Optimal asset allocation for a large number of investment opportunities

This paper introduces a stock‐picking algorithm that can be used to perform an optimal asset allocation for a large number of investment opportunities. The allocation scheme is based upon the idea of causal risk. Instead of referring to the volatility of the assets time series, the stock‐picking algorithm determines the risk exposure of the portfolio by concerning the non‐forecastability of the assets. The underlying expected return forecasts are based on time‐delay recurrent error correction neural networks, which utilize the last model error as an auxiliary input to evaluate their own misspecification. We demonstrate the profitability of our stock‐picking approach by constructing portfolios from 68 different assets of the German stock market. It turns out that our approach is superior to a preset benchmark portfolio. Copyright © 2005 John Wiley & Sons, Ltd.     

Money demand in the euro area: new insights from disaggregated data

Conventional money demand specifications in the euro area have become unstable since 2001. We specify a money demand equation in deviations of individual euro area Member States variables from the euro area average and show that the income elasticity as well as the interest rate semi-elasticity remain stable. The corresponding deep parameters of the utility function have not changed fundamentally. Aggregate money demand instability does therefore not result from altered standard factors determining the preference for holding money. Instead, other factors determine the aggregate monetary overhang. Since monetary developments cannot easily be explained by changing preferences, they should be closely monitored as they may actually be a sign of other factors.     

Making public transport financially sustainable

Over the past two decades, Germany has improved the quality of its public transport services and attracted more passengers while increasing productivity, reducing costs, and cutting subsidies. Public transport systems reduced their costs through organizational restructuring and outsourcing to newly founded subsidiaries; cutting employee benefits and freezing salaries; increasing work hours, using part-time employees, expanding job tasks, and encouraging retirement of older employees; cooperation with other agencies to share employees, vehicles, and facilities; cutting underutilized routes and services; and buying new vehicles with lower maintenance costs and greater passenger capacity per driver. Revenues were increased through fare hikes for single tickets while maintaining deep discounts for monthly, semester, and annual tickets; and raising passenger volumes by improved quality of service, and full regional coordination of timetables, fares, and services. Those efforts by public transport agencies were enhanced by the increasing costs and restrictions on car use in German cities. Although the financial performance of German public transport has greatly improved, there are concerns of inequitable burdens on labor, since many of the cost reduction measures involved reducing wages or benefits of workers.     

Retail banking and behavioral financial engineering: The case of structured products

We apply cumulative prospect theory and hedonic framing to evaluate discount reverse convertibles (DRCs) and reverse convertible bonds (RCBs) as important examples of structured products from a boundedly rational investor’s point of view. While common expected utility theory would also conclude that DRCs and RCBs are of interest to investors with moderate return expectations and underestimated stock return volatility, that theory would overestimate the market success of DRCs and underestimate that of RCBs in comparison to a situation with bounded rationality. Hedonic framing and relatively low subjectively felt competence levels of investors are decisive for the demand for RCBs.