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Jun 30, 2018
06/18

by
Amirhossein Sobhani; Mariyan Milev

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In this Article, a fast numerical numerical algorithm for pricing discrete double barrier option is presented. According to Black-Scholes model, the price of option in each monitoring date can be evaluated by a recursive formula upon the heat equation solution. These recursive solutions are approximated by using Legendre multiwavelets as orthonormal basis functions and expressed in operational matrix form. The most important feature of this method is that its CPU time is nearly invariant when...

Topics: Quantitative Finance, Mathematical Finance, Computational Finance

Source: http://arxiv.org/abs/1703.09129

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0.0

Jun 30, 2018
06/18

by
Giulia Livieri; Saad Mouti; Andrea Pallavicini; Mathieu Rosenbaum

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It has been recently shown that spot volatilities can be very well modeled by rough stochastic volatility type dynamics. In such models, the log-volatility follows a fractional Brownian motion with Hurst parameter smaller than 1/2. This result has been established using high frequency volatility estimations from historical price data. We revisit this finding by studying implied volatility based approximations of the spot volatility. Using at-the-money options on the S&P500 index with short...

Topics: Mathematical Finance, Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1702.02777

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1.0

Jun 30, 2018
06/18

by
T. A. McWalter; R. Rudd; J. Kienitz; E. Platen

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Quantization techniques have been applied in many challenging finance applications, including pricing claims with path dependence and early exercise features, stochastic optimal control, filtering problems and efficient calibration of large derivative books. Recursive Marginal Quantization of the Euler scheme has recently been proposed as an efficient numerical method for evaluating functionals of solutions of stochastic differential equations. This method involves recursively quantizing the...

Topics: Quantitative Finance, Mathematical Finance, Computational Finance

Source: http://arxiv.org/abs/1701.02681

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0.0

Jun 30, 2018
06/18

by
Matteo Gardini; Marco Diana

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The article describes the algorithm used to define the electricity price in day-ahead and itraday energy markets in Italy. Details of Matlab implementation of one of its simplified versions, capable of producing good results in a extremely short time, are then provided and numerical results are discussed.

Topics: Quantitative Finance, Mathematical Finance, Computational Finance

Source: http://arxiv.org/abs/1703.09782

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3.0

Jun 30, 2018
06/18

by
Alexander Lipton

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We introduce blockchains and distributed ledgers and describe their potential applications to money and banking. The analysis compares public and private ledgers and outlines the suitability of various types of ledgers for different purposes. Furthermore, a few historical prototypes of blockchains and distributed ledgers are presented, and results of their hard forking are illustrated. Next, some potential applications of distributed ledgers to trading, clearing and settlement, payments, trade...

Topics: Quantitative Finance, General Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.01505

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1.0

Jun 30, 2018
06/18

by
Chunfa Wang

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The COS method proposed in Fang and Oosterlee (2008), although highly efficient, may lack robustness for a number of cases. In this paper, we present a Stable pricing of call options based on Fourier cosine series expansion. The Stability of the pricing methods is demonstrated by error analysis, as well as by a series of numerical examples, including the Heston stochastic volatility model, Kou jump-diffusion model, and CGMY model.

Topics: Quantitative Finance, Mathematical Finance, Computational Finance

Source: http://arxiv.org/abs/1701.00886

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Jun 30, 2018
06/18

by
Matthias Raddant; Dror Y. Kenett

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The global financial system is highly complex, with cross-border interconnections and interdependencies. In this highly interconnected environment, local financial shocks and events can be easily amplified and turned into global events. This paper analyzes the dependencies among nearly 4,000 stocks from 15 countries. The returns are normalized by the estimated volatility using a GARCH model and a robust regression process estimates pairwise statistical relationships between stocks from...

Topics: General Finance, Statistical Finance, Economics, Quantitative Finance

Source: http://arxiv.org/abs/1704.01028

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Jun 30, 2018
06/18

by
Leonardo dos Santos Pinheiro; Flavio Codeco COelho

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This work develops an agent-based model for the study of how the leverage through the use of repurchase agreements can function as a mechanism for the propagation and amplification of financial shocks in a financial system. Based on the analysis of financial intermediaries in the repo and interbank lending markets during the 2007-08 financial crisis we develop a model that can be used to simulate the dynamics of financial contagion.

