Integrated Optimization of Line Planning, Timetabling and Rolling Stock Allocation for Urban Railway Lines

In order to improve train operation planning from the two perspectives of enterprise operating costs and passengers’ travel time, this paper proposes an integrated optimization model of three sub-problems, namely line planning, timetabling and rolling stock allocation for urban railway transit lines based on passengers’ travelling demands and the constraints of the urban rail line. The model features dwelling time at stations, turnaround operations at terminal stations, entering/exiting depot operations and an assignment for passengers’ travelling flow. We propose a solution method based on a metaheuristic method that simulates annealing to generate an optimal solution for the overall problem using MATLAB. Finally, we use the example of Xi’an metro line one to demonstrate the performance of the model.

Market Timing and Stock Selection Strategies in Shariah- Compliant Stock Portfolio

This study focuses on market timing and stock selection strategies that could be implemented by individual investors of Shariah-compliant equity using the top ten constituents of the FTSE Bursa Malaysia Hijrah Shariah Index. Investors are assumed to enter and exit the stock market following the buy-and-sell signal from Moving Average Crossover. Meanwhile, for stock selection, this study aims to construct the optimal portfolio using the Sharpe Ratio Maximisation model and Naïve (1/N) portfolio. The level of market timing and selectivity skills of individual investors following the suggested investment strategies will be measured by using the Treynor-Mazuy model. The empirical results showed that the best Moving Average Crossover gave plausible trading frequencies and provided the most return to investors was the (1, 100, 0.01) strategy. Albeit, the stock allocation for the constructed portfolio was less diversified compared to the Naïve (1/N) portfolio, the composition of portfolio weights of the constructed portfolio was able to offer a more than average risk to reward ratio. Furthermore, in the out-of-sample framework, both portfolios outperformed the market benchmark. Unlike previous studies, this study backed tests the strategy and found that it was beneficial for individual investors of Shariah-compliant equities to enhance market timing and selectivity skills in stock investment.

An Improved MV Method for Stock Allocation Based on the State-Space Measure of Cognitive Bias with a Hybrid Algorithm

In classical finance theory, cognitive bias does not play any role in predicting returns. With the development of the economy, the classical theory gradually finds it difficult to offset the irrational demand through arbitrage. Due to the rise of behavioral economics, how to allocate stock portfolios in the highly subjective environment is an unavoidable problem. Considering the decision heterogeneity between the rational market and the irrational one, the mean-variance (MV) method was improved in the construction of a market bias index for stock portfolio allocation, which we called EMACB (exponential moving average of cognitive bias)-variance method. Besides, due to the lack of related research, we introduced a measure of aggregate investor cognitive bias by adopting the state-space model. Finally, the proposed method was applied in an investment allocation example to prove its feasibility, and its advantages were emphasized by a comparison with another relevant approach.