This paper considers horizon effects on portfolio weights under time varying and forecastable return volatility. The return volatility is modelled as a GARCH-M, which is general enough to encompass both constant and time varying mean. The analysis confirms earlier results, namely that there are no horizon effects when the stochastic process, that governs asset returns, has constant mean. Howeve...

this paper discusses the portfolio selection based on robust optimization. since the parameters values of the portfolio optimization problem such as price of the stock, dividends, returns, etc. of per share are unknown, variable and their distributions are uncertain because of the market and price volatility, therefore, there is a need for the development and application of methodologies for de...

Recently, the economic crisis has resulted in instability in stock exchange market and this has caused high volatilities in stock value of exchanged firms. Under these conditions, considering uncertainty for a favorite investment is more serious than before. Multi-objective Portfolio selection (Return, Liquidity, Risk and Initial cost of Investment objectives) using MINMAX fuzzy goal programmin...

the stock evaluation process plays an important role in portfolio selection because it is the prerequisite for investment and directly influences on the stock allocation. this paper presents a methodology based on data envelopment analysis for portfolio selection, decision making units which can be stocks or other financial assets. first, dmus efficiencies are computed based on input/output com...

The cryptocurrency market has experienced stunning growth, with value exceeding USD 1.5 trillion. We use a DCC-MGARCH model to examine the return and volatility spillovers across three distinct classes of cryptocurrencies: coins, tokens, stablecoins. Our results demonstrate that conditional correlations are time-varying, peaking during COVID-19 pandemic sell-off March 2020, both ARCH GARCH effe...

We examine the high-frequency return and volatility of major cryptocurrencies reveal that spillovers among them exist. Our analysis shows clustering structures are distinct different cryptocurrencies, suggesting might have spillover patterns. Further investigation via minimal spanning trees points out BTC, LTC ETH most relevant in general, serving as connection hubs for linking many other crypt...