Past Mathematical and Computational Finance Seminar

8 June 2017
16:00
to
17:30
Antoine Savine
Abstract

This document reviews the so called least square methodology (LSM) and its application for the valuation and risk of callable exotics and regulatory value adjustments (xVA). We derive valuation algorithms for xVA, both with or without collateral, that are particularly accurate, efficient and practical. These algorithms are based on a reformulation of xVA, designed by Jesper Andreasen and implemented in Danske Bank's award winning systems, that hasn't been previously published in full. We then investigate the matter of risk sensitivities, in the context of Algorithmic Automated Differentiation (AAD). A rather recent addition to the financial mathematics toolbox, AAD is presently generally acknowledged as a vastly superior alternative to the classical estimation of risk sensitivities through finite differences, and the only practical means for the calculation of the large number of sensitivities in the context of xVA. The theory and implementation of AAD, the related check-pointing techniques, and their application to Monte-Carlo simulations are explained in numerous textbooks and articles, including Giles and Glasserman's pioneering Smoking Adjoints. We expose an extension to LSM, and, in particular, we derive an original algorithm that resolves the matters of memory consumption and efficiency in differentiating simulations together with the LSM step.

  • Mathematical and Computational Finance Seminar
18 May 2017
16:00
to
17:30
Francesca Biagini
Abstract

We  study  the  concept  of   financial  bubble  under model uncertainty.
We suppose the agent to be endowed with a family Q of local martingale measures for  the  underlying  discounted  asset  price. The priors are allowed to be mutually singular to each other.
One fundamental issue is the definition of a well-posed concept of robust fundamental value of a given  financial asset.
Since in this setting we have no linear pricing system, we choose to describe robust fundamental values through superreplication prices.
To this purpose, we investigate a dynamic version of robust superreplication, which we use
to  introduce  the  notions  of  bubble  and  robust  fundamental  value  in  a  consistent way with the existing literature in the classical case of one prior.

This talk is based on the works [1] and [2].

[1] Biagini, F. , Föllmer, H. and Nedelcu, S. Shifting martingale measures
and the slow birth of a bubble as a submartingale, Finance and
Stochastics: Volume 18, Issue 2, Page 297-326, 2014.


[2] Biagini, F., Mancin, J.,
Financial Asset Price Bubbles under Model 
Uncertainty, Preprint, 2016.

  • Mathematical and Computational Finance Seminar
11 May 2017
16:00
to
17:30
Martin Herdegen
Abstract


We study risk-sharing equilibria with trading subject to small proportional transaction costs. We show that the frictionless equilibrium prices also form an "asymptotic equilibrium" in the small-cost limit. To wit, there exist asymptotically optimal policies for all agents and a split of the trading cost according to their risk aversions for which the frictionless equilibrium prices still clear the market. Starting from a frictionless equilibrium, this allows to study the interplay of volatility, liquidity, and trading volume.
(This is joint work with Johannes Muhle-Karbe, University of Michigan.)
 

  • Mathematical and Computational Finance Seminar
4 May 2017
16:00
to
17:30
Blanka Horvath
Abstract

We consider rough stochastic volatility models where the driving noise of volatility has fractional scaling, in the “rough” regime of Hurst pa- rameter H < 1/2. This regime recently attracted a lot of attention both from the statistical and option pricing point of view. With focus on the latter, we sharpen the large deviation results of Forde-Zhang (2017) in a way that allows us to zoom-in around the money while maintaining full analytical tractability. More precisely, this amounts to proving higher order moderate deviation es- timates, only recently introduced in the option pricing context. This in turn allows us to push the applicability range of known at-the-money skew approxi- mation formulae from CLT type log-moneyness deviations of order t1/2 (recent works of Alo`s, Le ́on & Vives and Fukasawa) to the wider moderate deviations regime.

This is work in collaboration with C. Bayer, P. Friz, A. Gulsashvili and B. Stemper

  • Mathematical and Computational Finance Seminar
27 April 2017
16:00
to
17:30
Arnulf Jentzen
Abstract

In this lecture I intend to review a few selected recent results on numerical approximations for high-dimensional nonlinear parabolic partial differential equations (PDEs), nonlinear stochastic ordinary differential equations (SDEs), and high-dimensional nonlinear forward-backward stochastic ordinary differential equations (FBSDEs). Such equations are key ingredients in a number of pricing models that are day after day used in the financial engineering industry to estimate prices of financial derivatives. The lecture includes content on lower and upper error bounds, on strong and weak convergence rates, on Cox-Ingersoll-Ross (CIR) processes, on the Heston model, as well as on nonlinear pricing models for financial derivatives. We illustrate our results by several numerical simulations and we also calibrate some of the considered derivative pricing models to real exchange market prices of financial derivatives on the stocks in the American Standard & Poor's 500 (S&P 500) stock market index.

  • Mathematical and Computational Finance Seminar
9 March 2017
16:00
to
17:30
Christa Cuchiero
Abstract

Cover’s celebrated theorem states that the long run yield of a properly chosen “universal” portfolio is as good as the long run yield of the best retrospectively chosen constant rebalanced portfolio. We formulate an abstract principle behind such a universality phenomenon valid for general optimization problems in the long run. This allows to obtain new results on modelfree portfolio optimization, in particular in continuous time, involving larger classes of investment strategies. These modelfree results are complemented by a comparison with the log-optimal numeraire portfolio when fixing a stochastic model for the asset prices. The talk is based on joint work with Walter Schachermayer and Leonard Wong.

  • Mathematical and Computational Finance Seminar
2 March 2017
16:00
to
17:30
Matheus Grasselli
Abstract

Thomas Piketty's influential book “Capital in the Twenty-First Century” documents the marked and unequivocal rise of income and wealth inequality observed across the developed world 
in the last three decades. His extrapolations into the distant future are much more controversial and has 
has been subject to various criticisms from both mainstreams and heterodox economists. This motivates the search for an alternative standpoint incorporating 
heterodox insights such as endogenous money and the lessons from the Cambridge capital controversies. We argue that the Goodwin-Keen approach paves the road towards such an alternative.
We first consider a modified Goodwin-Keen model driven by consumption by households, instead of investment by firms, leading to the same qualitative features 
of the original Keen 1995 model, namely the existence of an undesirable equilibrium characterized by infinite private debt ratio and zero employment, 
in addition to a desirable one with finite debt and non-zero employment. By further subdividing the household sector into workers and investors, we are able to investigate their relative 
income and wealth ratios for in the context of these two long-run equilibria, providing a testable link between asymptotic inequality and private debt accumulation.

  • Mathematical and Computational Finance Seminar
23 February 2017
16:00
to
17:30
Neofytos Rodosthenous
Abstract

We consider impatient decision makers when their assets' prices are in undesirable low regions for a significant amount of time, and they are risk averse to negative price jumps. We wish to study the unusual reactions of investors under such adverse market conditions. In mathematical terms, we study the optimal exercising of an American call option in a random time-horizon under spectrally negative Lévy models. The random time-horizon is modeled by an alarm of the so-called Omega default clock in insurance, which goes off when the cumulative amount of time spent by the asset price in an undesirable low region exceeds an independent exponential random time. We show that the optimal exercise strategies vary both quantitatively and qualitatively with the levels of impatience and nervousness of the investors, and we give a complete characterization of all optimal exercising thresholds. 

  • Mathematical and Computational Finance Seminar

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