Journal: Quantitative Finance

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Taylor & Francis

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ISSN

1469-7688
1469-7696

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Publications 1 - 10 of 14
  • Smooth and bid-offer compliant volatility surfaces under general dividend streams
    Item type: Journal Article
    Bachem, Olivier; Drimus, Gabriel; Farkas, Walter (2013)
    Quantitative Finance
  • On the Predictability of Stock Market Bubbles: Evidence from LPPLS Confidence Multiscale Indicators
    Item type: Journal Article
    Riza, Demirer; Demos, Guilherme; Gupta, Rangan; et al. (2018)
    Quantitative Finance
  • Estimating value-at-risk: a point process approach
    Item type: Journal Article
    Chavez-Demoulin, Valérie; Davison, Anthony C.; McNeila, Alexander J. (2005)
    Quantitative Finance
    We consider the modelling of extreme returns in financial time series, and introduce a marked point process model for the exceedances of a high threshold. This model has a self-exciting, Hawkes-process structure in which recent events affect the current intensity of threshold exceedances more than distant ones. Estimates of value-at-risk are derived for real datasets and the success of the estimation method is evaluated in backtests.
  • Patterns in high-frequency FX data: Discovery of 12 empirical scaling laws
    Item type: Journal Article
    Glattfelder, James B.; Dupuis, A.; Olsen, Richard B. (2011)
    Quantitative Finance
  • A model of financial bubbles and drawdowns with non-local behavioral self-referencing
    Item type: Journal Article
    Malevergne, Yannick; Sornette, Didier; Wei, Ran (2025)
    Quantitative Finance
    We propose a novel class of asset price models in which the crash hazard rate is determined by a function of a non-local estimation of mispricing. Rooted in behavioral finance, the non-local estimation embodies in particular the characteristic of 'anchoring' on past price levels and the 'probability judgment' about the likelihood of a crash as a function of the self-referential mispricing, enabling us to disentangle the risk-return relationship from its instantaneous connection. By describing drawdowns and crashes as market regimes with correlated negative jumps clustering over a finite period of time, our model provides a solution to the problem plaguing most crash jump models, which are in general rejected in calibrations of real financial time series because they assume that crashes occur in a single large negative jump, which is counterfactual. The model estimation is implemented on synthetic time series and real markets, shedding light on the estimation of the 'true' expected return, which is usually confounded by the entanglement between volatility and jump risks. Estimated from the daily time series of three stock indexes, the hidden expected return exhibits a secular increase over time and tends to be larger than the realized return, suggesting that financial markets have been overall underpriced.
  • An adaptive dynamical model of default contagion
    Item type: Journal Article
    Smug, Damian; Ashwin, Julian; Ashwin, Peter; et al. (2022)
    Quantitative Finance
    The dynamics of default contagion is modeled in terms of adaptively coupled stochastic measures of financial health
  • Cycles, determinism and persistence in agent-based games and financial time-series II
    Item type: Journal Article
    Satinover, J. B.; Sornette, Didier (2012)
    Quantitative Finance
  • Optimal liquidation under indirect price impact with propagator
    Item type: Journal Article
    Dupret, Jean-Loup; Hainaut, Donatien (2025)
    Quantitative Finance
    We propose in this paper a new framework of optimal liquidation strategies for a trader seeking to liquidate his large inventory based on a jump-dependent price impact model with propagator. This new jump-dependent price impact model best reproduces the empirical direct and indirect effects of market orders on the transaction price. More precisely, different choices of propagators are proposed and their implications in terms of temporary, permanent and transient impacts on the transaction price are discussed. For each choice of such kernels, we formulate the most relevant optimal liquidation problem faced by the trader, derive explicitly the related Hamilton-Jacobi-Bellman equation and solve it numerically. We then also show how our price impact model can be extended to incorporate the use of limit orders by the liquidating trader. Therefore, we aim with this paper to propose an alternative, more realistic and flexible description of the order book's dynamic, thereby contributing to bridging the gap between high-frequency price models and optimal liquidation problems.
  • Randomized signature methods in optimal portfolio selection
    Item type: Journal Article
    Akyildirim, Erdinç; Gambara, Matteo; Teichmann, Josef; et al. (2025)
    Quantitative Finance
    We present convincing empirical results on the application of Randomized Signature Methods for non-linear, non-parametric drift estimation for a multi-variate financial market. Even though drift estimation is notoriously inaccurate due to small signal to noise ratio, one can still try to learn optimal non-linear maps from past data to conditional expectations of future returns for the purposes of portfolio optimization. Randomized Signatures, in contrast to classical signatures, allow for high dimensional markets and provide features on the same scale. We do not contribute to the theory of Randomized Signatures here, but rather present our empirical findings on portfolio selection in real world settings including real market data and transaction costs.
  • A simple mechanism for financial bubbles: time-varying momentum horizon
    Item type: Journal Article
    Lin, Li; Schatz, Michael; Sornette, Didier (2019)
    Quantitative Finance
Publications 1 - 10 of 14