#05-01 Robust Artificial Neural Networks for Pricing of European Options
#05-02 Hybrid Artificial Neural Networks for Efficient Valuation of Real Options and Financial Derivatives
#05-03 Real Options with Random Controls, Rare Events, and Risk-to-ruin
#05-04 Risk Factor Analysis and Portfolio Immunization in the Corporate Bond Market
#05-05 Controlling Currency Risk with Options or Forwards
#05-06 Incorporated Options in Scenario-Based Portfolio Optimization Models
#05-07 Environmental Management and Firm Performance in Financial Services
#05-08 On the Simulation of Portfolios of Interest Rate and Credit Risk Sensitive Securities
#05-09 Estimation of Asset Demands by Heterogeneous Agents
#05-10 The Survey of Consumer Finances: Sampling and Surveying in Cyprus
#05-11 Portfolio Inertia and Stock Market Fluctuations
#05-12 Defining Household Wealth in Business
#05-13 Asset and Liability Management for Insurance Products with Minimum Guarantees: The UK Case
#05-14 Integrating Market and credit Risk: A Simulation and Optimisation Perspective
Abstracts and downloadables
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Robust Artificial Neural Networks for Pricing of European Options
Panayiotis Andreou, Chris Charalambous, and Spiros H. Martzoukos, 2005
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Abstract The option pricing ability of Robust Artificial Neural networks optimized with the Huber function is compared against those optimized with Least Squares. Comparison is in respect to pricing European call options on the S&P 500 using daily data for the period April 1998 to August 2001. The analysis is augmented with the use of several historical and implied volatility measures. Implied volatilities are the overall average, and the average per maturity. Beyond the standard neural networks, hybrid networks that directly incorporate information from the parametric model are included in the analysis. It is shown that the artificial neural network models with the use of the Huber function outperform the ones optimized with least squares.
Computational Economics, Volume 27, Number (2-3), May 2006
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Hybrid Artificial Neural Networks for Efficient Valuation of Real Options and Financial Derivatives
Chris Charalambous and Spiros H. Martzoukos, 2005
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Abstract A hybrid valuation methodology is proposed and tested for improving the efficiency of contingent claims pricing by combining Artificial Neural Networks (ANN) and conventional parametric option pricing techniques. With one application on financial derivatives and one on real options the method's superiority is demonstrated. The resulting efficiency is instrumental for real time applications.
Computational Management Science, Volume 2, Issue 2, pp. 155-161, 2005
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Real Options with Random Controls, Rare Events, and Risk-to-ruin
Nicos Koussis, Lenos Trigeorgis, and Spiros H. Martzoukos, 2005
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Abstract Situations involving real investment options in the presence of multiple sources of jump risk, and controls are analyzed. Randomly arriving jumps include also the special cases of jump-to-ruin on the underlying asset, or on the contingent claim. Management has available impulse-type controls with random outcome. The analytic solutions when available, and a Markov-Chain numerical approach for solving more general investment decision problems are demonstrated.
Advances in Computational Management Science, Volume 9, Optimization, Econometrics and Financial Analysis, Part III, pp. 251-271, Springer Berlin Heidelberg, 2007
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Risk Factor Analysis and Portfolio Immunization in the Corporate Bond Market
Marida Bertocchi, Rosella Giacometti and Stavros A. Zenios, 2005
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Abstract In this paper we develop a multi-factor model for the yields of corporate bonds. The model allows the analysis of factors which influence the changes in the term structure of corporate bonds. More than 98% of the variability in the corporate bond market is captured by the model, which is then used to develop credit risk immunization strategies for corporate bonds of multiple credit ratings. Empirical results are given for the US market using data for the period 1992–1999.
