A hybrid approach detects financial market regime switches using PCA and k-means.
problem Detecting regime switches in financial markets for trend forecasting.
method Dimensionality reduction with PCA and clustering with k-means.
result Trading strategies based on detected regimes show improved performance.
Optimal futures trading strategy in a changing market model.
problem Dynamic trading in a regime-switching market.
method Utility maximization approach with HJB equations reduced to linear ODEs.
result Optimal futures positions and portfolio value across market regimes.
Model predicts risk-adjusted returns across various financial markets.
problem Stationary models fail in predicting risk-adjusted returns due to market regime changes.
method Asset-independent regime-switching model using hidden Markov models.
result Accurately detects bull, bear, and high volatility periods for improved risk-adjusted returns.
The article detects market regimes from covariance matrices using VLSTAR and clustering models.
problem Market regime switching is hard to detect due to time-varying correlation coefficients.
method The article applies VLSTAR and unsupervised hierarchical clustering on monthly realized covariance matrices.
result VLSTAR outperforms clustering in detecting market regimes.
This work models market regimes using CTMSTOU and simulates trading policies.
problem Defining and understanding market regimes in finance.
method Discrete event time multi-agent market simulation with CTMSTOU model.
result Illustrates the importance of regime-awareness in trading policies.
Investigates JM for reducing downside risk in market regimes.
problem Mitigating downside risk during market downturns.
method Statistical jump model for identifying market regimes, optimizing penalty for state transitions.
result JM-guided strategies outperform traditional models in reducing risk and enhancing returns.
Researchers adaptively analyze market regimes to reveal investor behavior shifts.
problem Market relationships shift across different regimes, affecting investor behavior.
method Combining Kalman filtering, Markov-switching, and asymmetric response estimation.
result Foreign investors' predictive power increases during crises, while individual investors react more strongly to positive shocks.
Investigates optimal portfolio selection with regime-switching-induced stock price shocks.
problem Mean-variance portfolio selection with regime-switching and stock price jumps.
method Modeling regime-switching and stock price jumps, deriving optimal portfolio strategy and efficient frontier using ODEs.
result Added complexity due to regime-switching-induced stock price shocks, leading to nonlinear ODEs.
This paper compares hedging strategies for pegged FX markets using a RS model.
problem Hedging performance in pegged foreign exchange markets.
method Regime switching model, Fourier approach for calibration, exact and approximated delta hedging.
result Approximated RS delta hedge is a viable alternative to the exact RS delta hedge and significantly faster.
We consider option pricing in a regime-switching diffusion market. As the market is incomplete, there is no unique price for a derivative. We apply the good-deal pricing bounds idea to obtain ranges for the price of a derivative. As an illustration, we calculate the good-deal pricing bounds for a European call option a…
We study a portfolio selection problem in a continuous-time Itô-Markov additive market with prices of financial assets described by Markov additive processes which combine Lévy processes and regime switching models. Thus the model takes into account two sources of risk: the jump diffusion risk and the regime switching …
Optimized portfolio management with dynamic market regimes using RL and OC learning.
problem Mean-Variance portfolio optimization in a regime-switching market.
method Reinforcement learning (RL) with Orthogonality Condition (OC) learning for regime-switching market dynamics.
result OC learning outperforms TD learning in simulated and real market scenarios, leading to better portfolio performance.
The study uses State Switching Markov Autoregressive models to identify and predict market regimes.
problem Adapting to abrupt changes in financial markets and identifying stable investment strategies.
method State Switching Markov Autoregressive models and Wyckoff Price Regimes.
result A dynamically adaptive trading system that outperforms traditional alphas.
A new method for pricing European options in changing market conditions.
problem Lack of closed-form solutions for pricing European options in regime-switching models.
method Physics-informed residual learning (PIRL) for efficient option pricing.
result PIRL eliminates the need for retraining and offers near-instantaneous pricing.
Optimal credit and consumption strategies in a switching market with default contagion.
problem Optimal portfolio and consumption decisions in a credit market with default contagion.
method Cobb-Douglas utility, recursive ODE system, backward solution from all-default state.
result Existence and uniqueness of optimal feedback controls, verification theorem.
Study optimal portfolios in a non-Markovian regime-switching model with random time horizon.
problem Optimal portfolio selection in a market with non-Markovian regime-switching and random time horizon.
method Formulated as a constrained stochastic linear-quadratic optimal control problem, derived closed-form expressions for optimal portfolios and efficient frontier.
result Closed-form expressions for optimal portfolios and efficient frontier derived under non-Markovian regime-switching and random time horizon.
