Inability to identify asset price Bubbles and their types (Single and Multiple) causes adverse effects on economy. New economic instruments make, not only the analysis of mild explosive behavior but also the determination of origination and termination of Bubbles possible, of Bubbles possible. The present study aims to detect price Bubbles of Tehran stock exchange and OTC, and determine date of origination, burst, and complete deletion of Bubbles in the period of 2010.03 to 2016.03. To this end, the study uses total index, industry index, index of 50 firms and total OTC index. The results show that the stock market and OTC have experienced 2 and 5 bubble periods, respectively. The results also show that stock and OTC markets were bubbling in 59% and 57% of sample period, respectively. Therefore, these markets have had Bubbles in more than half of the study period indicating the great instability in the stock prices.

Hydrodynamics of Multiple rising Bubbles as a fundamental two-phase phenomenon is studied numerically by lattice Boltzmann method and using Lee two-phase model. Lee model based on Cahn-Hilliard diffuse interface approach uses potential form of intermolecular forces and isotropic finite difference discretization. This approach is able to avoid parasitic currents and leads to a stable procedure to simulate two-phase flows. Deformation and coalescence of Bubbles depend on a balance between surface tension forces, gravity forces, inertia forces and viscous forces. A simulation code is developed and validated by analysis of some basic problems such as bubble relaxation, merging Bubbles, merging droplets and Single rising bubble. Also, the results of two rising Bubbles as the simplest interaction problem of rising Bubbles have been calculated and presented. As the main results, square and lozenge initial configuration of nine rising Bubbles are studied at Eotvos numbers of 2, 10 and 50. Two-phase flow behavior of Multiple rising Bubbles at same configurations is discussed and the effect of Eotvos number is also presented. Finally, velocity field of nine rising Bubbles is presented and discussed with details.

Usually attention to the buying and keeping gold will increase with economic crises in the global economy, because gold has intrinsic value and in the economic crisis not only maintain its value but also high demand of it cause increase in its value. With increasing demand for gold, the possibility of existence of Bubbles in its market will increase; therefor gold holders will tolerate destructive effects because of not identifying of the price Bubbles.New economic tools not only make possible the analysis of middle explosive behavior of the bubble but also provide the possibility of identifying origination and termination date of that. According to this, the aim of this study is to explore price Bubbles in gold market and to determinate date stamping of origination, explosion and complete deletion of them in the period of 01/07/2000 t0 30/12/2015. The methodologies that use for detection of Bubbles are standard ADF, Rolling Window ADF, Supremum ADF and Generalized Supremum ADF tests. The results indicate that gold price is bubbling in at least 39% of sample period. The existence of the Multiple Bubbles is also confirmed in this market.

Prior to the 2008 crisis, economists paid little attention to the role of the bubble and its detrimental effects on the real sector of the economy; But with the crisis, it became clear that the effect of the bubble in asset markets was not limited to nominal effects and could severely affect the real sector of the economy. Accordingly, the main purpose of this study is to investigate the existence of Bubbles in the housing market and also to identify the exact time of its origination and collapse. In this regard, using the quarterly data of Tehran housing market in the period 1372: 1 to 1399: 3 and also using the new approach of Philips and Shi (2018), the existence of Bubbles in this market was tested. The results of this study indicate that there is a price bubble in the housing market in some time periods in our sample. Examination of the real price as well as the price-to-earnings ratio indicates that there have been periods in our sample that have had very similar characteristics to bubble periods. The results obtained from the Phillips and Shi test also confirm this and indicate that the Tehran housing market has witnessed a price bubble in 1381, 1397, 1398 and 1399. Graphical analysis of bubble collapse periods also shows that after these periods, real prices in the housing market have decreased significantly. This is exactly in line with price behavior in bubble periods and confirms the results of previous tests.

The housing sector is one of the key sectors of Iran, which is of great importance. One of the issues that this market faces is the presence of speculators in this market, which leads to the bubble of this market and, thus, imposes a lot of costs on society. In this regard, determining the bubble and date stamping and determining the type of existing Bubbles in a Single or Multiple type can be of great help to policymakers. Considering this, the main objective of the present study was to investigate the Bubbles dating in the housing market (land and rent house), the date stamping and determination of the Single or Multiple Bubbles. The method used in this study is recursive unit root approach provided by Philips et al (2013), known as RADF and GSADF tests. The results of this study showed that Tehran and all urban areas, large cities, small and medium sized cities in the years 1382 to 1392 have experienced bubble periods at land prices and rentals, of which the most important bubble interval was from 1386 to 1387. There were also bubble periods in land prices and rentals from 1390 to 1392.

This article investigates integrated production-inventory models with backorder. A Single supplier and a Single buyer are considered and shortage as backorder is allowed for the buyer. The proposed models determine optimal order quantity, optimal backorder quantity and optimal number of deliveries on the joint total cost for both buyer and supplier. Two cases are discussed: Single-setup-Single-delivery (SSSD) case and Single-setup-Multiple-deliveries (SSMD) case. Two algorithms are applied for optimizing SSMD case: Gradient search and particle swarm optimization (PSO) algorithms. Finally, numerical example and sensitivity analysis are provided to compare the total cost of the SSSD and SSMD cases and effectiveness of the considered algorithms. Findings show that the policy of frequent shipments in small lot sizes results in less total cost than Single shipment policy.