Radu Tunaru
University of Kent, Kent Business School, Faculty Member
This book brings together the latest concepts and models in real-estate derivatives, the new frontier in financial markets. The importance of real-estate derivatives in managing property price risk that has destabilized economies... more
This book brings together the latest concepts and models in real-estate derivatives, the new frontier in financial markets. The importance of real-estate derivatives in managing property price risk that has destabilized economies frequently over the last hundred years has been brought into the limelight by Robert Shiller. In spite of his masterful campaign for the introduction of real-estate derivatives, these financial instruments are still in a state of infancy. This book aims to provide a state-of-the-art overview of real-estate derivatives, covering the description of these financial products, their applications, and the most important models proposed in the literature. In order to facilitate a better understanding of the situations when these products can be successfully used, ancillary topics such as real-estate indices, mortgages, securitization, and equity release mortgages are also discussed. The book examines econometric aspects of real-estate index prices time series and ...
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Research Interests: Finance, Economics, Econometrics, Financial Economics, Empirical Finance, and 15 moreBanking, Bayesian Inference, Credit Rating, Markov Chain Monte Carlo, Credit Risk, Model Calibration, Key words, Basel II, Markov chain, Low Risk, Bayesian Probability, Hg, Bayesian approach, Finance and Investment Banking, and Latent Factors
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Review of Economics and Statistics: Forthcoming
Running title: Modeling stochastic political risk In this paper we model political risk for international capital budgeting as the value of a hypothetical insurance policy that pays the holder any and all losses arising from political... more
Running title: Modeling stochastic political risk In this paper we model political risk for international capital budgeting as the value of a hypothetical insurance policy that pays the holder any and all losses arising from political events. We address three important aspects of political risk that are widely acknowledged in the literature but either missing or incomplete in existing mathematical models: 1) loss causing political events arise from a wide range of sources, which are often mutually dependent; 2) the effect of a political event in terms of actual losses can vary depending on the economic, social and political conditions when it occurs; 3) the composition and the importance of the individual sources of political risk can change over time. Thus, the multivariate nature and dependency of loss causing political events are modeled as a conditional Poisson process that allows for dependency between the increments of the counting process. To account for the random effect of ...
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Although property markets represent a large proportion of total wealth in developed countries, the real-estate derivatives markets are still lagging behind in volume of trading and liquidity. Over the last few years there has been... more
Although property markets represent a large proportion of total wealth in developed countries, the real-estate derivatives markets are still lagging behind in volume of trading and liquidity. Over the last few years there has been increased activity in developing derivative instruments that can be utilised by asset managers. In this paper, we discuss the problems encountered when using property derivatives for managing European real-estate risk. We also consider a special class of structured interest rate swaps that have embedded real-estate risk and propose a more efficient way to tailor these swaps.
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In this article I investigate empirically what determines the dynamics of the IPD index that is representative for the commercial real-estate in UK. The... more
In this article I investigate empirically what determines the dynamics of the IPD index that is representative for the commercial real-estate in UK. The macroeconomicandinterestratevariablesidentifiedinthiscontextcanreproduceaproxyfundamentaleconomiccomponentunderpinning thecommercial real-estate price returns in UK. The analysis covers the period January 1987 to December 2011 and it is conducted at monthly and quarterly frequency. The motivation for this research is to provide a tool for pricing IPD property derivatives and other investment applications based on these financial products. The IPD derivatives pricing is developed employing the conditional Esscher transform, suitable for incomplete markets such as property. The model can also be used for risk management purposes and for trading strategies based on signalling of market disillusion.
Index-linked securities are offered by banks, financial institutions and building societies to investors looking for downside risk protection whilst still providing upside equity index participation. This article explores how reverse... more
Index-linked securities are offered by banks, financial institutions and building societies to investors looking for downside risk protection whilst still providing upside equity index participation. This article explores how reverse cliquet options can be integrated into the structure of a guaranteed principal bond. Pricing problems are discussed under the standard Black-Scholes model and under the constant-elasticity-of-variance model. Forward start options are the main element of this structure and new closed formulae are obtained for these options under the latter model. Risk management issues are also discussed. An example is described showing how this structure can be implemented and how the financial engineer may forecast the coupon payment that will be made to investors buying this product without exposing the issuing institution to risk of loss.
