Search Results - "Quantitative finance"

Volatility is rough by Gatheral, Jim, Jaisson, Thibault, Rosenbaum, Mathieu

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Universal features of price formation in financial markets: perspectives from deep learning by Sirignano, Justin, Cont, Rama

“…Using a large-scale Deep Learning approach applied to a high-frequency database containing billions of market quotes and transactions for US equities, we…”
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Quant GANs: deep generation of financial time series by Wiese, Magnus, Knobloch, Robert, Korn, Ralf, Kretschmer, Peter

“…Modeling financial time series by stochastic processes is a challenging task and a central area of research in financial mathematics. As an alternative, we…”
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Pricing under rough volatility by Bayer, Christian, Friz, Peter, Gatheral, Jim

“…From an analysis of the time series of realized variance using recent high-frequency data, Gatheral et al. [Volatility is rough, 2014] previously showed that…”
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A critical investigation of cryptocurrency data and analysis by Alexander, C., Dakos, M.

“…Less than half the crytocurrency papers published since January 2017 employ correct data…”
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Deep hedging by Buehler, H., Gonon, L., Teichmann, J., Wood, B.

“…We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, liquidity constraints or risk…”
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Extreme risk spillover network: application to financial institutions by Wang, Gang-Jin, Xie, Chi, He, Kaijian, Stanley, H. Eugene

“…Using the CAViaR tool to estimate the value-at-risk (VaR) and the Granger causality risk test to quantify extreme risk spillovers, we propose an extreme risk…”
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Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models by Horvath, Blanka, Muguruza, Aitor, Tomas, Mehdi

“…We present a neural network-based calibration method that performs the calibration task within a few milliseconds for the full implied volatility surface. The…”
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Exploring the attention mechanism in LSTM-based Hong Kong stock price movement prediction by Chen, Shun, Ge, Lei

“…State-of-the-art methods using attention mechanism in Recurrent Neural Networks have shown exceptional performance targeting sequential predictions and…”
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Machine learning for quantitative finance: fast derivative pricing, hedging and fitting by De Spiegeleer, Jan, Madan, Dilip B., Reyners, Sofie, Schoutens, Wim

“…In this paper, we show how we can deploy machine learning techniques in the context of traditional quant problems. We illustrate that for many classical…”
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The multiplex structure of interbank networks by Bargigli, L., di Iasio, G., Infante, L., Lillo, F., Pierobon, F.

“…The interbank market has a natural multiplex network representation. We employ a unique database of supervisory reports on Italian banks to the Banca d'Italia…”
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Gold price dynamics and the role of uncertainty by Beckmann, Joscha, Berger, Theo, Czudaj, Robert

“…This study focuses on the dynamics of the gold price against bonds, stocks and exchange rates based on a disaggregation of the underlying relationships across…”
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Hawkes processes and their applications to finance: a review by Hawkes, Alan G.

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Investing with cryptocurrencies - evaluating their potential for portfolio allocation strategies by Petukhina, Alla, Trimborn, Simon, Härdle, Wolfgang Karl, Elendner, Hermann

“…Cryptocurrencies (CCs) have risen rapidly in market capitalization over the past years. Despite striking volatility, their high average returns and low…”
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Filling in the blanks: network structure and interbank contagion by Anand, Kartik, Craig, Ben, von Peter, Goetz

“…The network pattern of financial linkages is important in many areas of banking and finance. Yet, bilateral linkages are often unobserved, and maximum entropy…”
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Bayesian regularized artificial neural networks for the estimation of the probability of default by Sariev, Eduard, Germano, Guido

“…Artificial neural networks (ANNs) have been extensively used for classification problems in many areas such as gene, text and image recognition. Although ANNs…”
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Multilayer information spillover networks: measuring interconnectedness of financial institutions by Wang, Gang-Jin, Yi, Shuyue, Xie, Chi, Stanley, H. Eugene

“…We propose multilayer information spillover networks to measure the interconnectedness of financial institutions by comprehensively considering mean spillover…”
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Lifting the Heston model by Abi Jaber, Eduardo

“…How to reconcile the classical Heston model with its rough counterpart? We introduce a lifted version of the Heston model with n multi-factors, sharing the…”
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Short-time near-the-money skew in rough fractional volatility models by Bayer, C., Friz, P. K., Gulisashvili, A., Horvath, B., Stemper, B.

“…We consider rough stochastic volatility models where the driving noise of volatility has fractional scaling, in the 'rough' regime of Hurst parameter . This…”
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Deep learning for limit order books by Sirignano, Justin A.

“…This paper develops a new neural network architecture for modeling spatial distributions (i.e. distributions on ) which is more computationally efficient than…”
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