A new network learns market conditions and predicts stock performance.
problem Optimizing stock portfolio performance in the US equities market.
method Residual Switching Network combining two ResNets: a switching module and a main module.
result The residual switching network strategy outperformed other models with an average annual Sharpe ratio of 2.22.
Study improves S&P 500 volatility forecasting through regime-switching methods.
problem Accurate prediction of S&P 500 volatility for risk management and investment.
method Regime-switching methods including soft Markov switching, spectral clustering, and coefficient-based clustering.
result Coefficient-based clustering algorithm outperformed other models during all time periods.
Model interest rates and energy futures with regime-switching dynamics.
problem Modeling interest rates and energy futures with regime-switching dynamics.
method HJM model with Markov-chain modulated forward rates, proving affine structure for term structure.
result Explicit solutions for forward curves in many cases.
Solves new quadratic BSDE systems for market performance analysis.
problem Characterizing forward performance processes in regime switching markets.
method Introduces and solves ergodic BSDE systems in infinite time horizon.
result Connection between ergodic BSDE solutions and long-term growth rates of utility maximization.
This project attempts to address the problem of asset pricing in a financial market, where the interest rates and volatilities exhibit regime switching. This is an extension of the Black-Scholes model. Studies of Markov-modulated regime switching models have been well-documented. This project extends that notion to a c…
Study strategic competition in commodity markets using impulse-switching controls.
problem Strategic competition between upstream and downstream firms in commodity markets.
method Non-zero-sum stochastic differential game with mixed impulse/switching controls.
result Multiple Nash equilibria found, depending on the number of switches by the downstream firm.
Study optimal investment and reinsurance for insurance companies in a dynamic market model.
problem Optimal investment and reinsurance strategies for insurance companies in a regime-switching market model.
method Forward dynamic exponential utility, value function construction, proportional reinsurance optimization.
result Characterization of optimal investment strategy and proportional reinsurance level.
This study compares VaR-based portfolio insurance with CPPI in a regime-switching market.
problem Designing dynamic portfolio insurance strategies in a market with multiple regimes.
method Extends VaR-based portfolio insurance to a Markov-modulated regime-switching market, comparing it to CPPI.
result CPPI strategy generally offers better risk-return tradeoff and stability.
Model shows stock markets can be inefficiently mispriced.
problem Limits of informationally efficient stock markets.
method Chartist-fundamentalist model with chartists and fundamentalists trading conditions.
result Stock markets can exhibit constant or oscillatory mispricing.
This paper proposes a multi-scale Markov-Switching GARCH model for EUR/USD volatility.
problem Non-stationary financial volatility requires models that capture changing market conditions across multiple timescales.
method Triple-timeframe Markov-Switching GARCH (MS-GARCH) framework with AR(1)-MS-GARCH models and TVTP for short horizons.
result The proposed model produces statistically distinct regimes and superior volatility forecasting performance.
This paper studies the optimal VIX futures trading problems under a regime-switching model. We consider the VIX as mean reversion dynamics with dependence on the regime that switches among a finite number of states. For the trading strategies, we analyze the timings and sequences of the investor's market participation,…
Combines dynamic programming and neural networks for optimal portfolio execution in regime-switching markets.
problem Optimal execution in a market with multiple regimes and non-linear impact costs.
method Four-step numerical framework: approximated orthogonal portfolios, dynamic program for schedule, neural network optimization.
result Neural network optimized strategy outperforms traditional methods in both CRRA and mean-variance objectives.
The rBergomi model is improved with a regime switching change of measure to match market VIX smiles.
problem The rBergomi model produces flat VIX smiles, not matching market observations.
method A regime switching stochastic change of measure is applied to the rBergomi model, using an inhomogeneous fractional Ornstein-Uhlenbeck equation and an efficient Monte Carlo method.
result The model produces upward sloping VIX smiles, aligning with market observations.
Novel method recovers market regime changes from option prices.
problem Recovering market regime changes from option prices.
method Assumed Markov regime switching, computed implied volatility, validated recovery of regime changes.
result Implied volatility time series can recover market regime changes.
Study optimal consumption and investment strategies with constraints in a market with random coefficients.
problem Optimal consumption and investment strategies with constraints in a regime switching market with random coefficients.
method Explicit optimal strategies provided via solutions to new BSDE systems.
result Solving new BSDEs to find optimal values and strategies.
Paper optimizes insurer's investment strategy in a fluctuating market with memory effects.
problem Optimizing insurer's investment in a market with regime switching and noisy memory.
method Formulated as a stochastic differential delay game, solved using BSDE approach.
result Derives analytical solutions for a specific case of a quadratic penalty function.
