Qualitative Construction of Growth Stock Portfolios – a Score Based Approach

2021 ◽  
Vol 10 (2) ◽  
pp. 427-439
Keyword(s):  
Stock Portfolios

A DECISION TREE-BASED CLASSIFICATION APPROACH TO RULE EXTRACTION FOR SECURITY ANALYSIS

2006 ◽  
Vol 05 (01) ◽  
pp. 227-240 ◽  
Author(s):  
N. REN ◽  
M. ZARGHAM ◽  
S. RAHIMI
Keyword(s):  
Decision Tree ◽  
High Performance ◽  
Security Analysis ◽  
Predictive Performance ◽  
Classification Model ◽  
Stock Selection ◽  
Selection Rules ◽  
Stock Portfolios ◽  
Decision Tree Classification ◽  
C4.5 Decision Tree

Stock selection rules are extensively utilized as the guideline to construct high performance stock portfolios. However, the predictive performance of the rules developed by some economic experts in the past has decreased dramatically for the current stock market. In this paper, C4.5 decision tree classification method was adopted to construct a model for stock prediction based on the fundamental stock data, from which a set of stock selection rules was derived. The experimental results showed that the generated rules have exceptional predictive performance. Moreover, it also demonstrated that the C4.5 decision tree classification model can work efficiently on the high noise stock data domain.

Leveraged stock portfolios over long holding periods: A continuous-time model

2006 ◽  
Vol 30 (3) ◽  
pp. 356-375
Author(s):  
Dale L. Domian ◽  
Marie D. Racine ◽  
Craig A. Wilson
Keyword(s):  
Continuous Time ◽  
Continuous Time Model ◽  
Time Model ◽  
Stock Portfolios

scholarly journals A Balanced Portfolio Can Have a Higher Geometric Return than the Risky Asset

2021 ◽  
Vol 14 (9) ◽  
pp. 409
Author(s):  
Miriam Arden ◽  
Tiemen Woutersen
Keyword(s):  
Risk Premium ◽  
Large Fraction ◽  
Developed Countries ◽  
Policy Implications ◽  
Government Bonds ◽  
Stock Portfolios ◽  
Bond Portfolio ◽  
Target Date ◽  
Stock Portfolio ◽  
The U.S

In the U.S., the geometric return on stocks has been higher than the geometric return on bonds over long periods. We study whether balanced portfolios have a larger geometric return (and expected log return) than stock portfolios when the risk premium is low. We use a theoretical model and historical data and find that this is the case. This low-risk premium is often observed in other developed countries. Further, in the past two decades, a balanced portfolio with 70% or 90% invested in the U.S. stock market (with the remainder invested in U.S. government bonds) performed better than a 100% stock or bond portfolio. The reason for this is that a pure stock portfolio loses a large fraction of its value in a downturn. We show that this result is not driven by outliers, and that it occurs even when the returns are log normally distributed. This result has broad policy implications for the construction of pension systems and target-date mutual funds.

scholarly journals Do good fundamentals generate alpha?

2020 ◽  
Vol 14 (2) ◽  
Author(s):  
Luís Chagas ◽  
Ricardo Leal ◽  
Raphael Roquete
Keyword(s):  
Financial Reporting ◽  
Risk Premium ◽  
International Financial Reporting Standards ◽  
Reporting Standards ◽  
Value Stocks ◽  
Financial Reporting Standards ◽  
Stock Portfolios ◽  
Significant Coefficient ◽  
The Moment

Objective: To verify abnormal risk-adjusted returns in Brazilian stock portfolios formed according to the F-Score that indicates the presence of good fundamentals. Method: The sample has 146 companies per year on average, includes the period of adoption of the International Financial Reporting Standards (IFRS) from July 2008 to June 2018 and uses equally weighted portfolios formed at the end of June of each year with information from the previous year. Results: The high F-Score portfolio showed greater average returns, lower beta, and a positive and significant alpha that disappeared in the sub-period initiating after the full adoption of IFRS. Significant coefficients for the small capitalization risk premium and egalitarian weighting suggest that large companies do not dominate its performance. High and low F-Score portfolios cannot be characterized as value stocks. The low F-Score portfolio displayed a negative and significant coefficient for the moment factor, suggesting persistence of negative returns. Contributions: Portfolios with high F-Score may have less chance of catastrophic returns. The technique can be employed by less sophisticated investors to build defensive portfolios of companies with good fundamentals.

scholarly journals The Performance of Stock Portfolios formed using Fuzzy Logic

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Amit K. Sinha 1 ◽  
Andrew J. Jacob 2
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Expert System ◽  
Expert Systems ◽  
Fuzzy Membership ◽  
Thought Process ◽  
Membership Functions ◽  
Fuzzy Membership Functions ◽  
Stock Portfolios ◽  
Financial Securities

Expert systems, a type of artificial intelligence that replicate how experts think, can aide unskilled users in making decisions or apply an expert’s thought process to a sample much larger than could be examined by a human expert. In this paper, an expert system that ranks financial securities using fuzzy membership functions is developed and applied to form portfolios. Our results indicate that this approach to form stock portfolios can result in superior returns than the market as measured by the return on the S&P 500. These portfolios may also provide superior risk-adjusted returns when compared to the market.

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