Key Highlights

• Daily data cover 3096 cryptocurrency scams from 2018 to 2026.
• Rug pulls, honeypots, and technical exploits show distinct market sensitivities.
• Fraud incidence rises with stronger sentiment, liquidity, gas fees, and COVID-period conditions.
• Sentiment and volatility sensitivities weaken after Terra and remain lower after FTX.
• Stronger sentiment predicts more fraud but smaller conditional monetary losses.

Abstract

This study examines how investor-facing cryptocurrency fraud varies with market conditions, incident technology, and major market disruptions using daily data from the De.Fi REKT database over February 2018 to October 2026. The analytical sample contains 3,096 recorded incidents, with rug pulls, honeypots, and phishing classified as investor-facing fraud and technical exploits examined separately. Negative Binomial count models show that investor-facing fraud is more frequent when investor sentiment is stronger, markets are more liquid, Ethereum network activity is more intensive, and during the COVID period. These relationships remain comparatively stable across alternative outcome definitions, sentiment orthogonalization, and controls for temporally concentrated incidents. By contrast, the positive baseline volatility relationship weakens once concentration effects are addressed, while market-regime effects are not robust across alternative cycle filters. Formal cross-type tests reveal substantial heterogeneity: rug pulls are particularly responsive to sentiment and network activity, whereas technical exploits exhibit little systematic sensitivity to investor sentiment. Crisis-period interaction models further show that the pre-Terra sensitivities of fraud to sentiment and volatility weaken materially after the 2022 market disruptions. Monetary-loss models reveal a distinct incidence-severity trade-off: stronger sentiment is associated with more frequent fraud but smaller conditional losses, whereas volatility is more strongly related to loss magnitude once losses occur. Overall, cryptocurrency fraud is state-dependent, technology-specific, and multidimensional, implying that surveillance based solely on aggregate scam counts or broad market cycles can overlook important changes in fraud composition and financial severity.

Sovbetov, I. (2027). Fear, greed, and fraud: crypto scams across market cycles. The North American Journal of Economics and Finance , Vol.87. https://doi.org/10.1016/j.najef.2026.102740

@article{sovbetov2027fear,
  author = {Ihlas Sovbetov},
  title = {Fear, greed, and fraud: crypto scams across market cycles},
  journal = {The North American Journal of Economics and Finance},
  year = {2027},
  doi = {10.1016/j.najef.2026.102740},
  url = {https://doi.org/10.1016/j.najef.2026.102740}
}

Key Highlights

• FOMC-crypto associations vary systematically with market uncertainty.
• Voice Tone is positively associated with crypto returns under low uncertainty.
• Negative facial affect is linked to weaker short-run returns under high uncertainty.
• Facial associations strengthen when statement and press-conference tones diverge.
• Intraday Bitcoin evidence localizes key associations to post-communication windows.

Abstract

This paper examines whether textual, vocal, and facial features of FOMC communication are associated with cryptocurrency returns beyond policy actions and the semantic content of written statements and press-conference responses. Using 107 FOMC meetings from 2013 to 2025, we construct three communication measures: Net Hawkish Tone from domain-adapted text classification, Voice Tone from within-Chair standardized pitch and intensity, and Face Negative Tone from synchronized press-conference video. We estimate state-dependent local projections in which these associations vary smoothly with predetermined VIX-based uncertainty, while conditioning on target-rate, forward-guidance, and asset-purchase policy surprises and predetermined macro-financial controls. The most persistent result is a positive association between Voice Tone and equal-weighted cryptocurrency portfolio returns under low uncertainty. Negative facial affect is associated with lower returns at short and medium horizons under high uncertainty, particularly for Bitcoin, and this association becomes more negative when press-conference tone diverges from the formal statement. Net Hawkish Tone is also associated with lower returns at longer horizons when uncertainty is elevated, although its formal state contrast is weaker than for the principal nonverbal findings. Additional analyses show that the main nonverbal patterns remain evident across alternative timing, measurement, inference, and characteristic-sorted portfolio specifications. Overall, the results show that the association between FOMC communication and cryptocurrency returns varies across communication channels, uncertainty conditions, and the consistency of verbal signals.

Sovbetov, I. (2026). Beyond words: FOMC text, voice, and facial tone in crypto markets. International Review of Financial Analysis , Vol.119. https://doi.org/10.1016/j.irfa.2026.105462

@article{sovbetov2026beyond,
  author = {Ihlas Sovbetov},
  title = {Beyond words: FOMC text, voice, and facial tone in crypto markets},
  journal = {International Review of Financial Analysis},
  year = {2026},
  doi = {10.1016/j.irfa.2026.105462},
  url = {https://doi.org/10.1016/j.irfa.2026.105462}
}

Key Highlights

• Retail-oriented tokens show stronger weekend return premiums.
• Institutional-grade assets display Monday and Wednesday effects.
• Thin weekend liquidity amplifies Saturday return asymmetries.
• Weekday anomalies vary by size, liquidity, volatility, and regimes.
• Sentiment and Google Trends robustness checks support the results.

