Credit derivative strategies : new thinking on managing risk and return

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Spectacular debacles like that of the hedge fund Long-Term Capital Management in remind us that so-called "outlier events" may occur. Another risk measure oriented to behavioral tendencies is a drawdown , which refers to any period during which an asset's return is negative relative to a previous high mark. In measuring drawdown, we attempt to address three things: the magnitude of each negative period how bad , the duration of each how long , and the frequency how often. One measure for this is beta known as "market risk" , based on the statistical property of covariance.

A beta greater than 1 indicates more risk than the market and vice versa. Beta helps us to understand the concepts of passive and active risk. The returns are cash-adjusted, so the point at which the x and y-axes intersect is the cash-equivalent return. Drawing a line of best fit through the data points allows us to quantify the passive risk beta and the active risk alpha. The gradient of the line is its beta. For example, a gradient of 1. A manager employing a passive management strategy can attempt to increase the portfolio return by taking on more market risk i.

If the level of market or systematic risk were the only influencing factor, then a portfolio's return would always be equal to the beta-adjusted market return. Of course, this is not the case as returns vary because of a number of factors unrelated to market risk. Investment managers who follow an active strategy take on other risks to achieve excess returns over the market's performance.

Active strategies include stock, sector or country selection, fundamental analysis , and charting. Active managers are on the hunt for an alpha, the measure of excess return. In our diagram example above, alpha is the amount of portfolio return not explained by beta, represented as the distance between the intersection of the x and y-axes and the y-axis intercept, which can be positive or negative.

In their quest for excess returns, active managers expose investors to alpha risk , the risk that the result of their bets will prove negative rather than positive. If unexpected economic developments cause energy stocks to sharply decline, the manager will likely underperform the benchmark, an example of alpha risk.

In general, the more active the investment strategy the more alpha a fund manager seeks to generate , the more an investor will need to pay for exposure to that strategy. The difference in pricing between passive and active strategies or beta risk and alpha risk respectively encourages many investors to try and separate these risks e. This is popularly known as portable alpha , the idea that the alpha component of a total return is separate from the beta component. To the investor, that 1. Portable alpha strategies use derivatives and other tools to refine how they obtain and pay for the alpha and beta components of their exposure.

Risk is inseparable from return. Every investment involves some degree of risk, which can be very close to zero in the case of a U. Treasury security or very high for something such as concentrated exposure to Sri Lankan equities or real estate in Argentina.

Risk is quantifiable both in absolute and in relative terms.

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A solid understanding of risk in its different forms can help investors to better understand the opportunities, trade-offs, and costs involved with different investment approaches. Portfolio Management. Risk Management.

Credit Derivative Strategies: New Thinking on Managing Risk and Return by -

Mutual Fund Essentials. Hedge Funds Investing. Investopedia uses cookies to provide you with a great user experience. By using Investopedia, you accept our. Your Money. Personal Finance. Your Practice. Popular Courses. Login Newsletters. Investing Portfolio Management. Table of Contents Expand. What is Risk Management? Good, Bad, and Necessary Risk.

How Investors Measure Risk. Over the years, corporate managers have learned that focusing on better process management and quality can enhance financial returns and customer satisfaction. They have learned that correcting errors, downtime in critical systems, and undertraining of staff all result in higher costs and lost revenue opportunities.

I challenge you to consider the corporate governance structure appropriate to your bank's unique business strategy and scale as an important investment, and to consider returns on that investment in terms of the avoidance of the costs of poor internal controls and of customer dissatisfaction. As you know, once an organization gets lax in its approach to corporate governance, problems tend to follow.

We have some experience in that regard. Some of you may recall the time and attention that management of U. Then the process became routine, delegated to lower levels of management and unresponsive to changes in the way the business was being run. Unfortunately, for organizations with weak governance, trying to change the culture again to meet Sarbanes-Oxley requirements is taking an exceptional amount of senior management and directors' time--time taken away from building the business. The challenge, therefore, is not only to achieve the proper control environment at one point in time, but also to maintain that discipline and, indeed, ensure that corporate governance keeps pace with the changing risks that you will face in the coming years.

