the difficulty of determining intrinsic value of stock prices have led many people to use technical analysis in order to forecast stock prices in the future. to predict the stock price we need to determine the generating process of stock prices. in recent years many time - series methods have been used for forecasting purposes. one of these methods is the rescaled range analysis (ris). in the a...

∃ many models suitable for exploitation of financial time series and stochastic models with continuous time ∃ various specific problems, e.g. – various levels of information on various sources of uncertainty – demographic data, economic factors – correlations of stock market and bond returns – problem specific additional random factors (prepayment rates, defaults ...) – difficulties to model il...

This paper offers an explanation for stock market crashes which focuses on the role of rational but uninformed traders. We show that uninformed traders can precipitate a price crash because as prices decline, they surmise that informed traders received negative information, which leads them to reduce their demand for assets and drive the price of stocks even lower. The model yields several impl...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...

The measurement of house prices poses significant conceptual and practical problems, mainly because dwellings are heterogeneous assets whose prices can only be observed when they are sold. There are now seven main house price indices for the United Kingdom. In broad terms, each measures one of three different concepts: the value of a representative set of house transactions; the price of a hous...

We study how recognizability affects assets’ acceptability, or liquidity. Some assets, like US currency, are readily accepted because sellers can easily recognize their value, unlike stock certificates, bonds or foreign currency, say. This idea is common in monetary economics, but previous models deliver equilibria where less-recognizable assets are always accepted with positive probability, ne...

The stock price of a company can be used to determine its success. One the efforts made increase cash and capital is sell securities. Parties who have funds (investors) in making investments certainly want maximize profits minimize risk by conducting analysis. To analyze ups downs prices there are 2 analytical techniques, namely technical analysis also fundamental techniques. Researchers discus...

This paper develops the method for pricing bivariate contingent claims under General Autoregressive Conditionally Heteroskedastic (GARCH) process. In order to provide a general framework being able to accommodate skewness, leptokurtosis, fat tails as well as the time varying volatility that are often found in financial data, generalized hyperbolic (GH) distribution is used for innovations. As t...

The mean, co-variability, and predictability of the return of different classes of financial assets challenge the rational economic model for an explanation. The unconditional mean aggregate equity premium is almost seven percent per year and remains high after adjusting downwards the sample mean premium by introducing prior beliefs about the stationarity of the price-dividend ratio and the (no...

This study aims to analyze the impact of Current Ratio, Debt Asset and Total Turnover on stock prices mediated by Return Assets in various food beverage sector companies listed Indonesia Stock Exchange from 2017 2020. The types research are quantitative, number samples is eight, sampling technique purposive sampling. Multiple linear regressions were used analysis hypothesis testing with t F tes...