Applied and Computational Mathematics

Special Issue

Computational Methods in Monetary and Financial Economics

  • Submission Deadline: Feb. 19, 2016
  • Status: Submission Closed
  • Lead Guest Editor: Christoph Wegener
About This Special Issue
Quantitative and computational methods have become increasingly important in monetary and financial economics. Financial risk managers, for example, today use techniques from mathematics and physics to improve their ability to measure and control financial risks in the economy. The financial crisis also has shown that monetary policy does matter in this context. Numerous central banks all around the world have used the tools of monetary policy to enhance liquidity and thereby rescue financial service institutions (e.g., banks and insurers). Consequently, financial and monetary economics have to be discussed using an integrated point of view. This special issue tries to summarize important relevant ideas and to develop new concepts focusing on quantitative and computational techniques in financial and monetary economics.

Main topic areas

1. Asset pricing and Computational Finance
2. Business Cycle Modeling
3. Physical Methods in Economics
4. Modeling Financial Crises
5. Inflation Dynamics
6. Learning and Evolutionary Economics
7. Market Structure
8. Monetary Policy
9. Monte Carlo Methods
10. Optimization and Solution Methods
11. Time Series Econometrics and Analysis
12. Volatility Modeling
13. Financial Risk Management
Lead Guest Editor
  • Christoph Wegener

    Center for Risk and Insurance at Leibniz University of Hannover, Hannover, Germany, Germany

Published Articles
  • Pensions and Growth: A Cointegration Analysis

    Miguel Rodriguez Gonzalez , Christoph Schwarzbach

    Issue: Volume 5, Issue 1-1, February 2016
    Pages: 21-35
    Received: May 07, 2015
    Accepted: Jun. 01, 2015
    Published: Jul. 03, 2015
    DOI: 10.11648/j.acm.s.2016050101.13
    Abstract: This article investigates the long-term relationship between economic growth and old-age provision using time series analysis, particularly the techniques of cointegration. The neoclassical growth model by Solow (1956) provides atheoretical basis for the empirical analysis. The results are based onquarterly data from 1970 to 2013 for the US-economy... Show More
  • Impact of Interest Rate Shocks on the Asset Structure of Private Households in Germany with Particular Reference to Insurance

    Tim Linderkamp

    Issue: Volume 5, Issue 1-1, February 2016
    Pages: 14-20
    Received: May 26, 2015
    Accepted: May 27, 2015
    Published: Jun. 10, 2015
    DOI: 10.11648/j.acm.s.2016050101.12
    Abstract: This paper investigates the portfolio structure of private households in Germany from 1994 to 2014. We focus on the question of how sensitively private households react to a shock in the interest rate level. We use a vector autoregressive model and analyze the corresponding impulse-response functions. The data set is provided by Deutsche Bundesbank... Show More
  • Identification of Company-Specific Stress Scenarios in Non-Life Insurance

    Wiltrud Weidner , J.-Matthias Graf von der Schulenburg

    Issue: Volume 5, Issue 1-1, February 2016
    Pages: 1-13
    Received: Apr. 18, 2015
    Accepted: Apr. 23, 2015
    Published: Jun. 10, 2015
    DOI: 10.11648/j.acm.s.2016050101.11
    Abstract: This paper provides an effective approach, known as dynamic financial analysis, to the systematic development of stress scenarios for the risk profile of non-life insurers, which can be used in risk analysis for the regulatory and rating assessment. The determination of company-specific stress scenarios is demonstrated, the resulting critical scena... Show More