The lifetime of a financial bubble

Agarwal, S., Al-Saleh, J.: Generalized gamma type distribution and its hazard rate function. Commun. Stat. Theory Methods 30(2), 309–318 (2001). doi:10.1081/STA-100002033

Andersen, L.B.G., Piterbarg, V.: Moment explosions in stochastic volatility models. Financ. Stoch. 11, 29–50 (2007)

Barber, D.: Bayesian Reasoning and Machine Learning. Cambridge University Press, Cambridge (2012)

Bayraktar, E., Kardaras, C., Xing, H.: Strict local martingale deflators and valuing American call-type options. Financ. Stoch. 16, 275–291 (2011)

Biagini, F., Föllmer, H., Nedelcu, S.: Shifting martingale measures and the slow birth of a bubble. Financ. Stoch. 18, 297–326 (2014)

Cox, A., Hobson, D.: Local martingales, bubbles and option prices. Financ. Stoch. 9, 477–492 (2005)

Cox, C.: The generalized F distribution: an umbrella for parametric survival analysis. Stat. Med. 27, 4301–4312 (2008)

Delbaen, F., Schachermayer, W.: The fundamental theorem of asset pricing for unbounded stochastic processes. Math. Ann. 312(2), 215–250 (1998)

Delbaen, F., Shirakawa, H.: No arbitrage condition for positive diffusion price processes. Asia-Pacific Financ. Mark. 9, 159–168 (2002)

Florens-Zmirou, D.: On estimating the diffusion coefficient from discrete observations. J. Appl. Probab. 30, 790–804 (1993)

Herdegen, M., Schweizer, M.: Economics-Based Financial Bubbles (and Why They Imply Strict Local Martingales), Swiss Finance Institute Research Paper No. 15-05. doi:10.2139/ssrn.2566815, SSRN: http://ssrn.com/abstract=2566815 (2015)

Hollebeek, T., Ho, T.S., Rabitz, H.: Constructing multidimensional molecular potential energy surfaces from AB initio data. Annu. Rev. Phys. Chem. 50, 537–570 (1999)

Jacod, J.: Rates of convergence to the local time of a diffusion. Ann. l’Inst. Henri Poincaré, Sect. B 34, 505–544 (1998)

Jacod, J.: Non-parametric Kernel estimation of the coefficient of a diffusion. Scand. J. Stat. 27, 83–96 (2000)

Jacod, J., Protter, P.: Probability Essentials, 2nd edn. Springer, Heidelberg (2004)

Jacod, J., Protter, P.: Strict Local Martingale Solutions of Stochastic Differential Equations. Working Paper (2015)

Jarrow, R., Kchia, Y., Protter, P.: How to detect an asset bubble. SIAM J. Financ. Math. 2, 839–865 (2011)

Jarrow, R., Protter, P., Shimbo, K.: Asset price bubbles in a complete market. In: Madan, D.B. (ed.) Advances in Mathematical Finance, pp. 105–130. Birkhauser, Boston (2006)

Jarrow, R., Protter, P., Shimbo, K.: Asset price bubbles in incomplete markets. Math. Financ. 20, 145–185 (2010)

Kardaras, C., Kreher, D., Nikeghbali, A.: Strict local martingales, bubbles. Ann. Appl. Probab. 25, 1827–1867 (2015)

Kotani, S.: On a condition that one dimensional diffusion processes are martingales. Memoriam Paul-André Meyer. Springer, Berlin (2006)

Lienhard, J.H., Meyer, P.L.: A physical basis for the generalized gamma distribution. Q. Appl. Math. 25(3), 330–334 (1967)

Lions, P.L., Musiela, M.: Correlations and bounds for stochastic volatility models. Ann. Inst. Henri Poincaré, (C) Nonlinear Anal. 24(1), 1–16 (2007)

Loewenstein, M., Willard, G.A.: Rational equilibrium asset-pricing bubbles in continuous trading models. J. Econ. Theory 91, 17–58 (2000)

Mijatović, A., Urusov, M.: On the martingale property of certain local martingales. Probab. Theory Relat. Fields 152, 1–30 (2012)

Prentice, R.L.: A log gamma model and its maximum likelihood estimation. Biometrika 61(3), 539–544 (1974)

Protter, P.: A mathematical theory of financial bubbles. In: Benth, F.E., et al. (eds.) Paris-Princeton Lectures on Mathematical Finance 2013, Lecture Notes in Mathematics (2081), pp. 1–108. Springer, Cham (2013)

Schneikman, J., Xiong, W.: Overconfidence and speculation bubbles. J. Polit. Econ. 111(6), 1183–1220 (2003)

Stacy, E.W.: A generalization of the gamma distribution. Ann. Math. Stat. 33, 1187–1192 (1962)

Sommerfeld, A.: Lectures on Theoretical Physics: Thermodynamics and Statistical Mechanics, vol. 5. Acadmemic Press, New York (1964)

Zhang, L., Mykland, P., Aït-Sahalia, Y.: A tale of two time scales: Determining integrated volatility with noisy high-frequency data. J. Am. Stat. Assoc. 100(472), 1394–1411 (2005). doi:10.1198/016214505000000169