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Jun 29, 2018
06/18

by
Vygintas Gontis

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We address microscopic, agent based, and macroscopic, stochastic, modeling of the financial markets combining it with the exogenous noise. The interplay between the endogenous dynamics of agents and the exogenous noise is the primary mechanism responsible for the observed long-range dependence and statistical properties of high volatility return intervals. By exogenous noise we mean information flow or/and order flow fluctuations. Numerical results based on the proposed model reveal that the...

Topics: Statistical Finance, Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.06407

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Jun 29, 2018
06/18

by
Omar El Euch; Mathieu Rosenbaum

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It has been recently shown that rough volatility models, where the volatility is driven by a fractional Brownian motion with small Hurst parameter, provide very relevant dynamics in order to reproduce the behavior of both historical and implied volatilities. However, due to the non-Markovian nature of the fractional Brownian motion, they raise new issues when it comes to derivatives pricing. Using an original link between nearly unstable Hawkes processes and fractional volatility models, we...

Topics: Mathematical Finance, Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1609.02108

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Jun 29, 2018
06/18

by
Tetsuya Takaishi

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In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated.

Topics: Statistical Finance, Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.08088

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Jun 29, 2018
06/18

by
Lisana B. Martinez; M. Belen Guercio; Aurelio F. Bariviera; Antonio Terceño

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This paper investigates the presence of long memory in corporate bond and stock indices of six European Union countries from July 1998 to February 2015. We compute the Hurst exponent by means of the DFA method and using a sliding window in order to measure long range dependence. We detect that Hurst exponents behave differently in the stock and bond markets, being smoother in the stock indices than in the bond indices. We verify that the level of informational efficiency is time-varying....

Topics: Statistical Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1605.06700

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Jun 29, 2018
06/18

by
Philip Ernst; Dean Foster; Larry Shepp

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We pose an optimal control problem arising in a perhaps new model for retirement investing. Given a control function $f$ and our current net worth as $X(t)$ for any $t$, we invest an amount $f(X(t))$ in the market. We need a fortune of $M$ "superdollars" to retire and want to retire as early as possible. We model our change in net worth over each infinitesimal time interval by the Ito process $dX(t)= (1+f(X(t))dt+ f(X(t))dW(t)$. We show how to choose the optimal $f=f_0$ and show that...

Topics: Statistical Finance, Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1605.01028

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Jun 29, 2018
06/18

by
Maria d'Errico; Alessandro Laio; Guido L. Chiarotti

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We propose a stylized model of production and exchange in which long-term investors set their production decision over a horizon {\tau} , the "time to produce", and are liquidity constrained, while financial investors trade over a much shorter horizon {\delta} ( < < {\tau} ) and are therefore more duly informed on the exogenous shocks affecting the production output. The equilibrium solution proves that: (i) long-term producers modify their production decisions to anticipate the...

Topics: Mathematical Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1607.07582

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Jun 29, 2018
06/18

by
Moshe A. Milevsky; Thomas S. Salisbury

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Tontines were once a popular type of mortality-linked investment pool. They promised enormous rewards to the last survivors at the expense of those died early. And, while this design appealed to the gambling instinc}, it is a suboptimal way to generate retirement income. Indeed, actuarially-fair life annuities making constant payments -- where the insurance company is exposed to longevity risk -- induce greater lifetime utility. However, tontines do not have to be structured the historical way,...

Topics: Mathematical Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.10078

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Jun 29, 2018
06/18

by
Julien Hok; Tat Lung Chan

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Here we develop an option pricing method based on Legendre series expansion of the density function. The key insight, relying on the close relation of the characteristic function with the series coefficients, allows to recover the density function rapidly and accurately. Based on this representation for the density function, approximations formulas for pricing European type options are derived. To obtain highly accurate result for European call option, the implementation involves integrating...

Topics: Mathematical Finance, Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.03086

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Jun 29, 2018
06/18

by
M A Szybisz; L Szybisz

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An extension of the nonlinear feedback (NLF) formalism to describe regimes of hyper- and high-inflation in economy is proposed in the present work. In the NLF model the consumer price index (CPI) exhibits a finite time singularity of the type $1/(t_c -t)^{(1- \beta)/\beta}$, with $\beta>0$, predicting a blow up of the economy at a critical time $t_c$. However, this model fails in determining $t_c$ in the case of weak hyperinflation regimes like, e.g., that occurred in Israel. To overcome...

