Multistage portfolio optimization models are difficult to solve when market risk is measured by Value-at-Risk (VaR), this paper proposes a soft method for solving VaR-based portfolio optimization models based on a soft optimization approach. In order to demonstrate the validity of the proposed soft method, we perform portfolio management experiments with real data from the New York stock market...

In this paper we test for the inclusion of the bid-ask spread in the consumption CAPM, in the UK stock market over the time period of 1980-2000. Two econometric models are used; first, Fisher’s (1994) asset pricing model is estimated by GMM, and secondly, the VAR approach proposed by Campbell and Shiller is extended to include the bid-ask spread. Overall the statistical tests are unable to reje...

The data presented in this article are related to the research article entitled "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation. North American Journal of Economics and Finance, 40, 116-135. doi:10.1016/j.najef.2017.02.006 (Li, 2017) [1]. Data on daily stock index return for the Canadian, UK, and US equity markets, as compiled by Mor...

In this paper, we analyze and compare long-range power-law correlations of returns, absolute returns, squared returns, cubed returns and square waved returns for sixteen individual stocks from the block of energy sources of Chinese stock market and five stock indices (Shanghai Composite Index, Shenzhen Component Index, Dow Jones Industrial Average index, Nasdaq Composite Index, the Standard and...

modeling and analysis of future prices has been hot topic for economic analysts in recent years. traditionally, the complex movements in the prices are usually taken as random or stochastic process. however, they may be produced by a deterministic nonlinear process. accuracy and efficiency of economic models in the short period forecasting is strategic and crucial for business world. nonlinear ...

State-space or latent-variable models for stock prices specify a process for expected returns and expected and unexpected dividend growth, and then derive dividend yields and returns from a present value relations. They are a useful structure for understanding and interpreting forecasting relations. In this note, I connect state-space representations with their observable counterparts, and VAR/...

In stock markets, the performance of traditional technology-based investment methods is limited because they only take into account singledimensional event factors. The paper shows how the integration of multi-dimensional event factors can improve performance, in which we emphasize on one key thing that previous studies have neglected: a two-way reflexivity model of investors’ decisions and mar...

a r t i c l e i n f o Keywords: Fractional cointegration Long memory Range Volatility Daily high and low prices This work provides empirical support for the fractional cointegration relationship between daily high and low stock prices, allowing for the non-stationary volatility of stock market returns. The recently formalized fractionally cointegrated vector autoregressive (VAR) model is employ...