Regime-switching Model Research Articles

Investments, credit guarantees, and government subsidies in a regime-switching framework

Abstract This paper examines how credit guarantees and government subsidies impact investment in a regime-switching model. We provide new explicit pricing formulas for a general standard asset. Almost all common corporate securities’ prices can be easily derived by the explicit formulas though project cash flows are driven by both a Brownian motion and a two-state Markov chain. We provide a method about how governments should specify a proper tax subsidy standard for a given tax rate to motivate a firm to invest in a project in the way they wish. If the tax subsidy is sufficiently high (low), an overinvestment (underinvestment) occurs. The higher the tax rate, the more significant the overinvestment (underinvestment). We pin down the subsidy amount required for motivating a firm to invest immediately and fix the optimal capital structure with government subsidies.

The non-linear relationship between ESG performance and bank stability in the digital era: new evidence from a regime-switching approach

This study analyzes the effect of environmental, social, and governance (ESG) performance on banking stability in the digital era for a selected group of European banking institutions. Unlike many research, this paper incorporates the digital environment in which the European banking system operates into its investigation to capture the relationship between ESG scores, digitization, and bank stability from 2005 to 2022. This study uses a regime-switching model to investigate the non-linear hypothesis of the relationship, an aspect that has received insufficient attention in previous research. The empirical results confirm the non-linearity between ESG performance and banking stability in the digital era, identifying three ESG performance regimes. Moreover, higher ESG scores are associated with a lower risk of bank failure, aligning with stakeholder theory. Finally, European banks with weak ESG scores fail to avoid the fragility caused by investments in technological infrastructure. Overall, our results suggest that critics and proponents of banks’ commitment to social responsibility are, to some extent, right. Indeed, low or moderate ESG performance (Regimes 1 and 2) aligns with the classical perspective, while high ESG engagement (Regime 3) is consistent with the stakeholder view. Consequently, European banks need to adopt a digital strategy based on improving sustainability to leverage the positive impact of digitization and ESG performance on bank stability. On the policymakers’ side, they need to strengthen the legal infrastructure to support digitization and engagement in social responsibility activities.

Backtest overfitting in the machine learning era: A comparison of out-of-sample testing methods in a synthetic controlled environment

We present a comprehensive framework to assess these methods, considering the unique characteristics of financial data like non-stationarity, autocorrelation, and regime shifts. Through our analysis, we unveil the marked superiority of the Combinatorial Purged (CPCV) method in mitigating overfitting risks, outperforming traditional methods as evidenced by its lower Probability of Backtest Overfitting (PBO) and superior Deflated Sharpe Ratio (DSR) test statistic. Walk-Forward, by contrast, exhibits notable shortcomings in false discovery prevention, characterized by increased temporal variability and weaker stationarity. This contrasts with CPCV’s demonstrable stability and efficiency. We introduce novel variants of CPCV, including Bagged CPCV and Adaptive CPCV, which enhance robustness through ensemble approaches and dynamic adjustments based on market conditions. Our empirical validation using historical SP 500 data confirms these advanced cross-validation methods’ practical applicability and resilience. The analysis also suggests that choosing between Purged K-Fold and K-Fold necessitates caution due to their comparable performance and potential impact on the robustness of training data in out-of-sample testing. Our investigation utilizes a Synthetic Controlled Environment incorporating advanced models like the Heston Stochastic Volatility, Merton Jump Diffusion, and Drift-Burst Hypothesis alongside regime-switching models. This approach provides a nuanced simulation of market conditions, offering new insights into evaluating cross-validation techniques. We also address the computational aspects of these methods, demonstrating that parallelization significantly improves efficiency, making them feasible for large-scale financial datasets. Our study underscores the necessity of specialized validation methods in financial modeling, especially in the face of growing regulatory demands and complex market dynamics.

Asset prices, regime switches, and monetary policy: evidence from China

ABSTRACT This paper develops a regime-switching DSGE model that can capture time-varying volatilities in economic activity and monetary policy. The model is then used to study regime switches in macroeconomic dynamics and monetary policy in China. The results suggest a better fitness of the regime-switching model than conventional constant-parameter models. We also find notable differences in macroeconomic dynamics and monetary policy reactions between high and low volatility regimes. Further counterfactual analysis suggests that, at least in an environment with regime-switching volatilities, the optimal reaction of monetary policy involves responses to asset price variations. The findings of the paper shed new light on the regime-switching properties of the economy and the optimal choice of monetary policy within this context.

