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on Financial Markets |
| By: | Dominika Langenmayr; David Streich |
| Abstract: | We provide evidence that individuals use cryptocurrencies to channel funds into and out of tax havens. Exploiting the Panama Papers (2016) and Paradise Papers (2017) leaks as shocks to offshore detection risk, we compare prices of cryptocurrency–fiat pairs involving Singapore and Hong Kong dollars — the two haven currencies with sufficient trading data — to those involving non-haven currencies on the same exchanges. Prices denominated in haven currencies rise by approximately 10% relative to non-haven currencies following the leaks, consistent with increased demand for crypto originating in tax havens. Effects are concentrated on smaller, less liquid exchanges where arbitrage is constrained, and dissipate within two months, consistent with market efficiency and limits-to-arbitrage theory. These findings suggest cryptocurrencies serve as an alternative channel for capital flows that bypass conventional anti-money-laundering infrastructure. |
| Keywords: | tax havens, illicit financial flows, cryptocurrencies |
| JEL: | H26 G12 G14 F31 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12740 |
| By: | Andreas Fagereng; Luigi Guiso; Marius Ring |
| Abstract: | Using administrative panel data on Norwegian investors' portfolios, we document strong but slow portfolio allocation responses to a persistent wealth-tax-induced shock to the equity premium. Short-run responses resemble the modest sensitivity documented using surveys. The longer-run responses are much larger and can be rationalized by moderate risk aversion. We document that equity premium shocks affect stock market entry but not exits, suggesting that entry costs dominate participation costs. Our finding of slow responses supports the asset-pricing literature that uses adjustment frictions to explain important asset-pricing puzzles, and has implications for optimal capital taxation when tax rates differ across assets. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2533 |
| By: | Hördahl, Peter; Kısacıkoğlu, Burçin; Xia, Fan Dora |
| Abstract: | Bond yields react to macroeconomic surprises, but the magnitude of this responsiveness depends on macroeconomic forecast disagreement and monetary policy uncertainty. Using intraday responses of US Treasury futures to surprises in macroeconomic data releases, we find that greater forecast disagreement about an economic indicator prior to its release dampens the yield curve response, while higher monetary policy uncertainty amplifies it. An exception is inflation surprises: prior to the post-COVID inflation surge, bond yield reactions to inflation surprises were not amplified by short-rate uncertainty. We use a model with Bayesian learning to rationalize these findings. Specifically, large forecast disagreement indicates a weak link between the macroeconomic variable and future monetary policy, reducing the information value of macro news to forecast monetary policy. In contrast, during periods of high monetary policy uncertainty, macro news becomes more informative. Before the post-COVID inflation surge, investors may have perceived that the Federal Reserve placed little emphasis on its price stability mandate, which could have muted the yield curve response to inflation news even when short rate uncertainty was high. The proposed model generates distinct, empirically testable effects of disagreement and monetary policy uncertainty on yield responses which, when extended to allow time-varying signal precision, accounts for the post-COVID shift in inflation sensitivity within a single unified framework. |
| Keywords: | Macroeconomic news; Forecast dispersion; Policy uncertainty; Bond yields; Bayesian learning |
| JEL: | E43 E44 G14 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21501 |
| By: | Nicholas Appiah; Ali Jaffri; Dilmi C. W. Hettiachchi-Halpe-Kankanamalage; Svetlozar T. Rachev |
| Abstract: | This paper examines portfolio optimization for commodity exchange-traded funds (ETFs) under heavy-tailed return behavior. Using daily Bloomberg data for 30 U.S.