Topics: Statistical Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1605.04945

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Jun 29, 2018
06/18

by
Ivan Guo; Gregoire Loeper

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Derivatives on the Chicago Board Options Exchange volatility index (VIX) have gained significant popularity over the last decade. The pricing of VIX derivatives involves evaluating the square root of the expected realised variance which cannot be computed by direct Monte Carlo methods. Least squares Monte Carlo methods can be used but the sign of the error is difficult to determine. In this paper, we propose new model independent upper and lower pricing bounds for VIX derivatives. In...

Topics: Computational Finance, Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.00464

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Jun 29, 2018
06/18

by
M. A. Milevsky; T. S. Salisbury

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There is growing interest in the design of pension annuities that insure against idiosyncratic longevity risk while pooling and sharing systematic risk. This is partially motivated by the desire to reduce capital and reserve requirements while retaining the value of mortality credits; see for example Piggott, Valdez and Detzel (2005) or Donnelly, Guillen and Nielsen (2014). In this paper we generalize the natural retirement income tontine introduced by Milevsky and Salisbury (2015) by combining...

Topics: Mathematical Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.09384

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Jun 29, 2018
06/18

by
Francisco Salas-Molina; Francisco J. Martin; Juan A. Rodríguez-Aguilar; Joan Serrà; Josep Ll. Arcos

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Cash management is concerned with optimizing the short-term funding requirements of a company. To this end, different optimization strategies have been proposed to minimize costs using daily cash flow forecasts as the main input to the models. However, the effect of the accuracy of such forecasts on cash management policies has not been studied. In this article, using two real data sets from the textile industry, we show that predictive accuracy is highly correlated with cost savings when using...

Topics: Computational Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1605.04219

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Jun 29, 2018
06/18

by
Oliver Janke

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In this article we consider an optimization problem of expected utility maximization of continuous-time trading in a financial market. This trading is constrained by a benchmark for a utility-based shortfall risk measure. The market consists of one asset whose price process is modeled by a Geometric Brownian motion where the market parameters change at a random time. The information flow is modeled by initially and progressively enlarged filtrations which represent the knowledge about the price...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.08644

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Jun 29, 2018
06/18

by
Huai-Long Shi; Zhi-Qiang Jiang; Wei-Xing Zhou

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China's stock market is the largest emerging market all over the world. It is widely accepted that the Chinese stock market is far from efficiency and it possesses possible linear and nonlinear dependence. We study the predictability of returns in the Chinese stock market by employing the wild bootstrap automatic variance ratio test and the generalized spectral test. We find that the return predictability vary over time and significant return predictability is observed around market turmoils....

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.04090

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Jun 29, 2018
06/18

by
Thai Nguyen

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This paper extends the results of the article [C. Kl\"{u}ppelberg and S. M. Pergamenchtchikov. Optimal consumption and investment with bounded downside risk for power utility functions. In Optimality and Risk: {\it Modern Trends in Mathematical Finance. The Kabanov Festschrift}, pages 133-169, 2009] to a jump-diffusion setting. We show that under the assumption that only positive jumps in the asset prices are allowed, the explicit optimal strategy can be found in the subset of admissible...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1604.05584

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Jun 29, 2018
06/18

by
Philip Ernst; Larry Shepp

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Using a bondholder who seeks to determine when to sell his bond as our motivating example, we revisit one of Larry Shepp's classical theorems on optimal stopping. We offer a novel proof of Theorem 1 from from \cite{Shepp}. Our approach is that of guessing the optimal control function and proving its optimality with martingales. Without martingale theory one could hardly prove our guess to be correct.

