Financial risk management

Neoclassical finance theory prescribes that (1) a firm should take on a project only if it increases shareholder value. Further, the theory suggests that (2) firm managers cannot create value for shareholders or investors by taking on projects that shareholders could do for themselves at the same cost; see Theory of the firm and Fisher separation theorem. Given these, there is therefore a fundamental debate relating to "Risk Management" and shareholder value. The discussion essentially weighs the value of risk management in a market versus the cost of bankruptcy in that market: per the Modigliani and Miller framework, hedging is irrelevant since diversified shareholders are assumed to not care about firm-specific risks, whereas, on the other hand hedging is seen to create value in that it reduces the probability of financial distress. When applied to financial risk management, this implies that firm managers should not hedge risks that investors can hedge for themselves at the same cost. "In a perfect market, the firm cannot create value by hedging a risk when the price of bearing that risk within the firm is the same as the price of bearing it outside of the firm." In practice, however, financial markets are not likely to be perfect markets. This suggests that firm managers likely have many opportunities to create value for shareholders using financial risk management, wherein they are able to determine which risks are cheaper for the firm to manage than for shareholders. Here, market risks that result in unique risks for the firm are commonly the best candidates for financial risk management. ==Application==

As outlined, businesses are exposed, in the main, to market, credit and operational risk. A broad distinction behind profitability, as well as of the quantum of capital they are required to hold. Financial risk management in banking has thus grown markedly in importance since the 2008 financial crisis. (This has given rise (see Too big to fail). Central to both commercial and investment banking is the function of maturity transformation, where institutions fund long-term assets using short-term liabilities. Commercial banks typify this by issuing demand deposits (which can be withdrawn at any time) to fund long-dated assets like mortgages, while investment banks often finance longer-term trading inventory or structured products through short-term repurchase agreements (repos). While this "borrowing short and lending long" strategy is profitable — normally capturing the spread between lower short-term rates and higher long-term rates — it creates an inherent mismatch on the balance sheet. This structural mismatch generates the primary risks that banks must manage - outlined in the preceding paragraph - but here especially: liquidity risk (the inability to meet short-term obligations without selling assets) and interest rate risk (changes in the yield curve affecting asset and liability values differently), making Asset and liability management (ALM) a critical discipline. The Basel Accords mandate the predominant risk management framework. Under "Pillar I" regulators define the minimum regulatory capital requirements for quantifiable risks — principally credit risk, market risk, and operational risk as outlined — using either standardised or approved internal‑model approaches. Under "Pillar II", banks must conduct an internal capital adequacy assessment (ICAAP) to capture all material risks, holding sufficient "economic capital" for those. These calculations are mathematically sophisticated, and within the domain of quantitative finance. The regulatory capital quantum is calculated via specified formulae: risk weighting the exposures per highly standardized asset-categorizations, applying the aside frameworks, and the resultant capital — at least 12.9% of these Risk-weighted assets (RWA) — must then be held in specific "tiers" and is measured correspondingly via the various capital ratios. In certain cases, banks are allowed to use their own estimated risk parameters here; these "internal ratings-based models" typically result in less required capital, but at the same time are subject to strict minimum conditions and disclosure requirements. As mentioned, additional to the capital covering RWA, the aggregate balance sheet will require capital for leverage and liquidity; this is monitored via Extensions to VaR include Margin-, Liquidity-, Earnings- and Cash flow at risk, as well as Liquidity-adjusted VaR. For both (i) and (ii), model risk is addressed through regular validation of the models used by the bank's various divisions; for VaR models, backtesting is especially employed. Regulatory changes, are also twofold. The first change, entails an increased emphasis on bank stress tests. These tests, essentially a simulation of the balance sheet for a given scenario, are typically linked to the macroeconomics, and provide an indicator of how sensitive the bank is to changes in economic conditions, whether it is sufficiently capitalized, and of its ability to respond to market events. The second set of changes, sometimes called "Basel IV", entails the modification of several regulatory capital standards (CRR III is the EU implementation). In particular FRTB addresses market risk, and SA-CCR addresses counterparty risk; other modifications are being phased in from 2023. To operationalize the above, Investment banks, particularly, employ dedicated "Risk Groups", i.e. Middle Office teams monitoring the firm's risk-exposure to, and the profitability and structure of, its various business units, products, asset