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On the modeling of employee voluntary early exercise for the valuation of Employee Stock Options
Chendra E.a,b, Sidarto K.A.a, Puspita D.a, Syamsuddin M.a, Lismayanti S.a
a Industrial and Financial Mathematics Group, Institute of Technology Bandung, Indonesia
b Department of Mathematics, Parahyangan Catholic University, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]Employee Stock Options (ESOs) are call options granted by a company to its employees on the stock of the company. ESOs are an important part of company compensation and the valuation of these options has become a focus attention in finance and accounting. ESOs have special characteristics, such as: they are not tradable; they can be exercised only after the vesting period; if employees leave the company during the vesting period then the ESOs are forfeited. So valuing these options using Black-Scholes framework is less appropriate. This paper extends the model proposed by Brisley and Anderson to account for the restricted set of possible exercise dates (Bermudan style) and the state-dependent employee exit rate. We analyze the optimal early exercise decision by risk neutral valuation model. Then the price of ESOs is computed using Monte Carlo method. The Monte Carlo method is flexible and easy to implement and modify. We also analyze ESOs properties and sensitivity with respect to the model parameters. © 2013 IEEE.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Andersons,Black-Scholes,Model parameters,Risk-neutral valuations,State-dependent,Stock options[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Brisley-Anderson model,Employee Stock Options,Monte Carlo method[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICACCI.2013.6637384[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]