Structured finance products like securitization and project finance are critical for financing large-scale energy investments, but lack robust valuation models. We build on Leland's (2007) elegant financial synergy framework, expanding it to incorporate non-risk-neutral pricing, long-term debt contracts, varying macro conditions and firm lifecycles, and stochastic interest rates and cash flows. This allows examining correlation effects on liability/asset values. We then apply the enhanced model to optimize energy financing decisionsassessing mergers, securitization, and project finance given financial synergies under different market states, lifecycle stages, and parameter correlations. Preliminary analysis finds low cash flow/rate correlations and later lifecycle stages promote separate financing vehicles by enabling greater risk reduction, while high correlations and early stages favor on-balance sheet merger financing to maximize financial/operating synergies. Market conditions help determine optimal timing.

This paper investigates the transmission mechanisms of high policy rate volatility episodes in T & uuml;rkiye, characterized by sharp and unpredictable interest rate fluctuations. Focusing on the bank lending channel, we employ a time-varying parameter structural vector autoregression with stochastic volatility model to analyze the evolving impact of monetary policy on bank lending. Our analysis examines several key aspects: the relative effectiveness of a single, large policy rate change compared to a series of gradual adjustments; the potential non-linearity of transmission, investigating whether tight or lax monetary policy exhibits greater effectiveness; and the differential responses of rate-based conventional banks and profit-loss-sharing Islamic banks to monetary policy shocks. The key findings indicate that the effectiveness of the bank lending channel varies with the nature and magnitude of monetary policy shocks. Notably, episodes of substantial monetary tightening, especially when coupled with significant exchange rate depreciation, exert a more pronounced dampening effect on lending activity. Furthermore, Islamic banks are more sensitive to policy shocks, largely because of their distinct reliance on profit-sharing arrangements and liquidity-dependent funding models.

We develop a systemic risk indicator approach using a structural GARCH option- based default risk framework incorporating volatility clustering, variance risk premiums, along with distance-to-capital features. We apply our model to the U.S. banking sector, testing its explanatory and forecasting power. Our model successfully identifies the most systemically risky banks during heightened systemic-risk episodes. Comparing our results to related approaches, especially the respected indicator of the Federal Reserve Bank of Cleveland, we evidence markedly improved performance. Given the recent implosion of Silicon Valley Bank, exploring new approaches to constructing banking systemic risk indicators should be of great interest to regulators and policy makers.

We develop and estimate a consumption-based asset pricing model that uses historical US financial data and assumes recursive utility, allowing for priced regime-switching risk and intrinsic bubbles. We also estimate several restricted versions, including only a subset of these features. Priced regime-switching risk is essential to the equity risk premium, explaining more than fifty per cent of it. Furthermore, a model that does not consider regime switching would overestimate the public's risk aversion, mistakenly assigning the observed risk premium to high-risk aversion instead of priced regime-switching. We also find that intrinsic bubbles are statistically significant, and even though they are not crucial in explaining the risk premium, they substantially improve the model's fit at the end of the sample.

The paper highlights the encountered problems in implementing real options under more realistic assumptions such as business cycle risk and normally distributed cash flows. The problems considered include (i) estimating empirical distribution of cash flows from real option investments; (ii) investment decisions across business cycles, and (iii) calculating the probability of investing with the above stated rich features. To this end, we estimate operating cash flows of US corporate firms using a Markov chain model under both geometric and arithmetic Brownian motions assumptions for cash flows and develop a valuation model of real option with normally distributed cash flows. Associated investment valuation models incorporating these estimates reveal that critical cash flow levels significantly differ across models and regimes.

This study investigates the economic growth implications of ongoing and prospective rises in corporate tax rates following G20 countries’ minimum corporation tax agreement. We use a panel data estimation approach to examine economic growth rates and associated macro-economic variables of 42 nations from 1990 to 2017. To elicit more comprehensive insights, we make a distinction between advanced countries (ACs) and emerging market economies (EMEs) and different levels of growth using a quantile estimation approach. The results reveal that corporate tax rate rises depress growth, with a relatively sizeable impact for EMEs, whereas it is not statistically significant for ACs. At high quantiles of growth rates, the impact of the corporate tax policy on growth increases. These findings suggest a dual effect for EMEs with relatively high growth rates and symmetric growth effects of corporate tax changes, necessitating innovative policy prescriptions to address the negative growth impact of prospective higher corporate tax rates.

When faced with capital flow and credit growth waves in recent years, policymakers have relied upon macroprudential regulation. This paper sheds light on a relatively less-analyzed policy issue: how macroprudential regulatory measures mitigate extreme credit growth episodes. We use a dynamic panel data approach to estimate the impact of MaPPs on credit growth volatility and the likelihood of credit growth boom and bust episodes. We find that MaPPs reduce credit growth volatility in both advanced economies (AEs) and emerging market economies (EMEs). In addition, MaPPs help to prevent credit surges in EMEs and stops in AEs. Our results show that there is a strong link between net capital flows and credit growth stop episodes. Net capital flow surges trigger a credit surge for EMEs. This suggests that policymakers should consider both MaPPs and capital flow management measures when designing policies to mitigate the risks associated with these phenomena.