Topics: Quantitative Finance, General Finance, Computational Finance

Source: http://arxiv.org/abs/1703.07513

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1.0

Jun 30, 2018
06/18

by
Kasper Larsen; Halil Mete Soner; Gordan Žitković

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We introduce the notion of a conditional Davis price and study its properties. Our ultimate goal is to use utility theory to price non-replicable contingent claims in the case when the investor's portfolio already contains a non-replicable component. We show that even in the simplest of settings - such as Samuelson's model - conditional Davis prices are typically not unique and form a non-trivial subinterval of the set of all no-arbitrage prices. Our main result characterizes this set and...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.02087

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1.0

Jun 30, 2018
06/18

by
Sabrina Mulinacci

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In this paper we study the distributional properties of a vector of lifetimes in which each lifetime is modeled as the first arrival time between an idiosyncratic shock and a common systemic shock. Despite unlike the classical multidimensional Marshall-Olkin model here only a unique common shock affecting all the lifetimes is assumed, some dependence is allowed between each idiosyncratic shock arrival time and the systemic shock arrival time. The dependence structure of the resulting...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1704.02160

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1.0

Jun 30, 2018
06/18

by
Ralph Rudd; Thomas A. McWalter; Joerg Kienitz; Eckhard Platen

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Recursive Marginal Quantization (RMQ) allows fast approximation of solutions to stochastic differential equations in one-dimension. When applied to two factor models, RMQ is inefficient due to the fact that the optimization problem is usually performed using stochastic methods, e.g., Lloyd's algorithm or Competitive Learning Vector Quantization. In this paper, a new algorithm is proposed that allows RMQ to be applied to two-factor stochastic volatility models, which retains the efficiency of...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1704.06388

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Jun 30, 2018
06/18

by
Jacob Lundgren; Yuri Shpolyanskiy

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The method and characteristics of several approaches to the pricing of discretely monitored arithmetic Asian options on stocks with discrete, absolute dividends are described. The contrast between method behaviors for options with an Asian tail and those with monitoring throughout their lifespan is emphasized. Rates of convergence are confirmed, but greater focus is put on actual performance in regions of accuracy which are realistic for use by practitioners. A hybrid approach combining...

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1702.00994

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1.0

Jun 30, 2018
06/18

by
Friedrich Hubalek; Paul Krühner; Thorsten Rheinländer

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We study a parsimonious but non-trivial model of the latent limit order book where orders get placed with a fixed displacement from a center price process, i.e.\ some process in-between best bid and best ask, and get executed whenever this center price reaches their level. This mechanism corresponds to the fundamental solution of the stochastic heat equation with multiplicative noise for the relative order volume distribution. We classify various types of trades, and introduce the trading...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1701.00993

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1.0

Jun 30, 2018
06/18

by
Vladimir Vovk; Glenn Shafer

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Without probability theory, we define classes of supermartingales, martingales, and semimartingales in idealized financial markets with continuous price paths. This allows us to establish probability-free versions of a number of standard results in martingale theory, including the Dubins-Schwarz theorem, the Girsanov theorem, and results concerning the It\^o integral. We also establish the existence of an equity premium and a CAPM relationship in this probability-free setting.

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.08715

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4.0

Jun 30, 2018
06/18

by
Gautier Marti; Frank Nielsen; Mikołaj Bińkowski; Philippe Donnat

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This document is a preliminary version of an in-depth review on the state of the art of clustering financial time series and the study of correlation networks. This preliminary document is intended for researchers in this field so that they can feedback to allow amendments, corrections and addition of new material unknown to the authors of this review. The aim of the document is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1703.00485

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6.0

Jun 30, 2018
06/18

by
Zachary Feinstein

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Gringotts Wizarding Bank is well known as the only financial institution in all of the Wizarding UK as documented in the works recounting the heroics of Harry Potter. The concentration of power and wealth in this single bank needs to be weighed against the financial stability of the entire Wizarding economy. This study will consider the impact to financial risk of breaking up Gringotts Wizarding Bank into five component pieces, along the lines of the Glass-Steagall Act in the United States. The...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1703.10469