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1605.00762

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Jun 29, 2018
06/18

by
Carol Alexander; Johannes Rauch

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Realised pay-offs for discretisation-invariant swaps are those which satisfy a restricted `aggregation property' of Neuberger [2012] for twice continuously differentiable deterministic functions of a multivariate martingale. They are initially characterised as solutions to a second-order system of PDEs, then those pay-offs based on martingale and log-martingale processes alone form a vector space. Hence there exist an infinite variety of other variance and higher-moment risk premia that are...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1602.00235

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Jun 29, 2018
06/18

by
Erwan Pierre; Stéphane Villeneuve; Xavier Warin

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We consider a singular control problem with regime switching that arises in problems of optimal investment decisions of cash-constrained firms. The value function is proved to be the unique viscosity solution of the associated Hamilton-Jacobi-Bellman equation. Moreover, we give regularity properties of the value function as well as a description of the shape of the control regions. Based on these theoretical results, a numerical deterministic approximation of the related HJB variational...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1603.09049

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Jun 29, 2018
06/18

by
Fabrizio Cipollini; Robert F. Engle; Giampiero M. Gallo

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The Multiplicative Error Model (Engle (2002)) for nonnegative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with nonnegative support. A multivariate extension allows for the innovations to be contemporaneously correlated. We overcome the lack of sufficiently flexible probability density functions for such processes by suggesting a copula function approach to estimate the parameters of the scale factors and of the...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1604.01338

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Jun 29, 2018
06/18

by
Sebastien Valeyre; Denis Grebenkov; Sofiane Aboura; Francois Bonnin

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We uncover a new anomaly in asset pricing that is linked to the remuneration: the more a company spends on salaries and benefits per employee, the better its stock performs, on average. Moreover, the companies adopting similar remuneration policies share a common risk, which is comparable to that of the value premium. For this purpose,we set up an original methodology that uses firm financial characteristics to build factors that are less correlated than in the standard asset pricing...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1602.00931

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1.0

Jun 29, 2018
06/18

by
Vladimir Filimonov; Guilherme Demos; Didier Sornette

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We present a detailed methodological study of the application of the modified profile likelihood method for the calibration of nonlinear financial models characterised by a large number of parameters. We apply the general approach to the Log-Periodic Power Law Singularity (LPPLS) model of financial bubbles. This model is particularly relevant because one of its parameters, the critical time $t_c$ signalling the burst of the bubble, is arguably the target of choice for dynamical risk management....

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1602.08258

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0.0

Jun 29, 2018
06/18

by
Robert Fernholz

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For a functionally generated portfolio, there is a natural decomposition of the relative log-return into the log-change in the generating function and a drift process. In this note, this decomposition is extended to arbitrary stock portfolios by an application of Fisk-Stratonovich integration. With the extended methodology, the generating function is represented by a structural process, and the drift process is subsumed into a trading process that measures the profit and loss to the portfolio...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1606.05877

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0.0

Jun 29, 2018
06/18

by
Du Nguyen

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We derive an explicit formula for likelihood function for Gaussian VARMA model conditioned on initial observables where the moving-average (MA) coefficients are scalar. For fixed MA coefficients the likelihood function is optimized in the autoregressive variables $\Phi$'s by a closed form formula generalizing regression calculation of the VAR model with the introduction of an inner product defined by MA coefficients. We show the assumption of scalar MA coefficients is not restrictive and this...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1604.08677

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Jun 29, 2018
06/18

by
Peter A. Bebbington; Julius Bonart

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We find a remarkable agreement between the statistics of a randomly divided interval and the observed statistical patterns and distributions found in horse racing betting markets. We compare the distribution of implied winning odds, the average true winning probabilities, the implied odds conditional on a win, and the average implied odds of the winning horse with the corresponding quantities from the "randomly broken stick problem". We observe that the market is at least to some...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1612.02567

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Jun 29, 2018
06/18

by
Feng-Hui Yu; Wai-Ki Ching; Jia-Wen Gu; Tak-Kuen Siu

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In this paper we consider a reduced-form intensity-based credit risk model with a hidden Markov state process. A filtering method is proposed for extracting the underlying state given the observation processes. The method may be applied to a wide range of problems. Based on this model, we derive the joint distribution of multiple default times without imposing stringent assumptions on the form of default intensities. Closed-form formulas for the distribution of default times are obtained which...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1603.02902

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0.0

Jun 29, 2018
06/18

by
Stefan Gerhold; I. Cetin Gülüm

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Given a finite set of European call option prices on a single underlying, we want to know when there is a market model which is consistent with these prices. In contrast to previous studies, we allow models where the underlying trades at a bid-ask spread. The main question then is how large (in terms of a deterministic bound) this spread must be to explain the given prices. We fully solve this problem in the case of a single maturity, and give several partial results for multiple maturities....