Abstract

This study investigates weekday return asymmetries in cryptocurrency markets using multi-factor regressions, GARCH models, Wald tests, and fixed-effects interaction specifications over the 2020-2024 period. The results reveal a robust Saturday premium that is more visible under thinner weekend liquidity and among speculative, lower-priced, and liquidity-sensitive tokens. Institutional-grade cryptocurrencies display distinct weekday effects: GARCH and Wald tests highlight stronger Wednesday patterns in benchmark-like assets, while fixed-effects interaction models show a stronger Monday differential and a modest Wednesday effect. Tuesday often records weaker returns, suggesting partial reversal after weekend price pressure rather than a uniform weekday premium. These patterns vary across asset classes and market regimes. The Saturday anomaly weakens during the COVID-19 period, when elevated trading activity blurred temporal rhythms, but re-emerges in the post-COVID and post-Terra phases. Overall, the findings show that calendar anomalies persist in 24/7 cryptocurrency markets but are reshaped by liquidity frictions, asset segmentation, investor attention, and the interaction between retail-oriented weekend trading and institutional-grade weekday effects.

Sovbetov, I. (2026). Retail Weekends, Institutional Weekdays: Liquidity and Return Asymmetries in Cryptocurrency Markets. Quarterly Review of Economics and Finance , Vol.110. https://doi.org/10.1016/j.qref.2026.102245

@article{sovbetov2026retail,
  author = {Ihlas Sovbetov},
  title = {Retail Weekends, Institutional Weekdays: Liquidity and Return Asymmetries in Cryptocurrency Markets},
  journal = {Quarterly Review of Economics and Finance},
  year = {2026},
  doi = {10.1016/j.qref.2026.102245},
  url = {https://doi.org/10.1016/j.qref.2026.102245}
}

Abstract

This chapter investigates whether algorithmic exchange-traded funds (ETFs) outperform traditional non-algorithmic ETFs across major industries. Using monthly data from 2013 to 2025, we examine technology, industrials, financials, healthcare, energy, and sin sectors. Employing Fama–French five-factor models and panel regressions, we find that algorithmic ETFs exhibit systematically lower volatility and market exposure, consistent with a defensive investment profile. However, they generally underperform sector-based ETFs in both raw and risk-adjusted returns, particularly in technology, financial, and energy sectors, where growth orientation and cyclical premia dominate performance. During the COVID-19 crisis, healthcare ETFs display superior resilience, while industrials and financials experience the largest contractions, and sin ETFs deliver modest but persistent excess returns. Overall, algorithmic ETFs excel in risk smoothing rather than return maximization, positioning them as volatility-management tools rather than performance-seeking substitutes for sector ETFs.

Sovbetov, I. (2026). Algorithmic Morality: AI-Driven Investing Across and Crises. In: Bagis, B. (Ed.), AI Driven Decision Making in Finance , Chapter 7, pages: 109-123. CRC Press: Taylor & Francis Group. United States, Florida, Boca Raton. E-ISBN: 9781003656463. https://doi.org/10.1201/9781003656463

@article{sovbetov2026algorithmic,
  author = {Ihlas Sovbetov},
  title = {Algorithmic Morality: AI-Driven Investing Across Industries and Crises},
  journal = {Chapter 7: AI Driven Decision Making in Finance},
  year = {2026},
  doi = {10.1201/9781003656463},
  url = {https://doi.org/10.1201/9781003656463}
}

Abstract

This study develops a dynamic zakat-based redistribution model within an overlapping generations framework to examine domestic poverty alleviation. The model incorporates four endogenous income classes and formalizes transfers from surplus-income individuals to economically vulnerable retirees and structurally poor groups. Zakat is evaluated against intergenerational, universal, and targeted poverty transfers under identical demographic structures and fiscal effort. Within the modeled framework, zakat outperforms alternative redistribution mechanisms. Its surplus-based structure targets absolute poverty while limiting fiscal pressure on near-threshold groups. It achieves the highest utility improvement-to-disruption ratio and generates pronounced reductions in income inequality and poverty depth under baseline conditions, with outcomes remaining robust across alternative macroeconomic and demographic environments. By formalizing zakat as a surplus-conditioned redistribution rule, the study contributes a theoretical framework for evaluating targeted poverty alleviation under fiscal and administrative constraints. The findings offer policy-relevant design insights for reducing persistent poverty while preserving efficiency and social sustainability.

Sovbetov, I. (2026). Poverty Alleviation with Zakat-based Redistribution Model. Journal of Poverty and Social Justice . https://doi.org/10.1332/17598273Y2026D000000067

@article{sovbetov2026poverty,
  author = {Ihlas Sovbetov},
  title = {Poverty Alleviation with Zakat-based Redistribution Model},
  journal = {Journal of Poverty and Social Justice},
  year = {2026},
  doi = {10.1332/17598273Y2026D000000067},
  url = {https://doi.org/10.1332/17598273Y2026D000000067}
}

Abstract

This paper examines risk-adjusted performance differences across AI-themed investment vehicles using monthly data from 2005 to 2025. We compare four equal-weighted portfolios: AI-powered ETFs, AI-focused thematic ETFs, AI/machine-learning (AIML) stocks, and a broad technology benchmark. We use factor models, GARCH volatility estimates, Sharpe ratios, quantile regressions, asset-level panels, ETF product-design controls, and non-AI benchmarks. The results show that AIML stocks deliver the strongest cumulative and abnormal returns but exhibit higher volatility, deeper drawdowns, and unstable exposure patterns. AI-powered ETFs show stronger risk-adjusted performance and a more efficient risk-conversion profile, reflected in lower betas, smoother volatility dynamics, milder downside deterioration, and higher return per unit of volatility. They also have a weaker association with lagged attention proxies, consistent with their defensive structure. Strategy-based tests show that the risk-efficiency advantage of AI-powered ETFs is most pronounced among volatility-targeting designs, while their non-volatility-targeting counterparts also compare favorably with AI-focused and non-AI defensive benchmarks.

