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The BIST 100 index is used to evaluate the success of the highest 100 shares in terms of criteria such as free float rate, transaction volume and market value. In this paper, it is aimed to determine whether the BIST 100 returns have a chaotic structure and short term predictability. First of all, using BIST 100 price index data between 02.01.2008 and 02.01.2018, BIST 100 returns were obtained. Using the optimal delay time and embedding dimension, the phase space required for chaos analysis was reconstructed. Then, the correlation dimension of the chaotic attractor in the new phase space obtained for this return series was calculated. BDS (Brock, Dechert and Scheinkman) test was used to determine whether the BIST 100 structure was linear. However, the Hurst exponential coefficient was determined by the transformed width method to determine whether the series had long term memory. As a result of positive Lyapunov exponent of return series, it was determined whether this series showed chaotic behavior. Following the chaos analysis, BIST 100 index was estimated by ANN and ANFIS model. The outputs of the model with the lowest error value are transformed into return series, and the estimated values of the BIST 100 returns are obtained. [ABSTRACT FROM AUTHOR]

In this study, the chaotic behavior of the T system is shown by analyzing Lyapunov exponents, Kaplan-Yorke dimension and equilibrium points. Also, the chaos control of T system showing chaotic behavior under certain parameters is investigated via linear feedback control. Routh- Hurwitz criterion is used to provide the condition of stability of the controlled system around the equilibrium points. The feedback gain is calculated to control the T chaotic system with single state feedback, then the same calculations repeated for the control of the system with two and three state feedback. The controller designed by calculating the feedback coefficients using the Routh-Hurwitz criterion is added to the T chaotic system. It is shown by phase portraits how the change of the feedback gains affects the control of the system. The design and implementation of the controller is quite simple. Due to the simple structure of the controller, the controller hardware is low and realized conveniently. Simulation results show that the controlled system with the application of feedback control converges to zero and other equilibrium points. [ABSTRACT FROM AUTHOR]