration and changes in default risk.	PDs and LGDs: PDs (not LGDs) change over time; through-the-cycle PDs based on prudential data and stressed PDs based on the change in the stock of NPLs (via satellite model) while provisioning levels at the start of the forecast horizon are maintained. RWAs were estimated in accordance with AIRB method under Basel III, plus adjustments for loan portfolio concentration and changes in default risk (i.e., RWAs for credit risk are reduced by the RWAs of defaulted exposures, which are assumed to be 2.5 times the average RWAs for non-defaulted exposures (accounting for the fact that risk-weights for defaulted exposures were higher prior to default)).	Credit loss rates, PDs and LGDs: change in response to shock (either based on estimated sensitivity to macro-financial variables (in the case of NBMCE, residential mortgages, property investment loans, and other loans) or historical loss at specified statistical confidence level (for credit card lending, stock related lending, debt securities)). RWAs for derivatives remain constant under the baseline scenario but increase by 30 and 50 percent under the “severe” and “more severe” scenario, respectively. Increase in IRB credit RWAs based on IRB banks’ historical data and stress test estimates, external data and internal analysis.	Market-implied expected losses (with endogenously determined PD and LGD) inform the amount of capital shortfall (if any) for each firm and jointly for the entire sample.
	Regulatory/Accounting and Market-based Standards	Full Basel III transition schedule. Capital definition according to the Basel III framework; includes phase-in of capital deductions and the phase-out of non-eligible forms of capital, without consideration of grandfathering, during the forecast horizon: Phase-in of adjustments to common CET1 capital: reduction of CET1 capital (such as goodwill, deferred tax assets and minority interests that exceed the permissible limit) deducted at a rate of 20 percent p.a. between 2014 and 2018; in the BU exercise, firms must document deductions if the total amount is less than 20.1 percent (which is the average value for Group 2 (small banks) according to the results from the latest Basel III monitoring exercise as of 30 June 2012 (BCBS, 2013b)). Phase-out of non-Tier 1 and Tier 2 capital elements: the higher of either (i) 10 percent (per annum) of the amount of capital to be phased-out based on results of the quantitative impact study (QIS) (BCBS, 2010) at 16.6 percent (≈1.7 percent p.a.) or (ii) the amount of capital maturing each year of the stress test horizon between 2014 and 2018 (BCBS, 2010a). RWAs: RWAs for operational risk remain constant throughout the forecast period. RWAs for credit risk and market risk are sensitive to the regulatory impact due to Basel III based on firm’s own data; in addition, credit RWAs are subject to the Basel I floor and sensitive both changes in PDs and portfolio concentration: (a) nonlinear effect of changes in PDs and (b) concentration risk impact on RWAs. RWA impact of defaulted loans: The risk-weights for credit risk are subsequently reduced by the RWAs of defaulted exposures, which are calculated by banks’ internal models or approximated by taking 2.5 times the average RWAs for non-defaulted exposures (accounting for the fact that risk-weights for defaulted exposures were higher prior to default).		Basel III hurdle rate for 2015. Capital definition according to the Basel III framework, including phase-in of adjustments to common CET1 capital and phase-out of non-eligible forms of capital, without consideration of grandfathering, during the forecast horizon (same as “Bottom-up by Banks”). RWAs: RWAs for operational and market risk remain constant throughout the forecast period. RWAs for credit risk are sensitive to the regulatory impact due to Basel III and are subject to the Basel I floor. RWA impact of defaulted loans: no replenishment of loan portfolio. Risk-weighted assets (RWAs): RWAs for market and operational risk remain constant throughout the forecast period. RWAs for credit risk change due to higher PD and LGD for the major asset classes under the IRB approach, and the counterparty risk valuation of OTC derivatives and Regulatory impact due to Basel III based on HKMA’s own data.	Full Basel III transition schedule. Capital definition according to the Basel III framework. RWAs: not applicable; however, under the concept of market-implied capital adequacy (MCAR) of the Systemic CCA model, the implied asset value of a firm corresponds to Pillar 1 RWAs.
6. Reporting Format for Results	Output presentation	Basel III (Common Equity Tier 1, Tier 1, Total Capital, plus conservation buffer) for each year of the risk horizon. Firms reported capital adequacy for each year over the forecast horizon based on an output template. In case of a capital shortfall, firms calculated the recapitalization needs. Firms reported the major risk drivers (profitability, credit/trading losses, RWAs) and showed the impact of including (i) haircuts on sovereign debt holdings, and (ii) capital phase-in/phase-out according to Basel III	Basel III (Common Equity Tier 1, Tier 1, Total Capital, plus conservation buffer) for each year of the risk horizon. Staff determined capital adequacy for each year over the forecast horizon. In case of a capital shortfall, recapitalization needs were calculated. The major risk drivers (profitability, haircuts on sovereign debt holdings, capital phase-in/phase-out and increases of RWAs according to Basel III) were identified.		Basel III (Common Equity Tier 1, Tier 1, Total Capital, plus conservation buffer) for each year of the risk horizon.

Table 4.

Hong Kong SAR: Financial Soundness Indicators of the Banking Sector, 2007–13

(In percent unless otherwise indicated)

Sources: Bankscope, HKMA and IMF staff calculations.Notes:

^{^1/}Calculated for all authorized institutions on HK office basis, unless otherwise indicated.

^{^2/}Locally incorporated authorized institutions.

^{^3/}HK office basis.

^{^4/}Consolidated basis. The “combined basis” of a bank means the position of the bank’s Hong Kong office plus its overseas branches, while the “consolidated basis” covers the combined basis plus the bank’s subsidiaries.

^{^5/}Combined basis. The “combined basis” of a bank means the position of the bank’s Hong Kong office plus its overseas branches

^{^6/}In percent of total customer deposits. Calculated for licensed banks.

^{^7/}Calculated for Hong Kong’s four largest banks on consolidated basis

^{^8/}All authorized institutions

^{^9/}WEO data was used for 2013H1 Hong Kong GDP data.

Table 4.

Hong Kong SAR: Financial Soundness Indicators of the Banking Sector, 2007–13

(In percent unless otherwise indicated)

