This paper addresses whether and to what extent econometric methods used in experimental studies can be adapted and applied to financial data to detect the best-fitting preference model. To address the research question, we implement a frequently used nonlinear probit model in the style of Hey...

The aim of this article is the study of complex structures which are behind the short-term predictability of stock returns series. In this regard, we employ a seasonal version of the Mackey-Glass-GARCH(p,q) model, initially proposed by Kyrtsou and Terraza (2003) and generalized by Kyrtsou (2005,...

In this paper we conduct a formal testing of the possibility of chaotic dynamics in daily exchange rate variables, namely exchange rate returns, volatility and normalized exchange rates. Substantial nonlinear dependence is found in exchange rate returns, even when GARCH-type structure is...

This study develops the Regime Dependent Generalized Auto Regressive Conditional Heteroskedasticity (RD-GARCH) model and applies it to a daily index of returns on U.S. equities covering the period 1926 to 2000. The RD-GARCH model is different from previous models from the ARCH family in that it...

This research identifies the presence of long memory given return series of the stock markets in the ASEAN-4 countries, namely, Indonesia, Malaysia, the Philippines and Thailand. Daily stock prices from 1994 to 2004, which were neither adjusted for dividends nor inflation, were employed in the...

In this paper we provide a mathematical derivation that links traditional time-value-of-money concepts to Metcalfe value, and use Bitcoin, Facebook as numerical examples of the proof. There is compelling evidence that suggests that the growth and price of bitcoin and other cryptocurrencies are...

Just as network effects can dramatically increase value through positive feedback, value can be lost as networks shrink due to competition or incompatibility. In the instance of cryptocurrency as a network and with Metcalfe's Law as the methodology, we illustrate by numerical example that...

Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form (the SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that...

A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...