Monetary models of exchange rates and the random walk

Three alternative monetary models of exchange rate are tested using data on the Italian lira - US doIIar exchange rate. II is shown that up to the early 1990s these economic models perform better than the random walk model in out-of-sample forecasts.

Random walk versus multiple trend breaks in stock prices : evidence from 15 European markets

This letter extends research reported in Narayan and Smyth (2005) by employing multiple trend break unit root tests to examine the random walk hypothesis for 15 European stock market indices. The results provide strong support for the view that stock prices are characterized by a random walk.

Mean reversion versus random walk in G7 stock prices evidence from multiple trend break unit root tests

This paper provides evidence on the random walk hypothesis in G7 stock price indices using unit root tests which allow for one and two structural breaks in the trend. Of the seven countries we find, at best, evidence of mean reversion in the stock price index of Japan. Thus, overall, our results support the random walk hypothesis. We also consider the implications of the identified structural breaks for movement in stock prices over time. Our main conclusion from this exercise is that the second break in stock prices has had a detrimental effect on movements in stock prices in the G7 countries.

Testing for a random walk in Italy's inflation in the post-war period, 1947-1996

This paper investigates the unit root properties of Italy’s inflation rate in the post-war period (1947-1996). To achieve the aim of this study, the Zivot and Andrews (1992) one break test and the Lumsdaine and Papell (1997) two breaks test for unit roots are applied. It is found that inflation for Italy was a non-stationary breakpoint for the period 1947-1996. This result has important implications for econometric modeling and in understanding the behavior of shocks to Italy’s inflation.

Testing for the random walk hypothesis in the case of visitor arrivals : evidence from Indian tourism

Testing for the random walk hypothesis, which asserts that a series is a non-stationary process or a unit root process, in the case of visitor arrivals has important implications for policy. If, for instance, visitor arrivals are characterized by a unit root, then it implies that shocks to visitor arrivals are permanent. However, if visitor arrivals are without a unit root, this implies that shocks to visitor arrivals are temporary. This study provides evidence on the random walk hypothesis for visitor arrivals to India using the recently developed Im et al. (2003) and Maddala and Wu (1999) panel unit root tests. Both tests allow one to reject the random walk hypothesis, implying that shocks to visitor arrivals to India from the 10 major source markets have a temporary effect on visitor arrivals.

Are OECD stock prices characterized by a random walk? Evidence from sequential trend break and panel data models

This paper examines whether stock prices for a sample of 22 OECD countries can be best represented as mean reversion or random walk processes. A sequential trend break test proposed by Zivot and Andrews is implemented, which has the advantage that it can take account of a structural break in the series, as well as panel data unit root tests proposed by Im et al., which exploits the extra power in the panel properties of the data. Results provide strong support for the random walk hypothesis.

Detection on application layer DDoS using random walk model

Application Layer Distributed Denial of Service (ALDDoS) attacks have been increasing rapidly with the growth of Botnets and Ubiquitous computing. Differentiate to the former DDoS attacks, ALDDoS attacks cannot be efficiently detected, as attackers always adopt legitimate requests with real IP address, and the traffic has high similarity to legitimate traffic. In spite of that, we think, the attackers' browsing behavior will have great disparity from that of the legitimate users'. In this paper, we put forward a novel user behavior-based method to detect the application layer asymmetric DDoS attack. We introduce an extended random walk model to describe user browsing behavior and establish the legitimate pattern of browsing sequences. For each incoming browser, we observe his page request sequence and predict subsequent page request sequence based on random walk model. The similarity between the predicted and the observed page request sequence is used as a criterion to measure the legality of the user, and then attacker would be detected based on it. Evaluation results based on real collected data set has demonstrated that our method is very effective in detecting asymmetric ALDDoS attacks. © 2014 IEEE.

Scaling relationships of Gaussian processes

Asset returns conforming to a Gaussian random walk are characterised by the temporal independence of the moments of the distribution. Employing currency returns, this note demonstrates the conditions that are necessary for risk to be estimated in this manner.

Price exhaustion and number preference : time and price confluence in Australian stock prices

Confluence occurs when different trading filters generate signals that point to the same directional move. Using regression analysis, this paper investigates confluence trading signals associated with number preference and price exhaustion, for a sample of Australian stocks. The results show that certain price levels tend to act as psychological barriers, and that price exhaustion signals are a real phenomenon in the Australian stock market. It is shown also that confluence exists in the Australian stock market. Importantly, confluence is associated with price retracements that are of economic and statistical significance, offering profitable trading opportunities. The results suggest that Australian stocks do not follow a random walk.

The exchange rate disconnect puzzle: a resolution?