Default risk increases substantially during financial stress times due to mainly the two reasons: volatility clustering and investors' desire to protect themselves from such increases in volatility. It manifested in the aftermath of the Global Financial Crisis of 2008–2009 with unpleasant outcomes of many bankruptcies and severe financial distress. To account for these features, we adapted the structural credit risk approach to include both time-varying (return) volatility and risk premium about the return volatility itself. By applying the model to US banks, we obtain better bank default indicators in comparison to the benchmark models.

We explore the role of taxes on stimulating investment decisions for levered firms under cash flows and investment costs uncertainty using the adjusted present value-based real options approach developed by Myers and Read (2019). We extend their work to consider combined tax credits and uncertain investment costs. We then run a numerical analysis to quantify the impact of uncertainty, corporate tax and investment tax credit in stimulating investments.

We estimate default measures for US banks using a model capable of handling volatility clustering like those observed during the Global Financial Crisis (GFC). In order to account for the time variation in volatility, we adapted a GARCH option pricing model which extends the seminal structural approach of default by Merton (J Finance 29(2):449, 1974) and calculated "distance to default" indicators that respond to heightened market developments. With its richer volatility dynamics, our results better reflect higher expected default probabilities precipitated by the GFC. The diagnostics show that the model generally outperforms standard models of default and offers relatively good indicators in assessing bank failures.

With lessons learned from previous episodes as well as substantial improvements in economic policies and fundamentals over the years emerging market economies (EMEs) on average are better positioned to withstand financial turbulences, both now and in the near future, than in the past. Since their respective last financial crises most EMEs have been implementing more prudent policies, made stronger their governance frameworks and created financial safety nets as a buffer against adverse shocks. As a result, they were able to strengthen their stock and flow balances and policy frameworks, deepen local capital markets, and diversify their production and exports together with stronger global trade and financial linkages.

This paper investigates episodes of financial stress and its relationship to economic activity in some Southeast Asian economies. To that end, we use a dynamic factor model to construct a financial stress index for Indonesia, South Korea, Malaysia, the Philippines, and Thailand and examine the relationship between financial stress and economic activity. Our financial stress index consists of riskiness in the banking sector, security market risk, currency risk, external debt and sovereign risk. Empirical results indicate that our financial stress index tracks recessions closely in the sample and impulse response functions suggest financial stress causes significant economic slowdowns.

This short paper provides an introduction to the historical and theoretical aspects of macroprudential regulation in order to shed insight on effective macroprudentional policies. The section on macroprudential policies attempts to use this insight in the discussion of the state of play in macroprudential policy tools.Full publication: Macroprudential Policy

We analyse how the effectiveness of price-based and quantity-based macroprudential measures vary by the level of financial development, using panel data for 37 advanced and emerging market economies over 1996–2011. First, we find that quantity-based measures effectively smooth the variations in total credit growth but price-based measures do not. We then show that at almost all levels of financial development, quantity-based measures significantly moderate credit growth, while price-based measures are effective only when the level of financial development is above a threshold level above the median. Our results suggest that policymakers should take the level of financial development into account when they choose macroprudential tools.Full publication: Macroprudential Policy

This study examines episodes of financial stress and develops a financial stress index for the Turkish economy for the 1997–2010 period. We consider various variables that summarize different aspects of financial conditions in the economy to gauge financial stress. We construct the index and show that financial stress affects economic activity significantly. Specifically, the index is a leading indicator of economic activity in Turkey. We then discuss how information provided by the financial stress index can be used to fine tune macroeconomic policy.

We develop a model of regime-switching risk premia as well as regime-dependent factor risk premia to price real options. The model incorporates the observation that the underlying risky income streams of real options are subject to discrete shifts over time as well as random changes. The presence of discrete shifts is due to systematic and unsystematic risk associated with changes in business cycles or in economic policy regimes or events such as takeovers, major changes in business plans. We analyze the impact of regime-switching behavior on the valuation of projects and investment opportunities. We find that accounting for Markov switching risk results in a delay in the expected timing of the investment while the regime-specific factor risk premia make the possibility of a regime shift more pronounced.

This brief country case study on Turkey aims to summarize the fundamental developments in the banking sector, which represents almost 90 percent of the financial sector in the country. The brief has two parts. The first covers the 2001 financial crisis and the developments until end of 2007, the year before the global financial crisis of 2008 started. The second part focuses on the macro-prudential policies applied by the Central Bank of the Republic of Turkey in response to the global financial crisis in three phases: (i) full liquidity support after Lehman Brothers' collapse (September 2008), (ii) the exit strategy (April 2010), and (iii) the new policy mix (final quarter of 2010).

The paper discusses the currents that led to the 2007–2009 financial crisis. We discuss the crisis in a historical context and present evidence regarding the incidence and unit price of risk. Our results show that the unit price of risk prior to the subprime crisis is comparable to the price of risk prior to the great depression and similar to the price of risk at onset of the technology bubble. We then discuss global imbalances, the associated risks with regard to international optimal allocation of capital, and arrangements to minimize problems of global imbalances.