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The role of industry, occupation, and location specific knowledge in the...

How do regions acquire the knowledge they need to diversify their economic activities? How does the migration of workers among firms and industries contribute to the diffusion of that knowledge? Here...

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Can Network Theory-based Targeting Increase Technology Adoption?....

In order to induce farmers to adopt a productive new agricultural technology, we apply simple and complex contagion diffusion models on rich social network data from 200 villages in Malawi to identify...

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Adaptive l1-regularization for short-selling control in portfolio selection....

We consider the l1-regularized Markowitz model, where a l1-penalty term is added to the objective function of the classical mean-variance one to stabilize the solution process, promoting sparsity in...

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Token Economics in Energy Systems: Concept, Functionality and Applications....

Traditional centralized energy systems have the disadvantages of difficult management and insufficient incentives. Blockchain is an emerging technology, which can be utilized in energy systems to...

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An analysis of high-frequency cryptocurrencies prices dynamics using...

This paper discusses the dynamics of intraday prices of twelve cryptocurrencies during last months' boom and bust. The importance of this study lies on the extended coverage of the cryptoworld,...

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Stock Price Correlation Coefficient Prediction with ARIMA-LSTM Hybrid Model....

Predicting the price correlation of two assets for future time periods is important in portfolio optimization. We apply LSTM recurrent neural networks (RNN) in predicting the stock price correlation...

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Physicists' approach to studying socio-economic inequalities: Can humans be...

A brief overview of the models and data analyses of income, wealth, consumption distributions by the physicists, are presented here. It has been found empirically that the distributions of income and...

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Generating VaR scenarios with product beta distributions. (arXiv:1808.02457v1...

We propose a new Monte Carlo simulation method to generate VaR scenarios for dependent risks on the basis of observed data. This is of particular interest for the construction of Internal Models under...

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Adapted $\theta$-Scheme and Its Error Estimates for Backward Stochastic...

In this paper we propose a new kind of high order numerical scheme for backward stochastic differential equations(BSDEs). Unlike the traditional $\theta$-scheme, we reduce truncation errors by taking...

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Pricing Financial Derivatives using Radial Basis Function generated Finite...

In this paper, we study the benefits of using polyharmonic splines and node layouts with smoothly varying density for developing robust and efficient radial basis function generated finite difference...

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Optimal stopping via deeply boosted backward regression. (arXiv:1808.02341v1...

In this note we propose a new approach towards solving numerically optimal stopping problems via boosted regression based Monte Carlo algorithms. The main idea of the method is to boost standard linear...

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A Machine Learning Framework for Stock Selection. (arXiv:1806.01743v2...

This paper demonstrates how to apply machine learning algorithms to distinguish good stocks from the bad stocks. To this end, we construct 244 technical and fundamental features to characterize each...

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Lattice Studies of Gerrymandering Strategies. (arXiv:1808.02826v1...

We propose three novel gerrymandering algorithms which incorporate the spatial distribution of voters with the aim of constructing gerrymandered, equal-population, connected districts. Moreover, we...

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Combining Independent Smart Beta Strategies for Portfolio Optimization....

Smart beta, also known as strategic beta or factor investing, is the idea of selecting an investment portfolio in a simple rule-based manner that systematically captures market inefficiencies, thereby...

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A generalized scheme for BSDEs based on derivative approximation and its...

In this paper we propose a generalized numerical scheme for backward stochastic differential equations(BSDEs). The scheme is based on approximation of derivatives via Lagrange interpolation. By...

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American Put Option pricing using Least squares Monte Carlo method under...

This paper explores alternative regression techniques in pricing American put options and compares to the least-squares method (LSM) in Monte Carlo implemented by Longstaff-Schwartz, 2001 which uses...

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The financial value of knowing the distribution of stock prices in discrete...

An explicit formula is derived for the value of weak information in a discrete time model that works for a wide range of utility functions including the logarithmic and power utility. We assume a...

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Network-based Referral Mechanism in a Crowdfunding-based Marketing Pattern....

Crowdfunding is gradually becoming a modern marketing pattern. By noting that the success of crowdfunding depends on network externalities, our research aims to utilize them to provide an applicable...

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Information Content of DSGE Forecasts. (arXiv:1808.02910v1 [econ.GN])

This paper examines the question whether information is contained in forecasts from DSGE models beyond that contained in lagged values, which are extensively used in the models. Four sets of forecasts...

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On smile properties of volatility derivatives and exotic products:...

We develop a method to study the implied volatility for exotic options and volatility derivatives with European payoffs such as VIX options. Our approach, based on Malliavin calculus techniques, allows...

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