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Financial option insurance. (arXiv:1708.02180v1 [q-fin.RM])

The option is a financial derivative, which is regularly employed in reducing the risk of its underlying securities. However, investing in option is still risky. Such risk becomes much severer for...

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Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive...

Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among...

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Model Misspecification in ABC: Consequences and Diagnostics....

We analyze the behavior of approximate Bayesian computation (ABC) when the model generating the simulated data differs from the actual data generating process; i.e., when the data simulator in ABC is...

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Machine learning in sentiment reconstruction of the simulated stock market....

In this paper we continue the study of the simulated stock market framework defined by the driving sentiment processes. We focus on the market environment driven by the buy/sell trading sentiment...

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Optimal Learning and Ellsberg's Urns. (arXiv:1708.01890v1 [q-fin.EC])

We consider the dynamics of learning under ambiguity when learning is costly and is chosen optimally. The setting is Ellsberg's two-urn thought experiment modified by allowing the agent to postpone her...

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On optimal periodic dividend strategies for L\'evy risk processes....

We revisit the optimal periodic dividend problem where dividend payments can only be made at the jump times of an independent Poisson process. Recent results have shown, in the dual (spectrally...

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A Two Factor Forward Curve Model with Stochastic Volatility for Commodity...

We describe a model for evolving commodity forward prices that incorporates three important dynamics which appear in many commodity markets: mean reversion in spot prices, decorrelation of moves in...

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Turbocharging Monte Carlo pricing for the rough Bergomi model....

The rough Bergomi model, introduced by Bayer, Friz and Gatheral [Quant. Finance 16(6), 887-904, 2016], is one of the recent rough volatility models that are consistent with the stylised fact of implied...

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Cardinality constrained portfolio selection via factor models....

In this paper we propose and discuss different 0-1 linear models in order to solve the cardinality constrained portfolio problem by using factor models. Factor models are used to build portfolios to...

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Nonlinear price impact from linear models. (arXiv:1708.02411v1 [q-fin.TR])

The impact of trades on asset prices is a crucial aspect of market dynamics for academics, regulators and practitioners alike. Recently, universal and highly nonlinear master curves were observed for...

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Derivative-Based Optimization with a Non-Smooth Simulated Criterion....

Indirect inference requires simulating realizations of endogenous variables from the model under study. When the endogenous variables are discontinuous functions of the model parameters, the resulting...

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Sequential testing for structural stability in approximate factor models....

We develop a monitoring procedure to detect a change in a large approximate factor model. Our statistics are based on a well-known property of the $% \left( r+1\right) $-th eigenvalue of the sample...

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Order Flows and Limit Order Book Resiliency on the Meso-Scale....

We investigate the behavior of limit order books on the meso-scale motivated by order execution scheduling algorithms. To do so we carry out empirical analysis of the order flows from market and limit...

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Risk Constrained Trading Strategies for Stochastic Generation with a...

Due to the limited predictability of wind power and other stochastic generation, trading this energy in competitive electricity markets is challenging. This paper derives revenue-maximising and...

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Exact probability distribution function for the volatility of cumulative...

In this paper we study the volatility and its probability distribution function for the cumulative production based on the experience curve hypothesis. This work presents a generalization of the study...

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Conditional-Mean Hedging Under Transaction Costs in Gaussian Models....

We consider so-called regular invertible Gaussian Volterra processes and derive a formula for their prediction laws. Examples of such processes include the fractional Brownian motions and the mixed...

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Sure profits via flash strategies and the impossibility of predictable jumps....

In an arbitrage-free financial market, asset prices should not exhibit jumps of a predictable magnitude at predictable times. We provide a rigorous formulation of this result in a fully general...

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Decoding Stock Market with Quant Alphas. (arXiv:1708.02984v1 [q-fin.PM])

We give an explicit algorithm and source code for extracting expected returns for stocks from expected returns for alphas. Our algorithm altogether bypasses combining alphas with weights into "alpha...

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On the overestimation of the largest eigenvalue of a covariance matrix....

In this paper, we use a new approach to prove that the largest eigenvalue of the sample covariance matrix of a normally distributed vector is bigger than the true largest eigenvalue with probability 1...

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Oil economy phase plot: a physical analogy. (arXiv:1708.03533v1 [q-fin.GN])

A phase plot of the oil economy is built using the literature data of world oil production, price, and EROEI (Energy Returned on Energy Invested). An analogy between the oil economy and the Benard...

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