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Empirical evaluation of the market price of risk using the CIR model

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Title: Empirical evaluation of the market price of risk using the CIR model
Authors: Bernaschi, M.1 massimo@iac.rm.cnr.it, Torosantucci, L.1,2 luca.torosantucci@bnlmail.com, Uboldi, A.3,4 adamo.uboldi@jrc.it
Source: Physica A. Mar2007, Vol. 376, p543-554. 12p.
Subjects: Market prices, Financial risk, Martingales (Mathematics), Estimation theory, Least squares
Abstract: Abstract: We describe a simple but effective method for the estimation of the market price of risk. The basic idea is to compare the results obtained by following two different approaches in the application of the Cox–Ingersoll–Ross (CIR) model. In the first case, we apply the non-linear least squares method to cross sectional data (i.e., all rates of a single day). In the second case, we consider the short rate obtained by means of the first procedure as a proxy of the real market short rate. Starting from this new proxy, we evaluate the parameters of the CIR model by means of martingale estimation techniques. The estimate of the market price of risk is provided by comparing results obtained with these two techniques, since this approach makes possible to isolate the market price of risk and evaluate, under the Local Expectations Hypothesis, the risk premium given by the market for different maturities. As a test case, we apply the method to data of the European Fixed Income Market. [Copyright &y& Elsevier]
Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 23676992
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PubTypeId: academicJournal
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  Data: <searchLink fieldCode="AR" term="%22Bernaschi%2C+M%2E%22">Bernaschi, M.</searchLink><relatesTo>1</relatesTo><i> massimo@iac.rm.cnr.it</i><br /><searchLink fieldCode="AR" term="%22Torosantucci%2C+L%2E%22">Torosantucci, L.</searchLink><relatesTo>1,2</relatesTo><i> luca.torosantucci@bnlmail.com</i><br /><searchLink fieldCode="AR" term="%22Uboldi%2C+A%2E%22">Uboldi, A.</searchLink><relatesTo>3,4</relatesTo><i> adamo.uboldi@jrc.it</i>
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  Data: <searchLink fieldCode="JN" term="%22Physica+A%22">Physica A</searchLink>. Mar2007, Vol. 376, p543-554. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Market+prices%22">Market prices</searchLink><br /><searchLink fieldCode="DE" term="%22Financial+risk%22">Financial risk</searchLink><br /><searchLink fieldCode="DE" term="%22Martingales+%28Mathematics%29%22">Martingales (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Estimation+theory%22">Estimation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Least+squares%22">Least squares</searchLink>
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  Data: Abstract: We describe a simple but effective method for the estimation of the market price of risk. The basic idea is to compare the results obtained by following two different approaches in the application of the Cox–Ingersoll–Ross (CIR) model. In the first case, we apply the non-linear least squares method to cross sectional data (i.e., all rates of a single day). In the second case, we consider the short rate obtained by means of the first procedure as a proxy of the real market short rate. Starting from this new proxy, we evaluate the parameters of the CIR model by means of martingale estimation techniques. The estimate of the market price of risk is provided by comparing results obtained with these two techniques, since this approach makes possible to isolate the market price of risk and evaluate, under the Local Expectations Hypothesis, the risk premium given by the market for different maturities. As a test case, we apply the method to data of the European Fixed Income Market. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.physa.2006.10.072
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        Text: English
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        StartPage: 543
    Subjects:
      – SubjectFull: Market prices
        Type: general
      – SubjectFull: Financial risk
        Type: general
      – SubjectFull: Martingales (Mathematics)
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      – SubjectFull: Estimation theory
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      – SubjectFull: Least squares
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              Text: Mar2007
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