Oguz Ersan

We investigate informed trading in the Bitcoin market throughout the COVID-19 pandemic. Compared to the pre-pandemic period, we find that informed trading is significantly higher in the affective first stage of the pandemic, before reverting to its pre-COVID-19 level during the later stage of the pandemic. Furthermore, information asymmetry tends to increase in daily COVID-19-related news: confirmed cases and deaths. Our findings are robust to alternative parameters and model specifications. The main implication for traders is that they should be extra cautious in timing their trading decisions during such events, as these tend to encourage informed trading.

The growing frequency of news arrivals, partly fueled by the proliferation of data sources, has made the assumptions of the classical probability of informed trading (PIN) model outdated. In particular, the model’s assumption of a single type of information event no longer reflects the complexity of modern financial markets, making the accurate detection of information types (layers) crucial for estimating the probability of informed trading. We propose a layer detection algorithm to accurately find the number of distinct information types within a dataset. It identifies the number of information layers by clustering order imbalances and examining their homogeneity using properly constructed confidence intervals for the Skellam distribution. We show that our algorithm manages to find the number of information layers with very high accuracy both when uninformed buyer and seller intensities are equal and when they differ from each other (i.e., between 86% and 95% accuracy rates). We work with more than 500,000 simulations of quarterly datasets with various characteristics and make a large set of robustness checks.

In this paper, we study the return and volatility connectedness between cryptocurrencies and DeFi Tokens, considering the impact of different uncertainty indices on their connectivity. Initially, we estimate a TVP‐VAR model to obtain the total connectedness between the two markets. We find that returns on the cryptocurrencies transmit significantly larger shocks and, thus, are responsible for most variations in the majority of DeFis' returns. Then, to analyse the impact of uncertainty on total return and volatility connectedness, we use four factors, namely, Economic Policy Uncertainty (EPU), The Chicago Board Options Exchange Volatility Index (VIX), Infectious Disease Equity Market Volatility Tracker (ID‐EMV) and Geopolitical Risks (GPR). We find that except for geopolitical risks, all three measures have a positive impact on return and volatility connectedness, while GPR exerts a negative impact. Finally, we provide implications for researchers, market participants and policymakers.

Assuming that investors can be foreign or local, do high-frequency trading (HFT) or not, and submit orders through a bank-owned or non-bank-owned broker, we associated trades to various investors. Then, building a panel vector autoregressive model, we analyzed the dynamic relation of these investors with returns and among each other before and during the COVID-19 market crash. Results show that investor groups have influence on each other. Their net purchases also interact with returns. Moreover, during the turmoil caused by the pandemic, except foreign investors not involved in HFT, the response of any investor group (retail/institutional, domestic investors doing HFT and those not doing HFT, and foreign investors doing HFT) significantly altered. This shows that the interrelation among investor groups is dynamic and sensitive to market conditions.

Using earthquake exposure during pregnancy as a proxy for in utero insult, we examine the impact of prenatal stress on investment decisions during adulthood. We find that investors exposed to major earthquakes in utero participate less in the stock market and hold less diversified portfolios, compared with investors born immediately before the earthquakes. Earthquake exposure in the third trimester of pregnancy has stronger impact, and female investors exhibit greater sensitivity to in utero insults. In contrast, the adverse impact of earthquake exposure is weaker among individuals who are exposed to extreme in utero insults, as surviving babies are likely to have superior characteristics.