						2007	2008	2009	2010	2011	2012	2013H1
Earnings and profitability ^1/
	Return on average assets					1.4	0.6	0.8	0.9	0.8	0.9	1.2
	Return on average equity ^2/					23.2	13.4	15.4	15.2	15.8	15.3	15.1
	Interest margin to gross income					42.8	57.5	47.7	44.0	45.2	47.9	44.2
		Interest margin ^7/				2.1	2.1	1.6	1.5	1.7	1.9	1.8
			Average yield on assets			5.0	3.7	2.2	2.0	2.4	2.6	2.5
			Average cost of funding			3.0	1.7	0.6	0.6	0.7	0.7	0.6
	Noninterest income to gross income					57.4	46.4	52.8	56.7	55.4	52.9	56.3
		Of which: Net fee and commission income ^7/				59.5	53.3	44.4	44.1	48.5	46.3	27.4
	Noninterest expenses to gross income					46.1	55.7	57.5	57.1	54.8	54.1	46.1
	Cost/income ratio					46.7	55.6	58.0	58.1	55.4	54.8	46.5
Structure of assets ^1/
	Total assets (in percent of GDP) ^9/					627.0	629.8	641.0	691.7	709.8	727.7	704.8
		Of which (in percent of total assets):
			Loans to credit institutions			43.6	37.4	35.3	33.7	32.5	29.6	26.2
			Loans to customers			28.6	30.6	30.9	34.4	37.0	37.5	39.9
				Of which (in percent of total loans):
					Residential real estate loans	19.0	18.0	19.7	17.6	15.8	15.7	14.8
					Commercial real estate loans	7.6	8.0	8.1	7.0	6.8	6.6	6.4
					FX loans	26.2	28.3	27.0	33.2	37.8	40.1	42.8
					Note: FX liabilities (in percent of total liabilities)	55.0	59.6	56.0	59.0	61.1	59.7	60.7
				Debt securities		17.2	17.8	23.1	22.5	21.3	21.7	23.1
				Equity instruments		1.3	0.9	1.1	1.1	0.9	1.1	1.1
				Other assets		9.2	13.3	9.6	8.4	8.3	10.2	9.7
Funding and liquidity (in percent of total assets) ^1/
	Debts to credit institutions					28.6	27.4	27.1	30.0	29.3	26.7	26.0
	Bank bonds and other debt securities					2.8	1.9	1.2	1.9	3.4	5.1	5.8
	Customer deposits					56.7	56.3	60.0	55.8	55.2	55.8	55.5
		Of which: Demand deposits ^6/				7.9	7.9	11.1	11.7	11.6	13.2	13.3
			Saving deposits			27.9	32.3	42.5	42.6	38.4	41.0	39.7
			Time deposits			64.2	59.8	46.4	45.8	50.0	45.8	47.0
	Liquid assets					29.6	25.9	28.5	24.2	22.3	23.6	21.6
	Liquid assets to short term liabilities					53.5	49.9	50.1	43.0	44.0	46.4	43.4
	Net open position in foreign exchange to capital ^2/^3/					5.6	7.8	5.6	3.1	2.5	6.6	3.5
Asset quality
	Sectoral distribution of loans (in percent of total loans) ^2/^3/
		HK financial corporations				9.1	8.9	6.0	6.0	5.6	5.3	5.3
		HK nonfinancial corporations				64.4	64.9	66.1	63.9	60.8	59.5	60.3
		HK other domestic sector				9.4	8.6	8.3	7.3	6.6	6.7	6.4
		Non-residents				17.0	17.5	19.5	22.8	27.0	28.5	28.0
	Non-performing loans (NPL) as percent of gross loans ^5/^8/					0.7	1.2	1.6	0.8	0.7	0.6	0.5
	Provisions as percent of NPL ^7/					60	73	63	28	23	27	-
	NPL net of provisions as percent of capital ^2/^5/					2.8	3.8	3.6	1.9	1.6	1.4	1.5
Capital adequacy
	Regulatory capital to risk-weighted assets ^2/^4/					13.4	14.7	16.8	15.8	15.8	15.7	15.9
	Regulatory Tier 1 capital to risk-weighted assets ^2/^4/					10.4	11.0	12.9	12.2	12.4	13.3	13.1
	Capital to assets ^2/^5/					8.5	7.5	8.8	8.6	8.1	8.7	8.8

Sources: Bankscope, HKMA and IMF staff calculations.Notes:

^{^1/}Calculated for all authorized institutions on HK office basis, unless otherwise indicated.

^{^2/}Locally incorporated authorized institutions.

^{^3/}HK office basis.

^{^5/}Combined basis. The “combined basis” of a bank means the position of the bank’s Hong Kong office plus its overseas branches

^{^6/}In percent of total customer deposits. Calculated for licensed banks.

^{^7/}Calculated for Hong Kong’s four largest banks on consolidated basis

^{^8/}All authorized institutions

^{^9/}WEO data was used for 2013H1 Hong Kong GDP data.

Table 4.

Hong Kong SAR: Financial Soundness Indicators of the Banking Sector, 2007–13

(In percent unless otherwise indicated)

						2007	2008	2009	2010	2011	2012	2013H1
Earnings and profitability ^1/
	Return on average assets					1.4	0.6	0.8	0.9	0.8	0.9	1.2
	Return on average equity ^2/					23.2	13.4	15.4	15.2	15.8	15.3	15.1
	Interest margin to gross income					42.8	57.5	47.7	44.0	45.2	47.9	44.2
		Interest margin ^7/				2.1	2.1	1.6	1.5	1.7	1.9	1.8
			Average yield on assets			5.0	3.7	2.2	2.0	2.4	2.6	2.5
			Average cost of funding			3.0	1.7	0.6	0.6	0.7	0.7	0.6
	Noninterest income to gross income					57.4	46.4	52.8	56.7	55.4	52.9	56.3
		Of which: Net fee and commission income ^7/				59.5	53.3	44.4	44.1	48.5	46.3	27.4
	Noninterest expenses to gross income					46.1	55.7	57.5	57.1	54.8	54.1	46.1
	Cost/income ratio					46.7	55.6	58.0	58.1	55.4	54.8	46.5
Structure of assets ^1/
	Total assets (in percent of GDP) ^9/					627.0	629.8	641.0	691.7	709.8	727.7	704.8
		Of which (in percent of total assets):
			Loans to credit institutions			43.6	37.4	35.3	33.7	32.5	29.6	26.2
			Loans to customers			28.6	30.6	30.9	34.4	37.0	37.5	39.9
				Of which (in percent of total loans):
					Residential real estate loans	19.0	18.0	19.7	17.6	15.8	15.7	14.8
					Commercial real estate loans	7.6	8.0	8.1	7.0	6.8	6.6	6.4
					FX loans	26.2	28.3	27.0	33.2	37.8	40.1	42.8
					Note: FX liabilities (in percent of total liabilities)	55.0	59.6	56.0	59.0	61.1	59.7	60.7
				Debt securities		17.2	17.8	23.1	22.5	21.3	21.7	23.1
				Equity instruments		1.3	0.9	1.1	1.1	0.9	1.1	1.1
				Other assets		9.2	13.3	9.6	8.4	8.3	10.2	9.7
Funding and liquidity (in percent of total assets) ^1/
	Debts to credit institutions					28.6	27.4	27.1	30.0	29.3	26.7	26.0
	Bank bonds and other debt securities					2.8	1.9	1.2	1.9	3.4	5.1	5.8
	Customer deposits					56.7	56.3	60.0	55.8	55.2	55.8	55.5
		Of which: Demand deposits ^6/				7.9	7.9	11.1	11.7	11.6	13.2	13.3
			Saving deposits			27.9	32.3	42.5	42.6	38.4	41.0	39.7
			Time deposits			64.2	59.8	46.4	45.8	50.0	45.8	47.0
	Liquid assets					29.6	25.9	28.5	24.2	22.3	23.6	21.6
	Liquid assets to short term liabilities					53.5	49.9	50.1	43.0	44.0	46.4	43.4
	Net open position in foreign exchange to capital ^2/^3/					5.6	7.8	5.6	3.1	2.5	6.6	3.5
Asset quality
	Sectoral distribution of loans (in percent of total loans) ^2/^3/
		HK financial corporations				9.1	8.9	6.0	6.0	5.6	5.3	5.3
		HK nonfinancial corporations				64.4	64.9	66.1	63.9	60.8	59.5	60.3
		HK other domestic sector				9.4	8.6	8.3	7.3	6.6	6.7	6.4
		Non-residents				17.0	17.5	19.5	22.8	27.0	28.5	28.0
	Non-performing loans (NPL) as percent of gross loans ^5/^8/					0.7	1.2	1.6	0.8	0.7	0.6	0.5
	Provisions as percent of NPL ^7/					60	73	63	28	23	27	-
	NPL net of provisions as percent of capital ^2/^5/					2.8	3.8	3.6	1.9	1.6	1.4	1.5
Capital adequacy
	Regulatory capital to risk-weighted assets ^2/^4/					13.4	14.7	16.8	15.8	15.8	15.7	15.9
	Regulatory Tier 1 capital to risk-weighted assets ^2/^4/					10.4	11.0	12.9	12.2	12.4	13.3	13.1
	Capital to assets ^2/^5/					8.5	7.5	8.8	8.6	8.1	8.7	8.8