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1.0

Jun 30, 2018
06/18

by
G. Ruiz López; A. Fernández de Marcos

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We provide evidence that cumulative distributions of absolute normalized returns for the $100$ American companies with the highest market capitalization, uncover a critical behavior for different time scales $\Delta t$. Such cumulative distributions, in accordance with a variety of complex --and financial-- systems, can be modeled by the cumulative distribution functions of $q$-Gaussians, the distribution function that, in the context of nonextensive statistical mechanics, maximizes a...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1702.06191

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0.0

Jun 30, 2018
06/18

by
Takuji Arai; Yuto Imai

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We derive an explicit closed-form representation of mean-variance hedging strategies for models whose asset price follows an exponential additive process. Our representation is given in terms of Malliavin calculus for L\'evy processes. In addition, we develop an approximation method to compute mean-variance hedging strategies for exponential L\'evy models, and illustrate numerical results.

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.07556

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2.0

Jun 30, 2018
06/18

by
Victor Haghani; Richard Dewey

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What would you do if you were invited to play a game where you were given \$25 and allowed to place bets for 30 minutes on a coin that you were told was biased to come up heads 60% of the time? This is exactly what we did, gathering 61 young, quantitatively trained men and women to play this game. The results, in a nutshell, were that the majority of these 61 players did not place their bets very well, displaying a broad panoply of behaviorial and cognitive biases. About 30% of the subjects...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1701.01427

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0.0

Jun 30, 2018
06/18

by
Stéphane Crépey; Shiqi Song

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We prove that the default times (or any of their minima) in the dynamic Gaussian copula model of Cr{\'e}pey, Jeanblanc, and Wu (2013) are invariance times in the sense of Cr{\'e}pey and Song (2017), with related invariance probability measures different from the pricing measure. This reflects a departure from the immersion property, whereby the default intensities of the surviving names and therefore the value of credit protection spike at default times. These properties are in line with the...

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1702.03232

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1.0

Jun 30, 2018
06/18

by
Wei Lin; Shenghong Li; Shane Chern

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In this paper, we relax the power parameter of instantaneous variance and develop a new stochastic volatility plus jumps model that generalize the Heston model and 3/2 model as special cases. This model has two distinctive features. First, we do not restrict the new parameter, letting the data speak as to its direction. The Generalized Methods of Moments suggests that the newly added parameter is to create varying volatility fluctuation in different period discovered in financial market....

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.06020

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4.0

Jun 30, 2018
06/18

by
Yuri Biondi; Feng Zhou

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Interbank lending and borrowing occur when financial institutions seek to settle and refinance their mutual positions over time and circumstances. This interactive process involves money creation at the aggregate level. Coordination mismatch on interbank credit may trigger systemic crises. This happened when, since summer 2007, interbank credit coordination did not longer work smoothly across financial institutions, eventually requiring exceptional monetary policies by central banks, and...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1702.08774

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Jun 30, 2018
06/18

by
Seyed Amir Hejazi; Kenneth R. Jackson; Guojun Gan

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Variable Annuity (VA) products expose insurance companies to considerable risk because of the guarantees they provide to buyers of these products. Managing and hedging these risks requires insurers to find the value of key risk metrics for a large portfolio of VA products. In practice, many companies rely on nested Monte Carlo (MC) simulations to find key risk metrics. MC simulations are computationally demanding, forcing insurance companies to invest hundreds of thousands of dollars in...

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1701.04134

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Jun 30, 2018
06/18

by
Tianran Geng; Thaleia Zariphopoulou

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We present turnpike-type results for the risk tolerance function in an incomplete market setting under time-monotone forward performance criteria. We show that, contrary to the classical case, the temporal and spatial limits do not coincide. We also show that they depend directly on the left- and right-end of the support of an underlying measure, which is used to construct the forward performance criterion. We provide examples with discrete and continuous measures, and discuss the asymptotic...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.05649

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0.0

Jun 30, 2018
06/18

by
Jiro Akahori; Xiaoming Song; Tai-Ho Wang

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Instantaneous volatility of logarithmic return in the lognormal fractional SABR model is driven by the exponentiation of a correlated fractional Brownian motion. Due to the mixed nature of driving Brownian and fractional Brownian motions, probability density for such a model is less studied in the literature. We show in this paper a bridge representation for the joint density of the lognormal fractional SABR model in a Fourier space. Evaluating the bridge representation along a properly chosen...

