Oil prices affect Russian banks' stability, with negative impacts from decreases.
problem The impact of international oil prices on Russian public banks' financial stability.
method Data from 17 Russian public banks (2008-2016), Pool Mean Group (PMG) estimator.
result An increase in international oil prices and price to book value ratio positively affects Russian public banks' stability in the long run, while negative shocks have the opposite effect.
Develops hybrid method for efficient option pricing.
problem Stability and accuracy in option pricing models.
method Hybrid approach combining tree and finite-difference methods.
result Hybrid methods allow efficient and accurate European and American option pricing.
Crowded trades cluster investors, affecting stock price stability.
problem Crowded trades lead to price instability and systemic risk.
method Market clustering measure using granular trading data.
result Market clustering has a causal effect on stock return distribution tails, especially positive tail.
Analytic solutions found for a financial market model with traders.
problem Analyzing stability and price dynamics in a financial market model.
method Developed a continuous-time financial market model with two types of traders and proved stability conditions.
result Analytic formulae derived for price dynamics and trader profitability.
Algorithmic stablecoins optimize monetary policy to balance price stability.
problem Persistent inflation from centralized monetary policy.
method Propose and study a rule-based monetary policy model for algorithmic stablecoins.
result Optimal trade-off between price stability and supply stability.
The paper solves a stability issue in pricing derivatives using optimal Skorokhod embedding.
problem Optimizing the Skorokhod embedding problem for derivative pricing.
method Derives dualities and geometric characterizations, analyzes convergence rates.
result The optimization problem converges to an optimal Skorokhod embedding problem as more prices are given.
Cryptocurrencies' value tied to liquidity, not intrinsic, making stability uncertain.
problem Cryptocurrencies lack tangible value, leading to price instability.
method Examined using asset flow equations and experimental markets.
result Cryptocurrency prices are influenced by liquidity, not intrinsic value.
The paper examines fair pricing and hedging stability under small numéraire perturbations.
problem Fair pricing and hedging stability under numéraire perturbations.
method Reformulating the stochastic control problem to show stability and deriving asymptotic formulas.
result Fair price and hedging strategy are stable with small numéraire perturbations.
Proposes indifference pricing to estimate weak information value.
problem Estimating the value of weak information in financial models.
method Tractable framework quantifying additional information, stability analysis.
result Sharp conditions for stability with counterexamples, including replicable claims.
Paper addresses stability in multi-asset American option pricing.
problem Stability in multi-asset American option pricing problems.
method Semi-discretization approach followed by full discretization.
result Stability conditions found for numerical solution.
Study examines crypto-backed stable derivatives in DeFi, focusing on DAI.
problem Stability of crypto-backed stablecoins in DeFi.
method Introduced a belief parameter to simulate DAI, proposed a mathematical model, analyzed risk factors.
result Belief parameter improves simulation of DAI price stability.
Improved stable pricing for European options using Fourier-Cosine series.
problem Lack of robustness in the COS method for various cases.
method Stable pricing of call options based on Fourier cosine series expansion.
result Stability demonstrated through error analysis and numerical examples.
Cryptocurrencies show stable prices as a medium of exchange.
problem Price stability of cryptocurrencies as a medium of exchange.
method Filtered daily returns of major cryptocurrencies compared to major financial assets using Pearson correlations, dynamic time-warping method, and Black-Scholes model.
result Cryptocurrencies exhibit stable daily returns relative to major financial assets over the years 2016-2020.
We obtain stability estimates and derive analytic expansions for local solutions of multi-dimensional quadratic BSDEs. We apply these results to a financial model where the prices of risky assets are quoted by a representative dealer in such a way that it is optimal to meet an exogenous demand. We show that the prices …
Stability of the utility maximization problem with random endowment and indifference prices is studied for a sequence of financial markets in an incomplete Brownian setting. Our novelty lies in the nonequivalence of markets, in which the volatility of asset prices (as well as the drift) varies. Degeneracies arise from …
The Runge-Kutta-Legendre scheme improves pricing American options and other derivatives.
problem Pricing American options and other derivatives with improved accuracy and stability.
method Runge-Kutta-Legendre finite difference scheme applied to Black-Scholes and Heston models.
result Improved convergence and stability compared to existing schemes.
