The concept of intrinsic time was introduced in Mandelbrot’s paper circa 1963 and further developed in discussion paper by Muller et al. (1993). As reported by Didenko et al. (2014), there are some evidencesthat sampling price series in volume domain results in almost normal returns, which could help to overcome some common issues in portfolio optimisation. First, we briefly survey flaws of classic approach to portfolio optimisation, then we test for statistical properties of intrinsic-time sampled return series, theorize on how intrinsic time could help in handling issues of portfolio optimisation, and then empirically test our guesses. We show that using intrinsic time helps in overcoming such flaws of Modern Portfolio Theory as poor diversification and reliance on normality of returns.

Defined by Hartzmark and Solomon (2012), dividend month premium is misvaluation of stocks in the months when companies are predicted to pay dividends. Following Hartzmark and Solomon methodology, this paper examines market reactions to Japanese companies in the dividend months. Portfolios consisting ofcompanies with a predicted dividend and all other companies were formed and regressed under the CAPM, the Fama-French 3 factor and the 4 factor models. In a data sample consisting of 2263 Japanese companies from January 1991 to October 2014, no statistically significant abnormal returns were found in predicted dividend portfolio. Nonetheless, this study recorded significant negative abnormal returns of dividend paying companies with respect to non-dividend payers.

This paper analyzes the efficiency of the rules described by famous "investment gurus". We backtested 30 strategies over the period of 20 years using monthly data from USA stock market and scored their comparative characteristics using DEA model. Although strategies vary in historical performance, 11 strategies managed to beat benchmarks over the long term. Most efficient strategies according to DEA appear to be Graham, Lian, Zweig, Siegel strategies.

We evaluate historical performance of one of the most famous Elliott Wave Theory proponents - Robert Prechter using Black-Litterman as framework for portfolio optimization with views. Our choice of the portfolio model for historical backtest contradicts to traditional "straightforward" approach to test historical predictions performance. We argue that this approach is more realistic as it allows to model Bayesian-rational decision-making of risk-averse agent with views, fueled by Elliott theory. Our results show that use of mentioned framework Elliott Wave Theory offers brings value to investor.

In our paper we outline some empirical evidences about aggregated analyst errors, i.e. systematic differences between consensually forecasted and observed prices. In particular, we find that the error is independent from the amount of analysts covering the stock, while industry plays an important role, although an error is bigger for growth companies. We also confirm previous evidence that price estimates aggregation over an index result in better estimates performance. Along with that, EPS is predicted better than price itself. Based on mentioned facts we deduce that the main reason for poor performance of analysts should likely be in their disability to choose correct discount rate. Our result contributes to literature on efficient market hypothesis, to studies of stock market analyst accuracy and to surveys of best/worst practices of equity valuation.

During the last decades the linkage between foreign direct investments (FDI) and economic growth has been extensively reviewed in the economic literature. Theories and modern literature provide conflicting results concerning this issue. Some authors argue that foreign direct investment could result in boosting host country economy, while others believe that FDI may bring about vulnerability and dependence to the country. This paper tries to extract the relationship between foreign direct investment and economic growth, specifically in Vietnam, trying to eventually extract a meaning revelation.

The purpose of this paper is to measure empirically the effects of currency depreciation on inflation and trade balance in the case of Vietnam. The author utilizes the quarterly data from 2000 to 2012 for the Vector Auto-Regression (VAR) model to build the impulse response functions and variance decompositions of inflation and trade balance. The obtained results are remarkably consistent with economic principles in the theoryreview. The impulse response functions indicate that currency depreciation has considerable negative impact on inflation while having fairly positive impacts on trade balance. However, variance decompositions of trade balance show that exchange rate itself can hardly explain much about the change in trade balance. Basing on these results, the author proposes (1) stabilization of exchange rate to restrain inflation and (2) enhancing the quality of exported goods to improve competitiveness.

It’s commonplace, that information drives prices. Can we infer the impact of information by just observing prices? Can we observe regime changes during crises, when markets are overwhelmed with waves of fear and greed? What happens in the aftermath? We estimate information flows on the world marketsby modeling volatility of regional stock indexes. Then we estimate VAR models for volatilities and use the capabilities of ‘circlize’ package from statistical environment ‘R project’ to visualize patterns of exposure and auto-determinism of information processes in global stock markets.