Browsing by Author "Ersan, Oguz"

Now showing 1 - 8 of 8

Citation Count: 22
Are Fan Tokens Fan Tokens?
(Academic Press Inc Elsevier Science, 2022) Ersan, Oğuz; Ersan, Oguz; Popesko, Boris
Fan tokens, digital assets providing privileges including rewards and promotions as well as voting rights in polls, recently became highly popular among the football clubs and the (fan) investors. Fan tokens differ from the stocks of football clubs with respect to ownership properties. Fan tokens might be associated with investor mood changes and reaction to match results. This paper aims to explore the impact of football match results on token prices of the clubs. We show that both the losses and wins in the most prestigious European tournament, UEFA Champions League affect the fan token abnormal returns, losses with an effect of a larger magnitude. Domestic matches and Europa League matches are not followed by similar reactions from the investors. Our results are robust to the use of alternative model specifications and various benchmark assets.
Citation Count: 18
Connectedness among fan tokens and stocks of football clubs
(Elsevier, 2022) Ersan, Oğuz; Demir, Ender; Assaf, Ata
This paper examines the dynamic connectedness among the fan tokens and their corresponding stocks using the TVP-VAR approach. We use daily data from December 11, 2020, to January 31, 2022, for the Juventus FC, AS Roma, Galatasaray, and Trabzonspor tokens and stocks. Our results indicate that shocks transmitted to any token are larger than the ones to the stocks, with the tokens being the net transmitters of shocks to both the tokens and stocks. Then, our results indicate that the two asset classes are considered independent of each other, with the total connectedness decreasing over time, and indicating that less than 10% of the contributions in any token (stock) is from the stocks (remaining stocks). This implies that the idiosyncratic contri-butions to the variations in the utilized group of assets are considerably low when compared to the system contributions. Finally, we provide some implications for investment and portfolio management.
Citation Count: 3
Detecting and date-stamping bubbles in fan tokens
(Elsevier, 2024) Ersan, Oğuz; Demir, Ender; Ersan, Oguz
We focus on the existence of bubbles in fan tokens, utilizing the Supremum Augmented DickeyFuller (SADF) and Generalized Supremum Augmented Dickey -Fuller (GSADF) tests. We use daily closing prices of the top 20 fan tokens according to their market capitalization, along with Bitcoin, Ethereum, and Chiliz. The evidence from the GSADF test results indicates that the prices of 13 out of 20 fan tokens and the three cryptocurrencies have explosive periods associated with bubbles. Our results also show that the percentage of bubble days is between 0 % and 5% for all fan tokens. Among the 13 fan tokens exhibiting bubble behavior in their prices, nine have multiple sub -periods associated with bubbles, while only four tokens have a single sub -period with explosive prices. Bubbles in token prices are short-lived bubbles; most last for a few days. As a robustness analysis, we also perform LPPLS (Log -Periodic Power Law Singularity), providing similar results. Further analysis shows that trading volume, fan token return, Economic Policy Uncertainty (EPU), Daily Infectious Disease Equity Market Volatility (EMVID) are positively associated with the presence of bubbles in fan token prices, while oil return is negatively associated with bubbles.
Citation Count: 6
High-frequency trading and market quality: The case of a slightly exposed market
(Elsevier Science Inc, 2022) Ersan, Oğuz; Ersan, Oguz
Impacts of high-frequency trading (HFT) on market quality and various actors have been broadly studied. However, what happens when HFT is not a prominent figure in a market remains relatively unexplored. The paper seeks to answer this question focusing on 30 blue chip stocks in an emerging market, Borsa Istanbul, through Dec 2015 to Mar 2017. Despite a low share in the overall activity, HFT has observable effects, i.e. liquidity provision by non-HFT traders significantly reduces with HFT. Moreover, HFT generates profits on both positive and negative return days. Yet, HFT activity does not have an impact on volatility. These findings raise concerns regarding HFT and show potential externalities are not specific to the markets with HFT dominance.
Citation Count: 0
Impact of the COVID-19 Market Turmoil on Investor Behavior: A Panel VAR Study of Bank Stocks in Borsa Istanbul
(Mdpi, 2024) Ersan, Oğuz; Ersan, Oguz
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.
Citation Count: 0
PINstimation: An R Package for Estimating Probability of Informed Trading Models
(R Foundation Statistical Computing, 2023) Ersan, Oğuz; Ersan, Oguz
The purpose of this paper is to introduce the R package PINstimation. The package is designed for fast and accurate estimation of the probability of informed trading models through the implementation of well-established estimation methods. The models covered are the original PIN model (Easley and O'Hara 1992; Easley et al. 1996), the multilayer PIN model (Ersan 2016), the adjusted PIN model (Duarte and Young 2009), and the volume-synchronized PIN (Easley, De Prado, and O'Hara 2011; Easley, Lopez De Prado, and O'Hara 2012). These core functionalities of the package are supplemented with utilities for data simulation, aggregation and classification tools. In addition to a detailed overview of the package functions, we provide a brief theoretical review of the main methods implemented in the package. Further, we provide examples of use of the package on trade-level data for 58 Swedish stocks, and report straightforward, comparative and intriguing findings on informed trading. These examples aim to highlight the capabilities of the package in tackling relevant research questions and illustrate the wide usage possibilities of PINstimation for both academics and practitioners.
Citation Count: 0
What drives the return and volatility spillover between DeFis and cryptocurrencies?
(Wiley, 2024) Ersan, Oğuz; Demir, Ender; Ersan, Oguz
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.
Citation Count: 5
Where do tourism tokens travel to and from?
(Routledge Journals, Taylor & Francis Ltd, 2023) Ersan, Oğuz; Demir, Ender; Ersan, Oguz
This study aims to identify the sources of spillovers affecting tourism tokens and classify the type of assets to which they correspond. Using daily data for different asset classes from June 2018 through November 2022, we employ a TVP-VAR methodology to test the connectedness between two tourism tokens, two leading travel equity indices, and the two dominant cryptocurrencies, namely, Bitcoin and Ethereum. The findings show that tourism tokens are relatively independent of fluctuations in the traditional sources affecting the travel and leisure sector, such as the U.S. dollar, the price of oil, or travel equity indices. These results hint that tourism tokens are more closely related to cryptocurrencies rather than pure travel goods. The results may help decision-makers in the travel and hospitality industries considering the use of tourism tokens identify the potential forces impacting them.