Financial stability

Financial stability is the absence of system-wide episodes in which a financial crisis occurs and is characterised as an economy with low volatility. It also involves financial systems' stress-resilience being able to cope with both good and bad times. Financial stability is the aim of most governments and central banks. The aim is not to prevent crisis or stop bad financial decisions. It is there to hold the economy together and keep the system running smoothly while such events are happening.

The foundation of financial stability is the creation of a system that is able to absorb all of the positive and negative events that happen to the economy at any given time. It has nothing to do with preventing individuals or businesses from failing, losing money, or succeeding. It is merely assisting in the creation of conditions for the system's continued efficient operation in the face of such occurrences.

The economy is one that is constantly changing and expanding, and it is full of businesses that start, grow, and fail: routine activities of the business cycle. Financial markets and financial institutions are considered stable when they are able to provide households, communities, and businesses with the resources, services, and products they require to invest, grow, and participate in a well-functioning economy. Financial institutions include banks, savings and loans, and other financial product and service providers. A financial system that meets the needs of typical families and businesses to borrow money to buy a house or car, save for retirement, or pay for college is considered to have financial stability. In a similar vein, businesses must take out loans in order to expand, construct factories, recruit new workers, and make payroll.

The ability to efficiently allot resources, assess and manage financial risks, maintain employment levels close to the natural rate of the economy, and eliminate relative price movements of real or financial assets that will affect monetary stability or employment levels are all features of a financially stable system. Financial imbalances that arise naturally or as a result of significant adverse and unforeseen events are dissipated when a financial system is in a range of stability. When the system is stable, it will primarily absorb shocks through self-corrective mechanisms, preventing adverse events from disrupting the real economy or other financial systems. Because the majority of real-world transactions take place through the financial system, financial stability is absolutely necessary for economic expansion.

The Altman's z‐score is extensively used in empirical research as a measure of firm-level stability for its high correlation with the probability of default. This measure contrasts buffers (capitalization and returns) with risk (volatility of returns) and has done well at predicting bankruptcies within two years. Despite development of alternative models to predict financial stability Altman's model remains the most widely used.

An alternate model used to measure institution-level stability is the Merton model (also called the asset value model). It evaluates a firm's ability to meet its financial obligations and gauges the overall possibility of default. In this model, an institution's equity is treated as a call option on its held assets, taking into account the volatility of those assets. Put-call parity is used to price the value of the implied “put” option, which represents the firm's credit risk. Ultimately, the model measures the value of the firm's assets (weighted for volatility) at the time that the debtholders exercises their “put option” by expecting repayment. Implicitly, the model defines default as when the value of a firm's liabilities exceeds that of its assets calculate the probability of credit default. In different iterations of the model, the asset/liability level could be set at different threshold levels.

In subsequent research, Merton's model has been modified to capture a wider array of financial activity using credit default swap data. For example, Moody's uses it in the KMV model both to calculate the probability of credit default and as part of their credit risk management system. The Distance to Default (DD) is another market-based measure of corporate default risk based on Merton's model. It measures both solvency risk and liquidity risk at the firm level.

Unfortunately, there is not yet a singular, standardized model for assessing financial system stability and for examining policies.