Schedule for Spring 2020
Seminars are on Thursdays
Time: 4:10pm – 5:25pm
Location: Columbia University, 903 SSW (1255 Amsterdam Ave, between 121st and 122nd Street)
Organizers: Ruimeng Hu, Ioannis Karatzas, Marcel Nutz, Philip Protter
Xiaofei Shi (CMU)
“Liquidity Risk and Asset Pricing”
We study how the price dynamics of an asset depends on its “liquidity” – the ease with which can be traded. An equilibrium is achieved through a system of coupled forward-backward SDEs, whose solution turns out to be amenable to an asymptotic analysis for the practically relevant regime of large liquidity. We also calibrate our model to time series data of market prices and trading volume, and discuss how to leverage deep-learning techniques to obtain numerical solutions. (Based on joint works in progress with Agostino Capponi, Lukas Gonon, Johannes Muhle-Karbe).
Carsten Chong (EPFL)
“High-frequency analysis of SPDEs (and how it relates to rough volatility estimation)”
We consider the problem of estimating stochastic volatility for a class of parabolic stochastic PDEs. Assuming that the solution is observed at high temporal frequency, we use limit theorems for power variations to construct consistent nonparametric estimators and asymptotic confidence bounds for the integrated volatility process. Special attention is given to the case of multiplicative noise. We explain how the involved methods relate to estimation of rough volatility.
Nizar Touzi (Polytechnique)
“Path-dependent mean field optimal planning.”
Max Reppen (Princeton)
“A Mean Field Games Model for Cryptocurrency Mining.”
We propose a mean field game model to study the question of how centralization of reward and computational power occur in Bitcoin-like cryptocurrencies. Miners compete against each other for mining rewards by increasing their computational power. This leads to a novel mean field game of jump intensity control, which we solve explicitly for miners maximizing exponential utility, and handle numerically in the case of miners with power utilities. We show that the heterogeneity of their initial wealth distribution leads to greater imbalance of the reward distribution, or a “rich get richer” effect. This concentration phenomenon is aggravated by a higher bitcoin price, and reduced by competition. Additionally, an advantaged miner with cost advantages such as access to cheaper electricity contributes a significant amount of computational power in equilibrium, unaffected by competition.
No seminar (Berkeley-Columbia meeting)
Jose Scheinkman (Columbia)
“Menu costs and the volatility of inflation” (joint with Makoto Nirei, University of Tokyo)
We present a state-dependent equilibrium pricing model that generates inflation rate fluctuations from idiosyncratic shocks to the cost of price changes of individual firms. A firm’s nominal price increase lowers other firms’ relative prices, thereby inducing further nominal price increases. We first study a mean-field limit where the equilibrium is characterized by a variational inequality and exhibits a constant rate of inflation. We use the limit model to show that in the presence of a large but finite number n of firms the snowball effect of repricing causes fluctuations to the aggregate price level and these fluctuations converge to zero slowly as n grows. The fluctuations caused by this mechanism are larger when the density of firms at the repricing threshold is high, and the density at the threshold is high when the trend inflation level is high. However a calibration to US data shows that this mechanism is quantitatively important even at modest levels of trend inflation and can account for the positive relationship between inflation level and volatility that has been observed empirically.
Yerkin Kitapbayev (NCSU)
No seminar (Spring Recess)
Matteo Basei (EDF)
Xunyu Zhou (Columbia)
Jaksa Cvitanic (Caltech)
Jim Gatheral (Baruch)
Semyon Malamud (EPFL)
Giulia Livieri (Pisa)