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1608.05585

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Jun 29, 2018
06/18

by
Seyed Amir Hejazi; Kenneth R. Jackson

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As part of the new regulatory framework of Solvency II, introduced by the European Union, insurance companies are required to monitor their solvency by computing a key risk metric called the Solvency Capital Requirement (SCR). The official description of the SCR is not rigorous and has lead researchers to develop their own mathematical frameworks for calculation of the SCR. These frameworks are complex and are difficult to implement. Recently, Bauer et al. suggested a nested Monte Carlo (MC)...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.01946

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Jun 29, 2018
06/18

by
David Hobson; Alex S. L. Tse; Yeqi Zhu

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In this article we consider the Merton problem in a market with a single risky asset and transaction costs. We give a complete solution of the problem up to the solution of a free-boundary problem for a first-order differential equation, and find that the form of the solution (whether the problem is well-posed, whether the problem is well-posed only for large transaction costs, whether the no-transaction wedge lies in the first, second or fourth quadrants) depends only on a quadratic whose...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1612.00720

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2.0

Jun 29, 2018
06/18

by
Tim Leung; Jamie Kang

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American Depositary Receipts (ADRs) are exchange-traded certificates that rep- resent shares of non-U.S. company securities. They are major financial instruments for investing in foreign companies. Focusing on Asian ADRs in the context of asyn- chronous markets, we present methodologies and results of empirical analysis of their returns. In particular, we dissect their returns into intraday and overnight com- ponents with respect to the U.S. market hours. The return difference between the...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.03110

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Jun 29, 2018
06/18

by
Atul Deshpande; B. Ross Barmish

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Pairs trading is a market-neutral strategy that exploits historical correlation between stocks to achieve statistical arbitrage. Existing pairs-trading algorithms in the literature require rather restrictive assumptions on the underlying stochastic stock-price processes and the so-called spread function. In contrast to existing literature, we consider an algorithm for pairs trading which requires less restrictive assumptions than heretofore considered. Since our point of view is...

Topics: Statistical Finance, Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1608.03636

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Jun 29, 2018
06/18

by
Jozef Barunik; Evzen Kocenda; Lukas Vacha

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We show how bad and good volatility propagate through forex markets, i.e., we provide evidence for asymmetric volatility connectedness on forex markets. Using high-frequency, intra-day data of the most actively traded currencies over 2007 - 2015 we document the dominating asymmetries in spillovers that are due to bad rather than good volatility. We also show that negative spillovers are chiefly tied to the dragging sovereign debt crisis in Europe while positive spillovers are correlated with...

Topics: Statistical Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1607.08214

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Jun 29, 2018
06/18

by
Masaaki Fujii; Akihiko Takahashi

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This article proposes a new approximation scheme for quadratic-growth BSDEs in a Markovian setting by connecting a series of semi-analytic asymptotic expansions applied to short-time intervals. Although there remains a condition which needs to be checked a posteriori, one can avoid altogether time-consuming Monte Carlo simulation and other numerical integrations for estimating conditional expectations at each space-time node. Numerical examples of quadratic-growth as well as Lipschitz BSDEs...

Topics: Computational Finance, Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1606.04285

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Jun 29, 2018
06/18

by
Joachim Sicking; Thomas Guhr; Rudi Schäfer

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We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only...

Topics: Mathematical Finance, Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1604.06917

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Jun 29, 2018
06/18

by
Giancarlo Salirrosas Martínez

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The purpose of this research paper it is to present a new approach in the framework of a biased roulette wheel. It is used the approach of a quantitative trading strategy, commonly used in quantitative finance, in order to assess the profitability of the strategy in the short term. The tools of backtesting and walk-forward optimization were used to achieve such task. The data has been generated from a real European roulette wheel from an on-line casino based in Riga, Latvia. It has been...

