Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Bong-Gyu Jang"'
Autor:
Bong-Gyu Jang, Hyeng Keun Koo
Publikováno v:
Seonmul yeongu, Vol 32, Iss 2, Pp 86-115 (2024)
We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the
Externí odkaz:
https://doaj.org/article/20d3cb5a78c54dd6a8af0f6b5ccfded3
Publikováno v:
Seonmul yeongu, Vol 29, Iss 2, Pp 116-133 (2021)
Purpose – This paper examines whether the successful bid rate of the OnBid public auction, published by Korea Asset Management Corporation, can identify and forecast the Korea business-cycle expansion and contraction regimes characterized by the OE
Externí odkaz:
https://doaj.org/article/3e41162f96ba42619f3dd2c7d6e996c1
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Journal of Derivatives and Quantitative Studies: 선물연구. 29:116-133
Purpose This paper examines whether the successful bid rate of the OnBid public auction, published by Korea Asset Management Corporation, can identify and forecast the Korea business-cycle expansion and contraction regimes characterized by the OECD r
Publikováno v:
European Financial Management. 28:208-232
Publikováno v:
Insurance: Mathematics and Economics. 94:25-39
In this paper, we study optimal retirement in a two-dimensional incomplete market caused by borrowing constraints and forced unemployment risk. We show that the two aspects jointly affect an individual’s optimal consumption, investment, and retirem
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Operations Research Letters. 48:549-551
We generalize the result of Yaari (1965) on annuitization with borrowing constraint. We show that inability to borrow against future labor income has a significant influence on an individual’s consumption and asset allocation strategies. We also sh
Publikováno v:
Finance Research Letters. 48:102894
Publikováno v:
SSRN Electronic Journal.
We adopt the semicovariance decomposition method and machine-learning models to forecast the realized correlation and realized volatility of oil and gold futures markets. The general framework consists of three steps: data preprocessing, accumulating