European Journal of Operational Research, Volume 161, Issue 2, pp. 348-363, 2005
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Controlling Currency Risk with Options or Forwards
Nikolas Topaloglou, Hercules Vladimirou, and Stavros A. Zenios, 2005
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Abstract We consider alternative means for controlling currency risk exposure in actively-managed international portfolios. We extend multi-stage stochastic programming models to incorporate decions for optimal selection of forward contracts or currency options for hedging purposes. We adapt a valuation procedure to price currency options consistently with discrete distributions of exchange rates that are used in the context of stochastic programming model. We empirically assess the comparative effectiveness of alternative decision strategies through extensive numerical tests. Besides individual put options, we also consider trading strategies that involve combinations of options, and contrast them with optimal choices of forward contracts. We compare the alternative strategies both in static tests - in terms of their risk-return profiles - as well as in dynamic backtesting simulations using market data in a rolling horizon basis. We find that optimally selected currency forward contracts yield superior results in comparison to single protective puts per currency. However, option-trading strategies with suitable payoffs can improve performance in terms of higher portfolio returns. Moreover, we demonstrate that a multi-stage (dynamic) stochastic programming model consistently outperforms its single-stage (myopic) counterpart and yields incremental benefits.
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Forthcoming in P.M. Pardalos and C. Zopounidis (eds.), Financial Engineering Handbook, Springer
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Incorporated Options in Scenario-based Portfolio Optimization Models
Nikolas Topaloglou, Hercules Vladimirou, and Stavros A. Zenios, 2005
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Environmental Management and Firm Performance in Financial Services
Andreas C. Soteriou, Panos C. Vlamis, and Stavros A. Zenios, 2005
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On the Simulation of Portfolios of Interest Rate and Credit Risk Sensitive Securities
Norbert J. Jobst and Stavros A. Zenios, 2005
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Abstract We discuss extensions of reduced-form and structural models for pricing credit risky securities to portfolio simulation and valuation. Stochasticity in interest rates and credit spreads is captured via reduced-form models and is incorporated with a default and migration model based on the structural credit risk modelling approach. Calculated prices are consistent with observed prices and the term structure of default-free and defaultable interest rates. Three applications are discussed: (i) study of the inter-temporal price sensitivity of credit bonds and the sensitivity of future portfolio valuation with respect to changes in interest rates, default probabilities, recovery rates and rating migration, (ii) study of the structure of credit risk by investigating the impact of disparate risk factors on portfolio risk, and (iii) tracking of corporate bond indices via simulation and optimisation models. In particular, we study the effect of uncertainty in credit spreads and interest rates on the overall risk of a credit portfolio, a topic that has been recently discussed by Kiesel et al. [The structure of credit risk: spread volatility and ratings transitions. Technical report, Bank of England, ISSN1268-5562, 2001], but has been otherwise mostly neglected. We find that spread risk and interest rate risk are important factors that do not diversify away in a large portfolio context, especially when high-quality instruments are considered.
European Journal of Operational Research, Volume 161, Issue 2, pp. 298-324, 2005
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Estimation of Asset Demands by Heterogeneous Agents
Rita L. D'Ecclesia and Stavros A. Zenios, 2005
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Abstract We develop optimization models to analyze the demand for financial assets by heterogeneous agents. The models extend Frankel's [J. Portfolio Manage. 11 (4) (1985) 18] earlier approach, and relax the assumption of normality of asset returns. Instead, we assume that investors maximize an expected utility of terminal wealth based on heterogeneous attitudes toward risk. Solving a bi-level optimization program, we endogenously estimate the risk aversion parameters and derive the optimal asset holdings for each agent. The models are tested on United States market data, explaining the market structure better than previously postulated models.
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The Survey of Consumer Finances: Sampling and surveying in Cyprus
Alex Karagregoriou, 2005
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Abstract The University of Cyprus and the Central Bank of Cyprus started in March 1997 a special research project titled "Portfolios of Cyprus Households" which is fully funded by the Central Bank of Cyprus and is designed to fulfill the scope of a standard Survey of Consumer Finances, namely to collect information on household wealth from a nationally representative sample of Cyprus households. The first Cyprus project on the Survey of Consumer Finances (CySCF) took place in 1999 while the second in 2002. The Cyprus research team is currently preparing the launching of the 2005
CySCF. The conclusions of the 1999 CySCF which is offering a picture of family finances for the period 1998-1999 can be found in Haliassos et al. (2001, 2003) while the conclusions of the 2002 CySCF which is offering a picture of family finances for the period 2001-2002 can be found in Antoniou et al. (2004). The details for the sampling design of the 1999 and 2002 CySCF can be found in Karagrigoriou and Michael (2001) and Karagrigoriou, Michael and Antoniou (2004).
