The Journal of Prediction Markets

Order Imbalances and Market Efficiency: Evidence from a Pure Order-Driven Market

Lagan Jindal — 2026-02-25

Using a sample of 196 stocks, this study investigates the intraday market efficiency of the National Stock Exchange of India (NSE), a market that is entirely order-driven. The return autocorrelation and variance ratio tests suggest that the hourly returns of stocks at NSE are not serially correlated. Hourly order imbalances (OIBs) are highly persistent up to four lags, and can help in return prediction. Investors appear to follow short-horizon OIBs to conduct counter-
vailing trades, and remove serial dependence in short-term returns. A simple order imbalance based trading strategy appears to offer abnormal returns; however, these returns vanish once the trading costs are factored in. Overall, the results indicate that the de-facto market making at NSE is effective.

Price Discovery in Carbon Markets: Evidence from Phase III & IV of EU-ETS

Charu Vadhava — 2026-02-25

This paper examines the price discovery process in the European Union Emission Trading Scheme (EU-ETS) – the largest carbon market across the world – for its third and fourth commitment periods. In particular, we examine the two leading carbon exchanges: European Energy Exchange (EEX: Spot and Futures) and European Climate Exchange (ECX: Futures). We examine the information transmission process in the EU-ETS for the three pairs, namely, (I) EEX spot-EEX futures, (II) EEX futures-ECX futures, and (III) EEX spot-ECX futures. To this end, we employ all three pair-wise bivariate vector error correction models (VECM) and price discovery measures, that is, component share (CS), information share (IS), and information leadership share (ILS) measures. We show that all three-price series substantially contribute to the price discovery. Moreover, the speed of adjustment and price discovery is comparable to the developed equity markets. The ability of carbon prices to incorporate the risk-premia related to climate-risk considerably depends on the pricing efficiency of carbon – one of the major objectives of the Kyoto Protocol and EU-ETS. Thus, these results have significant implications for policymakers, regulators, and academics in the forthcoming carbon markets from emerging economies (e.g., China, India).

Impacts of the 2023 NCAA Football Rules Changes on Scoring and the Totals Market

Evan Moore — 2026-02-25

The National Collegiate Athletics Association (NCAA) introduced rule changes prior to the 2023–24 season. According to the Football Foundation Rules Committee, “…the most significant 2023 football rule changes involve adjustments to the timing and clock rules,” with the purpose to shorten the length of the game and to “…moderately reduce the number of plays per game.” We examine the impact of these changes on actual and expected scoring during the season. The rule changes led to lower average scoring, which was not fully encompassed at the start of the season in the financial (betting) market. The early season volatility in the market subsided as the season progressed resulting in a generally efficient market.

Multilingual X / Twitter Sentiment Analysis of Geopolitical Risk Using Granger Causality Focusing on the Ukraine War and Financial Markets

John Burns — 2026-02-25

This paper investigates the changes in the financial assets and markets from December 1^st, 2021, to April 30th, 2022, during the start of the Ukraine War. These dates roughly correspond to the prelude to the War in December 20211 to a few weeks after Russian troops withdrew from the Kyiv area on April 7^th, 20222. We used the Goldstein 19923 Results Table to create Positive and Negative Geopolitical Risk bigrams (Goldstein, 1992, Pg. 5–6). With these bigrams, we collected over 3.6 million tweets during our research period in seven different languages (English, Spanish, French, Portuguese, Arabic, Japanese, and Korean) to capture worldwide reaction to the Ukraine War. Using various sentiment analysis methods, we constructed a time series of the change in the daily Geopolitical Risk sentiment and explored its relationship to 39 different financial assets and markets at various time lags. We found through granger causality that the geopolitical risk time series contained predictive information on several assets and market changes at different lag times.

Do Sportsbooks Accurately Price Money Line Odds?

Kevin Krieger — 2026-02-25

Employing a unique NFL gambling dataset that includes both spread and money line data, we examine the disconnect in profitability between similar betting strategies across the two markets. If a naïve bettor wagered $110 on the favorite in every game against the spread (money line) he or she would, on average, lose $4.50 ($4.53) per game. Conversely, if the same bettor wagered $110 on the underdog every game he or she would, on average, lose $3.11 per game in the spread market, but lose less than 1 cent per game in the money line market. Further examination shows that a bettor could earn a 2.17% return betting the money line on the underdog if the closing spread was 7 or less and greater than 3, and 6.55% if the spread is 3 or less. As such, our results challenge the market efficiency of the NFL betting market and have important implications for sportsbooks and bettors.

Governance and Drug Prices: An Empirical Analysis Within the European Monetary Union

Evangelos Vasileiou — 2026-02-25

This study employs a panel data analysis to explore the determinants of cocaine and heroin prices within the European Monetary Union (EMU) from 2002 to 2021. Using economic and governance indicators, our approach provides a nuanced understanding of how governance affects drug market dynamics. The main objective of this study is to investigate and provide empirical evidence for the relationship between governance performance and the pricing of illicit drugs. Additionally, the study highlights that different aspects of governance have varying effects on specific types of drugs. The empirical evidence shows that stronger governance structures are associated with higher drug prices, as higher risk leads to higher prices. Moreover, the findings reveal that the rule of law impacts drug prices in general, while corruption specifically affects heroin prices. This research provides a unique contribution by linking governance performance directly to the pricing of illicit drugs within the context of the European Monetary Union. Unlike existing studies that focus predominantly on the medical, psychological, or criminal aspects of drug use, our study emphasizes economic and governance factors influencing drug prices, offering a novel perspective for policymakers and stakeholders in the fight against drug trafficking. To the best of our knowledge, this is the first model for illicit drug pricing.