Topics: Computational Finance, General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1609.09601

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Jun 29, 2018
06/18

by
N. Serhan Aydin

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We introduce an interactive market setup with sequential auctions where agents receive variegated signals with a known deadline. The effects of differential information and mutual learning on the allocation of overall profit \& loss (P\&L) and the pace of price discovery are analysed. We characterise the signal-based expected P\&L of agents based on explicit formulae for the directional quality of the trading signal, and study the optimal trading pattern using dynamic programming...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.04051

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Jun 29, 2018
06/18

by
Cornelis S. L. de Graaf; Drona Kandhai; Christoph Reisinger

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The focus of this paper is the efficient computation of counterparty credit risk exposure on portfolio level. Here, the large number of risk factors rules out traditional PDE-based techniques and allows only a relatively small number of paths for nested Monte Carlo simulations, resulting in large variances of estimators in practice. We propose a novel approach based on Kolmogorov forward and backward PDEs, where we counter the high dimensionality by a generalisation of anchored-ANOVA...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1608.01197

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Jun 29, 2018
06/18

by
Ricardo T. Fernholz; Christoffer Koch

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We uncover a large and significant low-minus-high rank effect for commodities across two centuries. There is nothing anomalous about this anomaly, nor is it clear how it can be arbitraged away. Using nonparametric econometric methods, we demonstrate that such a rank effect is a necessary consequence of a stationary relative asset price distribution. We confirm this prediction using daily commodity futures prices and show that a portfolio consisting of lower-ranked, lower-priced commodities...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1607.07510

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Jun 29, 2018
06/18

by
Tetsuya Takaishi

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The realized stochastic volatility (RSV) model that utilizes the realized volatility as additional information has been proposed to infer volatility of financial time series. We consider the Bayesian inference of the RSV model by the Hybrid Monte Carlo (HMC) algorithm. The HMC algorithm can be parallelized and thus performed on the GPU for speedup. The GPU code is developed with CUDA Fortran. We compare the computational time in performing the HMC algorithm on GPU (GTX 760) and CPU (Intel...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1603.08114

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Jun 29, 2018
06/18

by
Olena Burkovska; Maximilian Gaß; Kathrin Glau; Mirco Mahlstedt; Wim Schoutens; Barbara Wohlmuth

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American options are the reference instruments for the model calibration of a large and important class of single stocks. For this task, a fast and accurate pricing algorithm is indispensable. The literature mainly discusses pricing methods for American options that are based on Monte Carlo, tree and partial differential equation methods. We present an alternative approach that has become popular under the name de-Americanization in the financial industry. The method is easy to implement and...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.06181

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Jun 29, 2018
06/18

by
Tanmay S. Patankar

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This project attempts to address the problem of asset pricing in a financial market, where the interest rates and volatilities exhibit regime switching. This is an extension of the Black-Scholes model. Studies of Markov-modulated regime switching models have been well-documented. This project extends that notion to a class of semi-Markov processes known as age-dependent processes. We also allow for time-dependence in volatility within regimes. We show that the problem of option pricing in such...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1609.04907

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Jun 29, 2018
06/18

by
Vinicius Albani; Uri M. Ascher; Jorge P. Zubelli

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We introduce a local volatility model for the valuation of options on commodity futures by using European vanilla option prices. The corresponding calibration problem is addressed within an online framework, allowing the use of multiple price surfaces. Since uncertainty in the observation of the underlying future prices translates to uncertainty in data locations, we propose a model-based adjustment of such prices that improves reconstructions and smile adherence. In order to tackle the...

Topics: Computational Finance, Quantitative Finance

Source: http://arxiv.org/abs/1602.04372

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Jun 29, 2018
06/18

by
Petr Jizba; Jan Korbel

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Multifractal analysis is one of the important approaches that enables us to measure the complexity of various data via the scaling properties. We compare the most common techniques used for multifractal exponents estimation from both theoretical and practical point of view. Particularly, we discuss the methods based on estimation of R\'enyi entropy, which provide a powerful tool especially in presence of heavy-tailed data. To put some flesh on bare bones, all methods are compared on various...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1610.07028

