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...

investment plays a vital role on economic growth. one of the main objectives of all countries is to achieve sustainable economic growth and development. nowadays, a considerable amount of activities performed by the managers and investors in general is to make a portfolio of assets effectively meeting demand goals. in this study, mean-variance markowitz model by cardinality constraints and also...

Mobile network sector is one of the important sectors in Malaysia which provides the network communication services to the users. The investors can get the return through the investment of the mobile network companies which are listed in Malaysia stock market. However, the investors will be exposed to the risk of loss in the investment. The mean-absolute deviation model is a portfolio optimizat...

We analyze the Merton portfolio optimization problem when the growth rate is an unobserved Gaussian process whose level is estimated by filtering from observations of the stock price. We use the Kalman filter to track the hidden state(s) of expected returns given the history of asset prices, and then use this filter as input to a portfolio problem with an objective to maximize expected terminal...

Abstract—Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be include...

Applications of Machine Learning (ML) to stock market analysis include Portfolio Optimization, Investment Strategy Determination, and Market Risk Analysis. This paper focuses on the problem of Investment Strategy Determination through the use of reinforcement learning techniques. Four techniques, two based on Recurrent Reinforcement Learning (RLL) and two based on Q-learning, were utilized. Q-l...

Evolutionary algorithms consist of several heuristics able to solve optimization tasks by imitating some aspects of natural evolution. In the field of computational finance, this type of procedures, combined with neural networks, swarm intelligence, fuzzy systems and machine learning has been successfully applied to a variety of problems, such as the prediction of stock price movements and the ...

Design of investment portfolios is the most important activity in the management of mutual funds, retirement and pension funds, bank and insurance portfolio management. Such problems involve, first, choosing individual firms, industries, or industry groups that are expected to display strong performance in a competitive market, thus, leading to successful investments in the future; second, it a...

We quantify the effect of a significant technological innovation, shale oil development, on asset prices. Using stock price changes on major news announcement days allows us to link aggregate stock price changes to shale development activity as well as other oil supply shocks. We exploit cross-sectional variation in industry portfolio returns on announcement days to construct a shale mimicking ...

We propose a robust portfolio optimization approach based on quantile statistics. The proposed method is robust to extreme events in asset returns, and accommodates large portfolios under limited historical data. Specifically, we show that the risk of the estimated portfolio converges to the oracle optimal risk with parametric rate under weakly dependent asset returns. The theory does not rely ...