Academic literature on the topic 'Two-dimentional the Cox-Ross-Rubinstein model'

Option is a financial instrument where price depends on the underlying stock price. The pricing of options, both selling options and purchase options, may use the CRR (Cox-Ross-Rubinstein) binomial model. Only two possible parameters were used that is u if the stock price rises and d when the stock price down. One of the elements that determine option prices is volatility. In the binomial model CRR volatility is constant. In fact, the financial market price of stocks fluctuates so that volatility also fluctuates. This article discusses volatility of fluctuating stock price movements by modeling it using binomial fuzzy with triangular curve representation. The analysis is carried out in relation to the existence of three interpretations of the triangular curve representation resulting in different degrees of membership. In addition to volatility, this study added the size or risk level ρ. As an illustration, this study used stock price movement data from PT. Antam (Persero) from August 2015 until July 2016. The results of one period obtained from the purchase price option for August 2016 with the largest volatility, medium and smallest respectively were Rp.143,43, Rp.95,49, and Rp.79,00. There was calculated at the risk level of ρ = 90%. The degree of membership for each option price varies depending on the interpretation of the triangle curve representation.
 
 Opsi merupakan instrumen keuangan yang harganya tergantung pada harga saham yang mendasarinya. Penentuan harga opsi, baik opsi jual maupun opsi beli dapat menggunakan model binomial CRR (Cox-Ross-Rubinstein). Dalam model ini hanya dimungkinkan adanya dua parameter yaitu u apabila harga saham naik dan d pada saat harga saham turun. Salah satu unsur yang menentukan harga opsi adalah volatilitas. Dalam model binomial CRR digunakan volatilitas yang bersifat konstan. Padahal, pada pasar keuangan pergerakan harga saham mengalami fluktuasi sehingga volatilitas juga menjadi fluktuatif. Artikel ini membahas volatilitas pergerakan harga saham yang fluktuatif dengan memodelkannya menggunakan binomial fuzzy dengan representasi kurva segitiga. Analisis dilakukan terkait dengan adanya tiga interpretasi terhadap representasi kurva segitiga tersebut yang menghasilkan derajat keanggotaan yang berbeda. Selain volatilitas, dalam penelitian ini ditambahkan ukuran atau tingkat risiko ρ. Sebagai ilustrasi, digunakan data pergerakan harga saham PT. Antam (Persero) dari Agustus 2015 hingga Juli 2016. Hasil penelitian dengan perhitungan satu periode diperoleh hasil harga opsi beli untuk bulan Agustus 2016 dengan volatilitas terbesar, menengah, dan terkecil masing-masing adalah Rp.143,43, Rp.95,49, dan Rp.79,00 yang dihitung pada tingkat risiko ρ = 90%. Derajat keanggotaan untuk masing-masing harga opsi berbeda-beda tergantung pada interpretasi dari representasi kurva segitiga.

We generalize the standard lattice approach of Cox, Ross, and Rubinstein (1976) from a fixed sum to a random sum in a subordinated process framework to accommodate pricing of derivatives with random-sum characteristics. The asset price change now is determined by two independent Bernoulli trials on information arrival/non-arrival and price up/down, respectively. The subordination leads to a nonstationary trinomial tree in calendar-time, while a time change to information-time restores the simpler binomial tree that now grows with the intensity of information arrival irrespective of the passage of calendar-time. We apply the model to price the CBOT catastrophe futures call spreads as a binomial sum of binomial prices, which illuminates the information conveyed by the randomness of catastrophe arrival. Numerical results demonstrate that the standard binomial formula that ignores random claim arrival produces largest undervaluation error for out-of-money short-maturity options when a small number of significant catastrophes may strike during the option's maturity.

The trading strategy of ‘buy-and-hold for superior stock and sell-at-once for inferior stock’, as suggested by conventional wisdom, has long been prevalent in Wall Street. In this paper, two rationales are provided to support this trading strategy from a purely mathematical standpoint. Adopting the standard binomial tree model (or CRR model for short, as first introduced in Cox, Ross and Rubinstein (1979)) to model the stock price dynamics, we look for the optimal stock selling rule(s) so as to maximize (i) the chance that an investor can sell a stock precisely at its ultimate highest price over a fixed investment horizon [0,T]; and (ii) the expected ratio of the selling price of a stock to its ultimate highest price over [0,T]. We show that both problems have exactly the same optimal solution which can literally be interpreted as ‘buy-and-hold or sell-at-once’ depending on the value of p (the going-up probability of the stock price at each step): when p›½, selling the stock at the last time step N is the optimal selling strategy; when p=½, a selling time is optimal if the stock is sold either at the last time step or at the time step when the stock price reaches its running maximum price; and when p‹½, time 0, i.e. selling the stock at once, is the unique optimal selling time.

The trading strategy of ‘buy-and-hold for superior stock and sell-at-once for inferior stock’, as suggested by conventional wisdom, has long been prevalent in Wall Street. In this paper, two rationales are provided to support this trading strategy from a purely mathematical standpoint. Adopting the standard binomial tree model (or CRR model for short, as first introduced in Cox, Ross and Rubinstein (1979)) to model the stock price dynamics, we look for the optimal stock selling rule(s) so as to maximize (i) the chance that an investor can sell a stock precisely at its ultimate highest price over a fixed investment horizon [0,T]; and (ii) the expected ratio of the selling price of a stock to its ultimate highest price over [0,T]. We show that both problems have exactly the same optimal solution which can literally be interpreted as ‘buy-and-hold or sell-at-once’ depending on the value of p (the going-up probability of the stock price at each step): when p›½, selling the stock at the last time step N is the optimal selling strategy; when p=½, a selling time is optimal if the stock is sold either at the last time step or at the time step when the stock price reaches its running maximum price; and when p‹½, time 0, i.e. selling the stock at once, is the unique optimal selling time.