25,734 research outputs found

    (WP 2014-01) Is Bitcoin the \u27Paris Hilton\u27 of the Currency World? Or Are the Early Investors onto Something That Will Make Them Rich? [updated version]

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    The bitcoin phenomenon, and the technological innovation that made it possible, is interesting - but for investors large and small, the more pertinent question is whether they should buy the digital currency or avoid it. We analyze a bitcoin investment from the standpoint of an investor with a diversified portfolio using both in-sample and out-of-sample settings. Within the in-sample setting, bitcoin does not yield added value to investors with utility function consistent with the mean-variance setting. On the other hand, they do offer diversification benefits to investors with negative exponential and power utility functions. However, these benefits are not preserved in the out-of-sample framework. In most cases, the optimal portfolios that include only the traditional asset classes appear to have superior performance

    Portfolio Performance Gauging in Discrete Time Using a Luenberger Productivity Indicator

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    This paper proposes a pragmatic, discrete time indicator to gauge the performance of portfolios over time. Integrating the shortage function (Luenberger, 1995) into a Luenberger portfolio productivity indicator (Chambers, 2002), this study estimates the changes in the relative positions of portfolios with respect to the traditional Markowitz mean-variance efficient frontier, as well as the eventual shifts of this frontier over time. Based on the analysis of local changes relative to these mean-variance and higher moment (in casu, mean-variance-skewness) frontiers, this methodology allows to neatly separate between on the one hand performance changes due to portfolio strategies and on the other hand performance changes due to the market evolution. This methodology is empirically illustrated using a mimicking portfolio approach (Fama and French 1996; 1997) using US monthly data from January 1931 to August 2007.shortage function, mean-variance, mean-variance-skewness, efficient portfolios, Luenberger portfolio productivity indicator

    E-finance-lab at the House of Finance : about us

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    The financial services industry is believed to be on the verge of a dramatic [r]evolution. A substantial redesign of its value chains aimed at reducing costs, providing more efficient and flexible services and enabling new products and revenue streams is imminent. But there seems to be no clear migration path nor goal which can cast light on the question where the finance industry and its various players will be and should be in a decade from now. The mission of the E-Finance Lab is the development and application of research methodologies in the financial industry that promote and assess how business strategies and structures are shared and supported by strategies and structures of information systems. Important challenges include the design of smart production infrastructures, the development and evaluation of advantageous sourcing strategies and smart selling concepts to enable new revenue streams for financial service providers in the future. Overall, our goal is to contribute methods and views to the realignment of the E-Finance value chain. ..

    Review of the Proposed Reserve Markets in New England

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    ISO New England proposes reserve markets designed to improve the existing forward reserve market and improve pricing during real-time reserve shortages. We support all of the main elements of the proposal. For example, we agree that little is gained by allowing reserve availability bids in the day-ahead market. Doing so greatly increases the complexity of the market without the prospect of more efficient pricing. Rather, offline reserves are most efficiently priced and awarded well in advance, as is done by the improved forward reserve market.Auctions; Multiple Object Auctions; Electricity Auctions

    Financial contagion: Evolutionary optimisation of a multinational agent-based model

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    Over the past two decades, financial market crises with similar features have occurred in different regions of the world. Unstable cross-market linkages during a crisis are referred to as financial contagion. We simulate crisis transmission in the context of a model of market participants adopting various strategies; this allows testing for financial contagion under alternative scenarios. Using a minority game approach, we develop an agent-based multinational model and investigate the reasons for contagion. Although the phenomenon has been extensively investigated in the financial literature, it has not been studied through computational intelligence techniques. Our simulations shed light on parameter values and characteristics which can be exploited to detect contagion at an earlier stage, hence recognising financial crises with the potential to destabilise cross-market linkages. In the real world, such information would be extremely valuable in developing appropriate risk management strategies
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