1,462 research outputs found
Optimal consumption and investment with bounded downside risk for power utility functions
We investigate optimal consumption and investment problems for a
Black-Scholes market under uniform restrictions on Value-at-Risk and Expected
Shortfall. We formulate various utility maximization problems, which can be
solved explicitly. We compare the optimal solutions in form of optimal value,
optimal control and optimal wealth to analogous problems under additional
uniform risk bounds. Our proofs are partly based on solutions to
Hamilton-Jacobi-Bellman equations, and we prove a corresponding verification
theorem. This work was supported by the European Science Foundation through the
AMaMeF programme.Comment: 36 page
Beta lives - some statistical perspectives on the capital asset pricing model
This note summarizes some technical issues relevant to the use of the idea of excess return in empirical modelling. We cover the case where the aim is to construct a measure of expected return on an asset and a model of the CAPM type is used. We review some of the problems and show examples where the basic CAPM may be used to develop other results which relate the expected returns on assets both to the expected return on the market and other factors
"Better Safe than Sorry" - Individual Risk-free Pension Schemes in the European Union - Macroeconomic Benefits, the Mobile Working Citizen's Perspective and Why Nots
Variations between the diverse pension systems in the member states of the European Union hamper labour market mobility, across country borders but also within the countries of the European Union. From a macroeconomic perspective, and in the light of demographic pressure, this paper argues that allowing individual instead of collective pension building would greatly improve labour market flexibility and thus enhance the functioning of the monetary union. I argue that working citizens would benefit, for three reasons, from pension saving in a risk-free savings account. First, citizens would have a clear picture of the accumulation of their own pension savings throughout their working life. Second, they would pay hardly any extra costs and, third, once retired they would not be subject to the whims of government or other pension fund managers. This paper investigates the feasibility of individual pension building under various parameter settings by calculating the pension saved during a working life and the pension dis-saved after retirement. The findings show that there are no reasons why the European Union and individual member states should not allow individual risk-free pension savings accounts. This would have macroeconomic benefits and provide a solid pension provision that can enhance mobility, instead of engaging workers in different mandatory collective pension schemes that exist around in the European Union
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Extremes on the discounted aggregate claims in a time dependent risk model
This paper presents an extension of the classical compound Poisson risk model for which the inter-claim time and the forthcoming claim amount are no longer independent random variables (rv's). Asymptotic tail probabilities for the discounted aggregate claims are presented when the force of interest is constant and the claim amounts are heavy tail distributed rv's. Furthermore, we derive asymptotic finite time ruin probabilities, as well as asymptotic approximations for some common risk measures associated with the discounted aggregate claims. A simulation study is performed in order to validate the results obtained in the free interest risk model
Derivatives and Credit Contagion in Interconnected Networks
The importance of adequately modeling credit risk has once again been
highlighted in the recent financial crisis. Defaults tend to cluster around
times of economic stress due to poor macro-economic conditions, {\em but also}
by directly triggering each other through contagion. Although credit default
swaps have radically altered the dynamics of contagion for more than a decade,
models quantifying their impact on systemic risk are still missing. Here, we
examine contagion through credit default swaps in a stylized economic network
of corporates and financial institutions. We analyse such a system using a
stochastic setting, which allows us to exploit limit theorems to exactly solve
the contagion dynamics for the entire system. Our analysis shows that, by
creating additional contagion channels, CDS can actually lead to greater
instability of the entire network in times of economic stress. This is
particularly pronounced when CDS are used by banks to expand their loan books
(arguing that CDS would offload the additional risks from their balance
sheets). Thus, even with complete hedging through CDS, a significant loan book
expansion can lead to considerably enhanced probabilities for the occurrence of
very large losses and very high default rates in the system. Our approach adds
a new dimension to research on credit contagion, and could feed into a rational
underpinning of an improved regulatory framework for credit derivatives.Comment: 26 pages, 7 multi-part figure
Sand in the wheels, or oiling the wheels, of international finance? : New Labour's appeal to a 'new Bretton Woods'
Tony Blair’s political instinct typically is to associate himself only with the future. As such, his explicit appeal to ‘the past’ in his references to New Labour’s desire to establish a “new Bretton Woods” is sufficient in itself to arouse some degree of analytical curiosity (see Blair 1998a). The fact that this appeal was made specifically in relation to Bretton Woods is even more interesting. The resonant image of the international economic context established by the original Bretton Woods agreements invokes a style and content of policy-making which Tony Blair typically dismisses as neither economically nor politically consistent with his preferred vision of the future (see Blair 2000c, 2001b)
Regularizing Portfolio Optimization
The optimization of large portfolios displays an inherent instability to
estimation error. This poses a fundamental problem, because solutions that are
not stable under sample fluctuations may look optimal for a given sample, but
are, in effect, very far from optimal with respect to the average risk. In this
paper, we approach the problem from the point of view of statistical learning
theory. The occurrence of the instability is intimately related to over-fitting
which can be avoided using known regularization methods. We show how
regularized portfolio optimization with the expected shortfall as a risk
measure is related to support vector regression. The budget constraint dictates
a modification. We present the resulting optimization problem and discuss the
solution. The L2 norm of the weight vector is used as a regularizer, which
corresponds to a diversification "pressure". This means that diversification,
besides counteracting downward fluctuations in some assets by upward
fluctuations in others, is also crucial because it improves the stability of
the solution. The approach we provide here allows for the simultaneous
treatment of optimization and diversification in one framework that enables the
investor to trade-off between the two, depending on the size of the available
data set
Dynamic modeling of mean-reverting spreads for statistical arbitrage
Statistical arbitrage strategies, such as pairs trading and its
generalizations, rely on the construction of mean-reverting spreads enjoying a
certain degree of predictability. Gaussian linear state-space processes have
recently been proposed as a model for such spreads under the assumption that
the observed process is a noisy realization of some hidden states. Real-time
estimation of the unobserved spread process can reveal temporary market
inefficiencies which can then be exploited to generate excess returns. Building
on previous work, we embrace the state-space framework for modeling spread
processes and extend this methodology along three different directions. First,
we introduce time-dependency in the model parameters, which allows for quick
adaptation to changes in the data generating process. Second, we provide an
on-line estimation algorithm that can be constantly run in real-time. Being
computationally fast, the algorithm is particularly suitable for building
aggressive trading strategies based on high-frequency data and may be used as a
monitoring device for mean-reversion. Finally, our framework naturally provides
informative uncertainty measures of all the estimated parameters. Experimental
results based on Monte Carlo simulations and historical equity data are
discussed, including a co-integration relationship involving two
exchange-traded funds.Comment: 34 pages, 6 figures. Submitte
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