A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio
Identifying where to invest and how much to invest can be very challenging for common people who have limited knowledge in the domain. Portfolio managers are financial professionals who spend a lot of time and effort to help investors in investing funds and implementing investment strategies, but no...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | Russian |
| Published: |
Government of the Russian Federation, Financial University
2022-09-01
|
| Series: | Финансы: теория и практика |
| Subjects: | |
| Online Access: | https://financetp.fa.ru/jour/article/view/1740 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849409879561732096 |
|---|---|
| author | J. R. Saini C. Vaz |
| author_facet | J. R. Saini C. Vaz |
| author_sort | J. R. Saini |
| collection | DOAJ |
| description | Identifying where to invest and how much to invest can be very challenging for common people who have limited knowledge in the domain. Portfolio managers are financial professionals who spend a lot of time and effort to help investors in investing funds and implementing investment strategies, but not all can afford to consult them. The study aims to develop a weighted hybrid recommendation system that recommends an optimized investment portfolio based on the investor’s preferences regarding risk and return. Generally, investors usually ask investment for advice from friends or relatives with similar risk preferences or if they are interested in a particular item, the investors ask for the experience of someone who already has invested in the same item. Therefore, the methodology considers the investor’s past behavior and the past behavior of the nearest neighbor investors with similar risk preferences. Using user-based collaborative filtering the number of stocks is recommended using Pearson correlation based on the investor’s income, then using another user-based collaborative filtering the number of stocks is recommended based on the investor’s age. Weights are assigned to the recommended number of stocks generated based on income and age and their weighted average is finally considered. Finally, the feasibility of the proposed system was assessed through various experiments. Based on the received results, the authors conclude that the proposed weighted hybrid approach is robust enough for implementation in the real world. The novelty of the paper lies in the fact that none of the existing approaches make use of more than one type of weighted recommendation algorithm. Additionally, the final results obtained this way have been never further fortified with the highest Sharpe ratio and minimum risk for the investor. This combination of hybrid and Sharpe ratios has never been explored before. |
| format | Article |
| id | doaj-art-e63d1e261bc340a491f28e3e032d5247 |
| institution | Kabale University |
| issn | 2587-5671 2587-7089 |
| language | Russian |
| publishDate | 2022-09-01 |
| publisher | Government of the Russian Federation, Financial University |
| record_format | Article |
| series | Финансы: теория и практика |
| spelling | doaj-art-e63d1e261bc340a491f28e3e032d52472025-08-20T03:35:20ZrusGovernment of the Russian Federation, Financial UniversityФинансы: теория и практика2587-56712587-70892022-09-0126426727610.26794/2587-5671-2022-26-4-267-276963A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment PortfolioJ. R. Saini0C. Vaz1Symbiosis Institute of Computer Studies and Research, Symbiosis International (Deemed UniversityDecision Analyst, EarlySalaryIdentifying where to invest and how much to invest can be very challenging for common people who have limited knowledge in the domain. Portfolio managers are financial professionals who spend a lot of time and effort to help investors in investing funds and implementing investment strategies, but not all can afford to consult them. The study aims to develop a weighted hybrid recommendation system that recommends an optimized investment portfolio based on the investor’s preferences regarding risk and return. Generally, investors usually ask investment for advice from friends or relatives with similar risk preferences or if they are interested in a particular item, the investors ask for the experience of someone who already has invested in the same item. Therefore, the methodology considers the investor’s past behavior and the past behavior of the nearest neighbor investors with similar risk preferences. Using user-based collaborative filtering the number of stocks is recommended using Pearson correlation based on the investor’s income, then using another user-based collaborative filtering the number of stocks is recommended based on the investor’s age. Weights are assigned to the recommended number of stocks generated based on income and age and their weighted average is finally considered. Finally, the feasibility of the proposed system was assessed through various experiments. Based on the received results, the authors conclude that the proposed weighted hybrid approach is robust enough for implementation in the real world. The novelty of the paper lies in the fact that none of the existing approaches make use of more than one type of weighted recommendation algorithm. Additionally, the final results obtained this way have been never further fortified with the highest Sharpe ratio and minimum risk for the investor. This combination of hybrid and Sharpe ratios has never been explored before.https://financetp.fa.ru/jour/article/view/1740sharpe ratiohybrid filteringinvestment portfoliorecommendation systemcollaborative filteringinvestorbased filtering |
| spellingShingle | J. R. Saini C. Vaz A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio Финансы: теория и практика sharpe ratio hybrid filtering investment portfolio recommendation system collaborative filtering investorbased filtering |
| title | A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio |
| title_full | A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio |
| title_fullStr | A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio |
| title_full_unstemmed | A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio |
| title_short | A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio |
| title_sort | novel weighted hybrid recommendation system using sharpe ratio for a profitable diversified investment portfolio |
| topic | sharpe ratio hybrid filtering investment portfolio recommendation system collaborative filtering investorbased filtering |
| url | https://financetp.fa.ru/jour/article/view/1740 |
| work_keys_str_mv | AT jrsaini anovelweightedhybridrecommendationsystemusingsharperatioforaprofitablediversifiedinvestmentportfolio AT cvaz anovelweightedhybridrecommendationsystemusingsharperatioforaprofitablediversifiedinvestmentportfolio AT jrsaini novelweightedhybridrecommendationsystemusingsharperatioforaprofitablediversifiedinvestmentportfolio AT cvaz novelweightedhybridrecommendationsystemusingsharperatioforaprofitablediversifiedinvestmentportfolio |