classes, desks, and / or geographies. limit values for each of the Greeks, or other sensitivities, that their traders must not exceed, and traders will then hedge, offset, or reduce periodically if not daily; see the techniques listed below. These limits are set given a range of plausible changes in prices and rates, coupled with the board-specified risk appetite re overnight-losses. • Desks, or areas, will similarly be limited as to their VaR quantum (total or incremental, and under various calculation regimes), corresponding to their allocated against thresholds set for various types of risk, and / or re a single counterparty, sector or geography. • Leverage will be monitored, at very least re regulatory requirements via LR, the Leverage Ratio, as leveraged positions could lose large amounts for a relatively small move in the price of the underlying. • Relatedly, liquidity risk is monitored: LCR, the Liquidity Coverage Ratio, measures the ability of the bank to survive a short-term stress, covering its total net cash outflows over the next 30 days with "high quality liquid assets"; NSFR, the Net Stable Funding Ratio, assesses its ability to finance assets and commitments within a year (addressing also, maturity transformation risk). Any "gaps", also, must be managed. • Systemically Important Banks hold additional capital such that their total loss absorbency capacity, TLAC, is sufficient given both RWA and leverage. (See also "MREL" for EU institutions.) Periodically, these all are estimated under a given stress scenario — regulatory and, often, internal — and risk capital, is correspondingly revisited (or optimized). The approaches taken center either on a hypothetical or historical scenario, A reverse stress test, in fact, starts from the point at which "the institution can be considered as failing or likely to fail... and then explores scenarios and circumstances that might cause this to occur". Economic Capital (EC) reflects the total risk capital that the bank requires to cover "all" its risks as a going concern assessed on a realistic basis, including survival in a worst-case scenario. The modelling - at least once annually - must be such that A key practice, incorporating and assimilating the above, is to assess the Risk-adjusted return on capital, RAROC, of each area (or product). Here, "economic profit" is divided by allocated-capital; and this result is then compared direct costs are (sometimes) also subtracted. RAROC is calculated both ex post as discussed, used for performance evaluation (and related bonus calculations), and ex ante - i.e. expected return less expected loss - to decide whether a particular business unit should be expanded or contracted. Other teams, overlapping the above Groups, are then also involved in risk management. Corporate Treasury is responsible for monitoring overall funding and capital structure; it shares responsibility for monitoring liquidity risk, and for maintaining the FTP framework. Middle Office maintains the following functions also: Product Control is primarily responsible for insuring traders mark their books to fair value — a key protection against rogue traders — and for "explaining" the daily P&L; with the "unexplained" component, of particular interest to risk managers. Credit Risk monitors the bank's debt-clients on an ongoing basis, re both exposure and performance; while (large) exposures are initially approved by an "investment committee". In the Front Office — since counterparty and funding-risks span assets, products, and desks — specialized XVA-desks are tasked with centrally monitoring and managing overall CVA and XVA exposure and capital, typically with oversight from the appropriate Group. "Stress Testing" is similarly centralized. over the various areas, products, teams, and measures — requires that banks maintain a significant investment in sophisticated infrastructure, finance / risk software, and dedicated staff. Risk software often deployed is from FIS, Kamakura, Murex, Numerix (FINCAD) and Refinitiv. Large institutions may prefer systems developed entirely "in house" - notably Goldman Sachs (SecDB), JP Morgan (Athena), Jane Street (Core), Barclays (BARX), BofA (Quartz), Citadel (Apollo), Morgan Stanley (SecMaster) - while, more commonly, the pricing library will be developed internally, especially as this allows for currency re new products or market features. Commercial and retail banking for retail and commercial banks Commercial and retail banks are, by nature, more conservative than Investment banks, earning steady income from lending and deposits; their focus is more on the "banking book" than the "trading book". The biggest concern here - as mentioned - is the credit risk due to loan defaults from individuals or businesses. Liquidity risk, in this context not having enough liquid assets to meet withdrawal demands, is also a major focus; while interest rate risk concerns the impact of interest rate changes on net interest margins (the spread between deposit and loan rates). For these banks, regulatory oversight is often tighter due to their direct impact on the financial system. Thus they are also highly regulated under Basel III and national banking laws, and will also be subject to regular stress testing by central banks; and all regulations above then apply (with local exceptions; e.g. an LCR "threshold" in the US). Additional to these, however, they must maintain high capital and liquidity ratios to protect depositors; see CAMELS rating system. Given their business model and risk appetite, than for assets typical in investment banking. See, e.g., the