Reza Habibi
Abstract
The Kalman-Bucy filter is studied under different scenarios for observation and state equations, however, an important question is, how this filter may be applied to detect the change points. In this paper, using the Bayesian approach, a modified version of this filter is studied which has good and justifiable ...
Read More
The Kalman-Bucy filter is studied under different scenarios for observation and state equations, however, an important question is, how this filter may be applied to detect the change points. In this paper, using the Bayesian approach, a modified version of this filter is studied which has good and justifiable properties and is applied in change point analysis.
Reza Habibi
Abstract
threaten system self-worth by preventing them from seeing themselves as a good system, and it can generally erode trust in society. Lying may be considered a game. This paper is concerned with the effect of lying in a system containing two agents using the game theory. From a repeated measurement model, ...
Read More
threaten system self-worth by preventing them from seeing themselves as a good system, and it can generally erode trust in society. Lying may be considered a game. This paper is concerned with the effect of lying in a system containing two agents using the game theory. From a repeated measurement model, two agents (which constitute a system) play a global game and it is seen that during a repeated game, the system will be destroyed by laying an agent. The probability of failing negotiation is derived and its behavior is studied under different scenarios. Simulation results are proposed to support theoretical results. Finally, concluding remarks are given.
ali naghib moayed; Reza Habibi
Abstract
Generally, no one can reject the fact that crypto currency market is expanded rapidly during last few years as, nowadays, crypto currency market is attractive for both traders and business who are not willing to pay for FATF services for transferring money. With this in mind, crypto currency price prediction ...
Read More
Generally, no one can reject the fact that crypto currency market is expanded rapidly during last few years as, nowadays, crypto currency market is attractive for both traders and business who are not willing to pay for FATF services for transferring money. With this in mind, crypto currency price prediction is crucial for many people and business entities. While there have been quite a few conventional statistical models to forecast crypto currency prices, we decided to make price prediction using decision Tree Based Regression. In this research we devised a decision tree models to predict Bitcoin which is the most renowned and frequently used crypto currency. we used Volume from, Volume to, New addresses, Active addresses, large transaction count, Block height, Hash rate, Difficulty, Current supply as predictor variables in addition to historical crypto currency price data during the with a total of 1000 Observations. We find that forecasting accuracy of decision tree models are higher than benchmark models such as linear regression and autoregressive integrated moving average(ARIMA).
Elham Daadmehr; Reza Habibi
Abstract
To check the financial stability, it is important to alarm the possibility of future potential financial crisis. In the literature, the early warning system (EWS) is designed to warn the occurrence of a financial crisis before it happens. This tool gives strengthens to managers to make efficient policy ...
Read More
To check the financial stability, it is important to alarm the possibility of future potential financial crisis. In the literature, the early warning system (EWS) is designed to warn the occurrence of a financial crisis before it happens. This tool gives strengthens to managers to make efficient policy in real economic activities. Hyperinflation, as a financial crisis, is an uncommon bad phenomenon in every economy. It quickly erodes the real value of the local currency, as the prices of all goods increase. This causes people to minimize their holdings in that currency as they usually switch to more stable foreign currencies, often the US Dollar. Hence, designing a EWS for detecting hyperinflation is valuable task. In the current paper, Iran monthly inflation is modeled by a first
orders autoregressive and moving average model (ARMA) with two-state Markov switching (MS) states, i.e., \( MS \left( 2 \right) -ARMA \left( 1,1 \right) \) . Based on this model, a logistic-EWS is proposed. From the empirical results, it is seen that, in Iran, the low inflation state is more probable than state of high inflation. Beside this, the time of remaining in the low inflation position is almost 9 times more than of high inflation position. To check validity of the results and control prediction errors,it is seen that at least 89 percentages of future states of inflation are correctly predicted with a low noise-to-signal ratio discrepancy measure.
