Neural Networks in the Capital Markets: An Application to Index Forecasting

In this article we construct an Index of Austrian Initial Public Offerings (IPOX) which is isomorph to the Austrian Traded Index (ATX). Conjecturing that the ATX qualifies as an explaining variable for the IPOX, we investigate the time trend properties of and the comovement between the two indices. We use the relationship to construct a TJ.eural network and a linear error-correction forecasting model for the IPOX and base a tracling scheme on either forecast. The results suggest that trading based on the forecasts significantly increases an investor's return as compared to Buy and Hold or simple Moving Average trading strategies.Series: Department of Economics Working Paper Serie

Wealth and cohort size: stock market boom or bust ahead?

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Human Capital Depletion, Human Capital Formation, and Migration. A Blessing in a "Curse"?

We specify conditions under which a strictly positive probability of employment in a foreign country raises the level of human capital formed by optimizing workers in the home country. While some workers migrate, "taking along" more human capital than if they had migrated without factoring in the possibility of migration (a form of brain drain), other workers stay at home with more human capital than they would have formed in the absence of the possibility of migration (a form of brain gain).Human Capital Formation, Migration

Forecasting Austrian IPOs: An Application of Linear and Neural Network Error-Correction Models

In this paper we apply cointegration and Granger-causality analyses to construct linear and neural network error-correction models for an Austrian Initial Public Offerings IndeX (IPOXATX). We use the significant relationship between the IPOXATX and the Austrian Stock Market Index ATX to forecast the IPOXATX. For prediction purposes we apply augmented feedforward neural networks whose architecture is determined by Sequential Network Construction with the Schwartz Information Criterion as an estimator for the prediction risk. Trading based on the forecasts yields results superior to Buy and Hold or Moving Average trading strategies in terms of mean-variance considerations.Initial Public Offerings, Neural Networks, Stock Market Index, Cointegration Analysis

Forecasting Stock Market Averages to Enhance Profitable Trading Strategies

In this paper we design a simple trading strategy to exploit the hypothesized distinct informational content of the arithmetic and geometric mean. The rejection of cointegration between the two stock market indicators supports this conjecture. The profits generated by this cheaply replicable trading scheme cannot be expected to persist. Therefore we forecast the averages using autoregressive linear and neural network models to gain a competitive advantage relative to other investors. Refining the trading scheme using the forecasts further increases the mean return as compared to a buy and hold strategy.Trading Strategy, Stock Market Index, Neural Networks, Cointegration

Prediction Risk and the Forecasting of Stock Market Indexes

In most of the empirical research on capital markets, stock market indexes are used as proxies for the aggregate market development. In previous work we found that a particular market segment might be less efficient than the whole market and hence easier to forecast. In this paper we extend the focus of this investigation by taking a comprehensive look at the Vienna Stock Exchange. We use feedforward networks and linear models to forecast the all share index WBI as well as various subindexes covering the highly liquid, semi-liquid, and initial public offering (IPO) market segment. In order to shed some light on network construction principles, we compare different models as selected by hold-out crossvalidation (HCV), Akaike's information criterion (AIC), and Schwartz' information criterion (SIC). The forecasts are subsequently evaluated on the basis of hypothetical trading in the out-of-sample period.Neural Network Architecture Selection, Information Criteria, Stock Market Indexes, Trading Strategy

An Exploratory Analysis of Joint Ventures' Performance in Romania

This paper gives empirical evidence for the superior performance of foreign direct investment in Romania in the presence of highly labor-intensive production and large market shares. Performance is measured in terms of investment volume and net profits. Partial state-ownership in joint ventures adversely affects performance, while a higher degree of import competition - in contrast to common conviction - favors profits during this stage of reforms. According to the results of a profitability analysis, the optimal size per investment has neither been reached nor even been surpassed yet.Economic Transition, Joint Ventures, Romania, Manufacturing Industry

Ökonomischer Nutzen Betrieblicher Gesundheitsförderung

aus dem Inhaltsverzeichnis: Einleitung; Betriebliche Gesundheitsförderung; Ökonomische Analyse betrieblicher Gesundheitsförderung; Internationale Ergebnisse und Vergleichsstudien; Ökonomische Effekte betrieblicher Gesundheitsförderung in Österreich;Executive Summary