Sovbetov, I. Hatipoglu, Y.Z. & Can, E.N. (2026). Risk-adjusted performance of AI-powered portfolios: Evidence on volatility, beta, and returns. Borsa Istanbul Review . 26(5). https://doi.org/10.1016/j.bir.2026.100872

@article{sovbetov2026riskadjusted,
  author = {Ihlas Sovbetov, Yildiz Zeliha Hatipoglu, Esin Nesrin Can},
  title = {Risk-adjusted performance of AI-powered portfolios: Evidence on volatility, beta, and returns},
  journal = {Borsa Istanbul Review},
  year = {2026},
  doi = {10.1016/j.bir.2026.100872},
  url = {https://doi.org/10.1016/j.bir.2026.100872}
}

Abstract

Purpose: This study examines whether Okun's Law varies across business-cycle phases and whether labor-market rigidity shapes the unemployment-output relationship across countries. Design/methodology: The analysis covers 52 countries over 1980–2020 and distinguishes between expansionary and recessionary periods. It applies country-level autoregressive distributed lag models and Pooled Mean Group panel ARDL estimators to estimate short-run and long-run Okun coefficients. Labor-market rigidity is incorporated through the OECD Employment Protection Legislation index, while Granger causality and impulse-response analyses are used to examine dynamic interactions. Findings: The results indicate long-run cointegration between output and unemployment in most countries, with more stable evidence in developed economies. Okun's coefficients are larger in magnitude during recessions, indicating stronger unemployment responses to output contractions. Short-run effects are relatively stronger in less rigid labor markets, whereas higher employment protection is associated with more stable long-run unemployment dynamics. Adjustment speeds differ across country groups, with slower responses observed in developed economies. The directional interaction between output and unemployment also varies across business-cycle phases, with unemployment feedback becoming more pronounced during recessions. Research limitations: The findings should be interpreted as associational rather than causal, since employment protection is related to broader institutional characteristics, including informality, bargaining structures, and enforcement quality. Originality/value: This study contributes by integrating business-cycle asymmetry and labor-market rigidity within a unified cross-country framework for examining Okun's Law. By incorporating the OECD Employment Protection Legislation index into country-level and panel ARDL models, it provides new evidence on how institutional settings are associated with the unemployment-output relationship across different phases of the business cycle.

Sovbetov, I. (2026). Okun's law across business cycles: the role of labor market rigidities. International Journal of Manpower , 47(5), 740-760. https://doi.org/10.1108/IJM-04-2025-0256

@article{sovbetov2026okuns,
  author = {Ihlas Sovbetov},
  title = {Okun's law across business cycles: the role of labor market rigidities},
  journal = {International Journal of Manpower},
  year = {2026},
  doi = {10.1108/IJM-04-2025-0256},
  url = {https://doi.org/10.1108/IJM-04-2025-0256}
}

Key Highlights

• Treasury inflows predict higher next-day ETF volatility.
• Gold outflows raise volatility; inflows have little effect.
• Effects are asymmetric and vary across volatility regimes.
• Results robust across OLS, HAR, IV, and volatility estimators.
• Tokenization signals differ by asset class and market frictions.

Abstract

This paper examines how tokenized real-world assets interact with traditional financial markets by linking daily flows of tokenized Treasuries and gold to next-day realized volatility in exchange-traded funds (ETFs). We build contract-level measures of circulating supply, convert them into percentage-point flows, and pair them with volatility controls and macro event calendars. For Treasuries, positive inflows on day t − 1 consistently predict higher day-t volatility, with results robust across OLS, HAR, quantile regressions, and instrumental-variable checks. The effects are economically small at the daily horizon but potentially decision-relevant for risk monitoring. For gold, the impact is asymmetric: outflows raise next-day volatility while inflows have little effect, consistent with redemption frictions and liquidity constraints. Robustness tests confirm that findings are not artifacts of volatility measurement or persistence. Overall, token flows provide incremental information for volatility forecasts and highlight asset-class asymmetries, underscoring how on-chain activity transmits signals to off-chain financial markets.

