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  <titleInfo>
    <title>OPTION PRICING AND HEDGING UNDER JUMP DIFFUSION MODEL WITH DIFFERENTIAL INTEREST RATES</title>
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    <namePart>Fang, Hui</namePart>
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  <abstract>Classical option pricing schemes have an ideal assumption that a single interest rate is used as risk free discounting rate. This assumption has been already relaxed due to deteriorating credit market. In this paper, we assume that risk free lending and borrowing rates are di erent. Under di erential interest rates setup, a no-arbitrage price band rather than a unique price is calculated. We extend this scheme to a jump di usion model. Under mild conditions, option prices can be calculated explicitly. We illustrate the pricing scheme through a European style call option. Numerical results show that funding spread between lending and borrowing interest rates has signi cant impact on the length of the option's no-arbitrage price band.</abstract>
  <note type="provenance">Submitted by Liana Khananashvili (khananashvili@iit.edu) on 2014-12-15T19:25:41Z No. of bitstreams: 2 Option Pricing and Hedging under Jump Diffusion Model with Differential Interest Rates July_2014.pdf: 235657 bytes, checksum: 526e41f4d9c4341e7f1dcfc61bf1fbf1 (MD5) Signed Title Page.pdf: 233101 bytes, checksum: f7240a63e68f19119387e6d9becb0487 (MD5)</note>
  <note type="provenance">Made available in DSpace on 2014-12-15T19:25:41Z (GMT). No. of bitstreams: 2 Option Pricing and Hedging under Jump Diffusion Model with Differential Interest Rates July_2014.pdf: 235657 bytes, checksum: 526e41f4d9c4341e7f1dcfc61bf1fbf1 (MD5) Signed Title Page.pdf: 233101 bytes, checksum: f7240a63e68f19119387e6d9becb0487 (MD5) Previous issue date: 2014-07</note>
  <note type="thesis">M.S. in Applied Mathematics, July 2014</note>
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    <dateCaptured>2014</dateCaptured>
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    <dateCreated keyDate="yes">2014-07</dateCreated>
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  <identifier type="hdl">http://hdl.handle.net/10560/3355</identifier>
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    <namePart>MATH / Applied Mathematics</namePart>
    <affiliation>Illinois Institute of Technology</affiliation>
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