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Through a series of articles spanning over 15 years of research, Paul D. Kaplan, who developed the methodologies behind the Morningstar Rating and the Morningstar Style Box tackles the issues investors face when they attempt to put the concepts of asset allocation into practice, among them: How should the asset classes be defined? Should equities be divided into asset classes based on investment style, geography, or other factors? Should asset classes be represented by market-cap-weighted indexes or should other principles, such as fundamental weights, be used? How do actively managed funds fit into asset-class mixes? Kaplan also interviews the intellectuals who have greatly influenced the evolution of asset allocation, including Harry Markowitz, Roger Ibbotson, and the late Benoit Mandelbrot. Throughout the book, Kaplan offers his own opinions and analysis. He includes three appendices that put theory into action with technical details for new asset-allocation frameworks, including the next generation of portfolio construction, which Kaplan dubs 'Markowitz 2.0.'

"Through a series of articles spanning over 15 years of research, Paul D. Kaplan, who developed the methodologies behind the Morningstar Rating and the Morningstar Style Box tackles the issues investors face when they attempt to put the concepts of asset allocation into practice, among them: How should the asset classes be defined? Should equities be divided into asset classes based on investment style, geography, or other factors? Should asset classes be represented by market-cap-weighted indexes or should other principles, such as fundamental weights, be used? How do actively managed funds fit into asset-class mixes? Kaplan also interviews the intellectuals who have greatly influenced the evolution of asset allocation, including Harry Markowitz, Roger Ibbotson, and the late Benoit Mandelbrot. Throughout the book, Kaplan offers his own opinions and analysis. He includes three appendices that put theory into action with technical details for new asset-allocation frameworks, including the next generation of portfolio construction, which Kaplan dubs 'Markowitz 2.0.'"--

Ereignisse wie die Asienkrise 1997, das Platzen der New Economy Blase um die Jahrtausendwende und die Subprime- und Kreditkrise ab 2007, haben tiefe Spuren hinterlassen. Anleger erlitten dieser Tage schwere Wertminderungen ihrer Portfolios bis hin zum Totalverlust ihres Vermögens. Enttäuschung und Frustration über die scheinbare Hilflosigkeit der Investmentbranche machte sich breit und die Risikoaversion der Marktteilnehmer stieg zusehends. Die vermeintlich zunehmende Häufigkeit spekulativer Booms mit anschließenden Kurseinbrüchen und das Versagen der Investmentbranche in solchen Krisenzeiten führte zu einer Desillusionierung hinsichtlich des Erfolgs traditioneller Asset Allocation. Im Zuge dieser Entwicklungen wurden viele von der Notwendigkeit eines Paradigmenwechsels im Portfolio Management überzeugt. Die mangelhafte Prognosefähigkeit der traditionellen Asset Allocation in hochvolatilen Zeiten begünstigte die Entwicklung moderner Verfahren, die solch riskante Phasen besser berücksichtigen sollen. In der vorliegenden Studie werden neben erprobten Ansätzen moderne risikoorientierte Verfahren präsentiert, die der zunehmenden Dynamik der Kapitalmärkte Rechnung tragen. Weiterhin wird das Phänomen spekulativer Blasen von ihrer Entstehung über die Wachstumsphase bis hin zum Zusammenbruch dargestellt. Auch die begrenzte Rationalität der Marktteilnehmer findet in den Ausführungen zur Behavioral Finance Theorie Beachtung. Michael Ledvinka wurde 1984 in Erlenbach am Main geboren. Der Autor schloss das Studium der Betriebswirtschaft und des Rechts mit den Schwerpunkten Finance und Controlling mit dem Diplom ab. Darüber hinaus sammelte er während seines Studiums umfangreiche Praxiserfahrung im In- und Ausland. Seit Abschluss seines Studiums ist er als Analyst im Bereich Finance in einer internationalen Managementberatung tätig.

