Asymmetry of copulas arising from shock models. (arXiv:1808.09698v1 [math.ST])
When choosing the right copula for our data a key point is to distinguish the family that describes it at the best. In this respect, a better choice of the copulas could be obtained through the...
View ArticleSmile Modelling in Commodity Markets. (arXiv:1808.09685v1 [q-fin.PR])
We present a stochastic-local volatility model for derivative contracts on commodity futures able to describe forward-curve and smile dynamics with a fast calibration to liquid market quotes. A...
View ArticleHow does latent liquidity get revealed in the limit order book?....
Latent order book models have allowed for significant progress in our understanding of price formation in financial markets. In particular they are able to reproduce a number of stylized facts, such as...
View ArticleSwitching Cost Models as Hypothesis Tests. (arXiv:1808.09686v1 [econ.GN])
We relate models based on costs of switching beliefs (e.g. due to inattention) to hypothesis tests. Specifically, for an inference problem with a penalty for mistakes and for switching the inferred...
View ArticleHierarchical communities in the walnut structure of the Japanese production...
This paper studies the structure of the Japanese production network, which includes one million firms and five million supplier-customer links. This study finds that this network forms a tightly-knit...
View ArticleThe role of complex analysis in modeling economic growth. (arXiv:1808.10428v1...
Development and growth are complex and tumultuous processes. Modern economic growth theories identify some key determinants of economic growth. However, the relative importance of the determinants...
View ArticleDissection of Bitcoin's Multiscale Bubble History from January 2012 to...
We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time...
View ArticleIdentifying the Discount Factor in Dynamic Discrete Choice Models....
Empirical applications of dynamic discrete choice models usually either take the discount factor to be known or rely on ad hoc functional form assumptions to identify and estimate it. We give...
View ArticleMultiplicative random cascades with additional stochastic process in...
Multiplicative random cascade model naturally reproduces the intermittency or multifractality, which is frequently shown among hierarchical complex systems such as turbulence and financial markets. As...
View ArticleIdentifying long-term precursors of financial market crashes using...
The study of the critical dynamics in complex systems is always interesting yet challenging. Here, we choose financial market as an example of a complex system, and do a comparative analyses of two...
View ArticleModel-free trading and hedging with continuous price paths....
In this paper, we provide a model-independent extension of the paradigm of dynamic hedging of derivative claims. We relate model-independent replication strategies to local martingales having a closed...
View ArticleFinding a promising venture capital project with todim under probabilistic...
Considering the risk aversion for gains and the risk seeking for losses of venture capitalists, the TODIM has been chosen as the decision-making method. Moreover, group decision is an available way to...
View ArticleModel Risk in Real Option Valuation. (arXiv:1809.00817v1 [q-fin.GN])
We introduce a general decision tree framework to value an option to invest/divest in a project, focusing on the model risk inherent in the assumptions made by standard real option valuation methods....
View ArticleTopological recognition of critical transitions in time series of...
We analyze the time series of four major cryptocurrencies (Bitcoin, Ethereum, Litecoin, and Ripple) before the digital market crash at the end of 2017 - beginning 2018. We introduce a methodology that...
View Article"Read My Lips": Using Automatic Text Analysis to Classify...
The increasing digitization of political speech has opened the door to studying a new dimension of political behavior using text analysis. This work investigates the value of word-level statistical...
View ArticleThe NEU Meta-Algorithm for Geometric Learning with Applications in Finance....
We introduce a meta-algorithm, called non-Euclidean upgrading (NEU), which learns algorithm-specific geometries to improve the training and validation set performance of a wide class of learning...
View ArticleHow to model fake news. (arXiv:1809.00964v1 [stat.AP] CROSS LISTED)
Over the past three years it has become evident that fake news is a danger to democracy. However, until now there has been no clear understanding of how to define fake news, much less how to model it....
View ArticleNon-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler....
In this work, we propose a model for estimating volatility from financial time series, extending the non-Gaussian family of space-state models with exact marginal likelihood proposed by Gamerman,...
View ArticleDeep Reinforcement Learning in High Frequency Trading. (arXiv:1809.01506v1...
The ability to give a precise and fast prediction for the price movement of stocks is the key to profitability in High Frequency Trading. The main objective of this paper is to propose a novel way of...
View ArticleA Bayesian GED-Gamma stochastic volatility model for return data: a marginal...
Several studies explore inferences based on stochastic volatility (SV) models, taking into account the stylized facts of return data. The common problem is that the latent parameters of many volatility...
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