-listed commodity ETFs from 12 December 2018 to 16 December 2024, we study funds spanning agriculture, energy, metals, and broad commodity index exposure. We compare a passive buy-and-hold portfolio with rolling-window optimized portfolios formed under mean--variance and conditional value-at-risk (CVaR) criteria, considering both long-only and restricted long--short strategies. The results showed substantial heterogeneity across commodity sectors, with energy and broad commodity index funds displaying pronounced volatility, skewness, and excess kurtosis. Historical optimization indicated that minimum-risk and CVaR-based portfolios provided more stable cumulative performance than tangent portfolios and generally improved Sharpe, Calmar, and STARR$_{0.95}$ ratios. Extreme-value diagnostics showed that optimized portfolios remained exposed to heavy downside tails, so improved risk-adjusted performance did not eliminate extreme-loss risk. A dynamic extension based on ARMA--GARCH marginal models, Student--$t$ copula dependence, and one-step-ahead predictive scenarios improved performance mainly when combined with minimum-risk or CVaR-based objectives. Dynamic mean--variance tangent portfolios performed less reliably, reflecting sensitivity to expected-return estimation error. Transaction-cost robustness checks further showed that the practical value of dynamic optimization depended on turnover control, with low-turnover dynamic CVaR tangent portfolios remaining more resilient to implementation costs. Overall, the analysis showed that commodity ETF allocation benefited most from conservative and downside-risk-aware optimization, while optimized portfolios continued to require explicit tail-risk and implementation diagnostics. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.26625 |
| By: | Tobias Lausser; Joao Eduardo Vuolo; Rudi Zagst |
| Abstract: | This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury market and bonds issued by the European Central Bank (ECB). To enhance predictive performance, macroeconomic variables are incorporated. The findings for both markets are separately analyzed and compared. To this end, we propose a robust model evaluation framework combining statistical accuracy metrics - such as RMSE, MAE, and directional accuracy - with the economic relevance of a quantitative bond trading strategy. Results show that NNs consistently outperform traditional models in both forecasting accuracy and portfolio performance. For the U.S., the most effective approach is a direct-forecasting NN that incorporates DNS factors to reduce the dimensionality of zero-rate data and an Autoencoder (AE) to extract macroeconomic features, while for Europe, the optimal model is a factor-based NN using PCA-derived zero-rate factors without the integration of macroeconomic variables. Overall, the paper demonstrates how combining traditional modeling approaches with modern ML techniques and evaluation can improve yield curve forecasts and support applications in fixed-income portfolio construction. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.26815 |
| By: | Broner, Fernando; Cortina, Juan J.; Schmukler, Sergio L.; Williams, Tomas |
| Abstract: | This paper examines how shifts in investor demand influence firm financing and investment decisions. For identification, the paper exploits a large-scale MSCI methodological reform that mechanically redefined the stock weights in major international equity benchmark indexes, changing the portfolio allocation of 2, 508 firms across 49 countries. Because benchmark-tracking investors closely follow these indexes, the rebalancing constituted a clean shock to equity demand. The results show that portfolio rebalancing by benchmark-tracking investors generated significant capital inflows and outflows at the firm level. Firms experiencing larger inflows increased equity issuance, even more so debt financing, and real investment. The paper complements the empirical analysis with a simple model of firm financing in which a decline in the cost of equity increases the value of equity and relaxes borrowing constraints. Higher equity valuations allow firms to expand borrowing even without issuing substantial new equity, so debt financing responds more strongly than equity issuance. |
| Keywords: | investment |
| JEL: | F33 G00 G01 G15 G21 G23 G31 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21311 |
| By: | Escobar, Mariana; Pandolfi, Lorenzo; Pedraza, Alvaro; Williams, Tomas |
| Abstract: | Benchmark index rebalancings are widely used to study non-fundamental demand shocks, but the underlying trading is rarely observed. Exploiting transaction-level data from the Colombian stock market and additions and deletions of stocks from MSCI international equity indexes, we trace who generates benchmark-driven demand, who absorbs it, and how it affects prices. Index demand extends beyond explicit index funds and ETFs: benchmarked but nominally active foreign institutions account for most rebalancing-driven trading. Domestic investors absorb most of the shock, while arbitrage capital plays only a limited role. We show that stock demand curves are steep, especially when retail participation is larger. |
| JEL: | F32 G11 G15 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21526 |
