To my prospective research-track students (PhD/MSc/Master's by Research degrees): 

Over the past many years, I have had the pleasure of working with superior, talented research-track students. From inbound to internal thesis students at VinUniversity to international and exchange students from the world's most prestigious institutions, such as (just a few listed here) the University of Melbourne (UMel, Australia), the National University of Singapore (NUS, Singapore), the University of Nottingham (UK), and Seoul National University (SNU), among many other famous universities, which are cumulatively fruitful working experiences for both the supervisor/mentees and research students. For research students who have been working with my constant sharing over the years, and also for prospective students joining in the future, the points listed below could be beneficial to my prospective research-track students (my personal experience and points of view) for them to consider:

Personality:

Going beyond conventional academic indicators (e.g., GPA, SAT, English, programming, etc.) that universities worldwide apply to determine top-performing candidates is helpful. An important indicator I would like to add is 'personality.' Why?

 The main reason is that supervising research students should be a highly customized mentoring working model, rather than a common practice. Therefore, I greatly appreciate and highly encourage my prospective students to explore working styles that best benefit the students' long-term growth and are motivationally favorable to ALL in a professional manner.

Research students working with me normally have the greatest flexibility, and they are normally 'my director,' for whom I play as a supporter to all the students' expected workloads and target academic outlets such as journals and conferences. I highly encourage students to set the bar as high as expected by students and for students' long-term development goals. Of course, I am here to offer general directions, and my students can consider which directions with customized practical plans suit them best. Hence, along the way we work together; my students are more than free to suggest 'anything' that they may be ambitious to achieve in medium- and long-term goals, as discussed with the supervisor, following professional policies of institutions, and I support it more than 100% from my side. 

At the end of the date, my students are the true experts in their fields of interest, with their personality that is matched with the supervisors they want to work with, I fully respect it. Hence, all of the students who have been working with me normally per the students' expression of interest (EOI sent formally) plus expert recommendations to me for acting as their research supervisor and/or mentors. Given my experience, all the students have been more than 100% performing superior and no doubt, with their proven academic achievements over the years. 

Research areas of interest:

Prospective students are highly encouraged to determine the long-term expertise portfolios of their interest that are aligned with the supervisor's core capacities, with proven professional credentials. Hence, I am more than open to listening to students' suggestions and ambitions toward their own research themes of interest. Feel always free to let the supervisor know your greatest research interests toward possible mutual supervisor-student optimal achievements when we are working together along the way. It is very crucial for our long-term work together.

Programming capacities:

Research students are free to choose specific programming languages that they find most comfortable working with and related packages. My recommendations are listed below.

1. STATA combined with Python and related integrated development environments (IDEs) such as PySTATA.

2. R combined with either STATA and/or Python. 

3. SAS is preferably combined with one of the above packages.

4. All the above combined with one or more of the following packages, such as Microsoft Excel, Power BI, Tableau, and SQL.

Tip: No need to show off that we are familiar with all the languages; choose one that you find most comfortable in combination with other supporting packages. working efficiently toward real scholarly outputs. For instance, I am most proficient with STATA, with line-by-line codes that are offered to the students, and I normally make use of other packages if they benefit some technical tasks more efficiently (if applicable). For microeconometrics, I found that STATA (the licensed version) offers handy documentation and textbooks along with other famous packages. Your choice at the end of the date, as long as we make sure that step-by-step replication packages are reproducible for responsible science from very raw datasets to scientific outputs such as journal articles, conference papers, books, and so on. Students with no programming experience are encouraged to explore and choose the ones that they potentially find good for empirical works, big data analytics, and modelling applications in their fields of interest. 

Major databases under my supervision:

 Under my direct step-by-step guidance, prospective students and all students working with me are strongly encouraged to gain early, in-depth exposure to the world's major databases for research projects in the mainstream of financial economics literature. I have made a dedicated, super detailed 'data archive'; students can check and make use of it. The list below is much more concise for the world's major databases with their subscriptions, for students' exploration:

1. Financial Markets Infrastructure and Data | LSEG [Check my published articles and many other working papers on SSRN. This database has global coverage, and research students have comprehensive access to all the data archives, ranging from capital markets data, corporate fundamentals, security-level databases, ESG/CSR databases, and corporate governance (e.g., board characteristics, CEO-related variables, etc.), and many more things that the supervisor and research students can use for handy high-quality publications.

2. Wharton Research Data Services [WRDS] with Compustat and Center for Research in Security Prices, LLC (CRSP), and many other data vendors through WRDS.

Research students can check my Master of Finance (MFIN) thesis published in the Pacific-Basin Finance Journal (PBFJ) in 2021, titled: Does stock liquidity affect bankruptcy risk? DID analysis from Vietnam. This is my master's thesis on market microstructure and corporate default risk, for which I have used WRDS-COMPUSTAT-CRSP for US markets and the LSEG workspace [formerly known as the Thomson Reuters DataStream WorkScope] for emerging financial markets [Vietnam]. 

Research students can also visit my PhD thesis with three (3) chapters on Empirical Corporate Finance and Asset Pricing Studies for the US markets using data archives from WRDS. My doctoral thesis is attached below:

 The financial impacts of climate risk: the dissertation presented in fulfillment of the requirements of the degree of Doctor of Philosophy, PhD in Finance at Massey University, Manawatū, New Zealand 

Another of my 2023 EMR-published articles is also helpful for research students using the LSEG workspace for financial markets research [stock returns, liquidity, default risk, etc.] as attached: Stock liquidity during COVID-19 crisis: A cross-country analysis of developed and emerging economies and economic policy uncertainty - ScienceDirect. This is one of my feature articles using the LSEG workspace, for which I have extracted and handled daily stock market data for the major developing and advanced equity markets. Check Sections 3 and 3.1; the sample countries for this study include three major developed economies [Australia, Japan, and the United States] and three major emerging economies [Brazil, China, and India]. 

The above are major databases for which my research students (for financial economics research) need to sharpen their skill sets, for which all my students have sufficient competition to confidently be admitted to doctoral [PhD] studies at world-class institutions such as R1 universities in the US, Russell Group universities in the UK, Group of Eight (G8) universities in Australia, and of course all other internationally recognized prestigious universities all over the world.

 Hence, my PhD-oriented research students get exposure to those research projects using the world's famous databases from day 1 under my direct principal supervision, one-on-one, for the students' portfolios of interest that are aligned with the supervisor's scientific portfolios and capacities. 

Incoming prospective students have the option to receive further support from my senior research students who have sustainable experience with real outputs jointly with the supervisor. In such a case, it is the job of incoming students to reach out to my senior research students for discussions. I am happy to recommend it, but it is up to the willingness of all the research students to the greatest happiness. The supervisor is happy to make recommendations; however, under my one-on-one supervision, all the students need to dedicate themselves first, assuming that they all have more than sufficient support and thorough guidance from the supervisor, as they are all becoming experts in their fields. Therefore, I expect all the students to be super independent in their fields of expertise. On the other hand, as said, I also strongly encourage all the students to keep in touch and learn from their peers as much as possible, with real contributions to teamwork being greatly appreciated and supported by all means from the supervisor's facilitation. Last but not least, each of my research students keeps in mind that you are building your own fortune. The supervisor facilitates it more than 100% in the most professional way in a fair competition among peers for your capacities in the international academic job markets.