Sovbetov, I. (2026). On-chain flows, off-chain volatility: Tokenized real assets in financial markets. Quarterly Review of Economics and Finance . Vol.107. https://doi.org/10.1016/j.qref.2026.102156

@article{sovbetov2026onchain,
  author = {Ihlas Sovbetov},
  title = {On-chain flows, off-chain volatility: Tokenized real assets in financial markets},
  journal = {Quarterly Review of Economics and Finance},
  year = {2026},
  doi = {10.1016/j.qref.2026.102156},
  url = {https://doi.org/10.1016/j.qref.2026.102156}
}

Abstract

This study investigates the impact of geographical indication (GI) certification on the export performance of Turkish agri-food products by analyzing both trade volume and unit value dynamics. Drawing on monthly data from 2000 to 2024 across 22 GI-certified products, the research employs product-level regressions, fixed-effects panel models with trait interactions, and Difference-in-Differences estimation with Goodman–Bacon decomposition. The results provide robust evidence that GI certification significantly improves export performance, with certified products showing substantial increases in both export volumes and unit prices. However, the effects are strongly heterogeneous across product types. The benefits in export volumes are concentrated in goods with high quality observability and product differentiation, while commoditized and storable products exhibit limited or even negative price responses. Furthermore, the study reveals that GI-labeled products demonstrate greater trade resilience during external shocks, such as the COVID-19 pandemic, by preserving price premiums despite temporary drops in export volume. These findings underscore that the effectiveness of GI schemes is contingent on product characteristics and market structures. The study contributes to the literature by offering a trait-based explanation of origin-labeling outcomes and provides strategic policy insights for enhancing GI effectiveness in emerging economies.

Sovbetov, I. & Ozdemir, M.B. (2026). Labeling Quality or Quantity? The Differential Impact of Geographical Indications on Export Performance in Turkish Agri-Food Products. Applied Economic Perspectives and Policy . https://doi.org/10.1002/aepp.70077

@article{sovbetov2026labeling,
  author = {Ihlas Sovbetov & Muge Burcu Ozdemir},
  title = {Labeling Quality or Quantity? The Differential Impact of Geographical Indications on Export Performance in Turkish Agri-Food Products},
  journal = {Applied Economic Perspectives and Policy},
  year = {2026},
  doi = {10.1002/aepp.70077},
  url = {https://doi.org/10.1002/aepp.70077}
}

Abstract

This paper examines the pricing of sin stocks across religious contexts using monthly data for 833 publicly listed firms from 1990 to 2025. Sin stocks—defined as firms involved in alcohol, tobacco, gambling, or military industries—are matched with sector-specific non-sin counterparts to isolate abnormal returns. The analysis finds that sin stocks consistently earn significant excess returns relative to both industry comparables and the market. The sin premium is strongest in the gambling and military sectors and is notably higher in countries with substantial Abrahamic religious presence, where moral restrictions on vice-related activities are more stringent. In contrast, the premium is weaker or even negative in atheist and non-Abrahamic settings. Fama–MacBeth cross-sectional regressions confirm that religious context significantly predicts sin stock return differentials, controlling for firm-level characteristics and broader cultural traits. These findings suggest that religion systematically shapes investor preferences and contributes to persistent mispricing. The study advances the literature on cultural finance, ethical investing, and the role of moral norms in asset pricing.

Sovbetov, I. (2026). Financial Price of Sin Stocks Across Religions. Journal of Business Ethics . Vol.204, pp.221-242. https://doi.org/10.1007/s10551-025-06072-z

@article{sovbetov2026financial,
  author = {Ihlas Sovbetov},
  title = {Financial Price of Sin Stocks Across Religions},
  journal = {Journal of Business Ethics},
  year = {2026},
  doi = {10.1007/s10551-025-06072-z},
  url = {https://doi.org/10.1007/s10551-025-06072-z}
}

Abstract

Decentralized finance (DeFi) lacks centralized oversight, often resulting in heightened volatility. In contrast, centralized finance (CeFi) offers a more stable environment with institutional safeguards. Institutional backing can play a stabilizing role in a hybrid structure (HyFi), enhancing transparency, governance, and market discipline. This study investigates whether HyFi-like cryptocurrencies, those backed by institutions, exhibit lower price risk than fully decentralized counterparts. Using daily data for 18 major cryptocurrencies from January 2020 to November 2024, we estimate panel EGLS models with fixed, random, and dynamic specifications. Results show that HyFi-like assets consistently experience lower price risk, with this effect intensifying during periods of elevated market volatility. The negative interaction between HyFi status and market-wide volatility confirms their stabilizing role. Conversely, greater decentralization is strongly associated with increased volatility, particularly during periods of market stress. Robustness checks using quantile regressions and pre-/post-Terra Luna subsamples reinforce these findings, with stronger effects observed in high-volatility quantiles and post-crisis conditions. These results highlight the importance of institutional architecture in enhancing the resilience of digital asset markets.