One weakness we have seen is the delegation by management of both the development and the assessment of the internal-control structure to the same risk-management, internal-control, or compliance group. It is important to emphasize that line management has the responsibility for identifying risks and ensuring that the mitigating controls are effective--and to leave the assessments to a group that is independent of that line organization.

Managers should be expected to evaluate the risks and controls within their scope of authority at least annually and to report the results of this process to the chief risk officer and the audit committee of the board of directors. An independent group, such as internal audit, should perform a separate assessment to confirm management's assessment.

Credit risk management The evolution of a portfolio approach to credit risk management has followed a path similar to that of asset-liability management. It began in the late s, in the aftermath of serious credit-quality deterioration. Models and databases on defaults and credit spreads have since become more sophisticated, and loan review committees have evolved into committees that consider more broadly the various aspects of portfolio risk management.

As a result, loans are priced better to reflect their varying levels of risk, they are syndicated and securitized to mitigate lenders' risk, and credit derivatives have been created to limit credit-risk exposures that are retained. On that last topic, I would be remiss not to draw your attention to a recent consultative paper on credit-risk transfer issued by the Joint Forum in October. This consultative paper focuses on credit derivatives and related transactions--themselves an outgrowth of better risk measurement--and is open to public comment through January In that context, the consultative paper responds to three questions: whether the transactions accomplish a clean transfer of risk, whether participants understand the risks involved, and whether undue concentrations of risk are developing.

Overall, the paper offers seventeen specific recommendations for improving the practice and supervisory oversight of credit risk transfer activity, drawing heavily on discussions with sophisticated market participants.

Risk Management in Finance

I encourage you to review this paper and consider its recommendations seriously. Let me discuss two of them briefly. One recommendation is that firms understand fully and apply discipline to their credit models in order to ensure quality and manage the usage of these models appropriately. Correlation assumptions receive special attention here, including the growing presence of "correlation trading desks" and the observation from several market participants that there may be too much commonality in these assumptions across market participants. Insufficient diversity in views could lead to the kind of turmoil that occurred in markets for longer-term Treasury instruments in mid In that case, unexpected increases in rates led a large number of similarly positioned financial institutions to seek to take the same side of transactions simultaneously.

Another recommendation is that participants properly understand the economic meaning of external ratings that are applied to credit risk transfer instruments, especially collateralized debt obligations or CDOs--as compared with ratings given to more traditional obligations. Identical ratings across different types of instruments do not guarantee identical risk characteristics, and in particular may imply equal probability of a loss event but unequal severity of loss. It is important to understand both the specific methodology used by the rating agency--which the agencies make available in extensive detail, including how default correlation is addressed--and the structure of a specific transaction in order to properly assess its contribution to a portfolio's risk profile.

Data integrity, broadly defined Even the best of processes suffers if the data used to measure risk and performance are flawed. In understanding the drivers of good risk management, qualitative factors are a critical influence on the reliability and characteristics of the "data" used to evaluate risk and performance. In this broader sense, "data integrity" can refer not only to the consistency, accuracy and appropriateness of the information in the data base and model, but also to the processes that produce and utilize these measures.

Used this way, "data integrity" includes the quality of credit files, tracking of key customer characteristics, internal processes and controls, and even the training that supports them all. When one says "data integrity" in risk-management circles these days, most people think of the qualifying standards for the internal-ratings-based approaches to credit risk capital under Basel II. I think it is a broader concept, so let me spend a moment on that subject.

Credit Derivatives : Trading, Investing,and Risk Management

The proposed timetable for U. As you probably know, the U.

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Even on that timetable, the regulatory community recognizes that substantial data limitations may prevent banks from developing viable and robust parameter estimates in the near term--even for probability of default in some cases. For this reason, both banks and their supervisors will have to wait while data accumulate before banks can estimate and validate parameter inputs in a reliable, robust manner.