Effect of Market-Wide Investor Sentiment on South African Government Bond Indices of Varying Maturities under Changing Market Conditions

The excess levels of investor participation coupled with irrational behaviour in the South African bond market causes excess volatility, which in turn exposes investors to losses. Consequently, the study aims to examine the effect of market-wide investor sentiment on government bond index returns of varying maturities under changing market conditions. This study constructs a new market-wide investor sentiment index for South Africa and uses the two-state Markov regime-switching model for the sample period 2007/03 to 2024/01. The findings illustrate that the effect investor sentiment has on government bond indices returns of varying maturities is regime-specific and time-varying. For instance, the 1–3-year government index return and the over-12-year government bond index were negatively affected by investor sentiment in a bull market condition and not in a bear market condition. Moreover, the bullish market condition prevailed among the returns of selected government bond indices of varying maturities. The findings suggest that the government bond market is adaptive, as proposed by AMH, and contains alternating efficiencies. The study contributes to the emerging market literature, which is limited. That being said, it uses market-wide investor sentiment as a tool to make pronunciations on asset selection, portfolio formulation, and portfolio diversification, which assists in limiting investor losses. Moreover, the findings of the study contribute to settling the debate surrounding the efficiency of bond markets and the effect between market-wide sentiment and bond index returns in South Africa. That being said, it is nonlinear, which is a better modelled using nonlinear models and alternates with market conditions, making the government bond market adaptive.

A Dynamic Regime-Switching Model Using Gated Recurrent Straight-Through Units

A Dynamic Regime-Switching Model Using Gated Recurrent Straight-Through Units

A generalized approach for pricing american options under a regime-switching model

Abstract Regime-switching models gained their popularity over the past decade because of their distinctive advantage of modelling different financial market statuses in a discrete manner rather than a continuous manner as in stochastic volatility models. When they are used in option pricing, the clear advantage is that they enable a larger parameter space for models to be calibrated for a specific market dynamics and thus allow a better quantitative risk management in terms of utilizing financial derivatives. However, when they are used to price American-style financial derivatives, a large number of economic statuses result in a demand for improved computational efficiency. This paper provides a new algorithm of high computational efficiency supplemented with a theorem that pre-analyzes the associated matrices and their eigenvalues, without concern about the possibility of duplicated roots being mistakenly identified as simple roots due to rounding errors or the presence of two extremely closely positioned simple roots within the original system.

Optimal dividends and capital injection: A general Lévy model with extensions to regime-switching models

This paper studies a general Lévy process model of the bail-out optimal dividend problem with an exponential time horizon, and further extends it to the regime-switching model. We first show the optimality of a double barrier strategy in the single-regime setting with a concave terminal payoff function. This is then applied to show the optimality of a Markov-modulated double barrier strategy in the regime-switching model via contraction mapping arguments. We solve these for a general Lévy model with both positive and negative jumps, greatly generalizing the existing results on spectrally one-sided models.

Pricing a Defaultable Zero-Coupon Bond under Imperfect Information and Regime Switching

We propose a pricing formula for a defaultable zero-coupon bond with imperfect information under a regime switching model using a structural form of credit risk modelling. This paper provides explicit representations of risky debt under regime switching with a constant interest rate and risky debt under regime switching with a regime switching interest rate. While the value of the firm’s equity is observed continuously, we assume that the total value of the firm is only observed at discrete times, such as the dates of the release of the firm’s annual reports, or quarterly reports. This uncertainty about the true value of the firm results in credit spreads that do not approach zero as the debt approaches maturity, which is a problem with many structural models. The firm’s value is typically decomposed into its equity and debt; however, we consider the asset–to–equity ratio, an accounting ratio used to examine a firm’s financial well-being. The parameters in our model are regime switching, where the regime can be thought of as the state of the economy. A Markov chain with a constant transition rate matrix produces the regime switching.

Closed-Form Formula for the Conditional Moment-Generating Function Under a Regime-Switching, Nonlinear Drift CEV Process, with Applications to Option Pricing

An analytical derivation of the conditional moment-generating function (MGF) for a regime-switching nonlinear drift constant elasticity of variance process is established. The proposed model incorporates both regime-switching mechanisms and nonlinear drift components to better capture market phenomena such as volatility smiles and leverage effects. Regime-switching models can match the tendency of financial markets to often change their behavior abruptly and the phenomenon that the new behavior of financial variables often persists for several periods after such a change. Closed-form formulas for the MGF under various conditions, which are then applied for option pricing, are also derived. The efficacy and accuracy of the results are validated through a discrete Markov chain simulation. The results obtained from the proposed formulas completely match with those from MC simulations, while requiring significantly less computational time.