Sovbetov, I. (2025). Institutional Backing and Crypto Volatility: A Hybrid Framework for DeFi Stabilization. Computational Economics . https://doi.org/10.1007/s10614-025-11179-6

@article{sovbetov2025institutional,
  author = {Ihlas Sovbetov},
  title = {Institutional Backing and Crypto Volatility: A Hybrid Framework for DeFi Stabilization},
  journal = {Computational Economics},
  year = {2025},
  doi = {10.1007/s10614-025-11179-6},
  url = {https://doi.org/10.1007/s10614-025-11179-6}
}

Abstract

This study examines the financial price of reputational backlash against Israeli firms following the Gaza War on October 7, 2023. We develop a sentiment–trade interaction framework that integrates Google Trends hostility queries, GDELT media tone, and a composite sentiment index with Israel’s bilateral trade exposure. Using a panel of 516 Israeli listed firms, we estimate a triple-interaction model that separates direct war effects from reputational backlash transmitted through bilateral trade linkages. Results show that a one-standard-deviation rise in backlash erased one to two months of typical equity gains, with effects most pronounced in Muslim-majority countries. Sectoral regressions reveal severe penalties in industrials, financials, basic materials, energy, and consumer-facing sectors, while defense and technology were comparatively insulated. Firm-level heterogeneity highlights stronger losses among firms with high foreign institutional ownership, insider concentration, ESG risk, and leverage. A step-dummy approach confirms persistence, underscoring how moral backlash imposes market penalties absent formal sanctions.

Sovbetov, I. (2025). The Price of Backlash: Performance of Israeli Firms Post-Gaza War. Borsa Istanbul Review , Vol. 25, No. 6, pp. 1486-1506. https://doi.org/10.1016/j.bir.2025.10.006

@article{sovbetov2025the,
  author = {Ihlas Sovbetov},
  title = {The Price of Backlash: Performance of Israeli Firms Post-Gaza War},
  journal = {Borsa Istanbul Review},
  year = {2025},
  doi = {10.1016/j.bir.2025.10.006},
  url = {https://doi.org/10.1016/j.bir.2025.10.006}
}

Abstract

Using the hybrid New Keynesian Phillips Curve, this paper provides the first multi-country estimation for Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan using quarterly data from 1996 to 2023, and continuously-updating GMM. We estimate closed- and open-economy specifications with perfect and imperfect pass-through. Inflation combines substantial backward-looking inertia with a meaningful forward-looking component: persistence is strongest in Tajikistan and Turkmenistan, while Georgia and Armenia are the most forward-oriented, and Kazakhstan is balanced. In panel estimates the backward- and forward-looking weights are about 0.55 and 0.45. Cost slopes indicate that domestic real marginal costs dominate, but imported pressures are material, accounting for about 46% of cost slopes under perfect pass-through and 41% under imperfect pass-through, with external channels especially salient in Kyrgyzstan and Tajikistan. Structural parameters imply price resets roughly every two to two and a half quarters and a high yet incomplete exchange-rate pass-through near 0.87.

Sovbetov, I. (2025). The hybrid Phillips curve and inflation in post-Soviet Central Asia and the South Caucasus. Post-Communist Economies , Vol.37, No.8, pp.1149-1171. https://doi.org/10.1080/14631377.2025.2576203

@article{sovbetov2025the,
  author = {Ihlas Sovbetov},
  title = {The hybrid Phillips curve and inflation in post-Soviet Central Asia and the South Caucasus},
  journal = {Post-Communist Economies},
  year = {2025},
  doi = {10.1080/14631377.2025.2576203},
  url = {https://doi.org/10.1080/14631377.2025.2576203}
}

Abstract

Economic dynamics vary across business cycles, particularly in the relationship between output and unemployment. This study examines Okun’s Law across 92 countries from 1980 to 2023, focusing on its validity and stability during expansion, recession, and recovery. The results confirm that Okun’s Law broadly holds, but its strength is highly regime- and country-specific. A consistent pattern emerges: the Okun coefficient is steeper during recessions, flatter during expansions, and statistically weaker or insignificant during recoveries, consistent with jobless recoveries. Cross-country evidence further reveals that high-income and OECD economies exhibit robust Okun relationships across regimes, while many low-income economies display weak or non-significant responses due to informality and structural labor market rigidities. Dynamic specifications confirm short-run stickiness in employment, with cumulative effects reinforcing the asymmetric adjustment of unemployment to output. By introducing a three-regime empirical design and incorporating post-pandemic labor market dynamics, this study provides the most comprehensive cross-country assessment of Okun’s Law to date. The findings underscore the importance of regime-contingent policy strategies: countercyclical support during recessions, targeted incentives during recoveries, and structural reforms in economies with weak output–employment linkages.

Sovbetov, I. (2025). The dynamics of Okun’s law: cross-country analysis across economic cycles (1980–2023). Empirica , Vol.52, pp. 687–720. https://doi.org/10.1007/s10663-025-09662-2

@article{sovbetov2025the,
  author = {Ihlas Sovbetov},
  title = {The dynamics of Okun’s law: cross-country analysis across economic cycles (1980–2023)},
  journal = {Empirica},
  year = {2025},
  doi = {10.1007/s10663-025-09662-2},
  url = {https://doi.org/10.1007/s10663-025-09662-2}
}

Abstract

This study examines the impact of employee happiness on firm performance in the UK using data from the “Best 100 British Companies to Work For” list (2001–2020). Applying the Carhart four-factor model to monthly data, we find that happier firms outperform the market, generating a monthly alpha of 32 basis points (3.86% annualized), which increases further to 34 basis points when weighted by ranking. Newly listed firms experience significant abnormal returns, whereas delisted firms show no excess returns, suggesting asymmetric market reactions to inclusion versus removal. Disaggregated analysis by industry shows the highest alpha in the technology sector, where human capital and innovation amplify the role of employee satisfaction. The industrial sector yields more modest alphas, likely reflecting capital intensity, more rigid work environments, and sectoral heterogeneity. A longevity analysis indicates that the market fully incorporates the intangible benefits of listing only after 36 months. Robustness checks using Fama-MacBeth regressions confirm that employee-related factors—such as workplace conditions, rewards, happiness, and demographics—significantly influence firm performance.

