Theory Of Financial Risk And Derivative Pricing

By Jean-Philippe Bouchaud, Marc Potters. 2000

615 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f0400ba52bf050d36782fe721d394371eba81f83

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In Economics and Econometrics

Citations in the corpus

Financial Applications of Random Matrix Theory: Old Laces and New Pieces (2005, neutral): “Another possible interpretation is through a constraint on the effective number of assets in the portfolio, defined as ( ∑ iw 2 i ) −1 [2].”
Modelling microstructure noise with mutually exciting point processes (2011, background): “Since Bachelier and the seminal work of Black and Scholes, most popular models at a coarse time scale—for daily data, say—are Brownian diffusions (see, for instance, the classical textbooks of Bouchaud and Potters (2003) and Musiela and Rutkowski (2004) and references therein).”
The implied volatility smirk (2008, methodology): “Proof: By expanding both sides of formula (6) for a small volatility, we may obtain the result by using some algebra. œ Remark 2: The leading order result in equation (9) was presented in Backus et al. (1997), and Bouchaud and Potters (2003), see also, Potters et al. (1998).”
FORECASTING VOLATILITY WITH THE MULTIFRACTAL RANDOM WALK MODEL (2008, methodology): “ths) such that one can make the following approximation by an additive model: S0e YT t ≃ S0(1+YT t ). Then, one can perform a cumulant expansion in formula (4.3) up to the kurtosis (see p. 244-245 in [6] for details) and obtain the following smile formula for the implied volatility Σ(K,t) as a funct”
Cross-Correlation Dynamics in Financial Time Series (2009, background): “03 21 v1 [ qfi n. ST ] 1 F eb The dynamics of the equal-time cross-correlation matrix of multivariate financial time series is explored by examination of the eigenvalue spectrum over sliding time windows.”
Random Matrix Theory and Fund of Funds Portfolio Optimisation (2007, methodology): “However, since our aim here is to demonstrate how Random Matrix Theory can be used to improve the risk/return profile for a portfolio of Hedge Funds, we assume that the eigenvalues corresponding to the noise band in RMT, λ− ≤ λ ≤ λ+, are not expected to correspond to real information following [6,7,”
Limit order books (2010, background): “…Aït-Sahalia et al. 2011), Euronext (Chakraborti et al. 2011b), FX markets (Cont et al. 1997, Bouchaud and Potters 2003), the S&P500 index (Gopikrishnan et al. 1999, Bouchaud and Potters 2003), German interest rates futures contracts (Bouchaud and Potters 2003), and crude oil futures (Zhao 2010).”
Volatility is rough (2014, methodology): “This fractal-type behaviour of the volatility has been investigated both empirically and theoretically in, for example, Bacry and Muzy (2003), Bouchaud and Potters (2003), Mantegna and Stanley (2000).”
Two centuries of trend following (2014, background): “7 , typical drawdowns last two years while drawdowns of 4 years are not exceptional (see [29, 30] for more on this topic).”
The characteristic function of rough Heston models (2016, background): “…© 2018 Wiley Periodicals, Inc. 3 • It reproduces well several important stylized facts of low-frequency price data, namely, leverage effect, time-varying volatility, and fat tails; see Bouchaud and Potters (2003), Christie (1982), Dragulescu and Yakovenko (2002), and Mandelbrot (1997).”