Beyond the glitter: An empirical assessment of the true risk and hedging role of precious metals

Precious metals are an essential component of asset class within the global financial market offering diverse benefits. Being significant store of value, they are immune to default risk, provide hedge against inflation and are deemed to be safe haven. This highlights the importance of precious metals in the broader context of financial and economic stability. This paper focuses on the S&P Precious Metal Index (PMI) to explore its resilience towards financial market risks and examines if it could offer effective hedge during crises. Using Markov Regime Switching model, we find significant volatility persistence in PMI returns undermining its suitability for dynamic hedging. However, absence of speculative trends makes the PMI a safe asset. Further, financial market stress, as revealed by estimated Component GARCH and Discrete Threshold Models, does not affect the unique and market risk of investing in PMI. Although we could not establish PMI as a strong safe haven or a zero-beta asset, its potential to be included in a risk-avert investor's portfolio cannot be negated. Its consistently low and stress-invariant time-varying beta safeguards wealth against losses. The role of PMI becomes particularly salient while considering portfolio optimization during crises. In recent years, particularly during and after the pandemic the hedging effectiveness of PMI has increased. There is, however, a point of concern. The market risk of PMI is explained mostly by its lagged values rather than exogenous factors like market stress. Given the endogenous nature of market risks, chaotic dynamics might be in operation making forecasting and regulating PMI prices difficult.

On measuring climate risks using attention search and testing the clean energy-climate hypothesis

ABSTRACT We measure physical and regulatory climate risks as innovations in several attention to climate change indexes that we construct using search volume data in Google Trends. The intention is to use the constructed risk indexes to test the empirical validity of the clean energy-climate hypothesis, which posits that clean energy prices fall (rise) following a drop (rise) in attention to climate risks. We test the empirical validity of this hypothesis at the macro (market level) using regime switching models and at the micro (firm level) using time-series regressions across clean energy sub-sectors. The macro analysis reveals that our hypothesis is only valid for climate pledges and physical climate risks. When attention to climate pledges drops or when physical climate risks are low, investors become reluctant to hold clean energy assets and vice-versa. Climate policy and climate solution risks have no impact on the nonlinear dynamic behaviour of clean energy prices. These results mean that investors and the public believe that climate policies lack credibility and climate solutions are not effective. The firm-level analysis confirms the findings of the macro analysis and reveals the heterogeneity of climate risks across clean energy sub-sectors.

A primal-dual active set approach to the valuation of American options in regime-switching models: numerical solutions and convergence analysis

A primal-dual active set approach to the valuation of American options in regime-switching models: numerical solutions and convergence analysis

ANALYSIS OF EXPORT-LED GROWTH MODEL FOR TÜRKİYE ECONOMY WITH MARKOV REGIME SWITCHING MODEL

Research on the export-led growth model is significant due to the contribution of exports to the development of domestic sectors and its positive impact on national values, especially employment and growth. Therefore, countries prefer the export-led growth model by increasing their export volumes with an outward-oriented policy. When Turkiye's growth figures are analyzed, it is feasible to say that there is a strong connection between exports and economic growth. In this study, within the framework of export-led growth hypotheses, the additive of exports to Turkiye's growth dynamics between 1980 and 2022 is investigated. The aim of the study is to econometrically test the intercourse between exports and GDP in the Turkiye economy. In the analysis, first linear unit root analyses were implemented. Then, the dynamic correlation relationship between exports and GDP was analyzed with DCC-GARCH, and the dynamic regression relationship was performed with the Markov regime switching model. As a consequence of the examines, it was seen that the dynamic correlation indicators and Markov model results were consistent with each other. While it was found that the correlation decreased during the high volatility period, a decrease in the number of regressions was observed according to the Markov model results.

Investor sentiments and performance of selected ESG indices in BRICS markets during bull and bear conditions

ABSTRACT Sustainability concerns are increasingly shaping global investment decisions, prioritising sustainable impacts over mere profit-making. This study examines the performance of Environmental, Social, and Governance (ESG) funds in emerging markets, focusing on bull and bear market scenarios. A Markov Regime Switching model was employed to analyse daily price data from BRICS (Brazil, Russia, India, China, and South Africa) ESG market indices spanning from 31 January 2011 to 2 January 2023. The analysis highlights the variability of ESG returns performance across different market conditions, emphasising the need for tailored investment strategies that account for market dynamics. Additionally, patterns in ESG returns and volatility are identified, along with pairwise relationships among ESG markets within the emerging markets bloc. The study also examines the influence of investor sentiments on ESG performance and controlled for the influence of macroeconomic factors on ESG performance amid changing market conditions. Finally, insights into transition probabilities between bullish and bearish market conditions offer guidance for more resilient investment portfolio management. This research contributes to advancing empirical knowledge on ESG investing in emerging markets, emphasising the significance of investor sentiments and market conditions for sustainable investment practices and long-term financial success.