Sources: Bankscope, HKMA and IMF staff calculations.Notes:

^{^1/}Calculated for all authorized institutions on HK office basis, unless otherwise indicated.

^{^2/}Locally incorporated authorized institutions.

^{^3/}HK office basis.

^{^5/}Combined basis. The “combined basis” of a bank means the position of the bank’s Hong Kong office plus its overseas branches

^{^6/}In percent of total customer deposits. Calculated for licensed banks.

^{^7/}Calculated for Hong Kong’s four largest banks on consolidated basis

^{^8/}All authorized institutions

^{^9/}WEO data was used for 2013H1 Hong Kong GDP data.

Table 5.

Hong Kong SAR: Economic Activity under Different Scenarios

(annual percentage change, unless otherwise indicated)

Sources: HKMA and IMF staff estimates and calculations. Note: Interest rates shown for 2013 above are recorded as of end-June 2013.

Table 5.

Hong Kong SAR: Economic Activity under Different Scenarios

(annual percentage change, unless otherwise indicated)

			Baseline Scenario						Slow Growth (SG) Scenario					Severe Adverse (SA) Scenario
			2013 (est.)	2014	2015	2016	2017	2018	2014	2015	2016	2017	2018	2014	2015	2016	2017	2018
Economic activity and labor market
	Real GDP		2.96	4.39	4.37	4.46	4.46	4.51	1.78	2.66	2.70	2.99	2.95	1.32	0.63	2.38	2.91	2.84
	Nominal household income		4.49	4.67	5.13	4.56	4.69	4.82	1.53	2.62	2.33	1.82	2.06	0.88	0.14	1.38	1.33	1.48
	Unemployment rate (% of labor force)		3.30	3.46	3.57	3.70	3.82	3.84	4.15	4.78	5.54	6.18	6.75	4.32	5.54	6.43	7.09	7.69
Price and cost developments
	Consumption prices (average CPI)		3.95	3.67	3.57	3.54	3.53	3.53	3.09	2.21	1.81	1.65	1.58	3.04	1.59	0.82	0.91	1.05
	Residential house prices		7.97	−1.68	−0.70	−1.20	−1.49	3.28	−9.54	−6.10	−6.51	−6.24	−1.84	−11.97	−12.58	−7.06	−5.98	−1.97
	Commercial real estate prices		−1.15	−9.35	−0.26	2.03	1.98	7.95	−17.05	−7.19	−4.99	−3.69	1.20	−19.26	−14.47	−6.96	−3.47	1.02
	Equity market index (Hang Seng index)		7.00	8.06	7.94	8.00	8.00	8.04	−13.95	−9.13	−9.39	−7.89	−8.32	−16.42	−20.00	−11.13	−8.28	−8.89
Interest rates
	3-month U.S. Treasury rate		0.10	0.17	0.13	0.26	0.46	0.57	0.10	0.20	0.90	2.10	3.10	0.35	0.53	1.23	2.43	3.90
	Time deposit rate (%)		0.15	0.22	0.18	0.31	0.51	0.62	0.15	0.25	0.95	2.15	3.15	0.40	0.58	1.28	2.48	3.95
	3-month HIBOR rate (%)		0.38	0.41	0.51	0.62	0.72	0.82	0.66	1.10	2.24	3.39	4.53	0.66	1.10	2.24	3.39	4.53
	12-month HIBOR rate (%)		0.87	1.00	1.10	1.20	1.30	1.40	1.25	1.68	2.84	3.99	5.15	1.25	1.68	2.84	3.99	5.15
	Best lending rate (%)		5.00	5.00	5.10	5.20	5.30	5.40	5.20	5.57	5.94	6.31	6.68	5.12	5.41	5.71	6.00	6.30
	Memo item
		Real GDP (P.R. China)	7.80	7.70	7.60	7.50	7.50	7.50	5.60	5.52	6.96	7.50	7.44	5.23	3.73	6.32	7.32	7.27

Sources: HKMA and IMF staff estimates and calculations. Note: Interest rates shown for 2013 above are recorded as of end-June 2013.

Table 5.

Hong Kong SAR: Economic Activity under Different Scenarios

(annual percentage change, unless otherwise indicated)

			Baseline Scenario						Slow Growth (SG) Scenario					Severe Adverse (SA) Scenario
			2013 (est.)	2014	2015	2016	2017	2018	2014	2015	2016	2017	2018	2014	2015	2016	2017	2018
Economic activity and labor market
	Real GDP		2.96	4.39	4.37	4.46	4.46	4.51	1.78	2.66	2.70	2.99	2.95	1.32	0.63	2.38	2.91	2.84
	Nominal household income		4.49	4.67	5.13	4.56	4.69	4.82	1.53	2.62	2.33	1.82	2.06	0.88	0.14	1.38	1.33	1.48
	Unemployment rate (% of labor force)		3.30	3.46	3.57	3.70	3.82	3.84	4.15	4.78	5.54	6.18	6.75	4.32	5.54	6.43	7.09	7.69
Price and cost developments
	Consumption prices (average CPI)		3.95	3.67	3.57	3.54	3.53	3.53	3.09	2.21	1.81	1.65	1.58	3.04	1.59	0.82	0.91	1.05
	Residential house prices		7.97	−1.68	−0.70	−1.20	−1.49	3.28	−9.54	−6.10	−6.51	−6.24	−1.84	−11.97	−12.58	−7.06	−5.98	−1.97
	Commercial real estate prices		−1.15	−9.35	−0.26	2.03	1.98	7.95	−17.05	−7.19	−4.99	−3.69	1.20	−19.26	−14.47	−6.96	−3.47	1.02
	Equity market index (Hang Seng index)		7.00	8.06	7.94	8.00	8.00	8.04	−13.95	−9.13	−9.39	−7.89	−8.32	−16.42	−20.00	−11.13	−8.28	−8.89
Interest rates
	3-month U.S. Treasury rate		0.10	0.17	0.13	0.26	0.46	0.57	0.10	0.20	0.90	2.10	3.10	0.35	0.53	1.23	2.43	3.90
	Time deposit rate (%)		0.15	0.22	0.18	0.31	0.51	0.62	0.15	0.25	0.95	2.15	3.15	0.40	0.58	1.28	2.48	3.95
	3-month HIBOR rate (%)		0.38	0.41	0.51	0.62	0.72	0.82	0.66	1.10	2.24	3.39	4.53	0.66	1.10	2.24	3.39	4.53
	12-month HIBOR rate (%)		0.87	1.00	1.10	1.20	1.30	1.40	1.25	1.68	2.84	3.99	5.15	1.25	1.68	2.84	3.99	5.15
	Best lending rate (%)		5.00	5.00	5.10	5.20	5.30	5.40	5.20	5.57	5.94	6.31	6.68	5.12	5.41	5.71	6.00	6.30
	Memo item
		Real GDP (P.R. China)	7.80	7.70	7.60	7.50	7.50	7.50	5.60	5.52	6.96	7.50	7.44	5.23	3.73	6.32	7.32	7.27

