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Fragmentation and inefficiencies in US equity markets: Evidence from the Dow...

Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in 2016 from the vantage point of a...

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Learning Threshold-Type Investment Strategies with Stochastic Gradient...

In online portfolio optimization the investor makes decisions based on new, continuously incoming information on financial assets (typically their prices). In our study we consider a learning...

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Existence of affine realizations for L\'evy term structure models....

We investigate the existence of affine realizations for term structure models driven by L\'evy processes. It turns out that we obtain more severe restrictions on the volatility than in the classical...

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Optimal transport on large networks a practitioner guide. (arXiv:1907.02320v1...

This article presents a set of tools for the modeling of a spatial allocation problem in a large geographic market and gives examples of applications. In our settings, the market is described by a...

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Sensitivity of Estimation Precision to Moments with an Application to a Model...

This paper introduces measures for how each moment contributes to the precision of the parameter estimates in GMM settings. For example, one of the measures asks what would happen to the variance of...

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Machine learning and behavioral economics for personalized choice...

Behavioral economics changed the way we think about market participants and revolutionized policy-making by introducing the concept of choice architecture. However, even though effective on the level...

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Emergent inequality and endogenous dynamics in a simple behavioral...

Standard macroeconomic models assume that households are rational in the sense that they are perfect utility maximizers, and explain economic dynamics in terms of shocks that drive the economy away...

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Elicitability and Identifiability of Systemic Risk Measures and other...

This paper is concerned with a two-fold objective. Firstly, we establish elicitability and identifiability results for systemic risk measures introduced in Feinstein, Rudloff and Weber (2017)....

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A Model of Presidential Debates. (arXiv:1907.01362v1 [econ.GN])

Presidential debates are thought to provide an important public good by revealing information on candidates to voters. However, this may not always be the case. We consider an endogenous model of...

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Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for...

Portfolio allocation is crucial for investment companies. However, getting the best strategy in a complex and dynamic stock market is challenging. In this paper, we propose a novel Adaptive Deep...

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Forecasting security's volatility using low-frequency historical data,...

Low-frequency historical data, high-frequency historical data and option data are three major sources, which can be used to forecast the underlying security's volatility. In this paper, we propose two...

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The evolving liaisons between the transaction networks of Bitcoin and its...

Cryptocurrencies are distributed systems that allow exchanges of native tokens among participants, or the exchange of such tokens for fiat currencies in markets external to these public ledgers. The...

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Existence of L\'evy term structure models. (arXiv:1907.03561v1 [q-fin.MF])

L\'evy driven term structure models have become an important subject in the mathematical finance literature. This paper provides a comprehensive analysis of the L\'evy driven Heath-Jarrow-Morton type...

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An intelligent financial portfolio trading strategy using deep Q-learning....

A goal of financial portfolio trading is maximizing the trader's utility by allocating capital to assets in a portfolio in the investment horizon. Our study suggests an approach for deriving an...

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Will a Large Economy Be Stable?. (arXiv:1901.09629v3 [physics.soc-ph] UPDATED)

We study networks of firms in which inputs for production are not easily substitutable, as in several real-world supply chains. Relying on results from Random Matrix Theory, we argue that such networks...

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Optimal Stopping and Utility in a Simple Model of Unemployment Insurance....

Managing unemployment is one of the key issues in social policies. Unemployment insurance schemes are designed to cushion the financial and morale blow of loss of job but also to encourage the...

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Improving Detection of Credit Card Fraudulent Transactions using Generative...

In this study, we employ Generative Adversarial Networks as an oversampling method to generate artificial data to assist with the classification of credit card fraudulent transactions. GANs is a...

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Systemic Risk and Heterogeneous Interbank Network. (arXiv:1907.03082v1...

We study the system of heterogeneous interbank lending and borrowing based on the relative average of log-capitalization through the linear combination of the average within groups and the ensemble...

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Artificial Intelligence Alter Egos: Who benefits from Robo-investing?....

Artificial intelligence, or AI, enhancements are increasingly shaping our daily lives. Financial decision-making is no exception to this. We introduce the notion of AI Alter Egos, which are shadow...

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Financial Time Series Data Processing for Machine Learning....

This article studies the financial time series data processing for machine learning. It introduces the most frequent scaling methods, then compares the resulting stationarity and preservation of useful...

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