A generalized integral equation formulation for pricing American options under regime-switching model

In this paper, we present a generalized and highly efficient integral equation formulation for the price of American put options under regime-switching model with a goal of improving computational efficiency in mind, particularly when the number of regimes is large. Our achieved high efficiency is based on a newly proved theorem, which facilitates the decoupling of a system with simultaneously coupled PDEs so that they can be solved recursively at the numerical solution stage. Such a high efficiency is also fueled further by that the integral equation approach being characterized with its excellent trade off between maximizing analytical tractability and minimizing numerical discretization. Upon providing some numerical examples to demonstrate the implementation of the new approach and its efficiency, we anticipate that the very same theorem can be used to reduce the computational burden if other numerical approaches are adopted, for this highly challenging nonlinear problem.

Crises and Contagion in Equity Portfolios

We examine the international impact of recent financial crises on contagion dynamics within international equity portfolios. First, we highlight the importance of macroeconomics for portfolio weighting for each region, and then we examine contagion via a structural regime-switching model and a contagion test. We also examine sources of contagion using regime variables, crisis events, and macroeconomic variables. In particular, we study the Argentine debt crisis, the US financial crisis, and the EU sovereign debt crisis. The macroeconomic variables include changes in market capitalization, trade integration, GDP growth, inflation rate, and interest rate. We also employ two classifications, one relating to the portfolio weighting scheme and another one that considers implied global and regional betas. The empirical findings reveal the existence of financial contagion for all the crises that we investigate. Both methods produce similar results. Stronger contagion is evident for global rather than regional betas. Europe is the region with the highest level of contagion and the one mostly affected by the crises. As far as macroeconomic variables are concerned, they are very important in two ways. They statistically significantly explain contagion, while they also reveal contagion under various portfolio weighting schemes. Both methods suggest that the Argentinian crisis mainly contributes to contagion. The research implications suggest that asset allocation and portfolio management should consider both the global and the regional aspects of contagion as differences can occur.

Does Regime-Dependent Volatility Drive Dynamism in Investor Herding?

The existing literature on herding often uses the static model to test herd behaviour in the Indian market context. Hence, the objective of this paper is to investigate the dynamic herd behaviour for S&P BSE 500 from 2009-2023 using the Markov Regime Switching model. Results exhibit the occurrence of three regimes, namely, high, low, and extremely volatile regimes. Findings suggest that the Indian market moves into the order of low, high, and extreme volatility (LHC), similar to other developed countries. This has implications for investors to either exit from the market or reframe their portfolio through hedging techniques before the market enters into extreme volatility. Moreover, the results exhibit anti-herding in high and low-volatile regimes. Our study discloses the presence of herding in crashes or extremely volatile regimes, showing that Indian investors start following each other during crash-like situations. This research is significant for individual investors, portfolio managers, and stock market regulators.

Environmental effects of waste electrical and electronic equipment valorization in burkina faso

The valorization of waste electrical and electronic equipment (WEEE) has become a challenge for countries around the world, especially for developing countries like Burkina Faso. The main objective of this article is to analyze the environmental effects of WEEE valorization in Burkina Faso. To do this, the regime-switching model, developed by Lee (1978), based on the Heckman correction model, was used. The data used was collected from 414 actors in the WEEE sector in the three major cities of Burkina Faso, Ouagadougou, Koudougou, and Bobo Dioulasso. The analysis of the results shows that the methods of WEEE valorization in Burkina Faso pollute the air, soil and water. This pollution results in damages amounting to 242,752,192.6 CFA francs per year, which the sector's actors should include in their investment costs in the form of internalization costs. These costs amount to an average of 560,628.62 CFA francs per year and per actor. The WEEE sector could be improved with the implementation of certain economic policies. These policies include raising awareness among the population on WEEE management, training of stakeholders in the sector on the effective valorization of WEEE and the implementation of strict environmental standards to reduce environmental pollution due to poor WEEE valorization in Burkina Faso.

Energy transition dynamics amid policy uncertainty, environmental regulations, and Geopolitics: Evidence from China

The time-varying dynamics of the transition to renewable energy reflect the effectiveness and efficiency of energy policy. This paper investigates renewable energy transition behavior in China using Markov regime-switching models. Two distinct phases, expansion and contraction, are identified based on the growth rates of renewable energy consumption share. We find that since China started its new-energy national strategy in 2005, there has been an extended period in which it has been in the expansion state, although it occasionally reverts to a contraction state. Intriguingly, we uncover that the timing of transition state changes can be explained by the changes in policy-related, market-based instruments and risk-related indexes. These findings present implications for policymakers in developing more precise and effective policies, that drives investment choices to align with the goal of a sustainable energy system.