In the interim, banks and supervisors will have to rely heavily on qualitative validation approaches--although not entirely. Supervisors across countries are working together to address validation issues, and, I believe, will develop useful guidelines for banks and supervisors alike. In the early years, more weight may need to be placed on qualitative reviews of a bank's internal policies and procedures, including its internal validation and documentation.

But we expect that, soon after implementation, banks should have the ability to generate the needed parameters from actual data, and supervisors will want to see positive steps being taken by banking organizations to develop good databases to provide the sort of data integrity I am discussing. Qualitative and quantitative benchmarking studies, which compare methodologies and parameter estimates across banks, will be important tools for validation and for encouraging the diffusion of best practices throughout the industry during both the initial, more qualitative and the later more quantitative, intervals.

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But, as I noted, high-quality data are important for strong risk management, and not just for Basel II. Data are needed for other models and risk measures used in financial services, including credit scoring models, market-based measures such as KMV, and value-at-risk and other economic capital models. As you know, these economic capital models are a key element of Pillar 2. The broader concept of data integrity also applies to the development and maintenance of well-controlled processes including those that measure risk and performance. If the environment in which the models operate is not appropriate--if an institution considers internal controls just to be a checklist--its risk measures will not provide the performance it hopes to achieve.

Accounting, disclosure, and market discipline Strong risk measurement and disciplined maintenance of data also improve the communication between the institution and its investors and counterparties. This sense of data integrity relates just as well to the information provided to these parties. I would like, now, to turn to some of the recent accounting issues surrounding complex instruments and the role of financial disclosure in promoting risk management. Some of you may have experienced earnings volatility resulting from the use of credit derivatives.

Under U. Most credit derivatives do not qualify for hedge accounting treatment, implying greater earnings volatility if the hedged portfolio or securities are carried at historic cost in their banking book. As a bank supervisor, I am concerned if the accounting treatment discourages the use of new risk-management financial instruments. You may be wondering if the answer to this volatility issue is fair value accounting. If the hedged asset were measured at fair value, the changes in values of the hedged item and the credit derivative would offset each other, reducing the volatility that arises when only the derivative is marked to market, depending of course on the effectiveness of the hedge.

But some volatility is likely to remain, since it is the lack of close correlation that prevents hedge accounting treatment. The IASB developed the new "fair value option" under International Accounting Standard IAS 39, under which firms could mark to market both the credit derivative and the hedged position and report changes in their fair values in current earnings. While at first glance the fair value option might be viewed as the solution to addressing the problems of the current accounting model, it also raises a number of concerns. Without observable market prices and sound valuation approaches, fair value measurements are difficult to determine, verify, and audit.

Reporting would become less comparable across institutions. Moreover, if an entity's creditworthiness deteriorates significantly, there is potentially a peculiar result.

In this circumstance, financial liabilities would be marked down to fair value and a gain would be recorded in the entity's profit and loss statement. In the most dramatic case, an insolvent entity might appear solvent as a result of marking to market its own deteriorated credit risk.

Many of these concerns, as well as recommendations to address them, were included in a July comment letter to the IASB from the Basel Committee. As institutions using IASB standards consider how to use the fair value option for their own financial reporting purposes, they should be aware of certain related complexities. For example, if loans are reported using the fair value option, changes in fair value would presumably affect loan loss allowances and thus regulatory capital, important asset-quality measures like nonperforming assets, and even net interest margins.

Credit derivative strategies : new thinking on managing risk and return Credit derivative strategies : new thinking on managing risk and return
Credit derivative strategies : new thinking on managing risk and return Credit derivative strategies : new thinking on managing risk and return
Credit derivative strategies : new thinking on managing risk and return Credit derivative strategies : new thinking on managing risk and return
Credit derivative strategies : new thinking on managing risk and return Credit derivative strategies : new thinking on managing risk and return
Credit derivative strategies : new thinking on managing risk and return Credit derivative strategies : new thinking on managing risk and return
Credit derivative strategies : new thinking on managing risk and return Credit derivative strategies : new thinking on managing risk and return

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