Liquidity Horseraces

When you conduct a liquidity study, which liquidity measure should you use?

Browsing through the literature, you will find hundreds of liquidity measures proposed and utilized by previous studies. This is because liquidity is multifaceted, and each indicator focuses only on a certain attribute of liquidity.

Faced with an enormous menu of liquidity proxies, do you select the most widely used or the easiest to compute?

To guide researchers in their selection, liquidity horseraces provide the reference point. These extensive exercises compare the performance of existing low frequency liquidity proxies, in particularly their correlations with intraday benchmarks, thus saving researchers enormous computational time and high subscription cost for extracting microstructure data.

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Statistical Tests for Weak-Form Market Efficiency

Over the years, I received numerous email enquiries on topics related to market efficiency. My survey article in Journal of Economic Surveys provides a useful guide, as the paper reviews all the statistical tests for weak-form market efficiency.

If readers ask me which tools I would recommend, the variance ratio tests come first. This is because the existence of return autocorrelations has strong theoretical justifications, especially in the context of market reactions (or mis-reactions) to information. Moreover, the market efficiency literature has shifted from testing absolute efficiency to measuring relative efficiency. The latter objective can be  achieved by using absolute variance ratio minus one.

The survey article by Charles and Darne (2009) provides an extensive review of the existing variance ratio tests. Jae Kim (my PhD supervisor) generously shares the R-codes for a battery of efficiency tests (click here). Among all the available statistical tests, my recommendation would be the wild bootstrap automatic variance ratio (WBAVR) test proposed by Kim (2009). The greatest appeal of this test is that the optimal value of lag order or holding period is selected automatically using a data-driven selection rule. Moreover, Monte Carlo simulations (see also Charles et al., 2011) show that the test possesses good small sample properties, and is robust to conditional heteroskedasticity that typically characterizes most financial time series. Applications of the WBAVR test include Kim et al. (2011), Lim and Kim (2011), Charles et al. (2012) and Lim et al. (2013).

If readers are bothered by the possible existence of nonlinear serial dependence in the returns series, I would then recommend the generalized spectral martingale test proposed by Escanciano and Velasco (2006). The selling point of this test can be found in my recent article in Applied Economics Letters.

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Web of Science: How to rectify data error?

I noticed that there was an error when Web of Science (WoS) recorded my paper published in Physica A. The Elsevier’s website reported two affiliations, namely Universiti Malaysia Sabah and Monash University. However, only the latter appeared in WoS. Since this error has implication on institutional search, I decided to contact the technical support team at Thomson Reuters.

To submit a request for data change, you can directly fill in this online form (click here). The entire data change process took about three weeks, and the error has finally been rectified.





Using Dropbox for Research

I have been using Dropbox for more than a year now, and have nothing but praise for this software.  Among the benefits that I reap are: (1) It provides online backup of all files in addition to my iMac Time Machine; (2) I am working using multiple computers- PC (at office), iMac (at home after office hour), and Netbook (while traveling). Dropbox will automatically update the files to the latest version in all computers; (3) I can easily share folders with big files with colleagues, collaborators and my postgraduate students; (4)  When I didn’t bring computers with me (especially in conferences), I still can access my files via iPhone.

I have recommended this software even to my undergraduate students, and they found it perfect for group projects. Dropbox also received good reviews from Prof Rob Hyndman (see here, here and here).

Do you still need more time to consider?

If you are using someone else computer, you still can access your files as long as there is internet connection


If you are working at home (iMac), office (PC) or traveling (Netbook), you can sync them via Dropbox


You can share your folders with colleagues, students or collaborators


Dropbox folders in my iMac


Sharing your folders with others via Dropbox


SciVerse Applications

SciVerse Applications is a marketplace and developer network that allows the scientific community to build, find and use applications that enhance the research experience. Through SciVerse Applications, researchers and librarians can customize their SciVerse search and discovery processes and collaborate with developers to create an ever-expanding universe of new applications.

You are blessed with choices in the Application Gallery (click here). I am sure that you will find some that meet your needs.


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