Sovbetov, I. (2025). Does employee happiness create value for firm performance? Humanities & Social Sciences Communications , 12. https://doi.org/10.1057/s41599-025-05024-2

@article{sovbetov2025does,
  author = {Ihlas Sovbetov},
  title = {Does employee happiness create value for firm performance?},
  journal = {Humanities & Social Sciences Communications},
  year = {2025},
  doi = {10.1057/s41599-025-05024-2},
  url = {https://doi.org/10.1057/s41599-025-05024-2}
}

Abstract

This study offers a novel approach to analyzing environmental degradation in the context of international trade by applying an Environmental Gravity Model. Covering 166 countries over the period 2000 to 2022, the study examines the carbon footprint embodied in global fiber trade, focusing on the effects of trade value, trade weight, and trade distance on emissions. The findings reveal that synthetic fibers – such as polyester, acrylic, and polyamide – impose significantly higher environmental burdens due to their energy-intensive production processes and heightened sensitivity to trade-related factors. In contrast, natural fibers, including bamboo and hemp, exhibit lower embodied carbon footprints, although cotton, wool, and silk display notable emissions linked to production and long-distance transportation. The study highlights the need for targeted policy interventions to promote low-carbon technologies, optimize trade logistics, and encourage the use of sustainable natural fibers.

Sovbetov, I. (2025). Carbon Footprint Embodied in Global Fiber Trades. Journal of Natural Fibers , 22(1). https://doi.org/10.1080/15440478.2025.2503970

@article{sovbetov2025carbon,
  author = {Ihlas Sovbetov},
  title = {Carbon Footprint Embodied in Global Fiber Trades},
  journal = {Journal of Natural Fibers},
  year = {2025},
  doi = {10.1080/15440478.2025.2503970},
  url = {https://doi.org/10.1080/15440478.2025.2503970}
}

Abstract

Although empirical literature regarding the Phillips curve is sizeable enough, there is still no wide consensus on its validity and stability. The literature shows that the Phillips relationship is fragile and varies across countries and time periods; a statistical relationship that appears strong during one decade (country) may be weak the next (other). This variability might have some grounds for idiosyncrasy of a country and its economic environment. To address it, this paper scrutinizes the Phillips relationship over 41 countries over the period 1980-2016, paying attention to how inflation dynamics behave during tranquil and recessionary periods. As a result, the paper confirms the variability of the Phillips relationship across countries, as well as time periods. It documents that the relationship holds in the majority of developed countries, while it fails to hold in emerging and frontier economies during tranquil periods. On the other hand, the relationship totally collapses during recessionary periods, even in developed markets. This shows that tranquillity of economic environment is significantly important for the Phillip trade-off to work smoothly. Moreover, both backward- and forward-looking fractions of inflation remarkably increase during recessionary periods as a result of the Phillips coefficient loses its significance within the model. This indicates that markets become more inflation-sensitive during these periods.

Sovbetov, Y. & Kaplan, M. (2019). Causes of Failure of the Phillips Curve: Does Tranquillity of Economic Environment Matter? The European Journal of Applied Economics , 16(2), pp. 139-154. https://doi.org/10.5937/EJAE16-21569

@article{sovbetov2019causes,
  author = {Yhlas Sovbetov & Muhittin Kaplan},
  title = {Causes of Failure of the Phillips Curve: Does Tranquillity of Economic Environment Matter?},
  journal = {The European Journal of Applied Economics},
  year = {2019},
  doi = {10.5937/EJAE16-21569},
  url = {https://doi.org/10.5937/EJAE16-21569}
}

Abstract

The empirical literature provides mixed results on the relationship between inflation and unemployment; therefore, there is no consensus on validity and stability of the Phillips Curve. It also seems to be closely related with country-specific factors and the examination time periods. Considering the importance of this trade-off for policy-makers, this study aims to examine validity and stability of expectations-augmented Phillips Curve across 41 countries focusing on three different time periods between 1980 and 2016. The study documents several findings both in country-specific and in panel estimation analysis. First, we find that forward-looking characteristic of inflation picks up weight after 1990’s which indicates that inflation became more sensitive to the expected prices. Second, we observe that inflation in developed markets is more forward-looking comparing to emerging and frontier markets. This indicates that developed markets dear forward-looking price expectations more than other markets. Third, we find that that both forward- and backward-looking Phillips Curve fails to work in Brazil, Greece, Indonesia, Mexico, South Africa, Romania, and Turkey. We address it to their long history of high and volatile inflation.

Sovbetov, Y. & Kaplan, M. (2019). Empirical examination of the stability of Expectations–Augmented Phillips Curve for developing and developed countries. Theoretical and Applied Economics , 26 (2/619), pp. 63-78.