Il presente elaborato affronta il tema dell'asset management, ossia della gestione di un portafoglio di attività finanziarie.Si tratta di un processo produttivo orientato alla realizzazione di combinazioni efficienti ex ante tra rischio e rendimento, in un definito orizzonte temporale di investimento. Molti investitori istituzionali adottano politiche di gestione dell'investimento che seguono strategie di "portfolio insurance", le quali tipicamente consistono nella massimizzazione dell'utilità attesa o di un'altra funzione obiettivo della ricchezza sotto il vincolo che la stessa sia superiore ad un determinato livello. In un tale contesto si è ritenuto interessante illustrare, sia al livello teorico che applicato, un particolare metodo di "asset allocation" che ha come obiettivo la selezione del portafoglio ottimo utilizzando la misura di rischio "Value-at-Risk" come vincolo di perdita attesa. Tale "framework" è stato adottato da vari autori, costituendo il punto di riferimento principale per la realizzazione di alcune applicazioni empiriche, aventi la finalità di derivare l'allocazione ottimale di portafoglio in differenti contesti.Il primo contesto, in questa sede presentato, consiste nella creazione di portafogli di investimento ottimali composti da azioni e obbligazioni "U.S."; il secondo ha la finalità di costruire portafogli attraverso combinazioni ottimali di attività finanziarie quali metalli preziosi, petrolio e azioni; infine, la terza ed ultima applicazione esposta adotta il suddetto metodo al fine di ricavare la suddivisione ottima della ricchezza tra titoli rischiosi e un titolo privo di rischio. In quest'ultimo caso, il "framework" di riferimento viene modificato, con lo scopo di permettere che la capacità di rischio dell'investitore rientri nella procedura di ottimizzazione. Ciò in quanto l'attività di asset allocation fa parte del processo più generale di financial planning, che si può definire come quel processo che va dall'introspezione psicologica dell'investitore (propensione al rischio), alla valutazione preventiva delle proprie necessità finanziarie (obiettivi di investimento), all'individuazione delle soluzioni più appropriate (asset allocation).La trattazione ha imposto la conoscenza di alcuni fondamenti teorici, importanti per la comprensione del modello adottato e dei vari risultati raggiunti attraverso la sua attuazione. Si è ritenuto dunque fondamentale esporre le basi della teoria di portafoglio di Markowitz e i suoi successivi sviluppi tra i quali si annoverano il capital asset pricing model e le misure VaR e CVaR. Il suddetto quadro teorico costituisce il primo capitolo del presente elaborato. A questa prima parte segue un secondo capitolo che, oltre a porre le basi teoriche della selezione di portafoglio laddove essa sia vincolata dalle misure VaR e CVaR, serve per eseguire un confronto delle suddette misure di rischio, ampiamente diffuse e comunemente impiegate dalle istituzioni finanziarie. Si è infine ritenuto essenziale ampliare la ricerca, dal punto di vista sperimentale, integrandola mediante la presentazione delle varie applicazioni del criterio di asset allocation proposto, le quali compongono il terzo capitolo.

We study the asset allocation of an investor with prospect theory (PT) preferences. First, we solve analytically the two-asset problem of the PT investor for one risk-free and one risky asset and find that loss aversion and the reference return affect differently less ambitious investors and more ambitious investors. Second, we empirically investigate the performance of a PT portfolio when diversifying among a stock market index, a government bond and gold, in Europe and the US. We focus on investors with PT preferences under different scenarios regarding the reference return and the degree of loss aversion and compare their portfolio performance with the performance of investors under CVaR, risk neutral, linear loss averse and in particular mean-variance (MV) preferences. We find that, in the US, PT portfolios significantly outperform (in terms of returns) mean-variance portfolios in the majority of cases. Also with respect to riskadjusted performance, PT investment outperforms MV investment in the US. Similar results, however, can not be observed in Europe. Finally, we analyze asymmetric effects along economic uncertainty and observe that PT investment leads to higher returns than MV investment in times of larger economic uncertainty, especially in the US.

We study the asset allocation of an investor with prospect theory (PT) preferences. First, we solve analytically the two-asset problem of the PT investor for one risk-free and one risky asset and find that loss aversion and the reference return affect differently less ambitious investors and more ambitious investors. Second, we empirically investigate the performance of a PT portfolio when diversifying among a stock market index, a government bond and gold, in Europe and the US. We focus on investors with PT preferences under different scenarios regarding the reference return and the degree of loss aversion and compare their portfolio performance with the performance of investors under CVaR, risk neutral, linear loss averse and in particular mean-variance (MV) preferences. We find that, in the US, PT portfolios signiffcantly outperform (in terms of returns) mean-variance portfolios in the majority of cases. Also with respect to riskadjusted performance, PT investment outperforms MV investment in the US. Similar results, however, can not be observed in Europe. Finally, we analyze asymmetric effects along economic uncertainty and observe that PT investment leads to higher returns than MV investment in times of larger economic uncertainty, especially in the US.

We study the asset allocation of an investor with prospect theory (PT) preferences. First, we solve analytically the two-asset problem of the PT investor for one risk-free and one risky asset and find that loss aversion and the reference return affect differently less ambitious investors and more ambitious investors. Second, we empirically investigate the performance of a PT portfolio when diversifying among a stock market index, a government bond and gold, in Europe and the US. We focus on investors with PT preferences under different scenarios regarding the reference return and the degree of loss aversion and compare their portfolio performance with the performance of investors under CVaR, risk neutral, linear loss averse and in particular mean-variance (MV) preferences. We find that, in the US, PT portfolios signiffcantly outperform (in terms of returns) mean-variance portfolios in the majority of cases. Also with respect to riskadjusted performance, PT investment outperforms MV investment in the US. Similar results, however, can not be observed in Europe. Finally, we analyze asymmetric effects along economic uncertainty and observe that PT investment leads to higher returns than MV investment in times of larger economic uncertainty, especially in the US.