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functions and uniformly most powerful tests for inverse Gaussian distribution
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Abstract: The aim of this paper is to develop a model for analyzing multiple response models for count data and that may take into account complex cor-relation structures. The model is specified hierarchically in several layers and can be... more
Abstract: The aim of this paper is to develop a model for analyzing multiple response models for count data and that may take into account complex cor-relation structures. The model is specified hierarchically in several layers and can be used for sparse data as it is shown in the second part of the paper. It is a discrete multivariate response approach regarding the left side of models equations. Markov Chain Monte Carlo techniques are needed for extracting inferential results. The possible correlation between different counts is more general than the one used in repeated measurements or longitudinal studies framework.
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studies [2], [4], [7], [10] and [14] showing how it can be applied to highly skewed data observed in various industrial processes. The Alpha distribution is less known [8], [9] and as such inferential tools are less developed. The aim of... more
studies [2], [4], [7], [10] and [14] showing how it can be applied to highly skewed data observed in various industrial processes. The Alpha distribution is less known [8], [9] and as such inferential tools are less developed. The aim of this paper is to fill that gap in the literature and provide uniformly most powerful unbiased tests for discriminating between series of data coming from different populations. The results presented here may have potential applications in reliability modelling and applied statistics for control of industrial processes as already exemplified in [1], [3], and [12]. The paper is organised as follows. The next section briefly introduces the main elements following from the classical exponential family set-up. Section 3 contains the main results of the paper concerning tests of the differences between the parameters of the same type when the other parameters are unknown. The last section summarises the conclusions.
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The aim of this paper is to discuss the hedging techniques that a company based in an emerging market country can use to hedge the risk associated with jet fuel or kerosene. The company can be an airline company or a market intermediary... more
The aim of this paper is to discuss the hedging techniques that a company based in an emerging market country can use to hedge the risk associated with jet fuel or kerosene. The company can be an airline company or a market intermediary offering contracts on this important commodity. An empirical analysis reveals two main directions for minimum risk hedging: one is to cross-hedge directly the commodity itself using the futures contract on another commodity or a basket of commodities highly correlated with jet fuel; the second is to use the futures contract on kerosene in Tokyo and then the problem is transformed into cross hedging the currency. JEL classification: G13, G15, F31
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The generalized Rayleigh distribution is a two-parameter family of distributions having Rayleigh, Maxwell and chi-square distributions as particular cases. We propose uniformly most powerful unbiased tests for discriminating between the... more
The generalized Rayleigh distribution is a two-parameter family of distributions having Rayleigh, Maxwell and chi-square distributions as particular cases. We propose uniformly most powerful unbiased tests for discriminating between the parameters θ of two generalized Rayleigh distributions, conditional on the value of parameters k.
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This study examines the risk premia embedded in index option prices using a sample of emerging European Union countries. In contrast to the `over-priced puts puzzle' in the US market, writing puts in developing European exchanges is... more
This study examines the risk premia embedded in index option prices using a sample of emerging European Union countries. In contrast to the `over-priced puts puzzle' in the US market, writing puts in developing European exchanges is found to offer insignificant returns after accounting for risk. However, investors were paying a substantial premium for insurance against volatility risk, especially during the crisis. Insurance against negative skewness also commanded a high premium before the crisis, that disappeared post 2008. The returns of profitable option-selling strategies cannot be explained in an obvious way as compensation for risk across a set of factors.
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In this paper hypothesis tests are proposed for discrimination between the populations of two Alpha distributions. This distribution is used for highly skewed data. The tests developed here are uniformly most powerful unbiased and can be... more
In this paper hypothesis tests are proposed for discrimination between the populations of two Alpha distributions. This distribution is used for highly skewed data. The tests developed here are uniformly most powerful unbiased and can be used to test various general hypotheses related to this probability distribution which is less known by professional statisticians.
