The paper compares traditional and state-space methods for analyzing foreign exchange risk premia.
problem Analyzing the existence and time-evolving property of foreign exchange risk premia.
method Examines foreign exchange risk premia from simple univariate regressions to state-space methods.
result State-space estimations are more effective in examining the time variability of unobservable risk premia.
Extended PELCoV for bivariate Student-t copulas to monitor foreign exchange risk.
problem Monitoring financial risk under asymmetric co-movements and tail dependence.
method Extending PELCoV to Student-t copulas, tracking dynamic risk spillovers.
result Potential to detect early signs of risk underestimation during financial stress.
The team predicts foreign exchange rates using clustering and attention models.
problem Complexity and unexpected events in foreign exchange markets.
method Clustering and attention models applied to historical data.
result Improved event-driven price prediction for oversold scenarios.
The currency carry trade is the investment strategy that involves selling low interest rate currencies in order to purchase higher interest rate currencies, thus profiting from the interest rate differentials. This is a well known financial puzzle to explain, since assuming foreign exchange risk is uninhibited and the …
This study examines how market makers balance risk and impact in foreign exchange markets.
problem Balancing risk management with market impact in foreign exchange markets.
method An intermediate scenario approach considering both instantaneous and permanent market impact components.
result Transient market impact is more prevalent than previously thought, challenging traditional market impact models.
Quantum computers can optimize foreign exchange reserves management.
problem Optimizing foreign exchange reserves management using quantum computing.
method Demonstrated through quantum Monte Carlo risk measurement and quantum algorithms for portfolio optimization.
result Quantum computers can theoretically optimize FX reserves management in the future.
The geometric Lévy model (GLM) is a natural generalisation of the geometric Brownian motion model (GBM) used in the derivation of the Black-Scholes formula. The theory of such models simplifies considerably if one takes a pricing kernel approach. In one dimension, once the underlying Lévy process has been specified, th…
In this article, we investigate whether exchange rate risk is priced. We use a multivariate GARCH-in-Mean specification and test alternative conditional international CAPM versions. Our results support strongly the international asset-pricing model that includes exchange rate risk for both developed and emerging stock …
Currency carry trade is the investment strategy that involves selling low interest rate currencies in order to purchase higher interest rate currencies, thus profiting from the interest rate differentials. This is a well known financial puzzle to explain, since assuming foreign exchange risk is uninhibited and the mark…
Using a Levy process we generalize formulas in Bo et al.(2010) for the Esscher transform parameters for the log-normal distribution which ensure the martingale condition holds for the discounted foreign exchange rate. Using these values of the parameters we find a risk-neural measure and provide new formulas for the di…
The aim of this paper is to determine the Value at Risk (VaR) of the portfolio consisting of long positions in foreign currencies on an emerging market. Basing on empirical data we restrict ourselves to the case when the tail parts of distributions of logarithmic returns of these assets follow the power laws and the lo…
AWARE-FX uses AI to audit foreign-exchange risk disclosures in corporate reports.
problem Weakly structured foreign-exchange risk disclosures in corporate reports.
method Combines lexicon, logic, encoders, and aggregation methods to convert text into traceable measures.
result FinBERT outperforms in most comparisons, improving F1 scores by up to 0.077.
Revisits Jarrow & Turnbull model for credit and liquidity risk.
problem Modeling credit and liquidity risk in financial markets.
method Uses foreign exchange analogy and partially observable exchange rate.
result Derives tractable term structure models and explicit valuation formulae.
Paper models foreign exchange markets and develops an on-line portfolio selection algorithm.
problem Modeling and predicting returns in foreign exchange markets.
method Matrix-valued time series model, trading matrices, and cross rate method.
result Proves the profitability and universality of the on-line portfolio selection algorithm.
Study examines factors influencing tail risk premia for long-term equity investors.
problem Determining factors affecting variance and higher-moment risk premia in equity markets.
method Empirical study using discretisation invariant swaps for log returns, focusing on skewness, kurtosis, and variance risk premia.
result Momentum is the dominant driver for skewness and kurtosis risk premia, while variance risk premium is influenced by size and growth.
