Suspicious Trading in NFTs

The hype surrounding nonfungible tokens is well documented. Allegations of price manipulation and rampant speculation abound for this nascent asset class. However, are these hypes warranted? Or is it merely fear of a new asset class? Together with my coauthor Syed Tariq, I attempt an answer to this question by studying a large NFT transaction database to detect non-humanlike trading patterns which could be indicative of wash trading.

More details to follow.

Interbank Liquidity Risk in Emerging Economies

In a forthcoming paper at the International Review of Financial Analysis, my co-authors and I document how interbank credit risk transmits from the US to five important emerging countries: Brazil, Russia, India, China, and South Africa. We achieve this by creating synthetic spreads representing funding liquidity risk and estimate a Bayesian model with time-varying parameters on daily data covering the bulk of the Global Financial Crisis, European Sovereign Debt Crisis, and the Covid-19 pandemic.

Key Findings

First, global policy indicators are weakly associated with interbank credit market situations in BRICS economies. Instead, the state of US financial system matters more. This finding derives from the overwhelmingly significant results stemming from Chicago Fed’s NFCI indicator, which has a reputation for a leading indicator of US economic activities.

Second, our results’ temporal patterns imply that key central banking decisions precede or coincide with reduced spillover.

Third, we further examine whether interbank credit crunch depresses market liquidity in the corresponding domestic markets using a Granger causality approach. The results indicate that it often does, and the augmented conditional causality analysis shows that the state of fear and credit market conditions in the US economy holds some causal influence on the aforesaid relationship.

The published version of the paper is linked below:

If you require an author’s copy PDF, do send me an e-mail. Alternatively, you can check an earlier version on SSRN or Researchgate.


Imtiaz Sifat (Radboud University), Alireza Zarei (Coventry University), Seyed Hosseini (Cardiff University), and Elie Bouri (Lebanese American University)

Oil Price

Whether oil prices matter for the real and financial sectors of the economy is a multi-decade long question. The common wisdom on the street is that it does matter. Media appears to have helped solidify this perception; so much so that many (myself included) considered it a foregone conclusion. Research in the recent times appears to gainsay this; at least for the developed economies.

I ran an asymmetric copula test with time-varying parameters to capture how the extreme oil movements sync up with stock prices. The test’s interpretation is as follows: if the value is large, either or both of variables have predictive values for the other. If the sign is positive, they share a common direction. If not, there may be capital flight implications. The graph below is a representation of my early finding. Check the first panel for stocks. I only used S&P 500 here. Will add FTSE-100 and DAX results later and perhaps some emerging indices if time permits.

My result appears to align with recent efforts of researchers. Ordinarily, this would have been the end of the story. However, some brilliant researchers have been churning several indices of late capturing various dimensions of risk. One such effort I came across recently is by Prof. Sydney Ludvigson. When I plugged in the same codes for three types of uncertainty she quantified–Financial, Real Economic, and Macro–the results are starkly different. The co-movements in level and shocks are much stronger compared to stocks. Furthermore, if you notice the density plots and histograms below, the dispersion of the dependence parameters suggests that although oil prices may matter less for the stock markets (at least in terms of prediction or arbitrage value) it still matters as a conduit of investor sentiment. It’s also a lot more uncertain. Check the boxplots for clarity.

I haven’t yet looked at how these dependencies themselves co-move, or whether there are seasonal/cyclical elements in there–frankly, I suspect there is. Neither have I controlled for business cycle variables (yet). Once I do, a richer picture of the oil-finance relationship is likely to surface.I will update this post if/when I find something worthwhile. 


IMF Debt and Capital Control

In the mid-1990s, a collapse of Thai Baht precipitated a cascade of currency collapses, culminating in a full-blown economic crisis in the South-East and East Asian regions. Ever since, this crisis has remained significant for academics and policymakers owing to its sudden trigger, rapid percolation, and varied consequences. For economists concentrating on crises, the 1997 crisis also serves as an epicenter for tracking crisis management schemes and recovery trajectories. In this regard, two economies—Malaysia and Korea—stand out as candidates for deeper investigation due to disparate recovery paths undertaken. The former imposed hard capital controls, while the latter acceded to IMF bail-out and restructuring. Since then, both economies performed impressively. As a ripple effect of the crisis, some countries embraced protectionist measures to safeguard stability of own currency. Malaysia, for example, opted for capital controls, whereas Thailand, South Korea and Indonesia underwent governmental and economic policy overhaul at the behest of the International Monetary Fund (IMF). This brings us to the issue of capital control; a means of regulating the flow of money in and out of domestic economy. Economists’ views on it are multifarious. While some extol its ability to facilitate free movement of capital across economies, others castigate its straitening effects on growth, productivity and mobility. Induced by factors such as globalization and financial market integration, lately most advanced economies have adopted a more liberal approach when it comes to capital control. Developing nations, however, remain sporadic exponents of stricter controls as their typically low reserves make them vulnerable to volatility. It is noteworthy that despite generally open approach to capital control measures, most advanced economies still have ad hoc contingency plans in place to forestall sudden mass capital exit or to deter speculative attack on domestic currency.

My co-authors and I have undertaken several research projects revisiting the aftermath and dynamics of the divergent paths taken by Malaysia and South Korea in pursuit of an economic recovery since the late 1990s. Links to the papers are available to the left.

The papers’ full versions are available at the publishers’ site. Author versions are available at

Predictive Power of Web Search Behavior

This paper investigates the predictive ability of web search behavior in connection with stock market returns and trading volume in five emerging economies in the ASEAN region using econometric and signal-processing techniques. More specifically, we use Vector Error Correction Model in conjunction with Wavelet analysis and find consistently low predictive ability of search activity in Google. In fact, investors in nearly all five markets appear to be interested in searching terms related to the market after high returns or high trading activities occur. In other words, high returns or high activities precede search interest. Our findings are at odds with the general results reported in earlier studies conducted in developed countries. Additionally, our analysis in the time-frequency domain detects a two-week lead-lag phenomenon in the association between search behavior and market returns for all markets but the Philippines.

Full paper can be accessed at publisher’s website: