Article Per Year (5 Year)
p-Index From 2021 - 2026
2.319
P-Index
This Author published in this journals
All Journal Journal of Indonesian Applied Economics Journal of Indonesian Economy and Business JOIV : International Journal on Informatics Visualization Jurnal Akuntansi : Kajian Ilmiah Akuntansi (JAK) Indonesian Journal of Artificial Intelligence and Data Mining Politik Indonesia: Indonesian Political Science Review Jurnal Samudra Ekonomi dan Bisnis Jurnal Manajemen Jurnal Manajemen dan Usahawan Indonesia Jurnal Akuntansi dan Keuangan Jurnal Akuntansi dan Keuangan Indonesia Indonesian Capital Market Review The South East Asian Journal of Management Inkubis: Jurnal Ekonomi dan Bisnis Eduvest - Journal of Universal Studies Indonesian Journal of Advanced Research (IJAR) Prosiding Seminar Nasional dan Call Paper STIE Widya Wiwaha Jurnal Manajemen dan Usahawan Indonesia International Research Journal of Business Studies
Husodo, Zaafri Ananto
Department Of Management, Faculty Of Economics And Business, Universitas Indonesia
Aerospace Engineering Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Neuroscience Social Sciences

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 27 Documents
Search

 1   2   3 
Time-Varying Correlation Between Stock and Government Bond in Asia: Flight-to-Quality Margani, Mahanani; Husodo, Zaafri Ananto
Jurnal Politik Indonesia: Indonesian Political Science Review Vol 7, No 2 (2022): Politics and Business
Publisher : Political Science Program, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ipsr.v7i2.37838

Abstract

This study aims to provide an overview of how the relationship between stock and bond market in Asia when a crisis occurs (in this case the 2008 global crisis and the COVID-19 pandemic) using the DCC-GARCH method to prove the flight-to-quality phenomenon in Asia (China, Japan, Indonesia, Singapore, Malaysia, Thailand, and India). The results showed that during the 2008 global crisis, the flight-to-quality phenomenon happened in Thailand where the correlation between stock returns and government bonds in that country became increasingly negative during the crisis period, indicating that there was a shift in investment from stocks to government bonds. In addition, this research also proved that during the COVID-19 pandemic, the flight-to-quality phenomenon was also proven to occur in Malaysia.
Analisis Faktor Risiko pada Saham Perbankan ASEAN – 4 Periode 2006 – 2015 Dengan Pendekatan Fama and French Three Factor Model dan Intertemporal Capital Asset Pricing Model Adela, Lita Tiami; Husodo, Zaafri Ananto
Jurnal Manajemen dan Usahawan Indonesia Vol. 43, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to determine the effect of market, size, and value on Fama and French Three Factor Model toward portofolio excess return using value weighted and equally weighted method on ASEAN – 4 banking stock. This research also determine the effect of market factor and term struc- tured factor on Intertemporal Capital Asset Pricing Model on ASEAN – 4 banking stock. The result shows only market factor that has significant effect towards banking stock portofolio excess return on Fama and French Three Factor Model, using both value weighted dan equally weighted. The term- structure factor on Intertemporal Capital Asset Pricing Model has significant effect towards banking stock portofolio excess return using equally weighted method.
Households Perceptions on Factors Affecting Resilience towards Natural Disasters in Indonesia Viverita, Viverita; Kusumastuti, Ratih Dyah; Husodo, Zaäfri Ananto; Suardi, Lenny; Danarsari, Dwi Nastiti
The South East Asian Journal of Management Vol. 8, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Most areas in Indonesia are prone to natural disasters. Learning the lessons from the Aceh Tsunami in 2004, areas with high risks of natural disasters are in the process of preparing themselves for such an unexpected event, by increasing their resilience. The objective of this study is to shed more lights on factors affecting the resilience from two sources namely, existing literatures and the application of disaster management in four disaster-prone areas in Indonesia -Padang, Sleman, Cilacap, and Palu. To enrich our analysis, we collect data from the field to compare the preparedness and to get insights on people’s perceptions towards the factors of resilience in those areas.We employ IDI and FGD to identify the factors of resilience and the preparedness in the areas investigated. Thereafter, a preliminary survey is conducted to identify people’s perceptions towards the aspects of resilience in the areas. Results from the survey conducted to 800 households in Padang and Cilacap indicates that from the social aspect, community’s value cohesiveness is one of important factor affecting their resilience towards natural disaster. In addition, since almost 85 percent of their income was spending to fulfill their daily basic needs such as foods, clothing, and housing. Therefore, when disaster occurred, they heavily relied on the help of debt or selling some of their assets, as well as used cash in hand as emergency funds. In general, respondents in all sample cities are able to re-start their economic activities as soon as two weeks after the event of disaster. In addition, the survey found that most of respondents were aware that the government has programs to educate people on the disaster mitigation.
Pendekatan “Real Option” Dalam Valuasi Aset Jalan Tol Trans Sumatera Muhammad Rifqy; Zaäfri Ananto Husodo
JAK (Jurnal Akuntansi) Kajian Ilmiah Akuntansi Vol. 11 No. 2 (2024)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jak.v11i2.7669

Abstract

Sumatra Island is the locomotive of Indonesia's economic development in the western region, so the development of the economy in Sumatra Island is one of the conditions for the sustainability of the economy in western Indonesia and the Indonesian economy in general. Therefore, if development in Sumatra Island stagnates, the development of the surrounding areas will also be hampered. In order to improve the smooth movement of goods and people and distribution on the island of Sumatra, the central government encourages the construction of the Trans Sumatra Toll Road ("JTTS"). In its implementation, the concession of JTTS is assigned to PT Hutama Karya (Persero) ("HK") through Presidential Regulation. However, JTTS is not financially feasible, so the operation of 5 (five) JTTS sections has an impact on HK's performance due to the large interest expense that must be borne by the company. One solution that can be done is to do an asset recycle or asset disposal (divestment) of JTTS that has been operating. Valuation with the real option method pays attention to the flexibility of cash flows over the volatility of the toll road business within a certain period of time expressed in binomial step nodes. With the limitation that the divestment value is at least 1 (one) time compared to the value that has been invested by the company (par value), the option to wait can assist management in making decisions to divest operating segments simultaneously within a certain period of time until it reaches a minimum par value.
Identifying Green Bonds Impact on Company Reputation and Risk Estiningrum, Widya; Husodo, Zaäfri Ananto
International Research Journal of Business Studies Vol. 17 No. 1 (2024): April - July 2024
Publisher : Universitas Prasetiya Mulya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21632/irjbs.17.1.1-19

Abstract

In recent years, there has been a growing awareness of the severity of climate-related risks, prompting a global imperative for environmental preservation. As a result, companies are now vital contributors to sustainability efforts, requiring them to integrate environmental, social, and governance factors into their investment and financing decisions. This paper aims to provide other researchers and stakeholders with some new ideas and a clear understanding of the important research trends in studies about how certain methods linked to issuing green bonds can impact a company's reputation and associated risk. By employing a Systematic Literature Review (SLR) and content analysis of 45 articles, the research takes a corporate-centric perspective. The findings of this paper reveal a gap in the literature concerning the direct influence of green bond issuance on company reputation and associated risks. While previous studies have explored the impact of bond issuance on various performance metrics, there remains a notable absence of detailed analysis on the relationship between green bonds and corporate reputation. By shedding light on the implications of green bond issuance for corporate reputation and risk, this research underscores the importance of integrating environmental and social considerations into strategic decision-making processes.
Sustainability Metrics in Emerging Markets: Analyzing ESG Scores Through Financial Returns and Risks Lirisanti, Dika; Husodo, Zaäfri Ananto
Indonesian Journal of Advanced Research Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijar.v4i1.13616

Abstract

This study examines the impact of stock returns and risks on ESG (Environmental, Social, and Governance) scores in emerging Asian markets during the COVID-19 pandemic. Utilizing panel data from Refinitiv Eikon for March 2019 to March 2022, this research investigates how returns, risks, and control variables such as Excess Market Return, SMB, HML, and Liquidity influence ESG scores. The findings reveal that returns and risks exhibit differential impacts on ESG scores, with social factors emerging as the most influential ESG component. These results highlight the nuanced role of financial performance in driving ESG metrics during crises, particularly in less-developed markets.
Connectedness Analysis And Investment Strategy Between Stablecoins And International Stock Indices Ika Maradjabessy; Zaafri Ananto Husodo
Jurnal Manajemen Vol. 28 No. 3 (2024): October 2024
Publisher : Fakultas Ekonomi dan Bisnis, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jm.v28i3.2008

Abstract

This research analyzes the dynamic connectedness between fiat-based stablecoins represented by USDC, USDP, and USDT, and gold-based stablecoins represented by DGX  and GLC  with indices international stocks represented by S&P500, STOXX50, Nikkei225, CSI300, and JKSE using the new method,  the DCC-GARCH based dynamic, connected approach. The result shows dynamic connectedness between stablecoins and the stocks indices; this research continues to adopt the DCC-GARCH t-copula method to find investment strategies by calculating the hedging ratio and portfolio weight. Overall, this research finds evidence that portfolio construction can significantly reduce investment risk in all assets used on two assets, Nikkei225 and JKSE. In contrast, the investment strategy with portfolio weights in long positions is suitable for gold-based stablecoins GLC and DGX, where these two assets can be a diversification strategy in compiling a portfolio in long positions with all the assets used.
The Influence of Characteristics Individual’s Investor on Financial Investment Decision of Young Generation Sari, Ayula Candra Dewi Mulia; Husodo, Zaäfri Ananto
Jurnal Samudra Ekonomi dan Bisnis Vol 16 No 1 (2025): JSEB
Publisher : Fakultas Ekonomi Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jseb.v16i1.10814

Abstract

This study aims to determine influence of individual investor characteristics, including financial literacy, overconfidence bias, herding behavior, risk tolerance and demographic factors on the financial asset investment decisions of young generation. This study used purposive sampling, with sample consisting of capital market investors within age range of gen Y and gen Z and location of domiciles in five major cities on Java. Primary data were collected through an online questionnaire, with a total of 195 investors. Hypotesis testing was conducted using binary logistic regression model and processed with STATA-17. Result of the study indicate that overconfidence bias, herding behavior, risk tolerance and gender influence financial investment decisions of young generation. But financial literacy, income and age do not have a significat effect on investment decision of young generation.
Synergy Analysis on Cryptocurrency Returns and Investor Sentiment Using Bidirectional Encoder Representations from Transformers (BERT) Hardiyanto, Reynaldy; Husodo, Zaäfri Ananto
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.33315

Abstract

Cryptocurrencies have become prominent alternative investments. Unlike traditional financial assets, their intrinsic value is a subject of ongoing debate since they do not have a tangible backing asset. As a result, investor sentiment heavily influences price volatility and serves as a key indicator of perceived value based on collective investor beliefs. However, major events such as the FTX scandal can severely weaken investor confidence. Social media drives market discussions, making sentiment analysis vital for understanding behavior and predicting price movements. This study examined sentiment analysis techniques to construct an investor sentiment index and investigate its relationship with cryptocurrency returns during the FTX collapse. We employed DistilBERT and the AFINN lexicon method to develop sentiment index, finding that DistilBERT achieves an F1-score of 76.49%, significantly outperforming AFINN's 30.65%. Furthermore, our results indicate a positive correlation between investor sentiment and cryptocurrency returns during the FTX collapse. Our findings indicate that deep learning models can be more effective than lexicon-based approaches for sentiment analysis in financial markets
Assessing Data Imbalance in Financial Distress Prediction: A Comparative Approach of Machine Learning and Economic Models Rahayu, Dyah Sulistyowati; Suhartanto, Heru; Husodo, Zaäfri Ananto
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3397

Abstract

This study aims to compare the effectiveness of machine learning models and economic models in predicting corporate bankruptcy, with a focus on addressing the issue of data imbalance. In this context, the number of companies experiencing financial difficulties is significantly smaller than that of healthy companies, which can lead to bias in predictions. The method used is an experiment with various data handling techniques and involves several classification models, namely Decision Tree, Neural Network (NN), K-Nearest Neighbors (KNN), Case-Based Reasoning (CBR), Support Vector Machine (SVM), and Merton Structural Model, which are tested on several data scenarios with resampling techniques, including Random Oversampling (ROS), Random Undersampling (RUS), and a combination of both. The evaluation results show that the Decision Tree, excluding ROA variables, and the Neural Network provide the best performance, with the Decision Tree achieving 86% accuracy and an AUC of 77.75, and the Neural Network achieving 86.76% accuracy and an AUC of 90.5. Other models, such as KNN and SVM, exhibit lower performance, achieving around 80% accuracy and a lower AUC. Based on these results, Decision Tree without ROA and Neural Networks are the best choices for predicting corporate bankruptcy. This study also demonstrates that financial models, such as the Merton Structural Model, are not significantly affected by data imbalance. The ultimate goal of this study is to provide recommendations for more reliable prediction models that enable financial institutions, investors, and companies to make more informed strategic decisions, as well as reduce financial risks through the early detection of companies at risk of failure.
Co-Authors Adela, Lita Tiami Anggayasti Hayu Anindita Ariani, Alexandra Widuri Awwaliyah, Intan Nur Boniarga Mangiring Dwi Nastiti Danarsari Dyah Sulistyowati Rahayu Estiningrum, Widya Futty Pratiwi Harapon Angun Kasogi Hardiyanto, Reynaldy Henker, Thomas Heru Suhartanto Hubbansyah, Aulia Keiko Ika Maradjabessy Intan Nurul Awwaliyah Intan Nurul Awwaliyah Irwan Adi Ekaputra Kristiani Tri Lestari Lenny Suardi Lirisanti, Dika Lita Tiami Adela Mangiring, Boniarga Margani, Mahanani Maulana Harris Muhajir Muhammad Budi Prasetyo Muhammad Rifqy Nurhayati, Immas Nurtantyo Pratomo Suyadi Ratih Dyah Kusumastuti Ririen Setiati Risca Fleureta Hudiyono Sari, Ayula Candra Dewi Mulia Sekar Satiti Sigit Sulistyo Wibowo Teto, Columbanus Thomas Henker Usman Arief Usman Arief Viverita Viverita