| By: | Zhou, Peng (Cardiff Business School, Cardiff University, Cardiff, UK); Ding, Wenjie (Business School, Sun Yat-sen University); Mazouz, Khelifa (Cardiff Business School, Cardiff University); Jin, Shijie (Cardiff Business School, Cardiff University) |
| Abstract: | Using bibliometric techniques, we classify green bonds literature into three main clusters: (i) asset-pricing research examining green bonds' connectedness with other assets; (ii) corporate-finance studies on the determinants of green bond issuance; and (iii) corporate-finance research on their environmental effects, such as carbon-emission reductions and renewable-energy deployment. Early studies primarily focused on pricing dynamics and market connectedness, whereas recent research emphasizes the intrinsic environmental value of green bonds, particularly their role in financing renewable-energy projects and supporting climate-policy objectives. This review integrates these strands into a unified energy-finance framework. On the theoretical side, we map green bond studies along a spectrum from instrumental to intrinsic value. On the methodological side, we synthesize the principal identification strategies used to address endogeneity, a challenge central to establishing credible links between green-bond financing and energy-transition outcomes. Building on these foundations, we set out a future research agenda that highlights underexplored issues concerning cross-market dynamics during energy crises, the effectiveness of green bonds in accelerating decarbonization, and the policy implications for energy-market regulators. Taken together, our findings provide a structured foundation for advancing research on green bonds within energy economics and climate finance. |
| Keywords: | Energy Transition; Green Bonds; Carbon Markets; Clean Energy Finance; Systematic Literature Review |
| JEL: | G00 G10 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:cdf:wpaper:2026/10 |
| By: | Latansa Izzata Dien Elam (C); Martina Nardon (Ca’ Foscari University of Venice) |
| Abstract: | Green bonds have become a key instrument for financing projects with environmental and climate-related benefits, amid the rapid growth of ESG investments across institutional, wealth, and retail investors. While the global green bond market has expanded substantially across both developed and emerging economies, evidence on how equity investors respond to green bond issuances in Asian markets remains limited. This paper examines stock market reactions to green bond announcements by publicly listed firms in Asia over the period 2014–2025. It combines a descriptive overview of green bond market development across major Asian economies with an event-study analysis based on the market model, used to estimate cumulative abnormal returns around announcement dates. The empirical analysis considers heterogeneity across countries, sectors, first-time and repeated issuances, developed and developing markets, sub-periods, and the pre- and post-COVID periods. The results show no statistically significant aggregate stock market reaction across alternative event windows. However, responses vary across countries and sectors, suggesting that equity investors may assess green bond announcements differently depending on the institutional context and the credibility or materiality of the underlying environmental commitment. Overall, the findings indicate that, in Asian equity markets, green bond issuance is generally perceived as a neutral financing decision rather than a systematic short-term value-creating event. The paper contributes by documenting the evolution of Asian green bond markets and by providing baseline empirical evidence on the equity-market implications of green bond announcements in the region. |
| Keywords: | Sustainable Finance, Green Bonds, Stock Market Reaction, Event Study, Asian Markets |
| JEL: | G14 G15 G23 Q56 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ven:wpaper:2026:19 |
| By: | Tuncer, Ali Coskun |
| Abstract: | Using a monthly security-level dataset, this paper reconstructs market size, composition, and equity returns for Alexandria, Cairo, and Istanbul. By 1913, equity capitalization reached 40% of GDP in Egypt but 14% in Ottoman Turkey. Growth came through new issuance rather than price appreciation, while risk-adjusted returns were low. Istanbul returns co-moved more strongly with London, reflecting foreign-incorporated mining and banking firms linked to international capital markets, while Egypt’s larger market was concentrated in land and mortgage finance tied to its cotton economy. The findings show that legal regimes governing foreign capital shaped how peripheral exchanges interacted with global financial markets. |
| Keywords: | Stock market capitalization |
| JEL: | N25 G15 F65 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21520 |