In these times of enhanced market risk leading to financial risk, the eminent question for all business entities has become how to save costs. Where and how to cut costs and save funds. Is reengineering an answer
Managing operations in such a way that time spend and waste is eliminated should be the objective in order to combat financial crunch. Operational research which identifies slack and eliminates waste is the answer.
The obvious questions that would be striking your mind must be "What does operations research have to do with Financial Risk management?"
Let us first understand what transformation is
The discipline of applying advanced analytical methods to help make better decisions. By using techniques such as mathematical modeling to analyze complex situations, operations research gives executives the power to make more effective decisions and build more productive systems.
Change is unique It's best of breed, employing highly developed methods practiced by specially trained professionals. It's powerful, using advanced tools and technologies to provide analytical power that no ordinary software or spreadsheet can deliver out of the box, and it's tailored to you, because an O.R. professional offers you the ability to define your specific challenge in ways that make the most of your data and uncover your most beneficial options.
To achieve these results, professionals draw upon the latest analytical technologies, including:
- Simulation : Giving you the ability to try out approaches and test ideas for improvement
- Optimization : Narrowing your choices to the very best when there are virtually innumerable feasible options and comparing them is difficult
- Probability and Statistics : Helping you measure risk, mine data to find valuable connections and insights, test conclusions, and make reliable forecasts
Financial risk management
The practice followed by corporate managers/accountants to control the uncertainity in the total portfolio of firms is termed as Financial Risk Management or FRM. Financial risk management aims to minimize the risk of loss from unexpected changes in the prices of currencies, interest rates, commodities, and equities. In the context of international accounting, financial risk management also contains an element of political, legal and "culture" risk--exposure to uncertainty in the outcomes of business transactions and asset transfers that comes with most international business operations. Accountants are closely involved in the analysis and evaluation of the financial effects of currency movements and exchange rates, tax regimes and business laws, as well as risks of hostile takeover, expropriation and economic downturns that differ in every country around the globe.
Credit Risk
Credit risk can be defined as the potential of a bank borrower that fails to meet the financial obligations it has agreed to. While loans are probably the largest and highest of credit risks, trade financing, foreign exchange transactions, financial futures, bonds, and equities may also represent credit risk. A credit risk management program can help financial institutions address these risks by assisting with the identification, measurement, monitoring, and control of credit risks.
Market Risk
Market/Treasury risk focuses on an institution's financial risks that may come from adverse movements in the level or volatility of market prices of interest rate instruments, equities, commodities, and currencies. Through market/treasury risk management, financial institutions look to asset and liability management, trading controls management, risk pricing, transfer pricing, hedge management, and capital allocation management to help mitigate these risks.
Operational Risk
Operational risk management aims at identifying, enhancing, and integrating key processes and systems into an overall operational risk framework. The framework can help set operational risk strategies, identify inefficiencies, and quantify risks so they can be mitigated and managed.
To keep track of the myriad details of a risk management system, managers now rely upon a wide range of new tools and technologies- computer-based trading systems, telecommunications technology, decision support systems that quantify risk factors, and so on. Intelligent risk management helps a company stabilize cash flows, reduce risk of insolvency, manage foreign taxes, and focus on its primary business in each country and market.
Role Of Operations Research :
The four key pillars on which risk management strategies rest, are discussed below-
Pricing: To properly align the risks one first has to measure them.
Securitization: Properly priced risks can be securitized into new financial products that cater to the risk-management needs of diverse businesses.
Asset and liability management: Whatever financial risk is eventually retained by a business, it must be diversified and properly aligned with the firm's obligations.
Indexation: Broadly defined market indices provide the necessary benchmarks and guide managers in assessing how well their business manages its own risks vis-à-vis the markets.
These key functions of financial risk management i.e. pricing, securitization, asset and liability management, and indexation are supported by the extensive tools the operations research contains.
Pricing
Pricing of complex path-dependent options -- whose prices depend on a history of asset prices and not just the asset value on exercise -- requires Monte Carlo simulation methods. For several derivatives the decision whether to exercise the option, or not, follows from the solution of an optimization problem. Theoretical models of the price evolution of the risky assets must be linked with dynamic programming algorithms to arrive at options prices resulting from optimal exercise strategies.
When the exercise strategy is not optimal, the resulting prices will create arbitrage opportunities; arbitrageurs push the market toward optimal strategies, although they do not do so with the explicit use of optimization algorithms. Furthermore, pricing in incomplete markets requires specification of preference assumptions that can only be resolved in an optimization framework. Linear programming and linear complementarily problems are prevalent in options pricing. Some times the operations research models appear as alternative formulations to other options pricing formulas, enjoying some computational advantages. In other instances they provide the only formulations.
Securitization
Securitization with the design of innovative financial products and the re-packaging of financial risks can be made more effective with the use of optimization models. Like engineers -- who routinely use optimization techniques to optimize structural designs for safety, stability, cost or fuel efficiency -- financial engineers use optimization models to achieve their design goals along the competing dimensions of risk and reward.