Efficiently calibrates Bergomi models to VIX derivatives using vector quantization.
problem Calibrating Bergomi models to VIX derivatives for accurate pricing.
method Applied vector quantization in mixed Bergomi models for fast and efficient option pricing.
result Calibration of Bergomi models to VIX derivatives is feasible and accurate over daily data.
Cryptocurrency stability modeled using dynamical systems theory.
problem Stability of cryptocurrencies in the absence of traditional financial metrics.
method Modeling cryptocurrency assets as asset flow equations and analyzing stability of resulting ordinary differential equations.
result Conditions for system stability identified, with trends and liquidity affecting stability.
We derive high-order compact finite difference schemes for option pricing in stochastic volatility models on non-uniform grids. The schemes are fourth-order accurate in space and second-order accurate in time for vanishing correlation. In our numerical study we obtain high-order numerical convergence also for non-zero …
Study shows increased volatility in Korean stock market after price limit change.
problem Effects of price limit change on market volatility.
method Analysis of intraday stock price data using realized variance and discrete Fourier transform.
result Market becomes more volatile after price limit increase, affecting liquidity providers.
The paper analyzes stability and asymptotic behavior of hedging strategies in binomial and trinomial models.
problem Stability and asymptotic analysis of hedging strategies in incomplete financial models.
method Discrete-time Föllmer-Schweizer decomposition, perturbation analysis, and asymptotic approximation.
result Explicit formulas for leading order correction terms in asymptotic analysis.
The paper solves a complex option pricing model using finite elements.
problem Risk-Adjusted Pricing Methodology (RAPM) Black-Scholes model with transaction costs.
method Spatial finite element models based on P1 and/or P2 elements, combined with a Crank-Nicolson-type temporal scheme.
result Results compare favorably with finite difference methods in the literature.
This paper analyzes a time-dependent CFMM called RMM-01, focusing on its pricing and stability.
problem Analyzing the pricing and stability of a time-dependent CFMM called RMM-01.
method Introducing the general framework for CFMMs, analyzing pricing properties, and examining time-varying price stability.
result Determining parameter bounds for RMM-01 to achieve a more stable price than Uniswap.
Consider Least Squares Monte Carlo (LSM) algorithm, which is proposed by Longstaff and Schwartz (2001) for pricing American style securities. This algorithm is based on the projection of the value of continuation onto a certain set of basis functions via the least squares problem. We analyze the stability of the algori…
Neural networks predict crude oil prices with promising accuracy.
problem Accurately predicting crude oil prices for economic and financial planning.
method Multivariate analysis using neural networks.
result Simple neural network models perform similarly to ARIMA models in forecasting crude oil prices.
Study stability of contingent claim solutions under probabilistic perturbations.
problem Stability of solutions to discrete-time contingent-claim problems under uncertainty.
method Use Rockafellian perturbations to analyze stability of solutions.
result Establishes convergence of dual problems and shadow prices.
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…
HyFi cryptocurrencies backed by institutions show lower price risk than fully decentralized ones.
problem High volatility in decentralized finance (DeFi) cryptocurrencies.
method Panel EGLS models with fixed, random, and dynamic specifications using daily data for 18 major cryptocurrencies.
result HyFi-like assets exhibit lower price risk, especially during market stress.
This paper investigates - on the basis of the Cont-Bouchaud model - whether a Tobin tax can stabilize foreign exchange markets. Compared to earlier studies, this paper explicitly recognizes that a transaction tax-induced reduction in market depth may increase the price responsiveness of a given order. We find that the …
Econometrics is based on the nonempiric notion of utility. Prices, dynamics, and market equilibria are supposed to be derived from utility. Utility is usually treated by economists as a price potential, other times utility rates are treated as Lagrangians. Assumptions of integrability of Lagrangians and dynamics are im…
The paper addresses utility maximization in markets with transaction costs, focusing on stability and optimal dual processes.
problem Utility maximization in markets with proportional transaction costs.
method Analysis of primal and dual value functions, study of optimal dual process, construction of limiting ODP.
result The optimal dual process defines a shadow price in the limiting market.
This paper improves bidding price prediction for ancillary services markets, boosting revenues.
problem Volatility in renewable energy sources affects grid stability and revenue optimization.
method Machine learning models (SVR, DT, k-NN) and offset adjustment for pay-as-bid markets.
result The proposed approach increases potential revenues by 27.43% to 37.31% compared to baseline models.