Early empirical studies of exchange rate determinants demonstrated that fundamentals-based monetary models were unable to outperform the benchmark random walk model in out-of-sample forecasts while later papers found evidence in favor of long-run exchange rate predictability. More recent theoretical works have adopted a microeconomic structure; a utility-based new open economy macroeconomic framework and a rational expectations present value model. Some recent empirical work argues that if the models are adjusted for parameter instability, it is a good predictor of nominal exchange rates while others use aggregate idiosyncratic volatility to generate good predictions. This latest research supports the idea that fundamental economic variables are likely to influence exchange rates especially in the long run and further that the emphasis should change to the economic value or utility based value to assess these macroeconomic models.

Mean reversion in stock prices: new evidence from panel unit root tests

Purpose – There are several studies that investigate evidence for mean reversion in stock prices. However, there is no consensus as to whether stock prices are mean reverting or random walk (unit root) processes. The goal of this paper is to re-examine mean reversion in stock prices.
Design/methodology/approach – The authors use five different panel unit root tests, namely the Im, Pesaran and Shin t-bar test statistic, the Levin and Lin test, the Im, Lee, and Tieslau Lagrangian multiplier test statistic, the seemingly unrelated regression test, and the multivariate augmented Dickey Fuller test advocated by Taylor and Sarno.
Findings – The main finding is that there is no mean reversion of stock prices, consistent with the efficient market hypothesis.
Research limitations/implications – One issue not considered by this study is the role of structural breaks. It may be the case that the efficient market hypothesis is contingent on structural breaks in stock prices. Future studies should model structural breaks.
Practical implications – The findings have implications for econometric modelling, in particular forecasting.
Originality/value – This paper adds to the scarce literature on the mean reverting property of stock prices based on panel data; thus, it should be useful for researchers.

Concepts and dimensionality in modeling unsaturated water flow and solute transport

Many environmental studies require accurate simulation of water and solute fluxes in the unsaturated zone. This paper evaluates one- and multi-dimensional approaches for soil water flow as well as different spreading mechanisms to model solute behavior at different scales. For quantification of soil water fluxes,Richards equation has become the standard. Although current numerical codes show perfect water balances, the calculated soil water fluxes in case of head boundary conditions may depend largely on the method used for spatial averaging of the hydraulic conductivity. Atmospheric boundary conditions, especially in the case of phreatic groundwater levels fluctuating above and below a soil surface, require sophisticated solutions to ensure convergence. Concepts for flow in soils with macro pores and unstable wetting fronts are still in development. One-dimensional flow models are formulated to work with lumped parameters in order to account for the soil heterogeneity and preferential flow. They can be used at temporal and spatial scales that are of interest to water managers and policymakers. Multi-dimensional flow models are hampered by data and computation requirements.Their main strength is detailed analysis of typical multi-dimensional flow problems, including soil heterogeneity and preferential flow. Three physically based solute-transport concepts have been proposed to describe solute spreading during unsaturated flow: The stochastic-convective model (SCM), the convection-dispersion equation (CDE), and the fraction aladvection-dispersion equation (FADE). A less physical concept is the continuous-time random-walk process (CTRW). Of these, the SCM and the CDE are well established, and their strengths and weaknesses are identified. The FADE and the CTRW are more recent,and only a tentative strength weakness opportunity threat (SWOT)analysis can be presented at this time. We discuss the effect of the number of dimensions in a numerical model and the spacing between model nodes on solute spreading and the values of the solute-spreading parameters. In order to meet the increasing complexity of environmental problems, two approaches of model combination are used: Model integration and model coupling. Amain drawback of model integration is the complexity of there sulting code. Model coupling requires a systematic physical domain and model communication analysis. The setup and maintenance of a hydrologic framework for model coupling requires substantial resources, but on the other hand, contributions can be made by many research groups.

A model of the Australia-US exchange rate

This paper develops a model of exchange rate determination within an error correction framework. The intention is to identify both long and short term determinants that can be used to forecast the AUD/US exchange rate. The paper identifies a set of significant variables associated with exchange rate movements over a twenty year period from 1984 to 2004. Specifically, the overnight interest rate differential, Australia's foreign trade-weighted exposure to commodity prices as well as exchange rate volatility are variables identified that are able explain movements in the AUDIUS dollar relationship. An error correction model is subsequently constructed that incorporates an equilibrium correction term, a short-term interest rate differential variable, a commodity price variable and a proxy for exchange rate volatility. The model is then used to forecast out of sample and is found to dominate a naIve random walk model based on three different metrics.

Is South Korea’s stock market efficient?

This letter applies the Zivot and Andrews (Journal of Business and Economic Statistics, 10, 251-70, 1992) one break and the Lumsdaine and Papell (Review of Economic and Statistics, 79, 212-8, 1997) two break unit root tests to examine the random walk hypothesis for stock prices in South Korea. The results provide strong evidence that stock prices in South Korea are characterized by a unit root, which is consistent with the efficient market hypothesis.