ALLL and NPL ratios. • At the same time, credit exposure for these banks is to significantly more clients than at investment banks. For retail banks, "consumer credit risk" is often diversified across a vast number of borrowers, and these employ statistical models for (ongoing "behavioral") credit scoring and probability of default. Commercial banks deal with mid-sized corporate loans and bonds, and apply accounting- and financial analysis to determine creditworthiness; the approach differs re investment banking in that the broad client base allows for (necessitates) automation, with close monitoring on an exception basis. AI / ML is increasingly employed at all stages. • Concentration risk, relatedly, differs in its management: the concern is sector concentration as opposed to "name concentration". Here, in calculating VaR for a credit portfolio, banks will incorporate a joint default probability for the various sectors and / or industries. • Both retail and commercial banks employ strict liquidity management to ensure enough cash for customer withdrawals: at a minimum meeting the above NSFR and LCR requirements; but also complying with their regulator's reserve requirement. See also liquidity at risk. • Both use interest rate hedging (e.g., swaps) but here, in the main, to protect their profit margin against rate fluctuations, and the resultant "margin compression"; i.e., as opposed to addressing market risk per se. Re the latter, they will often employ the abovementioned cash flow at risk and earnings at risk models. They also hold specific capital for interest rate risk in the banking book, "IRRBB", which deals with the risks associated with a change in interest rates, including interest rate gaps, basis risk, yield curve risk, and option risk. • Banks' Economic Capital models, here, are focused more on credit- and operational risk. ICAAP applies; although allows for modelling which may be simpler, and with less stringent review by regulators. The Risk Management function typically exists independent of operations - although may sit in Treasury - and reports directly to the board. The scope here - ie in non-financial firms (re banking) to overlap enterprise risk management, and financial risk management then addresses risks to the firm's overall strategic objectives, incorporating various (all) financial aspects of the exposures and opportunities arising from business decisions, and their link to the firm’s appetite for risk, as well as their impact on share price. In many organizations, risk executives are therefore involved in strategy formulation: "the choice of which risks to undertake through the allocation of its scarce resources is the key tool available to management." Relatedly, strategic projects and major corporate investments must first undergo thorough analysis, with approval by an Investment Committee. Re the standard framework, — see following description — and is coupled with the use of insurance, managing the net-exposure as above: credit risk is usually addressed via provisioning and credit insurance; likewise, where this treatment is deemed appropriate, specifically identified operational risks are also insured. is concerned mainly with changes in commodity prices, interest rates, and foreign exchange rates, and any adverse impact due to these on cash flow and profitability, and hence share price. Correspondingly, the practice here covers two perspectives; these are shared with corporate finance more generally: • Both risk management and corporate finance share the goal of enhancing, or at least preserving, firm value. preempting any underperformance vs shareholders' required return. In larger firms, specialist Risk Analysts complement this work with model-based analytics more broadly; in some cases, employing sophisticated stochastic models, in, for example, financing activity prediction problems, and for risk analysis ahead of a major investment. • Firm exposure to long term market (and business) risk is a direct result of previous capital investment decisions. Where applicable here their investment bankers — risk analysts will manage and hedge interest rate- and foreign exchange hedges (see further below). Because company specific, "over-the-counter" (OTC) contracts tend to be costly to create and monitor — i.e. using financial engineering and / or structured products — "standard" derivatives that trade on well-established exchanges are often preferred. Multinational corporations are faced with additional challenges, particularly as relates to foreign exchange risk, and the scope of financial risk management modifies significantly in the international realm (essentially that discussed above), accounting exposure, and economic exposure — so the corporate will manage its risk differently. The forex risk-management discussed here and above, is additional to the per transaction "forward cover" that importers and exporters purchase from their bank (alongside other trade finance mechanisms). Hedging-related transactions will attract their own accounting treatment, and corporates (and banks) may then require changes to systems, processes and documentation; see Hedge accounting, Mark-to-market accounting, Hedge relationship, Cash flow hedge, IFRS 7, IFRS 9, IFRS 13, FASB 133, IAS 39, FAS 130. It is common for large corporations to have dedicated risk management teams — typically within FP&A or corporate treasury — reporting to the CRO; often these overlap the internal audit function (see Three lines of defence). For small firms, it is impractical to have a formal risk management function, but these