This paper analyzes stablecoins to address cryptocurrency volatility.
problem Cryptocurrency price volatility hinders adoption.
method Survey of 24 stablecoin projects, combined with monetary policy insights.
result Stablecoin designs often prioritize 1-to-1 stabilization, but literature suggests smoothing volatility is more sustainable.
A new algorithm reduces inference error in adaptive contextual bandits.
problem Challenges in statistical inference for adaptive contextual bandits.
method Proposes a regularized EXP4 algorithm that satisfies the Lai-Wei stability condition.
result Valid Wald-type confidence intervals for linear functionals can be achieved without the price of adaptivity.
We find a condition for stable asset pricing models.
problem Existence and uniqueness of equilibrium asset prices.
method Exact necessary and sufficient condition derived through stochastic discount factor decompositions.
result Sharpens and improves previous results on asset pricing.
Paper proposes a new stock price forecasting method using DRAGAN and feature matching.
problem Capturing correlations and training instability in GANs for stock price forecasting.
method Introduces DRAGAN and feature matching for improved training stability and correlation capture.
result Proposed method outperforms LSTM and basic GANs in stock price forecasting.
New analysis shows low volatility can be unstable in financial markets.
problem Understanding the relationship between volatility and market stability.
method Using mean first hitting time as a stability indicator and comparing to standard volatility measures.
result Low volatility can be associated with higher instability in financial markets.
Paper analyzes arbitrage in uncertain markets, providing quantitative asset pricing.
problem Dealing with model uncertainty in markets that allow small arbitrage.
method Quantitative analysis of arbitrage, focusing on asset price processes close to martingales.
result Quantitative version of the Fundamental Theorem of Asset Pricing and Super-Replication Theorem.
Cryptocurrency and NFT prices are highly correlated, mirroring historical bubbles.
problem Evaluating the wealth effect of cryptocurrency prices on real estate.
method Exploiting metaverse LAND and cryptocurrencies to track correlations and causality.
result Cryptocurrency prices Granger cause NFT LAND prices, similar to historical bubbles.
We study a phenomenological model for the continuous double auction, equivalent to two independent M/M/1 queues. The continuous double auction defines a continuous-time random walk for trade prices. The conditions for ergodicity of the auction are derived and, as a consequence, three possible regimes in the behavior …
DFMM automates market making with adaptive pricing and risk management.
problem Challenges in decentralised automated market making (AMMs).
method Data aggregator, order routing, rebalancing, arbitrageurs, protective buffers, algorithmic accounting.
result DFMM optimises inventory risk and ensures market stability.
In this paper a simple, effective adaptation of Alternating Direction Implicit (ADI) time discretization schemes is proposed for the numerical pricing of American-style options under the Heston model via a partial differential complementarity problem. The stability and convergence of the new methods are extensively inv…
Theory explains market crashes due to deleveraging and short sale constraints.
problem Market crashes caused by deleveraging and short sale restrictions.
method Developed a theoretical model of market dynamics involving two investor types.
result Short sellers can stabilize markets by providing supply or catching price drops.
Extends martingale transport for robust finance problems.
problem Addressing specific robust finance problems not covered by standard martingale transport.
method Introduces an additional parameter to the weak martingale optimal transport problem and proves stability.
result Stability of the extended problem with respect to risk-neutral marginal distributions.
Study analyzes price change patterns across different market capitalizations using Markov chains.
problem Understanding price dynamics in limit order markets across various market capitalizations.
method Discrete-time Markov chain analysis of intraday price changes in NASDAQ100 tick data.
result Systematic patterns in price inertia and stability across market capitalizations are identified.
Physics-Informed Neural Network improves option pricing accuracy.
problem Improving option pricing accuracy using machine learning.
method Physics-Informed Neural Network (PINN) applied to Black-Scholes equation.
result PINN model accurately captures option pricing behavior on both simulated and real market data.
Study shows how high-budget agents can manipulate prediction markets.
problem Manipulation of prediction markets by high-budget agents.
method Agent-based simulations and analytic characterization of price dynamics.
result High-budget agents can temporarily shift prediction market prices.
We present a model that investigates the spontaneous emergence of randomness in equity market microstructure. The phase space analysis of our model exposes an endogenous source of fluctuation in price and volume. We formulate a control problem for maximizing price regularity and stability while minimizing entanglement …