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Portfolio Inertia and Stock Market Fluctuations
Yannis Biias, Dimitris Georgarakos, and Michael Haliassos, September 2005
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Abstract Several recent studies have addressed household participation in the stock market, but relatively few have focused on household stock trading behavior. Household trading is important for the stock market, as households own more than 40% of the NYSE capitalization directly and can also influence trading patterns of institutional investors by adjusting their indirect stock holdings. Existing studies based on administrative data offer conflicting results. Discount brokerage data show excessive trading to the detriment of stockholders, while data on retirement accounts indicate extreme inactivity. This paper uses data representative of the population to document the extent of household portfolio inertia and to link it to household characteristics and to stock market movements. We document considerable portfolio inertia, as regards both changing stockholding participation status and trading stocks, and find that specific household characteristics contribute to the tendency to exhibit such inertia. Although our findings suggest some dependence of trading directly-held equity through brokerage accounts on the performance of the stock market index, they do not indicate that the recent expansion in the stockholder base and the experience of the stock market downswing have significantly altered the overall propensity of households to trade in stocks or to switch participation status in a way that could contribute to stock market instability.
Also available as CFS Working paper 2006/14
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Defining Household Wealth in Business
R. Bonci, L. Cannari, A. Karagregoriou, G. Marchese, and A. Neri, 2005
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Abstract In most European Countries, businesses represent an important share of household wealth. In Italy, according to the 2002 Italian Survey on Household Income and Wealth, more than 10 per cent of non financial assets are represented by businesses. Moreover such an asset accounts for about one third of the non financial wealth of entrepreneurs and members of arts or professions. Nevertheless, statistics on such components are not always readily available.
The main goal of the paper is to provide a pragmatic guide on the conceptual and practical issues which arise in the preparation of harmonised and comparable statistics on the value of businesses held by the household sector.
The analysis will focus on the national account definitions and on the questionnaires of the Canadian Survey of Financial Security (SFS), the Italian Survey on Household Income and Wealth (SHIW), the U.S. Survey on Consumer Finances (SCF) and the Cyprus Survey on Consumer Finances (CySCF).
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Asset and Liability Management for Insurance Products with Minimum Guarantees: The UK Case
Andrea Consiglio, David Saunders, and Stavros A. Zenios, 2005
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Abstract Modern insurance products are becoming increasingly complex, offering various guarantees, surrender options and bonus provisions. A case in point are the with-profits insurance policies offered by UK insurers. While these policies have been offered in some form for centuries, in recent years their structure and management have become substantially more involved. The products are particularly complicated due to the wide discretion they afford insurers in determining the bonuses policyholders receive. In this paper, we study the problem of an insurance firm attempting to structure the portfolio underlying its with-profits fund. The resulting optimization problem, a non-linear program with stochastic variables, is presented in detail. Numerical results show how the model can be used to analyze the alternatives available to the insurer, such as different bonus policies and reserving methods.
Journal of Banking & Finance, Volume 30, Issue 2, pp. 645-667, February 2006
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Integrating Market and credit Risk: A Simulation and Optimisation Perspective
Norbert J. Jobst, Gautam Mitra, and Stavros A. Zenios, 2005
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Abstract We introduce a modelling paradigm which integrates credit risk and market risk in describing the random dynamical behaviour of the underlying fixed income assets. We then consider an asset and liability management (ALM) problem and develop a multistage stochastic programming model which focuses on optimum risk decisions. These models exploit the dynamical multiperiod structure of credit risk and provide insight into the corrective recourse decisions whereby issues such as the timing risk of default is appropriately taken into consideration. We also present an index tracking model in which risk is measured (and optimised) by the CVaR of the tracking portfolio in relation to the index. In-sample as well as out-of-sample (backtesting) experiments are undertaken to validate our approach. The main benefits of backtesting, that is, ex-post analysis are that (a) we gain insight into asset allocation decisions, and (b) we are able to demonstrate the feasibility and flexibility of the chosen framework.
Journal of Banking & Finance, Volume 30, Issue 2, pp. 717-742,, February 2006
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