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1702.08081

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0.0

Jun 30, 2018
06/18

by
Samuel Drapeau; Peng Luo; Dewen Xiong

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We characterize a class of fully coupled forward backward stochastic differential equations in terms of optimal maximal sub-solutions of BSDEs. We present the application thereof in utility optimization with random endowment under probability and discounting uncertainty. We provide some explicit examples and show how to quantify the costs of incompleteness when using utility indifference pricing.

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.02694

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1.0

Jun 30, 2018
06/18

by
Daniel Lacker; Thaleia Zariphopoulou

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We analyze a family of portfolio management problems under relative performance criteria, for fund managers having CARA or CRRA utilities and trading in a common time horizon in log-normal markets. We construct explicit time-independent equilibrium strategies for both the finite population games and the corresponding mean field games, which we show are unique in the class of time-independent equilibria. In the CARA case, competition drives agents to invest more in the risky asset than they...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.07685

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0.0

Jun 30, 2018
06/18

by
Jean-Pierre Fouque; Ning Ning

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In this paper, we propose the uncertain volatility models with stochastic bounds. Like the regular uncertain volatility models, we know only that the true model lies in a family of progressively measurable and bounded processes, but instead of using two deterministic bounds, the uncertain volatility fluctuates between two stochastic bounds generated by its inherent stochastic volatility process. This brings better accuracy and is consistent with the observed volatility path such as for the VIX...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.05036

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9.0

Jun 30, 2018
06/18

by
Francisco Salas-Molina; Juan A. Rodríguez-Aguilar; Pablo Díaz-García

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Selecting the best policy to keep the balance between what a company holds in cash and what is placed in alternative investments is by no means straightforward. We here introduce PyCaMa, a Python module for multiobjective cash management based on linear programming that allows to derive optimal policies for cash management with multiple bank accounts in terms of both cost and risk of policies.

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1702.05005

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2.0

Jun 30, 2018
06/18

by
T. T. Chen; B. Zheng; Y. Li; X. F. Jiang

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Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of the agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogenous personal...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1703.06840

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Jun 30, 2018
06/18

by
Takanori Adachi; Yoshihiro Ryu

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We generalize the notion of monetary value measures developed with category theory in [Adachi, 2014] by extending their base category from the category \c{hi} to the category of probability spaces Prob introduced in [Adachi and Ryu, 2016].

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.01175

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Jun 30, 2018
06/18

by
Sachapon Tungsong; Fabio Caccioli; Tomaso Aste

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We report on time-varying network connectedness within three banking systems: North America, the EU, and ASEAN. The original method by Diebold and Yilmaz is improved by using exponentially weighted daily returns and ridge regularization on vector autoregression (VAR) and forecast error variance decomposition (FEVD). We compute the total network connectedness for each of the three banking systems, which quantifies regional uncertainty. Results over rolling windows of 300 days during the period...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1702.05944

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Jun 30, 2018
06/18

by
Opeoluwa Banwo; Fabio Caccioli; Paul Harrald; Francesca Medda

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We consider a model of financial contagion in a bipartite network of assets and banks recently introduced in the literature, and we study the effect of power law distributions of degree and balance-sheet size on the stability of the system. Relative to the benchmark case of banks with homogeneous degrees and balance-sheet sizes, we find that if banks have a power-law degree distribution the system becomes less robust with respect to the initial failure of a random bank, and that targeted shocks...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1704.06791

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0.0

Jun 30, 2018
06/18

by
Juozas Vaicenavicius

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Optimal liquidation of an asset with unknown constant drift and stochastic regime-switching volatility is studied. The uncertainty about the drift is represented by an arbitrary probability distribution, the stochastic volatility is modelled by $m$-state Markov chain. Using filtering theory, an equivalent reformulation of the original problem as a four-dimensional optimal stopping problem is found and then analysed by constructing approximating sequences of three-dimensional optimal stopping...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1701.08579

