By Brett King
The first version of BANK 2.0—#1 on Amazon's bestseller record for banking and finance within the US, united kingdom, Germany, France, and Japan for over 18 months—took the monetary international through typhoon and have become synonymous with disruptive shopper behaviour, know-how shift, and new banking models.
In BANK 3.0, Brett King brings the tale modern with the newest traits redefining monetary prone and payments—from the worldwide scramble for dominance of the mobile wallet and the expectancies created by means of tablet computing to the operationalising of the cloud, the explosion of social media, and the increase of the de-banked purchaser, who doesn't desire a financial institution at all.
BANK 3.0 indicates that the distance among consumers and fiscal providers avid gamers is quickly widening, leaving mammoth possibilities for brand spanking new, non-bank rivals to fully disrupt the industry.
"On the internet and on cellular, the client isn't king—he's dictator. hugely impatient, skeptical, cynical. Brett King knows deeply what drives this new hard-nosed patron. Banking pros might do good to heed his advice."
Gerry McGovern, writer of Killer internet Content
Read or Download Bank 3.0: Why Banking Is No Longer Somewhere You Go But Something You Do PDF
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Additional info for Bank 3.0: Why Banking Is No Longer Somewhere You Go But Something You Do
2 Comonotonic Upper Bound In this section, it will be shown how to derive an upper bound for a call option on the index in terms of call options on the individual stocks. For details, we refer to . In fact comonotonicity theory implies, that it is always possible to bound the index option price C (K, T ) from above, namely, with the price of the comonotonic index call price C c (K, T ). To do so, we first have to specify the comonotonic distribution FS c . Theorem 1 (Comonotonic distribution).
A solvable one-dimensional model of a diffusion inventory system. Math. Oper. Res. 11(1), 125–133 (1986) 14. : Stochastic lead times in continuous-time inventory models. Nav. Res. Logist. Q. 33(4), 763–774 (1986) 15. : Foundations of Inventory Management. McGraw-Hill/Irwin, NY (2000) FIX: The Fear Index—Measuring Market Fear J. Dhaene, J. B. Forys, D. Linders, and W. Schoutens Abstract In this paper, we propose a new fear index based on (equity) option surfaces of an index and its components.
Feng and Muthuraman  also show that for any given admissible policy (d, D,U, u), the corresponding cost function v(x) satisfies L v(x) = 0, ∀x ∈ (d, u), (11) v(x) = v(D) + K + k · (D − x), ∀x ≤ d, (12) v(x) = v(U) + L + l · (x − U), ∀x ≥ u. (13) That is, for a given policy (d, D,U, u), the associated cost function can be obtained by solving a fixed boundary differential equation. Next we show this algorithm results in policy improvement. Due to the above two theorems, each step of the following algorithm is well defined and converges to the optimal value functions.