Sources: HKMA and IMF staff estimates and calculations. Note: Interest rates shown for 2013 above are recorded as of end-June 2013.

Table 6.

Hong Kong SAR: HKMA Solvency Top-down Stress Test-Detailed Assumptions

(Scenario Analysis)

Table 6.

Hong Kong SAR: HKMA Solvency Top-down Stress Test-Detailed Assumptions

(Scenario Analysis)

		Scenario
		More severe	Severe	Baseline
Credit Risk
Non-bank Mainland China exposures		99% confidence level according to GDP-based model (with floor at 4.0%)	90% confidence level according to GDP-based model (with floor at 2.0%)	0.3% (according to GDP-based model with the baseline scenario same as IMF TD solvency test)
RML & property investment loans		1.24%	0.50%	0.01%
Other loans		99% confidence level according to GDP-based model (with floor at 3.0%)	90% confidence level according to GDP-based model (with floor at 1.8%)	0.17% (according to GDP-based model with the baseline scenario same as IMF TD solvency test)
Off-balance sheet exposures		drawdown rate of 20%; same loss rate as for “other loans”	drawdown rate of 15%; same loss rate as for “other loans”	drawdown rate of 10%; same loss rate as for “other loans”
Debt securities - securitization/non-securitization		99th percentile historical loss rate based on Moody’s data	90th percentile historical loss rate based on Moody’s data	latest available two-year loss rates provided by Moody’s reports
Credit card lending		99th percentile of individual banks’ historical loss (floor at 99th percentile of industry’s historical loss (20.9%))	90th percentile of individual banks’ historicalloss (floor at 90th percentile of industry’s historical loss (18.8°%))	50th percentile of individual banks’ historical loss
Stock-related exposures
	investment in listed shares	99th percentile of max drop in HSI within two yrs (-59.6%)	90th percentile of max drop in HSI within two yrs (-47.4%)	+16.64% (according to the baseline scenario same as IMF TD solvency test)
	IPO margin lending	3.00%	1.00%	0.0%
	Non-IPO margin lending	4.09%	1.55%	0.0%
	Other loans to stock brokers	99th percentile of individual banks’ historical loss (floor at 99th percentile of industry’s historical loss (3.5%))	90th percentile of individual banks’ historical loss (floor at 90th percentile of industry’s historical loss (2.0%))	50th percentile of individual banks’ historical loss
	Other loans to non-stock brokers	99th percentile of individual banks’ historical loss (floor at 99th percentile of industry’s historical loss (2.3%))	90th percentile of individual banks’ historical loss (floor at 90th percentile of industry’s historical loss (0.4%))	50th percentile of individual banks’ historical loss
Asset Prices
Property prices		−50%	−30%	−6% (according to the baseline scenario same as IMF TD solvency test)
HKD interest rate		Best lending rate: +400bps	Best lending rate: +200bps	Best lending rate: +10bps
		savings deposit rate: +400bps	savings deposit rate: +200bps	savings deposit rate: +0bps
		time deposit rate: +500bps	time deposit rate: +250bps	time deposit rate: +3bps
		HIBOR: +500bps	HIBOR: +250bps	HIBOR: +18bps (according to the baseline scenario same as IMF TD solvency test)
Profitability elements and other
Net interest income		the worse of ℒ5% or individual banks’ decrease in 97/98	the worse of ℒ3% or individual banks’ decrease in 97/98	Projected figures by individual banks
Non-interest income		the worse of ℒ20% or individual banks’ decrease in 97/98	the worse of ℒ10% or individual banks’ decrease in 97/98	Projected figures by individual banks
Procyclical effect		(IRB banks only) Overall credit RWA under IRB: ~ +35%	(IRB banks only) Overall credit RWA under IRB: ~ +25%	Increase of RWA for credit risk: +17% (according to the credit growth projection under the baseline scenario same as IMF TD solvency test)
Derivatives		RWA +50%	RWA +30%	RWA +0%
Dividend payout		Dividend payout is limited if the firm reports profits over the past year (and exhibits sufficient Tier 1 capitalization) but CAR falls below a certain threshold (which reflects the average Pillar 2 minimum CAR requirement imposed by the HKMA on the local banks under Basel III and the historical capital buffer of local banks over that requirement (3.2 percent)). Firms that are not capital constrained will have to pay out at least 45 percent of earnings after tax each year. The payout ratio declines by 10 percentage points for each 0.5 percentage point decline in the capital buffer; 100 percent retention if capital buffer is lower than the threshold.
Basel III capital definition (phase-in/phase-out)		according to reported values in line with Basel III transition schedule

Table 6.

Hong Kong SAR: HKMA Solvency Top-down Stress Test-Detailed Assumptions

(Scenario Analysis)