We pick up the regime switching model for asset returns introduced by Rogers and Zhang. The calibration involves various markets including implied volatility in order to gain additional predictive power. We focus on the calculation of risk measures by Fourier methods that have successfully been applied to option pricin…
Study indifference pricing for insurance policies in a regime-switching market model.
problem Indifference pricing of pure endowment policies in a stochastic-factor model with different economic regimes.
method Stochastic control approach based on Hamilton-Jacobi-Bellman equation, Feynman-Kac formula, and sensitivity analysis.
result Characterization of indifference price as a solution to a linear PDE and a backward PDE.
Optimizes control of hybrid systems with multiple switching processes.
problem Optimal control of hybrid systems with multiple Markov switching processes.
method Combines two separate Markov chains into one synthetic chain, derives HJB equations, and solves the portfolio choice problem.
result Derives explicit solutions and value functions for the optimal control problem.
The Financial Chaos Index models stock market volatility across three regimes based on mutual price fluctuations.
problem Capturing regime-dependent volatility in stock markets.
method Developed a regime-switching framework using the Financial Chaos Index (FCIX) and elastic net regression.
result Identified three market regimes: low-chaos, intermediate-chaos, and high-chaos, each with distinct volatility characteristics.
Model predicts stock returns from CDS spreads, useful for trading.
problem Predicting stock returns from market sentiment.
method Simple model with regime switching, analytically tractable.
result Extracts expected returns from CDS spreads, useful for statistical arbitrage.
Study on stock trading model with uncertain market status, proving free boundaries and optimal strategies.
problem Optimal trading strategies in a stock market with uncertain market status.
method Free boundary problem, variational inequality system, degenerate operator, C^∞-smoothness.
result All four switching free boundaries are no-overlapping, monotonic, and C^∞-smooth, and their relative localities are completely determined.
CapOptix uses options theory to price capacity in electricity markets.
problem Traditional capacity market designs fail to account for risk and price shocks.
method Interprets capacity commitments as reliability options and uses Markov Regime Switching Process.
result CapOptix provides more accurate pricing of capacity premia compared to existing mechanisms.
Study improves stock return prediction by switching between economic states, outperforming traditional methods.
problem Improving stock return prediction across economic regimes.
method State-switching specification using the slope of the yield curve, with an Aligned Economic Index.
result The Aligned Economic Index outperforms traditional predictors, especially during market turbulence.
The article uses dynamic factor allocation to improve portfolio performance by integrating regime-switching signals.
problem Improving portfolio performance through dynamic factor allocation.
method The authors apply the sparse jump model (SJM) to identify bull and bear market regimes for individual factors, then fine-tune hyperparameters using a hypothetical single-factor long-short strategy. These regime inferences are incorporated into the Black-Litterman framework to dynamically adjust allocations among indices.
result The constructed multi-factor portfolio significantly improves the information ratio (IR) relative to the market, raising it from 0.05 to approximately 0.4.
HireVAE adapts to market regimes for online stock prediction.
problem Building an online and adaptive factor model for stock prediction.
method HireVAE uses a hierarchical latent space to estimate latent factors from historical market information.
result HireVAE outperforms previous methods in active returns across benchmarks.
Quantum algorithms for financial derivatives and credit risk.
problem Estimating credit risk and option pricing in realistic financial models.
method Developed a regime switching volatility model for financial markets, using a Markov chain to determine volatility parameters.
result Quantum algorithms can be applied to realistic financial models, bringing quantum computing closer to practical applications.
Paper solves complex game theory problems with new equations.
problem Zero-sum stochastic games with non-Markovian switching.
method New multidimensional SRE and BSDE solutions.
result Existence and uniqueness of SRE solutions.
In this paper analytic formulas for electricity derivatives are calculated. To this end, we assume that electricity spot prices follow a 3-regime Markov regime-switching model with independent spikes and drops and periodic transition matrix. Since the classical derivatives pricing methodology cannot be used in case of …
In this paper we treat a gas storage valuation problem as a Markov Decision Process. As opposed to existing literature we model the gas price process as a regime-switching model. Such a model has shown to fit market data quite well in Chen and Forsyth (2010). Before we apply a numerical algorithm to solve the problem, …
Robots' agility in changing terrain helps financial models adapt to market shifts.
problem Challenges in financial market forecasting due to regime switching.
method Adapts pretrained LLMs using intrinsic market rewards and reinforcement learning.
result Significantly improved accuracy in adapting to market regime shifts.
In this paper we discuss the optimal liquidation over a finite time horizon until the exit time. The drift and diffusion terms of the asset price are general functions depending on all variables including control and market regime. There is also a local nonlinear transaction cost associated to the liquidation. The mode…