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Rabee Tourky

Publications and source records attributed to Rabee Tourky.

3 recordsLinked to original sources

The one-period Kyle model has one equilibrium

Let $V$ and $U$ be independent standard normal random variables. For each Borel-measurable function $\phi\colon\mathbb{R}\to\mathbb{R}$, let $P_\phi\colon\mathbb{R}\to\mathbb{R}$ be a Borel version of the inverse regression $y\mapsto\mathbb{E}[V\mid\phi(V)+U=y]$. We prove that $\phi(v)\in\operatorname*{arg\,max}_{x\in\mathbb{R}} \mathbb{E}[(v-P_\phi(x+U))x]$ for every $v\in\mathbb{R}$ if and only if $\phi=\operatorname{id}_{\mathbb{R}}$. The rigidity result implies that the one-period Gaussian Kyle (1985) insider-trading model has a unique Borel-measurable equilibrium strategy, namely Kyle's affine strategy. Building on preliminary results of McLennan, Monteiro, and Tourky (2017), the proof establishes that, at equilibrium, the total expected loss of noise traders attains a sharp universal upper bound and that any strategy attaining this bound must be affine almost everywhere.

math.PR

The optimal sub-Gaussian normalisation for randomised monotone functions

Let $\mathcal{M}$ denote the class of randomised monotone functions on $\mathbb{R}$ with values in $[0,1]$, and let $U_{\mathcal{M}}\colon \mathbb{R}_+\to \mathbb{R}_+$ be the minimal function for which $$ \mathbb{P}\left\{ \sqrt{\eta_f}\, \sup_{t\in\mathbb{R}} \left| f_Z(t) - \Exf{f_Z(t)} \right| \ge \varepsilon\sqrt{U_{\mathcal{M}}(\eta_f)} \right\} \le 2\e^{-2\varepsilon^2} $$ holds for every member $f_Z$ of $\mathcal{M}$ with finite effective sample size $\eta_f$ and every positive $\varepsilon$. We prove that for every $x> 1$, $$ \left| \sqrt{U_{\mathcal{M}}(x)} - \sqrt{\log_4 x} \right| \le 2 \min\!\left\{ 1,\, \frac{2 \ln(\e + \ln x)}{\sqrt{\ln x}} \right\}\,. $$ The optimal adjustment $\sqrt{U_{\mathcal{M}}(x)}$ matches $\frac{1}{\sqrt{2\ln 2}}\sqrt{\ln x}$ for all $x>1$, with residuals bounded as above.

math.PR