		Scenario
		More severe	Severe	Baseline
Credit Risk
Non-bank Mainland China exposures		99% confidence level according to GDP-based model (with floor at 4.0%)	90% confidence level according to GDP-based model (with floor at 2.0%)	0.3% (according to GDP-based model with the baseline scenario same as IMF TD solvency test)
RML & property investment loans		1.24%	0.50%	0.01%
Other loans		99% confidence level according to GDP-based model (with floor at 3.0%)	90% confidence level according to GDP-based model (with floor at 1.8%)	0.17% (according to GDP-based model with the baseline scenario same as IMF TD solvency test)
Off-balance sheet exposures		drawdown rate of 20%; same loss rate as for “other loans”	drawdown rate of 15%; same loss rate as for “other loans”	drawdown rate of 10%; same loss rate as for “other loans”
Debt securities - securitization/non-securitization		99th percentile historical loss rate based on Moody’s data	90th percentile historical loss rate based on Moody’s data	latest available two-year loss rates provided by Moody’s reports
Credit card lending		99th percentile of individual banks’ historical loss (floor at 99th percentile of industry’s historical loss (20.9%))	90th percentile of individual banks’ historicalloss (floor at 90th percentile of industry’s historical loss (18.8°%))	50th percentile of individual banks’ historical loss
Stock-related exposures
	investment in listed shares	99th percentile of max drop in HSI within two yrs (-59.6%)	90th percentile of max drop in HSI within two yrs (-47.4%)	+16.64% (according to the baseline scenario same as IMF TD solvency test)
	IPO margin lending	3.00%	1.00%	0.0%
	Non-IPO margin lending	4.09%	1.55%	0.0%
	Other loans to stock brokers	99th percentile of individual banks’ historical loss (floor at 99th percentile of industry’s historical loss (3.5%))	90th percentile of individual banks’ historical loss (floor at 90th percentile of industry’s historical loss (2.0%))	50th percentile of individual banks’ historical loss
	Other loans to non-stock brokers	99th percentile of individual banks’ historical loss (floor at 99th percentile of industry’s historical loss (2.3%))	90th percentile of individual banks’ historical loss (floor at 90th percentile of industry’s historical loss (0.4%))	50th percentile of individual banks’ historical loss
Asset Prices
Property prices		−50%	−30%	−6% (according to the baseline scenario same as IMF TD solvency test)
HKD interest rate		Best lending rate: +400bps	Best lending rate: +200bps	Best lending rate: +10bps
		savings deposit rate: +400bps	savings deposit rate: +200bps	savings deposit rate: +0bps
		time deposit rate: +500bps	time deposit rate: +250bps	time deposit rate: +3bps
		HIBOR: +500bps	HIBOR: +250bps	HIBOR: +18bps (according to the baseline scenario same as IMF TD solvency test)
Profitability elements and other
Net interest income		the worse of ℒ5% or individual banks’ decrease in 97/98	the worse of ℒ3% or individual banks’ decrease in 97/98	Projected figures by individual banks
Non-interest income		the worse of ℒ20% or individual banks’ decrease in 97/98	the worse of ℒ10% or individual banks’ decrease in 97/98	Projected figures by individual banks
Procyclical effect		(IRB banks only) Overall credit RWA under IRB: ~ +35%	(IRB banks only) Overall credit RWA under IRB: ~ +25%	Increase of RWA for credit risk: +17% (according to the credit growth projection under the baseline scenario same as IMF TD solvency test)
Derivatives		RWA +50%	RWA +30%	RWA +0%
Dividend payout		Dividend payout is limited if the firm reports profits over the past year (and exhibits sufficient Tier 1 capitalization) but CAR falls below a certain threshold (which reflects the average Pillar 2 minimum CAR requirement imposed by the HKMA on the local banks under Basel III and the historical capital buffer of local banks over that requirement (3.2 percent)). Firms that are not capital constrained will have to pay out at least 45 percent of earnings after tax each year. The payout ratio declines by 10 percentage points for each 0.5 percentage point decline in the capital buffer; 100 percent retention if capital buffer is lower than the threshold.
Basel III capital definition (phase-in/phase-out)		according to reported values in line with Basel III transition schedule

Table 7.

Hong Kong SAR: Liquidity Stress Test—Maturity Mismatch Analysis

Sources: HKMA and IMF staff estimates and calculations.

Table 7.

Hong Kong SAR: Liquidity Stress Test—Maturity Mismatch Analysis

		Maturity Mismatch
		(In percent of assets in each “maturity term bucket”)
Maturity tenor		less than 1 week	more than 1 week but less than 1 month	within 1-3 months	within 3-6 months	between 6-12 months	after 12 months
		Total Balance Sheet (All Currencies)
All sample firms (27)		—	10.59	12.1	13.0	20.5	67.7
	Local banks (Group 1) (19)	—	15.75	19.7	16.9	31.0	82.8
	Foreign branches (Group 2) (8)	—	—	—	—	—	—
		FX Balance Sheet
All sample firms (27)		0.81	13.97	14.4	5.7	11.3	15.6
	Local banks (Group 1) (19)	1.03	20.41	21.3	9.2	20.1	25.6
	Foreign branches (Group 2) (8)	—	—	—	—	—	—

Sources: HKMA and IMF staff estimates and calculations.

Table 7.

Hong Kong SAR: Liquidity Stress Test—Maturity Mismatch Analysis

		Maturity Mismatch
		(In percent of assets in each “maturity term bucket”)
Maturity tenor		less than 1 week	more than 1 week but less than 1 month	within 1-3 months	within 3-6 months	between 6-12 months	after 12 months
		Total Balance Sheet (All Currencies)
All sample firms (27)		—	10.59	12.1	13.0	20.5	67.7
	Local banks (Group 1) (19)	—	15.75	19.7	16.9	31.0	82.8
	Foreign branches (Group 2) (8)	—	—	—	—	—	—
		FX Balance Sheet
All sample firms (27)		0.81	13.97	14.4	5.7	11.3	15.6
	Local banks (Group 1) (19)	1.03	20.41	21.3	9.2	20.1	25.6
	Foreign branches (Group 2) (8)	—	—	—	—	—	—

Sources: HKMA and IMF staff estimates and calculations.

Table 8.

Hong Kong SAR: Systemic Contingent Claims Approach—Comparison of Total Assets for Locally Incorporated Licensed Banks (“Local Banks”) and Respective Listed Entities

(In millions of HKD, end-June 2013)

Sources: Bloomberg, Bankscope and IMF staff calculations.Notes: * The share of the locally incorporated bank (“local bank”) serves as scaling factor for the implied assets derived from the equity price and the implied equity volatility as inputs to the estimation of market-implied expected losses within the SCCA framework. A similar scaling is applied to adjusted liabilities as default barrier (Jobst and Gray, 2013). Note that the amount of total assets shown for HSBC as locally incorporated bank excludes Hang Seng Bank Ltd.

Table 8.

Hong Kong SAR: Systemic Contingent Claims Approach—Comparison of Total Assets for Locally Incorporated Licensed Banks (“Local Banks”) and Respective Listed Entities

(In millions of HKD, end-June 2013)

	Total assets of listed entity	Total assets of local bank	Share of local bank*
Bank of China (Hong Kong) Ltd.	17,116,824	1,764,584	10.3
Bank of East Asia, the Ltd.	697,433	697,433	100.0
Chong Hing Bank Ltd.	81,664	81,664	100.0
Fubon Bank (Hong Kong) Ltd.	1,122,118	68,029	6.1
Hang Seng Bank, Ltd.	1,106,657	1,106,657	100.0
HSBC Ltd.	20,518,393	4,874,703	23.8
Industrial and Commercial Bank of China (Asia) Ltd.	23,546,258	523,797	2.2
Standard Chartered Bank (Hong Kong) Ltd.	5,041,391	992,434	19.7
Wing Hang Bank, Ltd.	201,104	201,104	100.0

Table 8.

