10-12-2019 · 研究

Duration Times Spread: measuring credit risk

Accurately measuring credit risk is a significant challenge for credit investors. Credit volatility varies greatly over time and differs considerably between individual corporate bonds.

    作者

  • Erik van Leeuwen - Chief Operations Investments

    Erik van Leeuwen

    Chief Operations Investments

  • Olaf Penninga - Portfolio Manager

    Olaf Penninga

    Portfolio Manager

  • Patrick Houweling - Head of Quant Fixed Income

    Patrick Houweling

    Head of Quant Fixed Income

Robeco researchers1 developed an innovative method in 2003 to predict credit volatility more adaptively and more granularly. Although no model is ever perfect, the new methodology substantially improved the measurement of credit volatility compared to the traditional models at the time.

Also read: Duration Times Spread: a measure of spread exposure in credit portfolios

The methodology, Duration Times Spread (DTS), has become the industry standard for measuring the credit volatility of a corporate bond. It measures the sensitivity of the price of a bond to relative changes in credit spread, and is a single number that can be used to compare credit volatility across a wide range of bonds. In practice, it is applied in the portfolio management process to assess relative value, manage risk exposure in portfolio construction and conduct performance attribution.

Not all spread-durations are equal

Traditional risk models typically rely on the extrapolation of historical trends. An example is the use of volatility in returns over the most recent 36 months. One disadvantage of such an approach is that it fails to capture true risk when there is a break in the trend2.

For example, at the onset of the financial crisis in 2007, the output of such models would still have been based mainly on data from the quiet periods of 2005 and 2006, when credit spreads were relatively stable, and would have vastly underestimated the risk of a credit portfolio.

Similarly, immediately following a volatile period of large changes in credit spread, a traditional model that relies on historical returns would overestimate risk.

A further problem is that traditional risk measurement models tend to use an absolute approach, and do not account for the fact that the magnitude of spread changes are proportional to spread levels: bonds with wider spreads are riskier because they experience greater spread changes. Accurate risk measurement would thus need to factor in the sensitivity of returns to relative changes in spread.

Traditional models, moreover, are unable to weigh up different types of risk. Credit investors know that longer-dated credit is riskier than shorter-dated credit. They also know that bonds issued by lower-rated names are riskier than higher-quality credits. The difficulty is in comparing these two sources of risk: how, for example, does one rate the risk associated with a short-dated B-rated credit against the risk of a long-dated AA-rated credit?

The empirical observation that spreads move in a relative rather than an absolute fashion is at the heart of our DTS methodology

Calculating Duration Times Spread

The empirical observation that credit spreads move in a relative rather than an absolute fashion is at the heart of our DTS methodology. If higher-spread sectors represent greater exposure to sector-specific risks, then not all spread-durations are equal.

Our in-depth research shows that the risk of a bond – its future price volatility – is best measured by the product of its spread-duration and its spread, which is the DTS.

DTS = bond spread x duration spread of the bond

For example, a bond with one-year duration and a spread of 500 basis points has the same expected volatility (1 x 500 = 500) as a bond with five-year duration and spread of 100 basis points (5 x 100 = 500).

As our risk estimates based on this calculation depend directly on the observed spread, they react instantaneously to market turmoil, and so are more accurate than estimates based on recent history.

The simplicity of the DTS allows for a wide application. As it provides a single measurement, this method can be used to compare the exposure to the credit spreads of different types of credit assets – regardless of rating or maturity, for instance. It can also be used to compare the risk profile of different credit portfolios. The higher the DTS of a credit asset or a credit portfolio, the more its returns will decline in the event credit spreads widen.

Its versatility of use means that DTS is as important for credit investors as duration is for all fixed income investors.

Industry standard for risk measurement

The DTS concept is used for all of Robeco’s credit-related segments in its fixed income portfolios3. It is also applied broadly throughout the industry and has been implemented in leading risk management software, including MSCI RiskMetrics and Bloomberg PORT.

image.png

Specifically, we apply DTS to four key aspects of our portfolio management process, namely risk measurement, assessing relative value, portfolio construction and performance attribution.

A powerful tool

We consider DTS to be an accurate methodology for forecasting credit volatility, although on occasion it can be inclined to over- and underestimate risk. By using it in our credit investment processes, portfolio managers are able to construct well-diversified portfolios in which the risk contributions of their high-conviction positions are measured accurately.

Moreover, risk-adjusted returns can be calculated almost in real time, allowing timely relative value assessment.

Finally, we consider this a tool that allows for portfolio positions to be evaluated periodically in the same framework as they have been implemented, yielding important insights and possibly giving rise to re-evaluation of these positions.

Download the full report here

Footnotes

1 A joint project with Lehman Brothers led to the publication of the result; see: Ben Dor, A., Dynkin, L., Hyman, J., Houweling, P., Van Leeuwen, E., and Penninga, O., ‘DTS (Duration Times Spread)’, The Journal of Portfolio Management, 2007, vol. 33. no. 2, pp. 77-100. Downloadable here.
2 See Beekhuizen, P. and Houweling, P., ‘Smart Credit Investing - Risk Points and Their Applications’, Robeco White Paper, 2013, December.
3 See ‘Guide to credits: The Robeco approach’.

免責聲明

本文由荷宝海外投资基金管理(上海)有限公司(“荷宝上海”)编制, 本文内容仅供参考, 并不构成荷宝上海对任何人的购买或出售任何产品的建议、专业意见、要约、招揽或邀请。本文不应被视为对购买或出售任何投资产品的推荐或采用任何投资策略的建议。本文中的任何内容不得被视为有关法律、税务或投资方面的咨询, 也不表示任何投资或策略适合您的个人情况, 或以其他方式构成对您个人的推荐。 本文中所包含的信息和/或分析系根据荷宝上海所认为的可信渠道而获得的信息准备而成。荷宝上海不就其准确性、正确性、实用性或完整性作出任何陈述, 也不对因使用本文中的信息和/或分析而造成的损失承担任何责任。荷宝上海或其他任何关联机构及其董事、高级管理人员、员工均不对任何人因其依据本文所含信息而造成的任何直接或间接的损失或损害或任何其他后果承担责任或义务。 本文包含一些有关于未来业务、目标、管理纪律或其他方面的前瞻性陈述与预测, 这些陈述含有假设、风险和不确定性, 且是建立在截止到本文编写之日已有的信息之上。基于此, 我们不能保证这些前瞻性情况都会发生, 实际情况可能会与本文中的陈述具有一定的差别。我们不能保证本文中的统计信息在任何特定条件下都是准确、适当和完整的, 亦不能保证这些统计信息以及据以得出这些信息的假设能够反映荷宝上海可能遇到的市场条件或未来表现。本文中的信息是基于当前的市场情况, 这很有可能因随后的市场事件或其他原因而发生变化, 本文内容可能因此未反映最新情况,荷宝上海不负责更新本文, 或对本文中不准确或遗漏之信息进行纠正。