Causal relationship between construction investment policy and economic growth in Turkey

The construction industry in countries experiencing severe economic crisis has vital importance to get out of stagnation because of its direct relations with 200 different sectors. In this study, the relationship between the construction growth data (infrastructure, building and residential (public), building and residential (private) investment) and gross domestic product (GDP) is examined for Turkey. To this end, Engle–Granger cointegration, error correction model (ECM) and Granger causality tests were applied in order to determine the aforementioned relation. It has been found that the infrastructure and building–residential investments have direct relations with the GDP and have causality effects.     

The nonlinear price dynamics of U.S. equity ETFs

We investigate the price dynamics of large market-capitalization U.S. equity exchange-traded funds (ETFs) in order to uncover trader motivations and strategy. We show that prices of highly liquid ETFs can deviate significantly from their daily net asset values. By adjusting for changes in valuations, we report the impact of non-classical variables including price trend and volatility using data from 2008 to 2011. We find a cubic nonlinearity in the trend suggesting that traders are not only aware of the underreaction of others, but also self-optimize by anticipating others’ reactions, and sell when the uptrend is stronger than usual.     

Stock price dynamics: nonlinear trend,volume, volatility,resistance and money supply

We present a methodology to study a data set of 119 260 daily closed-end fund prices using mixed-effects regressions with the objective of understanding price dynamics. There is strong statistical support that relative price change depends significantly on (i) the recent trend in a nonlinear manner, (ii) recent changes in valuation, (iii) recent changes in money supply (M2), (iv) longer-term trend, (v) recent volume changes and (vi) proximity to a recent high price. The dependence on the volatility is more subtle, as short-term volatility has a positive influence, while the longer term is negative. The cubic nonlinearity in the weighted price trend shows that a percentage daily gain of up to 2.78% tends to yield higher prices, but larger gains lead to lower prices. Thus, the nonlinearity of price trend establishes an empirical and quantitative basis for both underreaction and overreaction within one large data set, facilitating an understanding of these competing motivations in markets. Increasing money supply is found to have a significant positive effect on stock price, while proximity to recent high prices has a negative effect. The data set consists of daily prices during the period 26 October 1998 to 30 January 2008.     

Performance of Electricity Price Forecasting Models: Evidence from Turkey

In this article, hourly prices of the Turkish Day Ahead Electricity Market are forecasted by using various univariate electricity price models, then the out-of-sample forecasts are compared with each other and the benchmarks. This article has two main contributions to the literature: Firstly, it provides a factorial Analysis of Variance (ANOVA) as a pre-whitening method of the price series and allows one to work with the stationary residuals series. Secondly, it is the first work, which compares the performances of all important statistical univariate forecast models in the Turkish electricity market. Results indicate the importance of the factorial ANOVA application and the SARIMA model’s success under the given conditions.     

Overreaction diamonds: precursors and aftershocks for significant price changes

Overreactions and other behavioral effects in stock prices can best be examined by adjusting for the changes in fundamentals. We perform this by subtracting the relative price changes in the net asset value (NAV) from that of market price (MP) daily for 134 406 data points of closed-end funds trading in US markets. We examine the days before and after a significant rise or fall in price deviation and MP return and find evidence of overreaction in the days after the change. Prior to a spike in deviation we find a gradual two- or three-day decline (and analogously in the other direction). Overall, there is a characteristic diamond pattern, revealing a symmetry in deviations before and after the significant change. Much of the statistical significance and the patterns disappear when the subtraction of NAV return is eliminated, suggesting that the frequent changes in fundamentals mask behavioral effects. A second study subdivides the data depending on whether the NAV or market price is responsible for the spike in the relative difference. In a majority of spikes, it is the change in market price rather than NAV that is dominant. Among those spikes for which there is little or no change in NAV, the results are similar to the overall study. Furthermore, the upward spikes are preceded by one or two days of declining market price while NAV rises slightly or is relatively unchanged. This suggests that a cause of the spike may be due to over-positioning of traders in the opposite direction in anticipation.