Hong Kong SAR: Systemic Contingent Claims Approach—Comparison of Total Assets for Locally Incorporated Licensed Banks (“Local Banks”) and Respective Listed Entities

(In millions of HKD, end-June 2013)

	Total assets of listed entity	Total assets of local bank	Share of local bank*
Bank of China (Hong Kong) Ltd.	17,116,824	1,764,584	10.3
Bank of East Asia, the Ltd.	697,433	697,433	100.0
Chong Hing Bank Ltd.	81,664	81,664	100.0
Fubon Bank (Hong Kong) Ltd.	1,122,118	68,029	6.1
Hang Seng Bank, Ltd.	1,106,657	1,106,657	100.0
HSBC Ltd.	20,518,393	4,874,703	23.8
Industrial and Commercial Bank of China (Asia) Ltd.	23,546,258	523,797	2.2
Standard Chartered Bank (Hong Kong) Ltd.	5,041,391	992,434	19.7
Wing Hang Bank, Ltd.	201,104	201,104	100.0

Table 9.

Hong Kong SAR: Overview of Sample Banks in the Solvency and Liquidity Stress Testing Exercise

(as of end-June 2013)

Sources: Banks’ disclosure statements, HKMA, and IMF staff calculations.Notes: The subsidiaries of HSBC and Bank of China in Group 1 are shown separately but are excluded from the reported sample coverage on a consolidated basis in order to avoid double-counting.

^{^1/}The “combined basis” of a bank means the position of the bank’s Hong Kong office plus its overseas branches, while the “consolidated basis” covers the combined basis plus the bank’s subsidiaries; reporting on a solo basis refers to the operations of the Hong Kong office only. The consolidated reporting of the TD stress test includes the banks marked (#) and (##) for subsidiaries of Bank of China (HK) and HSBC Ltd., respectively;

^{^2/}Based on Jobst and Gray (2013). Banks marked (*) are subject to an adjustment of their market-implied asset value/asset volatility as the equity price/equity volatility relates to the group-wide performance (which is dominated by activities outside HKSAR);

^{^3/}Apart from the ICF tests and solvency-liquidity linkage analysis, the Basel III standard liquidity measures (LCR and NSFR) are calculated for the purpose of analysing the banking sector’s liquidity conditions. It covers a selection of locally incorporated banks on a consolidated and/or combined basis, and foreign branches on a solo basis, which in aggregate accounts for about 60 percent of the banking sector in terms of total assets;

^{^4/}This part of the liquidity stress test includes approaches by both the HKMA and the IMF on a solo basis;

^{^5/}Banks liquidity conditions are tested on a consolidated basis using a pre-defined set of credit and market risk shocks affecting their solvency condition, based on Wong and Hui (2009). Bank of China’s consolidated reporting includes the two banks marked (#) while HSBC’s consolidated reporting for this test excludes Hang Seng Bank (##), which has been tested separately.

^{^6/}Foreign branches are also referred to as “non-locally incorporated, licensed banks”;

^{^7/}The number in parentheses indicates the number of firms in each category, which have been excluded from the stress test;

^{^8/}The 39 locally incorporated institutions comprise two locally incorporated licensed banks, 13 restricted license banks, and 24 deposit-taking companies. Since six deposit-taking companies are subsidiaries of the locally incorporated licensed banks in Group 1, these subsidiaries’ assets are removed from the total consolidated firms outside the scope of the stress test.

Table 9.

Hong Kong SAR: Overview of Sample Banks in the Solvency and Liquidity Stress Testing Exercise

(as of end-June 2013)

					SOLO BASIS			COMBINED BASIS			CONSOLIDATED BASIS			Basel II approach for credit risk (IRB or Standard) [Group 1]	Solvency			Liquidity ^3/
					TD IMF	TD HKMA	TD IMF	TD HKMA-IMF	TD HKMA
				Bank Name	TOTAL ASSETS (In million HKD)	% of peer group	% of banking sector	TOTAL ASSETS (In million HKD)	% of peer group	% of banking sector	TOTAL ASSETS (In million HKD)	% of peer group	% of banking sector		balance sheet-based, consolidated basis ^1/	balance sheet-based, combined basis ^1/	Systemic CCA, market-based ^2/	Implied Cash Flow ^4/	Solvency-Liquidity Linkage ^5/
Group 1: Locally incorporated, licensed banks (19)
		Hong Kong and Shanghai Banking Corporation (HSBC) Ltd.			—	—	—	—	—	—	5,981,060	51.1%	32.2%	IRB	x	x	x*	x	x
		Bank of China (Hong Kong) Limited			—	—	—	—	—	—	1,764,584	15.1%	9.5%	IRB	x	x	x*	x	x
			Hang Seng Bank Ltd. (→ HSBC)		—	—	—	—	—	—	1,106,657			IRB	x^##	x	x	x	x
		Standard Chartered Bank (Hong Kong) Ltd.			—	—	—	—	—	—	992,434	8.5%	5.3%	IRB	x	x	x*	x	x
		Bank of East Asia, Limited (The)			—	—	—	—	—	—	697,433	6.0%	3.8%	IRB	x	x	x	x	x
		Industrial and Commercial Bank of China (Asia) Ltd.			—	—	—	—	—	—	523,797	4.5%	2.8%	Std	x	x	x*	x	x
		DBS Bank (Hong Kong) Ltd.			—	—	—	—	—	—	296,400	2.5%	1.6%	IRB	x	x	—	x	x
			Nanyang Commercial Bank Ltd. {->Bank of China)		—	—	—	—	—	—	265,366			IRB	x	x	—	x	x
		China Construction Bank (Asia) Corporation Ltd.			—	—	—	—	—	—	220,489	1.9%	1.2%	Std	x	x	—	x	x
		Wing Lung Bank Ltd.			—	—	—	—	—	—	210,936	1.8%	1.1%	Std	x	x	—	x	x
		Wing Hang Bank Ltd.			—	—	—	—	—	—	201,104	1.7%	1.1%	Std	x	x	x	x	x
		China Citic Bank International Ltd.			—	—	—	—	—	—	186,196	1.6%	1.0%	Std	x	x	—	x	x
		Dah Sing Bank Ltd.			—	—	—	—	—	—	160,967	1.4%	0.9%	Std	x	x	—	x	x
		Citibank (Hong Kong) Ltd.			—	—	—	—	—	—	141,164	1.2%	0.8%	Std	x	x	—	x	x
		Shanghai Commercial Bank Ltd.			—	—	—	—	—	—	136,492	1.2%	0.7%	Std	x	x	—	x	x
		Chong Hing Bank Ltd.			—	—	—	—	—	—	81,664	0.7%	0.4%	Std	x	x	x	x	x
		Fubon Bank (Hong Kong) Ltd.			—	—	—	—	—	—	68,029	0.6%	0.4%	Std	x	x	x*	x	x
			Chiyu Banking Corporation Ltd. (→ Bank of China)		—	—	—	—	—	—	48,007			IRB	x	x	—	x	x
		Public Bank (Hong Kong) Ltd.			—	—	—	—	—	—	36,619	0.3%	0.2%	Std	x	x	−	x	x
Subtotal (w/o subsidiaries)					8,339,750	100.0%	54.7%	9,553,539	100.0%	58.0%	11,699,367	100.0%	63.0%		63.0%	58.0%	53.8%	54.7%	63.0%
Group 2: Foreign branches (8)^6/
	Bank of Communications Co. Ltd.				405,119.0	16.4%	2.7%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	China Construction Bank Corporation				367,521.2	14.9%	2.4%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Bank of Tokyo-Mitsubishi UFJ Ltd. (The)				330,882.8	13.4%	2.2%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Agricultural Bank of China Ltd.				327,630.6	13.3%	2.1%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Citibank, N.A.				308,902.6	12.5%	2.0%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Mizuho Corporate Bank Ltd.				292,372.3	11.9%	1.9%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Sumitomo Mitsui Banking Corporation				238,735.1	9.7%	1.6%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	BNP Paribas				194,553.8	7.9%	1.3%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
Subtotal					2,465,717	100.0%	16.2%	2,465,717	100.0%	15.0%	2,465,717	100.0%	13.3%		—	—	—	16.2%	—
Total sample					10,805,468	—	70.9%	12,019,257	—	73.0%	14,165,085	—	76.2%		63.0%	58.0%	53.8%	70.9%	63.0%
	Memo items
		Other ^7/
			Locally incorporated institutions (39)		131,042.1	3.0%	0.9%	131,042.1	3.0%	0.8%	106,458.9	2.4%	0.6%
			Foreign branches (133)		4,309,458.5	97.0%	28.3%	4,309,458.5	97.0%	26.2%	4,309,458.5	97.6%	23.2%
				− License banks (125)	4,275,284.4	96.3%	28.0%	4,275,284.4	96.3%	26.0%	4,275,284.4	96.8%	23.0%
				− Restricted license banks (⁸)	34,174.1	0.8%	0.2%	34,174.1	0.8%	0.2%	34,174.1	0.8%	0.2%
		Total system			15,245,968.1	100.0%	100.0%	16,459,757.2	100.0%	100.0%	18,581,002.3	100.0%	100.0%