@article{sovbetov2019empirical,
  author = {Yhlas Sovbetov & Muhittin Kaplan},
  title = {Empirical examination of the stability of Expectations–Augmented Phillips Curve for developing and developed countries},
  journal = {Theoretical and Applied Economics},
  year = {2019},
}

Abstract

The empirical literature that covers Phillips Curve analysis during recessionary periods is notably scant. The Great Recession has rekindled a debate on the validity and stability of the Phillips Curve which is still ongoing. The basis for this debate is the observation that real activity dropped sharply without causing a drop in inflation. This paper carries out an empirical analysis for the classical expectation-augmented Phillips curve model across 41 countries from1980-2016 by distinguishing tranquil and recessionary periods separately. Based on the results of the research, the paper finds that dynamics of Phillips Curve changes during recessionary periods and the empirical relationship becomes no longer valid. These findings support the ongoing debate about the missing disinflation and collapse of the Phillips curve, but only during the recessionary periods. In the case of tranquil periods, the empirical relationship still seems to be valid. Moreover, the paper also observes that both backward-looking and forward-looking fractions of inflation gain weight and significance during recessionary periods. However, the paper remains indecisive about which exact fraction gains more weight and significance as the panel model does not incorporate these two fractions of inflation in a single hybrid framework simultaneously.

Sovbetov, Y. (2019). Phillips curve estimation during tranquil and recessionary periods: evidence from panel analysis. Istanbul Journal of Economics , 69(1), pp. 23-41. https://doi.org/10.26650/ISTJECON2019-0016

@article{sovbetov2019phillips,
  author = {Yhlas Sovbetov},
  title = {Phillips Curve Estimation during Tranquil and Recessionary Periods: Evidence from Panel Analysis},
  journal = {Istanbul Journal of Economics},
  year = {2019},
  doi = {10.26650/ISTJECON2019-0016},
  url = {https://doi.org/10.26650/ISTJECON2019-0016}
}

Abstract

This paper studies the macroeconomic impact of economic freedom on foreign direct investments inflows in both global and regional panel analyses involving 156 countries through the period of 1995-2016. Unlike to prior literature, it includes often neglected nations such as Fragile and Conflict-Affected states, Sub-Saharan, Oceanian, and Post-Soviet countries. The paper finds a positive impact of economic freedom on FDI under fixed-effects model in global case where a unit change in economic freedom scales FDI inflows up to 1.15 units. More specifically, all 9 regions also refer to positive and significant impact of economic freedom on FDI. The highest impact is recorded in European countries, whereas the lowest ones are documented in Fragile-Conflict affected states, Sub-Saharan zone, and Oceanian countries.

Sovbetov, Y. & Moussa, M. (2019). Interaction of Economic Freedom and Foreign Direct Investment Globally: Special Cases from Neglected Regions. Journal of Economics and Financial Analysis , 3(2), pp.113-134

@article{sovbetov2019interaction,
  author = {Yhlas Sovbetov, Mohamed Moussa},
  title = {Interaction of Economic Freedom and Foreign Direct Investment Globally: Special Cases from Neglected Regions},
  journal = {Journal of Economics and Financial Analysis},
  year = {2019},
}

Abstract

This paper examines factors that influence prices of most common five cryptocurrencies such as Bitcoin, Ethereum, Dash, Litecoin, and Monero over 2010-2018 using weekly data. The study employs ARDL technique and documents several findings. First, cryptomarket-related factors such as market beta, trading volume, and volatility appear to be significant determinant for all five cryptocurrencies both in short- and long-run. Second, attractiveness of cryptocurrencies also matters in terms of their price determination, but only in long-run. This indicates that formation (recognition) of the attractiveness of cryptocurrencies are subjected to time factor. In other words, it travels slowly within the market. Third, SP500 index seems to have weak positive long-run impact on Bitcoin, Ethereum, and Litcoin, while its sign turns to negative losing significance in short-run, except Bitcoin that generates an estimate of -0.20 at 10% significance level. Lastly, error-correction models for Bitcoin, Etherem, Dash, Litcoin, and Monero show that cointegrated series cannot drift too far apart, and converge to a long-run equilibrium at a speed of 23.68%, 12.76%, 10.20%, 22.91%, and 14.27% respectively.

Sovbetov, Y. (2018). Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litecoin, and Monero. Journal of Economics and Financial Analysis , 2(2), pp. 1-27.

@article{sovbetov2018factors,
  author = {Yhlas Sovbetov},
  title = {Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litecoin, and Monero},
  journal = {Journal of Economics and Financial Analysis},
  year = {2018},
}

Abstract

This paper investigates impact of e-economic activities on female employment rates in Turkey over 1994–2016. The analysis unveils three major findings. First, 80.74% of variations in female employment are accounted by e-commerce and control variables. Second, Autoregressive Distributed Lag analysis documents that these series (female employment, e-commerce and control variables) are cointegrated, thus, a unit increase in per credit card e-commerce transactions leads the female employment rate to grow by 0.13 units in long-run at 1% significance level, whereas a percentage increase in internet penetration rate in Turkey augments the rates by 0.33%. Third, error-correction model analysis refers that the system quickly corrects its previous period disequilibrium converging at a speed of 75.43%, and also documents that the lags of per credit card e-commerce jointly have short-run impact on female employment rates. Thus, the study concludes that developing e-commerce incentivizing policies might help to empower women in Turkey significantly.