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Jun 29, 2018
06/18

by
Loretta Mastroeni; Pierluigi Vellucci

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We test whether the futures prices of some commodity and energy markets are determined by stochastic rules or exhibit nonlinear deterministic endogenous fluctuations. As for the methodologies, we use the maximal Lyapunov exponents (MLE) and a determinism test, both based on the reconstruction of the phase space. In particular, employing a recent methodology, we estimate a coefficient $\kappa$ that describes the determinism rate of the analyzed time series. We find that the underlying system for...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1611.07432

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Jun 29, 2018
06/18

by
David Hobson; Alex S. L. Tse; Yeqi Zhu

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In this article we study a multi-asset version of the Merton investment and consumption problem with proportional transaction costs. In general it is difficult to make analytical progress towards a solution in such problems, but we specialise to a case where transaction costs are zero except for sales and purchases of a single asset which we call the illiquid asset. Assuming agents have CRRA utilities and asset prices follow exponential Brownian motions we show that the underlying HJB equation...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1612.01327

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2.0

Jun 29, 2018
06/18

by
Francesca Biagini; Jacopo Mancin; Thilo Meyer Brandis

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In this paper we study mean-variance hedging under the G-expectation framework. Our analysis is carried out by exploiting the G-martingale representation theorem and the related probabilistic tools, in a contin- uous financial market with two assets, where the discounted risky one is modeled as a symmetric G-martingale. By tackling progressively larger classes of contingent claims, we are able to explicitly compute the optimal strategy under general assumptions on the form of the contingent...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1602.05484

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7.0

Jun 29, 2018
06/18

by
Justin Sirignano; Apaar Sadhwani; Kay Giesecke

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This paper analyzes multi-period mortgage risk at loan and pool levels using an unprecedented dataset of over 120 million prime and subprime mortgages originated across the United States between 1995 and 2014, which includes the individual characteristics of each loan, monthly updates on loan performance over the life of a loan, and a number of time-varying economic variables at the zip code level. We develop, estimate, and test dynamic machine learning models for mortgage prepayment,...

Topics: Statistical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1607.02470

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1.0

Jun 29, 2018
06/18

by
Tung-Lam Dao; Trung-Tu Nguyen; Cyril Deremble; Yves Lempérière; Jean-Philippe Bouchaud; Marc Potters

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The performance of trend following strategies can be ascribed to the difference between long-term and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of Commodity Trading Advisors (CTAs) which -- when adequately measured -- turns out to be much stronger than anticipated. We also highlight interesting connections with so-called Risk Parity portfolios....

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1607.02410

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1.0

Jun 29, 2018
06/18

by
Claudia Ceci; Katia Colaneri; Alessandra Cretarola

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In this paper we investigate the hedging problem of a unit-linked life insurance contract via the local risk-minimization approach, when the insurer has a restricted information on the market. In particular, we consider an endowment insurance contract, that is a combination of a term insurance policy and a pure endowment, whose final value depends on the trend of a stock market where the premia the policyholder pays are invested. We assume that the stock price process dynamics depends on an...

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1608.07226

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0.0

Jun 29, 2018
06/18

by
Lucia Bellenzier; Jørgen Vitting Andersen; Giulia Rotundo

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We study how the phenomenon of contagion can take place in the network of the world's stock exchanges due to the behavioral trait "blindeness to small changes". On large scale individual, the delay in the collective response may significantly change the dynamics of the overall system. We explicitely insert a term describing the behavioral phenomenon in a system of equations that describe the build and release of stress across the worldwide stock markets. In the mathematical...

Topics: General Finance, Quantitative Finance

Source: http://arxiv.org/abs/1602.07452

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0.0

Jun 29, 2018
06/18

by
Niushan Gao; Foivos Xanthos

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\begin{abstract} The aim of this paper is to study the spanning power of options in a static financial market that allows non-integrable assets. Our findings extend and unify the results in [8,9,18] for $L_p$-models. We also apply the spanning power properties to the pricing problem. In particular, we show that prices on call and put options of a limited liability asset can be uniquely extended by arbitrage to all marketed contingent claims written on the asset.

Topics: Mathematical Finance, Quantitative Finance

Source: http://arxiv.org/abs/1603.01288