^{^4/}This part of the liquidity stress test includes approaches by both the HKMA and the IMF on a solo basis;

^{^6/}Foreign branches are also referred to as “non-locally incorporated, licensed banks”;

^{^7/}The number in parentheses indicates the number of firms in each category, which have been excluded from the stress test;

Table 9.

Hong Kong SAR: Overview of Sample Banks in the Solvency and Liquidity Stress Testing Exercise

(as of end-June 2013)

					SOLO BASIS			COMBINED BASIS			CONSOLIDATED BASIS			Basel II approach for credit risk (IRB or Standard) [Group 1]	Solvency			Liquidity ^3/
					TD IMF	TD HKMA	TD IMF	TD HKMA-IMF	TD HKMA
				Bank Name	TOTAL ASSETS (In million HKD)	% of peer group	% of banking sector	TOTAL ASSETS (In million HKD)	% of peer group	% of banking sector	TOTAL ASSETS (In million HKD)	% of peer group	% of banking sector		balance sheet-based, consolidated basis ^1/	balance sheet-based, combined basis ^1/	Systemic CCA, market-based ^2/	Implied Cash Flow ^4/	Solvency-Liquidity Linkage ^5/
Group 1: Locally incorporated, licensed banks (19)
		Hong Kong and Shanghai Banking Corporation (HSBC) Ltd.			—	—	—	—	—	—	5,981,060	51.1%	32.2%	IRB	x	x	x*	x	x
		Bank of China (Hong Kong) Limited			—	—	—	—	—	—	1,764,584	15.1%	9.5%	IRB	x	x	x*	x	x
			Hang Seng Bank Ltd. (→ HSBC)		—	—	—	—	—	—	1,106,657			IRB	x^##	x	x	x	x
		Standard Chartered Bank (Hong Kong) Ltd.			—	—	—	—	—	—	992,434	8.5%	5.3%	IRB	x	x	x*	x	x
		Bank of East Asia, Limited (The)			—	—	—	—	—	—	697,433	6.0%	3.8%	IRB	x	x	x	x	x
		Industrial and Commercial Bank of China (Asia) Ltd.			—	—	—	—	—	—	523,797	4.5%	2.8%	Std	x	x	x*	x	x
		DBS Bank (Hong Kong) Ltd.			—	—	—	—	—	—	296,400	2.5%	1.6%	IRB	x	x	—	x	x
			Nanyang Commercial Bank Ltd. {->Bank of China)		—	—	—	—	—	—	265,366			IRB	x	x	—	x	x
		China Construction Bank (Asia) Corporation Ltd.			—	—	—	—	—	—	220,489	1.9%	1.2%	Std	x	x	—	x	x
		Wing Lung Bank Ltd.			—	—	—	—	—	—	210,936	1.8%	1.1%	Std	x	x	—	x	x
		Wing Hang Bank Ltd.			—	—	—	—	—	—	201,104	1.7%	1.1%	Std	x	x	x	x	x
		China Citic Bank International Ltd.			—	—	—	—	—	—	186,196	1.6%	1.0%	Std	x	x	—	x	x
		Dah Sing Bank Ltd.			—	—	—	—	—	—	160,967	1.4%	0.9%	Std	x	x	—	x	x
		Citibank (Hong Kong) Ltd.			—	—	—	—	—	—	141,164	1.2%	0.8%	Std	x	x	—	x	x
		Shanghai Commercial Bank Ltd.			—	—	—	—	—	—	136,492	1.2%	0.7%	Std	x	x	—	x	x
		Chong Hing Bank Ltd.			—	—	—	—	—	—	81,664	0.7%	0.4%	Std	x	x	x	x	x
		Fubon Bank (Hong Kong) Ltd.			—	—	—	—	—	—	68,029	0.6%	0.4%	Std	x	x	x*	x	x
			Chiyu Banking Corporation Ltd. (→ Bank of China)		—	—	—	—	—	—	48,007			IRB	x	x	—	x	x
		Public Bank (Hong Kong) Ltd.			—	—	—	—	—	—	36,619	0.3%	0.2%	Std	x	x	−	x	x
Subtotal (w/o subsidiaries)					8,339,750	100.0%	54.7%	9,553,539	100.0%	58.0%	11,699,367	100.0%	63.0%		63.0%	58.0%	53.8%	54.7%	63.0%
Group 2: Foreign branches (8)^6/
	Bank of Communications Co. Ltd.				405,119.0	16.4%	2.7%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	China Construction Bank Corporation				367,521.2	14.9%	2.4%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Bank of Tokyo-Mitsubishi UFJ Ltd. (The)				330,882.8	13.4%	2.2%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Agricultural Bank of China Ltd.				327,630.6	13.3%	2.1%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Citibank, N.A.				308,902.6	12.5%	2.0%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Mizuho Corporate Bank Ltd.				292,372.3	11.9%	1.9%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	Sumitomo Mitsui Banking Corporation				238,735.1	9.7%	1.6%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
	BNP Paribas				194,553.8	7.9%	1.3%	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.		—	—	—	x	—
Subtotal					2,465,717	100.0%	16.2%	2,465,717	100.0%	15.0%	2,465,717	100.0%	13.3%		—	—	—	16.2%	—
Total sample					10,805,468	—	70.9%	12,019,257	—	73.0%	14,165,085	—	76.2%		63.0%	58.0%	53.8%	70.9%	63.0%
	Memo items
		Other ^7/
			Locally incorporated institutions (39)		131,042.1	3.0%	0.9%	131,042.1	3.0%	0.8%	106,458.9	2.4%	0.6%
			Foreign branches (133)		4,309,458.5	97.0%	28.3%	4,309,458.5	97.0%	26.2%	4,309,458.5	97.6%	23.2%
				− License banks (125)	4,275,284.4	96.3%	28.0%	4,275,284.4	96.3%	26.0%	4,275,284.4	96.8%	23.0%
				− Restricted license banks (⁸)	34,174.1	0.8%	0.2%	34,174.1	0.8%	0.2%	34,174.1	0.8%	0.2%
		Total system			15,245,968.1	100.0%	100.0%	16,459,757.2	100.0%	100.0%	18,581,002.3	100.0%	100.0%