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0.0

Jun 30, 2018
06/18

by
Rahul Madhavan; Ankit Baraskar

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We have created a framework for analyzing subscription based businesses in terms of a unified metric which we call SCV (single customer value). The major advance in this paper is to model customer churn as an exponential decay variable, which directly follows from experimental data relating to subscription based businesses. This Bayesian probabilistic model was used to compute an expected value for the revenue contribution of a single user. We obtain an exact closed-form solution for the...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1704.05729

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1.0

Jun 30, 2018
06/18

by
M. Assadsolimani; D. Chetalova

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Using Monte Carlo simulation to calculate the Value at Risk (VaR) as a possible risk measure requires adequate techniques. One of these techniques is the application of a compound distribution for the aggregates in a portfolio. In this paper, we consider the aggregated loss of Gamma distributed severities and estimate the VaR by introducing a new approach to calculate the quantile function of the Gamma distribution at high confidence levels. We then compare the VaR obtained from the aggregation...

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1702.04388

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1.0

Jun 30, 2018
06/18

by
Clemence Alasseur; Olivier Feron

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We propose a new structural model that can compute the electricity spot and forward prices in two coupled markets with limited interconnection and multiple fuels. We choose a structural approach in order to represent some key characteristics of electricity spot prices such as their link to fuel prices, consumption level and production fleet. With this model, explicit formulas are also available for forward prices and other derivatives. We give some illustrative results of the behaviour of spot...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1704.06027

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0.0

Jun 30, 2018
06/18

by
Man Chung Fung; Gareth W. Peters; Pavel V. Shevchenko

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Cohort effects are important factors in determining the evolution of human mortality for certain countries. Extensions of dynamic mortality models with cohort features have been proposed in the literature to account for these factors under the generalised linear modelling framework. In this paper we approach the problem of mortality modelling with cohort factors incorporated through a novel formulation under a state-space methodology. In the process we demonstrate that cohort factors can be...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1703.08282

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0.0

Jun 30, 2018
06/18

by
Li Guo; Yubo Tao

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Media news reveals soft information about economic linkages between firms that is not immediately incorporated into stock price. In this paper, we propose a novel measure for aggregate market risk based on news network and news tones, namely media connection index (MCI). We show that the change of MCI predicts a negative return with a higher in-sample and out-of-sample performance than average correlation index in Pollet and Wilson (2010). In addition, our findings are also statistically as...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1703.02715

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0.0

Jun 30, 2018
06/18

by
Saul Jacka; Seb Armstrong; Abdelkarem Berkaoui

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We provide a dual characterisation of the weak$^*$-closure of a finite sum of cones in $L^\infty$ adapted to a discrete time filtration $\mathcal{F}_t$: the $t^{th}$ cone in the sum contains bounded random variables that are $\mathcal{F}_t$-measurable. Hence we obtain a generalisation of Delbaen's m-stability condition for the problem of reserving in a collection of num\'eraires $\mathbf{V}$, called $\mathbf{V}$-m-stability, provided these cones arise from acceptance sets of a dynamic coherent...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.03638

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Jun 30, 2018
06/18

by
Matthieu Mariapragassam; Andrei Cozma; Christoph Reisinger

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We propose a novel and generic calibration technique for four-factor foreign-exchange hybrid local-stochastic volatility models with stochastic short rates. We build upon the particle method introduced by Guyon and Labord\`ere [Nonlinear Option Pricing, Chapter 11, Chapman and Hall, 2013] and combine it with new variance reduction techniques in order to accelerate convergence. We use control variates derived from a calibrated pure local volatility model, a two-factor Heston-type LSV model (both...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1701.06001

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4.0

Jun 30, 2018
06/18

by
Valerii Salov

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Time and Sales of corn futures traded electronically on the CME Group Globex are studied. Theories of continuous prices turn upside down reality of intra-day trading. Prices and their increments are discrete and obey lattice probability distributions. A function for systematic evolution of futures trading volume is proposed. Dependence between sample skewness and kurtosis of waiting times does not support hypothesis of Weibull distribution. Kumaraswamy distribution is more suitable for waiting...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1704.01179

