BIST katılım endeksi için bir Markov zinciri analizi

This study addresses the trend estimation of the participation indices (PARTI) in the Istanbul Stock Exchange (BIST) using Markov chain (MC) theory. PARTI can be regarded as the Participation 50 Index (KAT50) and the Participation 30 Index (KATLM). Since KAT50 has only been calculated since 9th July 2014, there are only a few studies on this index. Therefore, in this study, we examine the PARTI indices. Firstly, we have employed MC method using 520 daily closing values of KATLM, between 1st July 2014 and 29th July 2016. For the KAT50 index, we used 514 daily closing values between 9th July 2014 and 29th July 2016, considering the states of these indices as increasing, decreasing or remaining stable. In order to perform a Markov chain analysis relating to prediction of the future situation, a transition probability matrix was created. Using this matrix, a steady-state analysis of the chain was performed and the future trends of KAT50-KATLM were forecasted successfully. It can be concluded that the results of this study are very helpful for individual and institutional investors’ investment decisions within global economies.Bu çalışma bir Markov zinciri (MZ) modeli ile Borsa İstanbul (BIST)’da yer alan Katılım Endekslerinin (KATLM, KAT50) hareketlerini tahmin etmeyi amaçlar. KAT50 Endeksi 9 Temmuz 2014 tarihinden bu yana işlem görmeye başladığından dolayı, literatürde bu endeks üzerinde yapılmış yeterince çalışma yoktur. Bu çalışmada ilk olarak, KATLM endeksinin 520 günlük (01.07.2014-29.07.2016), KAT50 endeksinin ise 514 günlük (09.07.2014-29.07.2016) kapanış değerleri göz önüne alınarak bir MZ modeli oluşturuldu. Bu modelde endekslerin artış, azalış ve sabit kalma durumları dikkate alındı. Endekslerin gelecekteki değerlerine ilişkin bir MZ analizi yapmak için geçiş olasılıkları matrisi oluşturuldu. Bu matristen yararlanılarak, kararlı durum analizi yapıldı ve KATLM-KAT30 endekslerinin gelecekteki hareketleri başarılı bir şekilde öngörüldü. Bu çalışmanın sonuçlarının, bireysel ve kurumsal yatırımcıların küresel ekonomilerdeki yatırım kararları için çok yararlı olduğu sonucuna varılabilir

MODEL PREDIKSI INDEKS HARGA SAHAM DI BURSA EFEK INDONESIA (BEI) MENGGUNAKAN RANTAI MARKOV DAN PROSES STOKASTIK FUZZY

Indeks harga saham atau stock prices indexes adalah harga atau nilai dari sekelompok saham yang dikumpulkan berdasarkan kategori tertentu. Indeks ini merupakan indikator pergerakan harga saham dari seluruh saham yang diwakilinya. Perubahan harga saham yang tidak menentu menjadi pertimbangan diperlukannya prediksi untuk harga saham di Indonesia pada Bursa Efek Indonesia. Salah satu model yang dapat digunakan untuk prediksi indeks harga saham adalah Rantai Markov dan Proses Stokastik Fuzzy. Tujuan dari penelitian ini adalah memprediksi indeks harga saham di Bursa Efek Indonesia dan perhitungan eror yang diperoleh dari Proses Stokastik Fuzzy dan Rantai Markov. Hasil prediksi indeks harga saham menggunakan Rantai Markov dan Proses Stokastik Fuzzy mempunyai MAPE (Mean Absolute Precentage Eror) dari data latih sebesar 1,40355% dan dari data uji sebesar 0,01900404%

SIMULATION-BASED DECISION MODEL TO CONTROL DYNAMIC MANUFACTURING REQUIREMENTS: APPLICATION OF GREY FORECASTING - DQFD

Manufacturing systems have to adapt to changing requirements of their internal and external customers. In fact, new requirements may appear unexpectedly and may change multiple times. Change is a straightforward reality of production, and the engineer has to deal with the dynamic work environment. In this perspective, this paper proposes a decision model in order to fit actual and future processes’ needs. The proposed model is based on the dynamic quality function deployment (DQFD), grey forecasting model GM (1,1) and the technique for order preference by similarity to ideal solution (TOPSIS). The cascading QFD-based model is used to show the applicability of the proposed methodology. The simulation results illustrate the effect of the manufacturing needs changes on the strategic, operational and technical improvements

Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

The impact of macroeconomic leading indicators on inventory management

Forecasting tactical sales is important for long term decisions such as procurement and informing lower level inventory management decisions. Macroeconomic indicators have been shown to improve the forecast accuracy at tactical level, as these indicators can provide early warnings of changing markets while at the same time tactical sales are sufficiently aggregated to facilitate the identification of useful leading indicators. Past research has shown that we can achieve significant gains by incorporating such information. However, at lower levels, that inventory decisions are taken, this is often not feasible due to the level of noise in the data. To take advantage of macroeconomic leading indicators at this level we need to translate the tactical forecasts into operational level ones. In this research we investigate how to best assimilate top level forecasts that incorporate such exogenous information with bottom level (at Stock Keeping Unit level) extrapolative forecasts. The aim is to demonstrate whether incorporating these variables has a positive impact on bottom level planning and eventually inventory levels. We construct appropriate hierarchies of sales and use that structure to reconcile the forecasts, and in turn the different available information, across levels. We are interested both at the point forecast and the prediction intervals, as the latter inform safety stock decisions. Therefore the contribution of this research is twofold. We investigate the usefulness of macroeconomic leading indicators for SKU level forecasts and alternative ways to estimate the variance of hierarchically reconciled forecasts. We provide evidence using a real case study