^{^4/}This part of the liquidity stress test includes approaches by both the HKMA and the IMF on a solo basis;

^{^6/}Foreign branches are also referred to as “non-locally incorporated, licensed banks”;

^{^7/}The number in parentheses indicates the number of firms in each category, which have been excluded from the stress test;

4. Key risks over both the short- and medium-term are incorporated into the design of the stress tests. The assessment is completed by considering three key channels of stress affecting bank balance sheets from a creditor perspective: (i) impairment charges (credit losses, other losses from held-to-maturity assets) and mark-to-market (MtM) valuation changes of fixed income securities (financial and government bonds) in both the trading and banking book³; (ii) changes in pre-impairment income, including changes in funding costs; and (iii) changes in risk-weighted assets (RWAs). The impact of general conditions affecting risk factors, such as rising risk aversion in capital markets (via market-implied risk measures) and upcoming regulatory reforms (Basel III) are examined. The stress test also incorporates specific risk factors, including cross-border developments (such as sovereign risk) and foreign currency risk in order to determine the capacity of banks to absorb the manifestation of macro-financial stress, without identifying individual institutions.⁴ The findings are to be used flexibly, given the forward-looking perspective and the objective of identifying emerging vulnerabilities under extreme but plausible stress scenarios. The completion and reporting of findings have been closely coordinated with the HKMA.

5. The purpose of the stress test exercise differs from that of supervisory stress testing. The multi-period FSAP stress test exercise is designed and completed for surveillance purposes, with a medium-term focus. The exercise typically involves very severe stress scenarios to assess the overall resilience of the banking sector. The results of the stress testing exercise have no immediate supervisory implications but provide input into a broader analysis undertaken by the FSAP, forming the basis for policy discussions with the authorities. This is different from the routine capital reviews undertaken by the authorities, which are aimed at identifying potential capital needs as part of the capital adequacy assessment under Pillar II, and for which management actions may be required. No management action would be expected as a result of the FSAP stress tests.

6. The banking sector is large and concentrated with several banking groups (Figure 2). The sector comprises 201 institutions—156 licensed banks, 21 restricted license banks, and 24 deposit-taking companies—with assets equivalent to 705 percent of GDP. The assets are concentrated in four banks, which account for almost half of the consolidated assets of the banking sector. The sector has been growing rapidly over the recent years, driven by mortgage-related lending and increasing exposure to non-financial corporates in Mainland China. Lending to the corporate sector represents around half of the banking system’s total lending, while property-lending accounts for about a third (Figure 6). Banks are primarily funded by customer deposits, which account for 71 percent of local banks’ total liabilities at end-2012 (Figure 3). In recent years, the aggregate loan-to-deposit ratio has increased as some banks issued certificates of deposits in the wholesale market to diversify their funding sources. In contrast, foreign branches in general rely more on interbank deposits and borrowing from their parent banks, with customer deposits representing a much smaller part of their total liabilities (31 percent).

7. Liquidity risks for banks are generally low (Figure 10). While banks are not reliant on wholesale funding, it is desirable for banks to develop alternative term funding sources at longer maturity tenors to augment the large deposit base, which creates considerable maturity mismatches beyond one year. Asset encumbrance is relatively low, with total unencumbered liquid assets remaining stable relative to the amount of short-term liabilities.

B. Synopsis

8. Comprehensive and stringent stress tests of the banking sector have been conducted in close cooperation with HKMA staff. Both solvency and liquidity stress tests are based on the mid-2013 financial data of the key institutions as well as the macroeconomic projections and financial market information available at that time. Up to 19 local banks and eight foreign branches were included in the stress tests.⁵ The FSAP’s close collaboration with the HKMA and banks meant that granular supervisory information as well as banks’ own internal data were used in the tests, in addition to publicly available information.

9. The objective of the stress testing exercise was to assess the resilience of the banking sector to solvency and funding shocks under different macroeconomic scenarios. The stress test considers the sector’s vulnerability to a renewed economic contraction, including a substantial rise in unemployment, a sharp depreciation of real estate prices, and declining profitability from lending due to competitive pressures on lending rates and rising funding costs. Also the impact of general conditions affecting risk factors, such as rising sovereign risk and upcoming regulatory reforms are examined.

10. The solvency tests are based on three scenarios, determined in collaboration with the HKMA. The scenarios comprise a baseline scenario and two adverse scenarios, specified contingent on the projected economic growth paths of HKSAR, Mainland China, and the United States. These have been identified as the core economies influencing the macro-financial linkages affecting the performance of the banking sector. Hurdle rates are applied according to the Basel III implementation schedule.

11. Cross-border effects are considered in all macroeconomic scenarios. Assumptions about the type of shocks (temporary or permanent) affecting the domestic economy—and the degree to which they also affect economies that banks hold exposures outside HKSAR (i.e., mainly Mainland China, Japan, the United Kingdom, and the United States)—have been aligned by allowing for time-varying patterns of selected macro-financial variables consistent with the forecasts for HKSAR under both baseline and adverse scenarios.

12. Liquidity tests complement the solvency tests and focus on the sudden, sizeable withdrawal of funding (i.e., liabilities run-off) and the sufficiency of existing liquidity buffers to withstand those shocks under stressed conditions. Various implied cash flow (ICF) tests under the HKMA’s liquidity risk framework (over the stress horizons of one week and three months) and liquidity tests developed by the FSAP team (over the stress horizons of one week and one month), and the standard liquidity measures under Basel III (the LCR and NSFR) are applied to determine the short- and medium-term resilience of individual banks and the overall system. The liquidity tests are supplemented by a stress test conducted by the HKMA staff incorporating the impact of market and credit risk arising from a prolonged period of negative asset price shocks on cash flow projections.

13. The stress test results confirm that the banking sector would remain sufficiently capitalized and liquid under the current regime. Analyses based on prudential data suggest that even a severe economic shock relative to the baseline would not result in an aggregate capital shortfall over a five-year forecast horizon.⁶ The results are consistent across the various different stress testing approaches utilized in this exercise. While all larger banks exhibit high levels of capitalization and are able to withstan

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Abstract

Introduction1

A. Background and Objective

B. Synopsis

Introduction¹