Borsa Istanbul supplies more of the signal across these four clubs, leading their token markets by seven significant tests to four. Traders would prefer the information to travel in reverse. Of the 16 causality statistics from stock returns to token returns, seven are significant; four run from token to stock. A useful token signal would let someone monitor the token overnight, then trade the club's listed equity at the Istanbul open. The venues keep different operational hours. Oğuz therefore removes weekend and holiday token observations before aligning the series.
The calculation
Beşiktaş, Fenerbahçe, Galatasaray and Trabzonspor are the four clubs with both fan tokens and listed shares. Other Turkish clubs issue tokens, but only these four trade as equities on Borsa Istanbul. Matriks Data supplies daily equity closes in TRY. Token prices are CoinGecko's global volume-weighted averages, translated into TRY using the central bank's official daily rate. Each sample starts when its token was listed and ends December 31, 2025. The resulting histories contain 564 observations for Beşiktaş, 1,098 for Fenerbahçe, 1,276 for Galatasaray and 1,288 for Trabzonspor.
Following Hatemi-J (2012), the paper separates each log-return series into positive and negative shocks. Hatemi-J provides two possible transformations, and the paper does not specify which it applies: cumulative sums from equation (3), or the plain positive and negative variations available when a series is stationary. Ng-Perron unit root tests classify every series as stationary at level. Four sign pairings in each direction produce eight tests per club, making thirty-two across the four clubs.
Each no-Granger-causality null is tested with a Wald statistic and bootstrapped critical values. Given the distributions, that choice makes sense. The Trabzonspor token alone records kurtosis of 46.376 and a Jarque-Bera statistic above 101,000.
The paper gives the usual reason for splitting shocks by sign. Agents respond differently to positive and negative price moves, with bear market news prompting more dramatic reactions than bull market news.
Eleven rejections from thirty-two
Seven of the sixteen stock-to-token statistics reject their nulls. Four of the sixteen token-to-stock statistics do the same. Altogether, there are eleven rejections in thirty-two tests. Critical values are bootstrapped separately for each test, without an adjustment for the family size. At the 10% level, thirty-two tests would generate roughly three chance rejections. Eleven clears that benchmark comfortably when treated as a set.
The club counts are less persuasive: one significant result for Trabzonspor, two for Beşiktaş, three for Fenerbahçe and five for Galatasaray.
Only one of the eleven rejections appears at the weakest threshold. Galatasaray's positive-token-to-positive-stock relation produces a Wald statistic of 5.858, above the 10% critical value of 5.132. Every other rejection clears 5% or 1%, the paper's strongest feature. Fenerbahçe's positive stock shocks predicting negative token shocks yield 20.878 against a 1% value of 13.405. That rejection is nowhere near the boundary. In the paper's words, Galatasaray "has emerged as the only club to exhibit bidirectional causality," and the club contributes five of the eleven hits.
The abstract and conclusion pull in different directions. For Beşiktaş, Fenerbahçe and Galatasaray, the abstract says that "positive developments in fan tokens have been observed to have a significant impact on their stock prices." The conclusion is more restrained. Its counts "can be interpreted as indicating that there is no strong causal relationship between the two markets for the clubs analyzed." It also says generalization across sports clubs "may not be appropriate," while club-by-club evaluation "might be more accurate."
The second interpretation is the candid one. At that point, the design has little room left. Each club-level judgment depends on eight tests, while the windows begin on different dates and have unequal lengths. Beşiktaş's 564 days sit inside Trabzonspor's 1,288. The clubs therefore enter with different statistical power, yet the comparison rests on how many tests reject.
One story cannot fit the signs
The abstract's claim depends on a peculiar cell. For all three clubs, the token-to-stock relation clearing 5% runs from positive token shocks to negative stock shocks. Beşiktaş records 13.807 against a 1% value of 13.062. Fenerbahçe records 16.464 against 13.363. Galatasaray comes in at 11.456 against a 5% value of 9.203.
Galatasaray supplies the sole case in which positive token shocks predict positive stock shocks: 5.858, significant only at 10%. Trabzonspor shows no token-to-stock relation under any sign pairing. Its single significant link goes from negative stock shocks to positive token shocks, with a Wald statistic of 10.574 against 8.089.
A token rally therefore precedes equity weakness for three clubs, while equity weakness precedes token strength for the fourth. The paper supplies no mechanism for either pattern, and we cannot build one that accommodates both. Each test takes one sign of innovation in one series and compares it with the opposite sign in the other. Turning that result into a directional forecast requires a strained reading.
One feature makes the interpretation harder. The token prices are converted into TRY, whereas the equities already trade in TRY. Token returns consequently include a TRY exchange-rate component absent from stock returns. The paper controls for none of it. It also does not control for Chiliz and Bitcoin market-wide moves or for match results, which studies in its review identify as a driver of token returns.
Can a rejected null become a trade?
None of the relations comes with a horizon because the paper does not report the lag orders selected by the HJC information criterion. There is no effect size, R-squared or hit rate. Analysis ends with the Wald column. A causality paper can reasonably stop there; a trader sizing a position cannot. Transaction costs receive no treatment.
The volatility gap deserves the trader's attention.
Galatasaray's token has daily standard deviation of 0.057, compared with 0.032 for its stock. Trabzonspor is wider still, at 0.066 against 0.033. Daily log returns for the Trabzonspor token range from +0.709 to -0.750, roughly a doubling at one end. Its equity remains between +0.098 and -0.106 because Borsa Istanbul enforces daily price limits. Beşiktaş flips the relationship, with token volatility of 0.027 against stock volatility of 0.037. Using such a wide series to predict a limit-constrained equity creates a signal-to-noise problem before any strategy begins.
Ersan, Demir and Assaf (2022), whom the paper cites in its own review, used a time-varying-parameter VAR on a partly overlapping group of club pairs. They found club tokens to be the main transmitter of shocks into both tokens and stocks, while idiosyncratic factors played a relatively larger role in stock returns. The counts here tilt the other way: seven from equities into tokens and four in reverse. Taken together, the studies leave a reader without an answer on which venue leads.
We could not reproduce the analysis ourselves. Its mechanism is same-issuer and cross-venue, requiring the exact pairs: Borsa Istanbul listings for the four clubs and TRY histories for their tokens. Our data cover US equities, ETFs and a limited selection of crypto pairs. Substituting either side would destroy the relationship under study.
The useful interpretation is the authors' own: a linkage exists, but it is weak enough to require judgment club by club. We have previously examined statistical connectedness that failed to justify portfolio weight in our note on cross-domain volatility connectedness. Four token-to-stock rejections out of sixteen, with all but one crossing signs, have the same character. Report the lag order for a single club pair, then show an out-of-sample hit rate for the open-to-open equity move. A trading desk could price that claim.