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Alexander McNeil, Rüdiger Frey, Paul Embrechts (2005): “Quantitative Risk Management”, Princeton Series in Finance, $79.50.-. [PDF]

Financial Markets and Portfolio Management, 2006
Stephan Süss
core   +4 more sources

Handbook of Quantitative Finance and Risk Management [PDF]

, 2010
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis.
Cheng-Few Lee, Lee, John, Lee, Alice C
openaire   +2 more sources

Quantitative Finance and Risk Management [PDF]

, 2004
Jan W. Dash
  +4 more sources

A Non-Gaussian Approach to Risk Measures [PDF]

, 2006
Reliable calculations of financial risk require that the fat-tailed nature of prices changes is included in risk measures. To this end, a non-Gaussian approach to financial risk management is presented, modeling the power-law tails of the returns ...
Bacry, Borland, Borland, Bouchaud, Efron, Enrica Cisana, Gell-Mann, Giacomo Bormetti, Goldstein, Guido Montagna, Heikkinen, Heston, Hill, Jorion, Kamdem, Mandelbrot, Mantegna, Mantegna, Mattedi, McNeil, Mina, Nelson, Oreste Nicrosini, Pafka, Press, Tsallis   +25 more
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The optimal use of return predictability : an empirical study [PDF]

, 2011
In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables.
Abhay Abhyankar, Alexander Stremme, Cochrane, Devraj Basu   +3 more
core   +2 more sources

WARNING: Physics Envy May Be Hazardous To Your Wealth! [PDF]

, 2010
The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in ...
A Blinder, A Damasio, A Hull, A Khandani, A Khandani, A Lo, A Lo, A Lo, A Lo, A Lo, A Lo, A Lo, Andrew W. Lo, B Lehmann, C Lloyd, D Crane, D Duffie, D Farmer, D Farmer, D Li, E Lorenz, E Peters, E Rolls, E Sirri, F Knight, F Reif, F Salmon, G Debreu, G Debreu, G Gigerenzer, G Loewenstein, H Scarf, H Theil, H White, J Bouchaud, J Caouette, J Coffee, J Elster, J Hamilton, J Hamilton, J Hawkins, J Lintner, J Muth, J Nash, J Satow, J Stiglitz, J Stiglitz, J Tinbergen, J Tobin, J Von Neumann, Kenneth Arrow, L Klein, L Pickard, M Gitterman, Mark T. Mueller, N Taleb, P Cootner, P Diaconis, P Samuelson, P Samuelson, P Samuelson, R Lucas, R Mantegna, R Mantegna, R Merton, R Merton, R Solow, S Grossberg, S Labaton, S Weinberg, S Woodward, Steven H Strogatz, T Brennan, T De Jong, T Masters, T Philippon, W Sharpe   +76 more
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Decision-making model on sustainable supply chain finance under uncertainties [PDF]

, 2018
Supply chain finance has received increasing attention. The combination of sustainable development and supply chain finance requires a deeper discussion to address the theoretical and managerial gaps. Thus, this study adopts the fuzzy Technique for Order
Hu, Jiayao, Tseng, Ming-Lang, Wang, Chin-Hsin, Wu, Kuo-Jui   +3 more
core   +1 more source

What is the best risk measure in practice? A comparison of standard measures [PDF]

, 2015
Expected Shortfall (ES) has been widely accepted as a risk measure that is conceptually superior to Value-at-Risk (VaR). At the same time, however, it has been criticised for issues relating to backtesting.
Emmer, Susanne, Kratz, Marie, Tasche, Dirk   +2 more
core   +1 more source

Rethinking bank business models: the role of intangibles [PDF]

, 2014
<p>Purpose: This paper provides a new way of rethinking banking models by using qualitative research on intangibles. This is required because the banking sector has been transformed significantly by the changing environment over the past two ...
Chen, L., Danbolt, J., Holland, J.
core   +2 more sources

Theoretical Sensitivity Analysis for Quantitative Operational Risk Management

, 2017
We study the asymptotic behavior of the difference between the values at risk VaR(L) and VaR(L+S) for heavy tailed random variables L and S for application in sensitivity analysis of quantitative operational risk management within the framework of the ...
Böcker C., Degen M., Embrechts P., Garman M., Kato T., McNeil A. J., TAKASHI KATO, Tasche D.   +7 more
core   +1 more source