typically apply the above practices, at least the first set, informally, as part of the financial management function; see discussion under Financial analyst. The discipline relies on a range of software, correspondingly, from spreadsheets (invariably as a starting point, and frequently in total) through commercial EPM and BI tools, often BusinessObjects (SAP), OBI EE (Oracle), Cognos (IBM), and Power BI (Microsoft). Insurance to model rare events such as "100-year floods". Pictured is Kaskaskia, Illinois, entirely submerged during the Great Flood of 1993. Insurance companies make profit through underwriting — selecting which risks to insure, charging a risk-appropriate premium, and then paying claims as they occur — and by investing the premiums they collect from insured parties. They will, in turn, manage their own risks are concerned more with longevity risk and interest rate risk; Short-Term Insurers (Property, Health, Casualty) emphasize catastrophe- and claims volatility risks. Fundamental here, therefore, are risk selection and pricing discipline, which as outlined, prevent insurers from taking on unprofitable business. For expected claims — i.e. those covered, on average, by the pricing model’s assumptions re claim frequency and severity — reserves are set aside (actuarial, with statutory reserves as a floor). These will cover both known claims, reported but unpaid, as well as those which are incurred but not reported (IBNR). To absorb unexpected losses, insurance companies maintain a minimum level of capital plus an additional solvency margin. Capital requirements are based on the risks an insurer faces, such as underwriting risk, market risk, credit risk, and operational risk, and are governed by frameworks such as Solvency II (Europe) and Risk-Based Capital (U.S.). To further mitigate large-scale risks — i.e. to reduce exposure to catastrophic losses — insurers transfer portions of their risk to Reinsurers. Here, analogous to VaR for banks, insurers use simulations to estimate potential losses at various thresholds, while stress tests assess how extreme events might impact capital and reserves under various scenarios. (Dynamic financial analysis (DFA) and the Wilkie model are used generally in scenario analytics, and may underpin the VaR engine.) In parallel with all these, as above, premiums collected are invested to generate returns which will supplement underwriting profits, and the fund is then risk-managed as follows: discussed in the next section. As for banks, all models are regularly reviewed, comparing, i.a., "Actual versus Expected". Specific treatments will, as outlined, differ by insurer-profile: • Life Insurers (or standard deviation) — the extent to which the portfolio's return is uncertain — and through diversification the portfolio is optimized so as to achieve the lowest risk for a given targeted return, or equivalently the highest return for a given level of risk: this approach is known as mean-variance optimization. (The collection of these risk-efficient portfolios form the "efficient frontier"; see Markowitz model.) The logic here is that returns from different assets are highly unlikely to be perfectly correlated, and in fact the correlation may sometimes be negative. In this way, market risk particularly, and other financial risks such as inflation risk (see below) can at least partially be moderated by forms of diversification. A key issue, however, is that the (assumed) relationships are (implicitly) forward looking. As observed in the late-2000s recession, historic relationships can break down, resulting in losses to market participants believing that diversification would provide sufficient protection (in that market, including funds that had been explicitly set up to avoid being affected in this way). A related issue is that diversification has costs: as correlations are not constant it may be necessary to regularly rebalance the portfolio, incurring transaction costs, negatively impacting investment performance; and as the fund manager diversifies, so this problem compounds (and a large fund may also exert market impact). See . The above mean-variance optimization is implemented (more or less) directly by asset allocation funds. At the same time - in part given the issues outlined - alternative methods for portfolio construction have been developed, including new approaches to defining risk, and to the optimization itself. — generically APT — using time series regression to design portfolios respectively: macro-, factor-, and style portfolios. The optimization, under both the mean-variance and factor model approaches, may be with respect to (tail) risk parity, focusing on allocation of risk, rather than allocation of capital, and employ, e.g. the Black–Litterman model which modifies the above "Markowitz optimization", to incorporate the "views" of the portfolio manager. Alongside these, Discretionary investment management funds, instead, lean heavily on traditional "stock picking", employing fundamental analysis in preference to advanced mathematical approaches. (These Managers are then the major consumers of securities research.) The specific concerns will, in turn, differ as a function of the Manager's investment philosophy and active strategy, preferring, e.g., value-, growth- or defensive stocks within her fund. Portfolios here are managed, also, using qualitative and subjective considerations, which include evaluations of company management, industry dynamics, and macro/political factors. As discussed below, Risk Management here will, correspondingly, be largely pragmatic and heuristic, as