Sharif Digital Repository

The objective of this thesis is to prioritize a portfolio of buildings for seismic retrofit. A new set of sensitivity measures is proposed to rank the buildings in accordance with the reduction in the loss of the entire portfolio. To this end, various risk measures are differentiated with respect to the cost of retrofit for each building. These risk measures are the moments of the portfolio cost probability distribution which imply the risk-neutral and risk-averse decision making. Two costs are considered: Construction cost due to retrofit and repair cost due to structural and non-structural damage. To quantify the risk, reliability methods are employed in which many interacting... 

For a Variety of reasons, financial economists tend to view individuals and institutions differently. In particular, while institutions are viewed as informed investors, individuals are believed to have psychological biases and are often thought of as the proverbial noise traders. One of the questions of interest to researchers in finance is how the behavior of different investor clienteles or their interaction in the market affects returns. In this paper we focus on the interaction between individual investors and stock returns in Iran capital market. Specifically, first we examine the extent to which intense net buying or selling by individuals in a stock is related to the stock’s past... 

This research is an event study about the effects of the Corona Virus Outbreak on different industries in the Iran Stock Exchange. This study examines which industries had been affected more negatively or positively by the COVID-19 pandemic outbreak. In the first step, we calculate Alphas, Betas, and expected returns of stocks in an estimation window before the event using the market model. Then, we group all stocks in 17 different industries and calculate average cumulative abnormal returns in the event period as good measures for examining defects of this outbreak. Our results show that transportation, chemical products, processed products, real estate, and automobile manufacturing were... 

Quality of Experience (QoE) indicates the overall quality of one service such as Voice over IP (VoIP) from users' point of view by considering several systems, human, and contextual factors. QoE measurement and prediction are more challenging than Quality of Service (QoS) which is only related to network parameters. There exist various objective and subjective methods for QoE prediction. This research investigates various features affecting QoE by proposing a comprehensive subjective evaluation by employing a large number of users. We show that many unconsidered factors including speaker specifications and signal properties, such as signal-to-noise ratio (SNR), can affect QoE so that the SNR... 

Toxic flow occurs when a trader with confidential information trades with a market maker without that information. The trade price is such that the market maker is obliged to provide the desired liquidity by taking the risk of loss for the order. The PIN (Probability of Informed Trading) is widely used to calculate the amount of toxic flow in a market and evaluate the market condition in terms of informed trading. However, Easley et al. (2012a) propose a new alternative method based on high-frequency data and daily orders called VPIN (Volume-Synchronized Probability of Informed Trading), and we apply it in the Iran stock market. This method can give the market makers the ability to predict... 

Condition monitoring of machinery is of significant economic importance to mitigate production losses resulting from downtimes. Unforeseen failure of roller element bearings is the most common issue observed in industrial units. However, detecting and tracking the progression of these failures through machine vibration monitoring and predicting the deterioration of these rotating components are viable solutions. Numerous studies have focused on using laboratory accelerated life test data for fault detection and remaining useful life prediction of these components. While online monitoring of all equipment in the industry may not be feasible, and conditions in the field differ from laboratory... 

Intelligent predictive maintenance is recognized as a cornerstone of Industry 4.0, where intelligent software is employed for the early detection of faults and the prevention of unexpected failures. Recent research indicates that the integration of multi-sensor data for fault diagnosis of gearboxes and bearings, using artificial intelligence models, has been successful. However, conventional methods face several challenges. These include an over-reliance on the signal characteristics of a single sensor and the impracticality of applying intelligent learning methods, particularly deep learning, despite their high potential, due to the unavailability of sufficiently large and diverse...