Sovbetov, Y. (2018). Impact of Digital Economy on Female Employment: Evidence from Turkey. International Economic Journal , 32(2), pp. 256-270. https://doi.org/10.1080/10168737.2018.1478868

@article{sovbetov2018impact,
  author = {Yhlas Sovbetov},
  title = {Impact of Digital Economy on Female Employment: Evidence from Turkey},
  journal = {International Economic Journal},
  year = {2018},
  doi = {10.1080/10168737.2018.1478868},
  url = {https://doi.org/10.1080/10168737.2018.1478868}
}

Abstract

This paper investigates both short and long-run interaction between BIST-100 index and CDS prices over January 2008 to May 2015 using ARDL technique. The paper documents several findings. First, ARDL analysis shows that 1 TL increase in CDS shrinks BIST-100 index by 22.5 TL in short-run and 85.5 TL in long-run. Second, 1000 TL increase in BIST index price causes 25 TL and 44 TL reducation in Turkey's CDS prices in short- and long-run respectively. Third, a percentage increase in interest rate shrinks BIST index by 359 TL and a percentage increase in inflation rate scales CDS prices up to 13.34 TL both in long-run. In case of short-run, these impacts are limited with 231 TL and 5.73 TL respectively. Fourth, a kurush increase in TL/USD exchange rate leads 24.5 TL (short-run) and 78 TL (long-run) reductions in BIST, while it augments CDS prices by 2.5 TL (short-run) and 3 TL (long-run) respectively. Fifth, each negative political events decreases BIST by 237 TL in short-run and 538 TL in long-run, while it increases CDS prices by 33 TL in short-run and 89 TL in long-run. These findings imply the highly dollar indebted capital structure of Turkish firms, and overly sensitivity of financial markets to the uncertainties in political sphere. Finally, the paper provides evidence for that BIST and CDS with control variables drift too far apart, and converge to a long-run equilibrium at a moderate monthly speed.

Sovbetov, Y. & Saka, H. (2018). Does it take two to tango: Interaction between Credit Default Swaps and National Stock Indices. Journal of Economics and Financial Analysis , 2(1), pp.129-149

@article{sovbetov2018does,
  author = {Yhlas Sovbetov; Hami Saka},
  title = {Does it take two to tango: Interaction between Credit Default Swaps and National Stock Indices},
  journal = {Journal of Economics and Financial Analysis},
  year = {2018},
}

Abstract

This paper examines influences of brand dynamics on insurance premium productions in Turkey using a dynamic GMM panel estimation technique sampling 31 insurance firms over 2005-2015. The results reveals that brands trust appears as a chief driving force behind premium production where its unit increase augments premium outputs by 5.32 million Turkish Liras (TL). Moreover, the brand value of firms also appears a statistically significant determinant of premium sales, but its size impact remains limited comparing to brand trust, i.e. a million TL increase in brand value generates only 0.02 million TL increase in sales. On the other hand, the study also documents a strong momentum driven from past years premium production with trade-off magnitude of 1 to 0.85. This might imply a higher loyalty-stickiness of customers in Turkey, as well as a self-feeding "bandwagon effect".

Sovbetov, Y. (2016). Impact of Brand Dynamics on Insurance Premiums in Turkey. Turkish Economic Review , 3(3), pp.453-465.

@article{sovbetov2016impact,
  author = {Yhlas Sovbetov},
  title = {Impact of Brand Dynamics on Insurance Premiums in Turkey},
  journal = {Turkish Economic Review},
  year = {2016},
}

Abstract

This paper has two contributions to the International Financial Reporting Stands (IFRS) adoption literature. First is the scrutinizing impact of IFRS adoption on value relevance in the UK with TEST-A analysis under the H01 hypothesis. The second contribution is capturing the impact of IFRS adoption on key financial indicators of firms with the TEST-B analysis that hypothesizes H02.The statistical differences of items of two different reporting standards are examined with non-parametric tests as all input variables failed the Shapiro-Wilk and Lilliefors normality tests in TEST-A. The finding rejects the H01 hypothesis for BvMv, and agrees that IFRS has impact on value relevance. Besides, Ohlson’s (1995) model documents that the coefficient of dummy variable (MODE) is positive. Therefore, the analysis concludes that IFRS has positive impact on value relevance. The aftermath of TEST-B rejects the H02 hypothesis for all profitability ratios (ROE, ROCE, ROA, PM) and gearing ratios (GR). It concludes that profitability and gearing ratios are affected by IFRS adoption, whereas efficiency-liquidity ratios are not. Also, in Forward Stepwise regression analysis only ROCE, ROA, and PM ratios show significant results. The analysis documents positive and significant impact of IFRS on these three ratios.

Sovbetov, Y. (2015). How IFRS Affects Value Relevance and Key Financial Indicators? Evidence from the UK. International Review of Accounting, Banking and Finance . 7(1), pp. 73-96.

@article{sovbetov2015how,
  author = {Yhlas Sovbetov},
  title = {How IFRS Affects Value Relevance and Key Financial Indicators? Evidence from the UK},
  journal = {International Review of Accounting, Banking and Finance},
  year = {2015},
}