opposed to quantitative. An important requirement, regardless of approach, is that the Manager must ensure of financial risk modeling techniques — including value at risk, historical simulation, stress tests, and the respective sensitivities, portfolio beta and option delta, determine the number of hedge-contracts required. Fund managers may (instead) engage in "portfolio insurance", a dynamic hedging process that involves selling index futures during periods of decline and using the proceeds to offset portfolio losses. • Fund managers, or traders, may also wish to hedge a specific stock's price. Here, they may likewise dedicated portfolio, liability-driven investment strategy, duration gap. • For individual bonds and other fixed income securities, specific credit and interest rate risks can be hedged ). Sensitivities re interest rates are measured using duration and convexity for bonds, and DV01 and key rate durations generally, and an offsetting derivative-position is purchased. For credit risk, sensitivities are measured via CS01, while analysts use models such as Jarrow–Turnbull and KMV to estimate the (risk neutral) probability of default, hedging where appropriate, usually via credit default swaps. Probabilities (actuarial) may also be obtained from Bond credit ratings; then, often at a portfolio level — e.g. for credit-VaR — analysts will use a transition matrix of these to estimate the probability and impact of a "credit migration", aggregating the bond-by-bond result. Interest rate- and credit risk together, may be hedged via a Total return swap. See Fixed income analysis • For derivative portfolios, and positions, the Greeks are a vital risk management tool: as above, these measure sensitivity to a small change in a given underlying price, rate, or parameter, and the portfolio is then rebalanced accordingly will suggest - i.e. limit - the size of a position that an investor should hold in her portfolio. Roy's safety-first criterion minimizes the probability of the portfolio's return falling below a minimum desired threshold. Chance-constrained portfolio selection similarly seeks to ensure that the probability of final wealth falling below a given "safety level" is acceptable. Managers likewise employ the abovementioned factor models on an ongoing basis to measure exposure to the relevant risk factors. allocation-strategy dependent (tactical, dynamic, or strategic) rebalance its asset allocation from e.g. equities to bonds. In parallel with the above, As relevant, they will similarly use style analysis to address style drift. See also Fixed-income attribution and Benchmark-driven investment strategy. Beyond market volatility, investment management requires rigorous control of liquidity, operational, and leverage risks (the concerns mirroring those discussed above re banking). Liquidity risk management ensures that a fund can meet redemption requests or rebalance portfolios without incurring excessive transaction costs, typically by maintaining cash buffers or limiting holdings in illiquid assets; this is closely tied to leverage concerns, where borrowed capital magnifies losses (as outlined above) and introduces the risk of margin calls or forced liquidation. Operational and counterparty risks—the potential for failure in internal systems, trade execution, or default by a trading partner—are mitigated through robust reconciliation processes, segregation of duties, and collateral agreements. These concerns differ significantly by fund structure: hedge funds often employ high leverage and hold illiquid assets to boost returns, managing the associated risks through "lock-up" periods that restrict withdrawals; in contrast, mutual funds and ETFs typically face regulatory limits on leverage and must provide daily liquidity, necessitating stricter risk controls to prevent asset-liability mismatches. Managers of Discretionary Funds, will, as mentioned, rely largely inflation risk will typically be managed at the portfolio level. Here the manager will programmatically (or heuristically) increase exposure the proportion of the portfolio in ILBs, for example, will correspond to its inflation beta (sensitivity of portfolio return to increases in inflation, measured using regression). See . Newer and broader, and often qualitative cybersecurity risks (a material drop in share prices caused, e.g., by a significant ransomware incident) and geopolitical risks. These risks are often less tangible and less immediately visible than traditional financial risks, and quantifying these can be challenging. While portfolio risks are managed day-to-day by the fund manager, the Chief Risk Officer - often Chief Investment Officer - is responsible for overall risk. The Risk Function ("Group" at an IB, as above) thus monitors aggregate firm-level risks (exposure across funds, as well as, e.g., reputational risk) ensuring alignment with the firm's risk appetite and regulatory obligations; it will, relatedly, be involved in scenario generation - economic and geopolitical - and stress testing. This team also provides independent challenge and escalation if a fund breaches its Risk Budget (e.g. VaR, stress losses and sector concentration). The CRO typically signs off on stress testing, liquidity risk reviews, and model validation. Given the complexity of these analyses and techniques, Fund Managers - and Risk Analysts - typically rely on sophisticated software (as do banks, above). Widely used platforms are provided by BlackRock (Aladdin), Refinitiv (Eikon), Finastra, Murex, Numerix, MPI, Morningstar, MSCI (Barra) and SimCorp (Axioma). == See also ==