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Uncertainty is one of the most important concept in financial mathematics applications. In this paper we review some important aspects related to the application of entropy-related concepts to option pricing. The Kullback-Leibler... more
Uncertainty is one of the most important concept in financial mathematics applications. In this paper we review some important aspects related to the application of entropy-related concepts to option pricing. The Kullback-Leibler information divergence and the informational energy introduced by Onicescu are the main tools investigated in this paper. We highlight a necessary condition that must be verified when obtaining the probability distribution minimising the Kullback-Leibler information divergence. Deriving a probability distribution by optimising the information energy has some pitfalls that are discussed in this paper.
Measuring model risk is required by regulators on financial and insurance markets. We separate model risk into parameter estimation risk and model specification risk, and we propose expected shortfall type model risk measures applied to... more
Measuring model risk is required by regulators on financial and insurance markets. We separate model risk into parameter estimation risk and model specification risk, and we propose expected shortfall type model risk measures applied to Levy jump models and affine jump-diffusion models. We investigate the impact of parameter estimation risk and model specification risk on the models' ability to capture the joint dynamics of stock and option prices. We estimate the parameters using Markov chain Monte Carlo techniques, under the risk-neutral probability measure and the real-world probability measure jointly. We find strong evidence supporting modeling of price jumps.
This paper tests how closely the three leading market-based systemic risk measures (SRM) agree with the list of global systemically important banks (G-SIB) from the Financial Stability Board (FSB) and how closely they match the... more
This paper tests how closely the three leading market-based systemic risk measures (SRM) agree with the list of global systemically important banks (G-SIB) from the Financial Stability Board (FSB) and how closely they match the categorization of G-SIBs into the five systemic risk buckets used by the FSB to assign capital surcharges to G-SIBs. In addition, we investigate the concordance among these SRMs and with the FSB's designation methodology for G-SIBs. Finally, we test how these SRMs incorporate the information from high volatile events between 2015 to 2018. Our results show that alternative measures produce different estimates of systemic risk, systemically important banks and categories, with the SRISK ranking having the highest concordance with the FSB's classification of G-SIBs. In contrast, the three measures all promptly react to high volatile events.
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Capital adequacy is the key microprudential and macroprudential tool of banking regulation. Financial models of capital adequacy are subject to errors, which may prevent from estimating a sufficient capital base to absorb bank losses... more
Capital adequacy is the key microprudential and macroprudential tool of banking regulation. Financial models of capital adequacy are subject to errors, which may prevent from estimating a sufficient capital base to absorb bank losses during economic downturns. In this paper, we propose a general method to account for model risk in capital requirements calculus related to market risk. We then evaluate and compare our capital requirements values with those obtained under Basel 2.5 and the new Basel 4 regulation. Capital requirements adjusted for model risk perform well in containing losses generates in normal and stressed times. In addition, they are as conservative as Basel 4 capital requirements, but they exhibit less fluctuations over time.
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This paper is concerned with models for accident numbers at sites within a road network. It highlights the need to analyse data in a disaggregated form, rather than considering total accidents at a site. Obviously it is easier to analyse... more
This paper is concerned with models for accident numbers at sites within a road network. It highlights the need to analyse data in a disaggregated form, rather than considering total accidents at a site. Obviously it is easier to analyse the data in a more aggregated form, but this approach can overlook important aspects of the underlying phenomena and misleading conclusions may be drawn from an aggregated analysis. The data analysed in this paper concern 156 single-carriageway link sites in Kent. The models proposed are multiple response models, where different types of accident (according to severity and the number of vehicles involved) are modelled simultaneously. Two quite similar classes of model are investigated. Both classes can be described as mixed generalised linear models, or hierarchical models, with the mean of each response variable equal to the product of a random effect and a regression term based on important explanatory variables such as speed limit, link length and estimated traffic. For one class the random effect is gamma distributed and for the other class it is a log-Normal random effect. The models are hierachical Bayesian, structuring the unknown parameters in different layers. In this way a better stochastic approximation is proposed of the causal machinery producing the phenomenon analysed. Inference is based on empirical quantities describing the posterior distributions of the parameters of interest. The multi-dimensional integrals involved in the analysis are approximated using Markov Chain Monte Carlo methods. (A)