By Philipp N. Baecker

Over the final years, because of in depth festival within the wisdom financial system, criminal facets surrounding highbrow estate (IP) rights - together with litigation and payment - have continually received in significance. Correspondingly, expert IP administration has turn into an crucial portion of profitable value-based administration (VBM) in research-intensive firms.

With this article, the writer proposes an built-in method of patent threat and capital budgeting in pharmaceutical study and improvement (R and D), constructing an option-based view (OBV) of imperfect patent security, which pulls upon contingent-claims research, stochastic online game idea, in addition to novel numerical equipment. Bridging a widening hole among fresh advances within the concept of economic research and present demanding situations confronted by means of pharmaceutical businesses, the textual content re-initiates a dialogue in regards to the contribution of quantitative frameworks to value-based R and D management.

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Extra resources for Real Options and Intellectual Property: Capital Budgeting Under Imperfect Patent Protection

Example text

Let Π(ω, s; t, T ) denote the path of cash flows generated by the option, conditional on the option not being exercised at or prior to time t and on the optimal stopping strategy being followed for all s ∈ (t, T ]. The expected continuation value under the risk-neutral measure, conditional on the information known at time tj , is ⎡ ⎤ F (ω; tj ) = EP∗ ⎣ n e−r(tk −tj ) Π(ω, tk ; tj , tn ) Ftj ⎦ , k=j+1 where EP∗ [·] is the expectation operator under the martingale measure and 0 ≤ tj < tn = T . Define an approximation M FM (ω; tj ) = ak Lk (Xtj ), k=0 17 18 19 For a detailed assessment of the least-squares Monte Carlo (LSM) approach see Moreno and Navas [249].

Let Π(ω, s; t, T ) denote the path of cash flows generated by the option, conditional on the option not being exercised at or prior to time t and on the optimal stopping strategy being followed for all s ∈ (t, T ]. The expected continuation value under the risk-neutral measure, conditional on the information known at time tj , is ⎡ ⎤ F (ω; tj ) = EP∗ ⎣ n e−r(tk −tj ) Π(ω, tk ; tj , tn ) Ftj ⎦ , k=j+1 where EP∗ [·] is the expectation operator under the martingale measure and 0 ≤ tj < tn = T . Define an approximation M FM (ω; tj ) = ak Lk (Xtj ), k=0 17 18 19 For a detailed assessment of the least-squares Monte Carlo (LSM) approach see Moreno and Navas [249].

0 am−1 1 + bm−1 0 ⎞ ⎛ ⎞ ⎛ 0 ................ h0,j −a1 1 − b1 −c1 ⎜ ⎟ ⎜ 0 −a2 1 − b2 −c2 0 . . . ⎟ ⎟ · ⎜ h1,j ⎟ , =⎜ ⎝. . . . . . . . . . . . . . . . . . . . ⎠ ⎝ . . ⎠ hm,j . . . . . 0 −am−1 1 − bm−1 −cm−1 or, more concisely, Aj+1 · hj+1 = Aj · hj − rj+1 . Defining b ≡ Aj · hj − rj+1 , x ≡ hj+1 , and dropping the remaining subscript leads to the generic matrix equation A · x = b. 0 Fig. 6. 1). The Black–Scholes PDE was discretized on a 500-by-500 grid using Courtadon’s Crank–Nicolson scheme.

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