Asset and Liability management
The management of assets and liabilities using the principles of diversification relies on quadratic optimization models. Significant developments since Markowitz's pioneering contribution in the 1950s -- derivative securities that violate assumptions on normality of returns, long time horizons of complex liability structures, increasing transaction costs for derivative securities -- ushered a new generation of multi-period portfolio optimization models. Dynamic financial analysis was developed to go beyond the single-period decisions of mean-variance analysis to the optimization of dynamic strategies. These strategies adapt with the arrival of new information. Stochastic programming for planning under uncertainty provides a versatile tool for dynamic financial analysis, and its use in finance has been gaining popularity since the 1980s.
Indexation
Finally, portfolio indexation and portfolio compression relies on the combination of pricing and simulation models with optimization models.
The risk factors of the index are simulated and optimization models create portfolios that respond to the risk factors in a way that mimics the market's response. When the risk factors are properly identified and correctly simulated, the optimized portfolio will closely track the index.
The interplay of financial risks with operational decisions
We have focused thus far on the use of operations research in managing financial risks. What remains yet unexplored is the interplay of financial risks with operational decisions. Indeed, in enterprise risk management this interaction is of paramount importance. Risks can be eliminated or controlled not only through the use of financial tools but also through operational decisions. For instance, the decision to delay capacity expansion could buffer demand or price uncertainty. Decisions to outsource production could eliminate some of the effects of exchange rate uncertainty. The field of real options -- options on non-traded underlying assets -- brings together the finance literature on options valuation with the operations management literature on flexibility. In addition to the value added to risk management by linking operational decisions with financial decisions, this link makes it also possible to communicate operational decisions to a firm's financial officers.
Transformation dealing with regulatory requirements
Finally, we explore the role of operations research tools in the support of regulatory requirements. Financial institutions are carefully regulated in their risk management practices. The Basel Accords, for instance, stipulate practices that should be followed by banks in the management of their risks. They are the bible for supervisory authorities worldwide. In an interesting development, recent Basel Accords allow institutions to develop internal models that, properly audited, are used to report risk exposures for regulatory compliance. Value-at-Risk (VaR) has become the standard of measurement in establishing an institution's long-term financial health.
Institutions are required to monitor their VaR and set aside adequate regulatory capital to cover extreme movements. The estimation of VaR requires Monte Carlo simulations, while the optimization of an institution's VaR can be achieved with models of global optimization. When the VaR calculations are flawed the results can be catastrophic. The managers of Long Term Capital Management, of Orange County (Calif.) or ENRON learned this lesson the hard way, at a large cost to shareholders.
Recently, operations researchers have pointed out that optimizing the expected losses conditioned on losses exceeding VaR can be formulated as a linear program. Minimization of expected shortfall, also known as Conditional Value-at-Risk (CVaR), is a simple linear program, while minimization of VaR is a global optimization problem. A debate that started on technical arguments (linear programming or global optimization?) brought to the surface an intriguing policy issue: Optimizing VaR is to the best interest of shareholders, but not of the public that regulators must serve. Shareholders do care about extreme losses (VaR) that may drive their institution into bankruptcy. But limited liability protects them if the institution goes into bankruptcy. Regulators and the public, on the other hand, are left with the burden of bailing out failing institutions. They have to absorb the expected losses once an institution is in distress. The cost to the public is the failing institution's CVaR and not its VaR. The question "To VaR or to CvaR" is contributing to the debate on the adoption of the new Basel Accord.
The Value Added Proposition of change management
We have seen that operations research tools have a significant role to play in enterprise risk management. The use of these tools has been constantly on the rise since the introduction of quadratic programming for portfolio management half a century ago. However, "tools" is not the value-added proposition of operations research to the brave new world of enterprise risk management. Several other disciplines physics, probability and statistics, numerical mathematics, fluid dynamics are contributing significant tools to finance.
The value-added proposition of operations research to enterprise-wide risk management is as follows: To align efficiently the firm's business with the risk factors of its environment, corporations must take a global view of the risks they are exposed to and an integrated view of the risk management process. As concurrent engineering calls for the integration of engineering design, manufacturing and marketing of products in a seamless process, similarly enterprise risk management calls for the integration of the design, pricing, capitalizing, marketing and funding of financial products. These functions are clearly interdependent. When multiple financial products are offered by an institution there is the additional problem of managing the business portfolio. Determining the appropriate product mix and allocating the firm's capital should again take an integrated view of the risks and returns of competing lines of business
Taking a global view of an enterprise requires a multidisciplinary systems approach that has been the cornerstone of operations research since its early World War II days. And the integration of the risk management process requires tools that integrate risk measurement with risk management over long-time horizons. Stochastic programming with large-scale optimization provides a powerful tool to integrate the risk-management process. In conclusion, operations research offers a unique perspective and the required technical tools for taking both a global and an integrated view of risk management.
Conclusions :
Operations research has a significant role to play in the world of finance. It has both roles to play, a support role, which would be providing tools from the toolkit of OR, and a main role in shifting the risk management paradigm from a compartmentalized approach toward an enterprise-wide view. But unlike other areas where operations research is applied -- logistics, transportation, military -- there is a rich theory describing the behavior of the financial system paradigm. But it provides us with a well-developed body of theory that describes the financial world, as we see it. Those who wish to engage in intellectual arbitrage between finance and operations research should be well versed in both areas. Otherwise they run the risk of being at the paying side of financial arbitrage trades.
By Pooja Varma, Consulting Manager, Ventures Middle East, www.ventures-me.com
© Zawya Select 2009
