Risk-Sensitive Compact Decision Trees for Autonomous Execution in Presence of...
We demonstrate an application of risk-sensitive reinforcement learning to optimizing execution in limit order book markets. We represent taking order execution decisions based on limit order book...
View ArticleImplied and Realized Volatility: A Study of Distributions and the...
We study distributions of realized variance (squared realized volatility) and squared implied volatility, as represented by VIX and VXO indices. We find that Generalized Beta distribution provide the...
View ArticleTransaction Cost Analytics for Corporate Bonds. (arXiv:1903.09140v2...
With the rise of the electronic trading, corporate bond traders have access to data information of past trades. As a first step to automation, they have to start monitoring their own trades, and using...
View ArticleThe varying importance of extrinsic factors in the success of startup...
We address the issue of the factors driving startup success in raising funds. Using the popular and public startup database Crunchbase, we explicitly take into account two extrinsic characteristics of...
View ArticleLearning from Others in the Financial Market. (arXiv:1906.03201v1 [q-fin.GN])
Prediction problems in finance go beyond estimating the unknown parameters of a model (e.g of expected returns). This is because such a model would have to include knowledge about the market...
View ArticleTensor Processing Units for Financial Monte Carlo. (arXiv:1906.02818v1 [cs.DC])
Monte Carlo methods are core to many routines in quantitative finance such as derivatives pricing, hedging and risk metrics. Unfortunately, Monte Carlo methods are very computationally expensive when...
View ArticleA comparison principle between rough and non-rough Heston models - with...
We present a number of related comparison results, which allow to compare moment explosion times, moment generating functions and critical moments between rough and non-rough Heston models of...
View ArticleBattling Antibiotic Resistance: Can Machine Learning Improve Prescribing?....
Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine...
View ArticleMarket Implementation of Multiple-Arrival Multiple-Deadline Differentiated...
An increasing concern in power systems is on how to elicit flexibilities in demands for better supply/demand balance. To this end, several differentiated energy services have been put forward, wherein...
View ArticleFeature Engineering for Mid-Price Prediction with Deep Learning....
Mid-price movement prediction based on limit order book (LOB) data is a challenging task due to the complexity and dynamics of the LOB. So far, there have been very limited attempts for extracting...
View ArticleMarkov cubature rules for polynomial processes. (arXiv:1707.06849v3 [math.PR]...
We study discretizations of polynomial processes using finite state Markov processes satisfying suitable moment matching conditions. The states of these Markov processes together with their transition...
View ArticleSemimartingale theory of monotone mean--variance portfolio allocation....
We study dynamic optimal portfolio allocation for monotone mean--variance preferences in a general semimartingale model. Armed with new results in this area we revisit the work of Cui, Li, Wang and Zhu...
View ArticleLearned Sectors: A fundamentals-driven sector reclassification project....
Market sectors play a key role in the efficient flow of capital through the modern Global economy. We analyze existing sectorization heuristics, and observe that the most popular - the GICS (which...
View ArticleAutomation and occupational mobility: A data-driven network model....
Many existing jobs are prone to automation, but since new technologies also create new jobs it is crucial to understand job transitions. Based on empirical data we construct an occupational mobility...
View ArticleMachine learning with kernels for portfolio valuation and risk management....
We introduce a computational framework for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the replicating martingale of a portfolio from a finite...
View ArticleThe Effects of the Introduction of Bitcoin Futures on the Volatility of...
This paper investigates the effects of the launch of Bitcoin futures on the intraday volatility of Bitcoin. Based on one-minute price data collected from four cryptocurrency exchanges, we first examine...
View ArticleDeep learning calibration of option pricing models: some pitfalls and...
Recent progress in the field of artificial intelligence, machine learning and also in computer industry resulted in the ongoing boom of using these techniques as applied to solving complex tasks in...
View ArticleAn optimal transport problem with backward martingale constraints motivated...
We study a single-period optimal transport problem on $\mathbb{R}^2$ with a covariance-type cost function $c(x,y) = (x_1-y_1)(x_2-y_2)$ and a backward martingale constraint. We show that a transport...
View ArticleA sensitivity analysis of the long-term expected utility of optimal...
This paper discusses the sensitivity of the long-term expected utility of optimal portfolios for an investor with constant relative risk aversion. Under an incomplete market given by a factor model, we...
View ArticleA Top-Down Approach for the Multiple Exercises and Valuation of Employee...
We propose a new framework to value employee stock options (ESOs) that captures multiple exercises of different quantities over time. We also model the ESO holder's job termination risk and incorporate...
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