scholarly journals Stock mechanics: Predicting recession in S&P500, DJIA and NASDAQ

Open Physics ◽  
2006 ◽  
Vol 4 (1) ◽  
Author(s):  
Çağlar Tuncay
Keyword(s):  
Power Law ◽  
Stock Exchange ◽  
Emerging Market ◽  
Original Method ◽  
Istanbul Stock Exchange

AbstractProposed in this paper is an original method assuming potential and kinetic energies for prices and for the conservation of their sum that has been developed for forecasting exchanges. Connections with a power law are shown. Semiempirical applications on the S&P500, DJIA, and NASDAQ predict a forthcoming recession in them. An emerging market, the Istanbul Stock Exchange index ISE-100 is found harboring a potential to continue to rise.

scholarly journals Impact of managerial ownership on capital structure: a survey of Turkish firms

2008 ◽  
Vol 5 (2) ◽  
pp. 8-14
Author(s):  
Özgür Arslan
Keyword(s):  
Capital Structure ◽  
Stock Exchange ◽  
Emerging Market ◽  
Debt Maturity ◽  
Managerial Ownership ◽  
Insider Ownership ◽  
Istanbul Stock Exchange ◽  
Dividend Smoothing ◽  
The Relationship ◽  
Considerable Support

This paper investigates the relationship between insider ownership and capital structure decisions made by managers for an emerging market. Therefore, we survey managers of 103 firms listed in the Istanbul Stock Exchange (ISE). Our findings lend considerable support to our expectation that leverage, debt maturity and dividend issues reduce ability of managers to divert resources from value maximisation. However the same monitoring and disciplining tax is not observed for stock issues. Also, our findings document that managers of firms listed in the ISE do not opt to dividend smoothing policy. Finally, the results are in line with our expectation that, the more willing are the managers to reduce asymmetric information between them and shareholders, the higher their ownership level in firms.

scholarly journals Extreme Value Volatility Estimators and Realized Volatility of Istanbul Stock Exchange: Evidence from Emerging Market

2016 ◽  
Vol 8 (8) ◽  
pp. 71 ◽  
Author(s):  
Hakki Ozturk ◽  
Umit Erol ◽  
Asli Yuksel
Keyword(s):  
Stock Exchange ◽  
Emerging Market ◽  
Realized Volatility ◽  
Extreme Value ◽  
Short Term ◽  
Forecasting Models ◽  
Major Index ◽  
Istanbul Stock Exchange ◽  
Forecasting Performance ◽  
The One

<p>This paper evaluates the forecasting performance of alternative models for the one-day ahead forecasts of BIST-30 index (Istanbul Stock Exchange- Borsa Istanbul major index that contains 30 blue-chip stocks) volatility. Realized volatility is used as the relevant benchmark for the evaluation of forecasts. We document evidence, which shows that realized volatility is a less noisy estimator than the daily square benchmark explaining more of the variation in the volatility. In addition; the benefit of using extreme value estimators as volatility proxies are discussed. It is empirically demonstrated that the extreme value estimators are 5 to 8 times more efficient than historical volatility measures. The use of extreme value estimators with simple forecasting models provide better short-term forecasts than the GARCH based volatility forecasts due to higher efficiency of extreme value estimators.</p>

scholarly journals Extreme Value Volatility Estimators and Realized Volatility of Istanbul Stock Exchange: Evidence from Emerging Market

2016 ◽  
Vol 8 (8) ◽  
pp. 73
Author(s):  
Hakki Ozturk ◽  
Umit Erol ◽  
Asli Yuksel
Keyword(s):  
Stock Exchange ◽  
Emerging Market ◽  
Realized Volatility ◽  
Extreme Value ◽  
Short Term ◽  
Forecasting Models ◽  
Major Index ◽  
Istanbul Stock Exchange ◽  
Forecasting Performance ◽  
The One

<p>This paper evaluates the forecasting performance of alternative models for the one-day ahead forecasts of BIST-30 index (Istanbul Stock Exchange- Borsa Istanbul major index that contains 30 blue-chip stocks) volatility. Realized volatility is used as the relevant benchmark for the evaluation of forecasts. We document evidence, which shows that realized volatility is a less noisy estimator than the daily square benchmark explaining more of the variation in the volatility. In addition; the benefit of using extreme value estimators as volatility proxies are discussed. It is empirically demonstrated that the extreme value estimators are 5 to 8 times more efficient than historical volatility measures. The use of extreme value estimators with simple forecasting models provide better short-term forecasts than the GARCH based volatility forecasts due to higher efficiency of extreme value estimators.</p>

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