PT Symmetry, Non-Gaussian Path Integrals, and the Quantum Black-Scholes...
The Accardi-Boukas quantum Black-Scholes framework, provides a means by which one can apply the Hudson-Parthasarathy quantum stochastic calculus to problems in finance. Solutions to these equations can...
View ArticleMarket Impact: A Systematic Study of the High Frequency Options Market....
This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of...
View ArticleDivestment may burst the carbon bubble if investors' beliefs tip to...
To achieve the ambitious aims of the Paris climate agreement, the majority of fossil-fuel reserves needs to remain underground. As current national government commitments to mitigate greenhouse gas...
View ArticleRobust Asset Allocation for Robo-Advisors. (arXiv:1902.07449v1 [q-fin.PM])
In the last few years, the financial advisory industry has been impacted by the emergence of digitalization and robo-advisors. This phenomenon affects major financial services, including wealth...
View ArticleMatching Refugees to Host Country Locations Based on Preferences and...
Facilitating the integration of refugees has become a major policy challenge in many host countries in the context of the global displacement crisis. One of the first policy decisions host countries...
View ArticleWhat is the central bank of Wikipedia?. (arXiv:1902.07920v1 [cs.SI])
We analyze the influence and interactions of 60 largest world banks for 195 world countries using the reduced Google matrix algorithm for the English Wikipedia network with 5 416 537 articles. While...
View ArticleStacking with Neural network for Cryptocurrency investment....
Predicting the direction of assets have been an active area of study and a difficult task. Machine learning models have been used to build robust models to model the above task. Ensemble methods is one...
View ArticleDeep Adaptive Input Normalization for Price Forecasting using Limit Order...
Deep Learning (DL) models can be used to tackle time series analysis tasks with great success. However, the performance of DL models can degenerate rapidly if the data are not appropriately normalized....
View ArticleMachine Learning for Yield Curve Feature Extraction: Application to Illiquid...
This paper studies an application of machine learning in extracting features from the historical market implied corporate bond yields. We consider an example of a hypothetical illiquid fixed income...
View ArticleAn Optimal Extraction Problem with Price Impact. (arXiv:1812.01270v1 [math.OC])
A price-maker company extracts an exhaustible commodity from a reservoir, and sells it instantaneously in the spot market. In absence of any actions of the company, the commodity's spot price evolves...
View ArticleMachine Learning for Yield Curve Feature Extraction: Application to Illiquid...
This paper studies an application of machine learning in extracting features from the historical market implied corporate bond yields. We consider an example of a hypothetical illiquid fixed income...
View ArticleOptimally stopping at a given distance from the ultimate supremum of a...
We consider the optimal prediction problem of stopping a spectrally negative L\'evy process as close as possible to a given distance $b \geq 0$ from its ultimate supremum, under a squared error penalty...
View ArticleA Game Theoretic Setting of Capitation Versus Fee-For-Service Payment...
We aim to determine whether a game-theoretic model between an insurer and a healthcare practice yields a predictive equilibrium that incentivizes either player to deviate from a fee-for-service to...
View ArticleThe Black-Scholes Equation in Presence of Arbitrage. (arXiv:1904.11565v1...
We apply Geometric Arbitrage Theory to obtain results in Mathematical Finance, which do not need stochastic differential geometry in their formulation. First, for a generic market dynamics given by a...
View ArticleMultiple Benefits through Smart Home Energy Management Solutions -- A...
From both global and local perspectives, there are strong reasons to promote energy efficiency. These reasons have prompted leaders in the European Union (EU) and countries of the Middle East and North...
View ArticleGated deep neural networks for implied volatility surfaces....
In this paper, we propose a gated deep neural network model to predict implied volatility surfaces. Conventional financial conditions and empirical evidence related to the implied volatility are...
View ArticleEmpirical facts characterizing banking crises: an analysis via binary time...
Various works have already showed that common shocks and cross-country financial linkages caused the banking systems of several countries to be highly interconnected with the result that during bad...
View ArticleIdentification of Key Companies for International Profit Shifting in the...
In the global economy, the intermediate companies owned by multinational corporations are becoming an important policy issue as they are likely to cause international profit shifting and diversion of...
View ArticleRough volatility of Bitcoin. (arXiv:1904.12346v1 [q-fin.ST])
Recent studies have found that the log-volatility of asset returns exhibit roughness. This study investigates roughness or the anti-persistence of Bitcoin volatility. Using the multifractal detrended...
View ArticleMean-variance portfolio selection under Volterra Heston model....
Motivated by empirical evidence for rough volatility models, this paper investigates the continuous-time mean-variance (MV) portfolio selection under Volterra Heston model. Due to the non-Markovian and...
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