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A Probabilistic Analysis of Autocallable Optimization Securities

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  • Gilna K. Samuel
  • Donald St. P. Richards

Abstract

We consider in this paper some structured financial products, known as reverse convertible notes, that resulted in substantial losses to certain buyers of these notes in recent years. We shall focus on specific reverse convertible notes known as "Autocallable Optimization Securities with Contingent Protection Linked to the S\&P 500 Financial Index," because these notes are representative of the broad spectrum of reverse convertibles notes. Therefore, the analysis provided in this paper is applicable to many other reverse convertible notes. We begin by describing the notes in detail and identifying potential areas of confusion in the pricing supplement to the prospectus for the notes. We deduce two possible interpretations of the payment procedure for the notes and apply the Law of Total Expectation to develop a probabilistic analysis for each interpretation. We also determine the corresponding expected net payments to note-holders under various scenarios for the financial markets and show that, under a broad range of scenarios, note-holders were likely to suffer substantial losses. As a consequence, we infer that the prospectus is sufficiently complex that financial advisers generally lacked the mathematical knowledge and expertise to understand the prospectus completely. Therefore, financial advisers who recommended purchases of the notes did not have the knowledge and expertise that is required by a fiduciary relationship, hence were unable to exercise fiduciary duty, and ultimately misguided their clients. We conclude that these reverse convertibles notes were designed by financial institutions to insure themselves, against significant declines in the equities markets, at the expense of note-holders.

Suggested Citation

  • Gilna K. Samuel & Donald St. P. Richards, 2018. "A Probabilistic Analysis of Autocallable Optimization Securities," Papers 1804.00825, arXiv.org.
  • Handle: RePEc:arx:papers:1804.00825
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