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Jun 30, 2018
06/18

by
Junbeom Lee; Chao Zhou

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In this paper, we investigate conditions to represent derivative price under XVA explicitly. As long as we consider different borrowing/lending rates, XVA problem becomes a non-linear equa- tion and this makes finding explicit solution of XVA difficult. It is shown that the associated valuation problem is actually linear under some proper conditions so that we can have the same complexity in pricing as classical pricing theory. Moreover, the conditions mentioned above is mild in the sense that...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.00259

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0.0

Jun 30, 2018
06/18

by
Kim Weston

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We prove the existence of a Radner equilibrium in a model with proportional transaction costs on an infinite time horizon. Two agents receive exogenous, unspanned income and choose between consumption and investing into an annuity. After establishing the existence of a discrete-time equilibrium, we show that the discrete-time equilibrium converges to a continuous-time equilibrium model. The continuous-time equilibrium provides an explicit formula for the equilibrium interest rate in terms of...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.01706

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Jun 30, 2018
06/18

by
Jean-Pierre Fouque; Ruimeng Hu

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Rough stochastic volatility models have attracted a lot of attentions recently, in particular for the linear option pricing problem. In this paper, starting with power utilities, we propose to use a martingale distortion representation of the optimal value function for the nonlinear asset allocation problem in a (non-Markovian) fractional stochastic environment (for all Hurst index $H \in (0,1)$). We rigorously establish a first order approximation of the optimal value, where the return and...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1703.06969

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Jun 30, 2018
06/18

by
Andrei Cozma; Christoph Reisinger

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We study convergence properties of the full truncation Euler scheme for the Cox-Ingersoll-Ross process in the regime where the boundary point zero is inaccessible. Under some conditions on the model parameters (precisely, when the Feller ratio is greater than three), we establish the strong order 1/2 convergence in $L^{p}$ of the scheme to the exact solution. This is consistent with the optimal rate of strong convergence for Euler approximations of stochastic differential equations with...

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1704.07321

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Jun 30, 2018
06/18

by
Alessandra Cretarola; Gianna Figà Talamanca

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We endorse the idea, suggested in recent literature, that BitCoin prices are influenced by sentiment and confidence about the underlying technology; as a consequence, an excitement about the BitCoin system may propagate to BitCoin prices causing a Bubble effect, the presence of which is documented in several papers about the cryptocurrency. In this paper we develop a bivariate model in continuous time to describe the price dynamics of one BitCoin as well as the behavior of a second factor...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1702.00215

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Jun 30, 2018
06/18

by
Tim Leung; Hongzhong Zhang

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Trailing stop is a popular stop-loss trading strategy by which the investor will sell the asset once its price experiences a pre-specified percentage drawdown. In this paper, we study the problem of timing buy and then sell an asset subject to a trailing stop. Under a general linear diffusion framework, we study an optimal double stopping problem with a random path-dependent maturity. Specifically, we first derive the optimal liquidation strategy prior to a given trailing stop, and prove the...

Topics: Quantitative Finance, Mathematical Finance

Source: http://arxiv.org/abs/1701.03960

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Jun 30, 2018
06/18

by
Wenting Chen; Kai Du; Xinzi Qiu

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This paper investigates analytic properties of American option prices under the finite moment log-stable (FMLS) model. Under this model the price of American options is characterised by the free boundary problem of a fractional partial differential equation (FPDE) system. Using the technique of approximation we prove that the American put price under the FMLS model is convex with respect the underlying price, and specify the impact of the tail index on option prices.

Topics: Quantitative Finance, Computational Finance

Source: http://arxiv.org/abs/1701.01515

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Apr 29, 2017
04/17

by
Various Artists

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Financial News Articles Capitalisms Self inflicted Apocalypse.html Crying Wolf Impending Global Financial Collapse.html Debt Dynamite Dominoes The Coming Financial Catastrophe.html Engineering a Global Depression to Create a Global Government.html Entering the Greatest Depression in History.html Exposing the Financial Core of the Transnational Capitalist Class.html Financial Weapons of Mass Destruction 516 Trillion Derivatives Time Bomb.html From Energy War to Currency War Americas Attack on...

Topic: finance