Selected Publications
Kallenos, T., Papakyriakou, P., Sakkas, A. & Taoushianis, Z. Tests of Global Flights to Safety With US Financial Firm Bankruptcy Announcements forthcoming at the European Financial Management. (Open Access)
This paper investigates whether bankruptcy announcements by large US financial institutions can induce flights to safety, leading investors to seek safer investments. To test this relationship, we employ a short‐horizon event study methodology and show that low‐risk investments—such as the US dollar, sovereign bonds and gold—exhibit significant appreciation following such announcements. This result is more pronounced when the local country‐level investor sentiment declines in the postannouncement period. We also analyze the transmission mechanism through which bankruptcy announcements cause flights to safety and empirically identify a global information contagion channel via negative shocks to the cash flows of stocks.
Rzayev, K., Sakkas, A. & Urquhart, A., 2025. An adoption model of cryptocurrencies. European Journal of Operational Research, 323(1), 253-266. SSRN version
The network effect, measured by users’ adoption, is considered an important driver of cryptocurrency market dynamics. This study examines the role of adoption timing in cryptocurrency markets by decomposing total adoption into two components: innovators (early adopters) and imitators (late adopters). We find that the innovators’ component is the primary driver of the association between user adoption and cryptocurrency returns, both in-sample and out-of-sample. Next, we show that innovators’ adoption improves price efficiency, while imitators’ adoption contributes to noisier prices. Furthermore, we demonstrate that the adoption model captures significant cryptocurrency market phenomena, such as herding behaviour, more effectively, making it better suited for forecasting models in cryptocurrency pricing. These results suggest that our methodology for linking early and late adopters to market dynamics can be applied to various domains, offering a framework for future research at the intersection of operational research and financial markets.
Sakkas, A. & Tessaromatis, N., 2022. Forecasting the Long-Term Equity Premium for Asset Allocation. Financial Analysts Journal, 78, 9-29.
Long-term country equity premium forecasts based on a cross-sectional global factor model (CS-GFM), where factors represent compensation for risks proxied by valuation and financial variables, are superior, statistically and economically, than forecasts based on time-series prediction models commonly used in academia and practice. CS-GFM equity premium forecasts produce significant utility gains compared to long-term asset allocation strategies based on eighteen commonly used prediction models, consistently across the US and eleven developed equity markets.
Li, Z., Sakkas, A. & Urquhart, A., 2022. Intraday time series momentum: Global evidence and links to market characteristics, Journal of Financial Markets, 57, 100619. SSRN version
We examine intraday time series momentum (ITSM) in an international setting by employing high-frequency data of 16 developed markets. We show that ITSM is economically sizable and statistically significant both in- and out-of-sample in most countries. Based on theories of investor behavior, we propose and test four hypotheses to reveal the source of ITSM profitability. We document both in the cross-section and time series dimension that ITSM is stronger when liquidity is low, volatility is high, and new information is discrete. Overall, our results suggest that the ITSM is driven by both market microstructure and behavioral factors.
Sakkas, A. & Tessaromatis, N., 2020. Factor based commodity investing. Journal of Banking & Finance, 115, 105807. SSRN version
A multi-factor commodity portfolio combining the momentum, basis, basis-momentum, hedging pressure and value commodity factor portfolios outperforms significantly, economically and statistically, widely used commodity benchmarks. We find evidence that a variance timing strategy applied to commodity factor portfolios generates timing gains for the commodity momentum factor but not the other commodity factors. Dynamic commodities strategies based on commodity factor return prediction models provide little value added.
Giamouridis, D., Sakkas, A. & Tessaromatis, N., 2017. Dynamic asset allocation with liabilities. European Financial Management, 23(2), pp.254-291. SSRN version
We develop an analytical solution to the dynamic multi-period portfolio choice problem of an investor with risky liabilities and time varying investment opportunities. We use the model to compare the asset allocation of investors who take liabilities into account, assuming time varying returns and a multi-period setting with the asset allocation of myopic ALM investors. In the absence of regulatory constraints on asset allocation weights, there are significant gains to investors who have access to a dynamic asset allocation model with liabilities. The gains are smaller under the typical funding ratio constraints faced by pension funds.
Angelidis, T., Sakkas, A. & Tessaromatis, N., 2015. Stock market dispersion, the business cycle and expected factor returns. Journal of Banking & Finance, 59, pp.265-279. SSRN version
We provide evidence using data from the G7 countries suggesting that return dispersion may serve as an economic state variable in that it reliably predicts time-variation in economic activity, market returns, the value and momentum premia and market volatility. A relatively high return dispersion predicts a deterioration in business conditions, a higher value premium, a smaller momentum premium and lower market returns. Dispersion based market and factor timing strategies outperform out-of-sample buy and hold strategies. The evidence are robust to alternative specifications of return dispersion and are not driven by US data. Return dispersion conveys incremental information relative to idiosyncratic risk.