We first show that there are in fact triangular arbitrage opportunities in the spot foreign exchange markets, analyzing the time dependence of the yen-dollar rate, the dollar-euro rate and the yen-euro rate. Next, we propose a model of foreign exchange rates with an interaction. The model includes effects of triangular…
This paper uses bivariate time series to analyze currency similarity in the foreign exchange market.
problem Analyzing similarity among currencies in the foreign exchange market.
method Applies Escoufier's RV coefficient to measure similarity between bivariate time series of currency exchange rates.
result Demonstrates the advantages of using RV coefficient for analyzing currency topological structure.
We derived similar to Bo et al. (2010) results but in the case when the dynamics of the FX rate is driven by a general Merton jump-diffusion process. The main results of our paper are as follows: 1) formulas for the Esscher transform parameters which ensure that the martingale condition for the discounted foreign excha…
Hybrid method reveals true currency correlations.
problem Identify currency status in foreign exchange networks.
method Combines DCCC and network deconvolution to filter indirect effects.
result Reflects currency status changes and is more stable.
Two new plots confirm trend following and risk premia findings.
problem Confirming trend following and risk premia strategies over new data.
method Presenting two additional plots to corroborate findings.
result New data fully corroborates trend following and risk premia findings.
We introduce an autoregressive-type model with self-modulation effects for a foreign exchange rate by separating the foreign exchange rate into a moving average rate and an uncorrelated noise. From this model we indicate that traders are mainly using strategies with weighted feedbacks of the past rates in the exchange …
Develops optimal trading strategy for illiquid currency pairs.
problem Maximizes revenues for a broker liquidating an illiquid currency pair.
method Uses a currency triplet strategy, considering model ambiguity, and employs simulations.
result Mean P&L increases and standard deviation decreases as ambiguity aversion increases.
We investigate the relative market efficiency in financial market data, using the approximate entropy(ApEn) method for a quantification of randomness in time series. We used the global foreign exchange market indices for 17 countries during two periods from 1984 to 1998 and from 1999 to 2004 in order to study the effic…
Optimal dividend strategy for insurance company in foreign currency.
problem Maximizing dividends paid in a foreign currency until ruin.
method Spectrally negative Lévy process, exponentially Lévy exchange rate, Hamilton--Jacobi--Bellman equation.
result Single dividend barrier strategy is optimal.
Derivatives impact U.S. banking sector's systemic risk, but loan and leverage ratios are more significant.
problem Systemic risk in U.S. banking sector due to derivatives and loans.
method Analysis of derivatives and loan data to assess systemic risk.
result Loan and leverage ratios are more influential in systemic risk than derivatives holdings.
Model estimates foreign exchange reserve compositions of undisclosed central banks.
problem Limited information on central bank reserve compositions hinders analysis.
method Hidden Markov Model relating portfolio valuation to exchange rates.
result China's reserve composition likely matches global average, while Singapore holds fewer US dollars.
Study analyzes price response and spread impact in foreign exchange markets.
problem Understanding deviations from Markovian behavior in foreign exchange markets.
method Detailed large-scale data analysis of price response functions for different years and time scales, using pip bid-ask spread definition.
result Large pip spreads significantly impact price response in foreign exchange markets.
In this paper we investigate the scaling behavior of the average daily exchange rate returns of the Indian Rupee against four foreign currencies namely US Dollar, Euro, Great Britain Pound and Japanese Yen. Average daily exchange rate return of the Indian Rupee against US Dollar is found to exhibit a persistent scaling…
Study optimal risk sharing in expanding pools, accounting for uncertainty.
problem Optimal risk sharing in expanding pools of cooperative agents.
method Analyzes asymptotic behavior of certainty equivalents and risk premia, considering ambiguity and uncertainty about probabilistic models.
result Explicit results on limits and rates of convergence of robust certainty equivalents and risk premia in expanding pools.
Study shows demonetization strengthened Indian currency and stock market.
problem Impact of demonetization on Indian stock market and foreign exchange rate.
method Daily rate of return analysis of foreign exchange rate and Nifty 50 index, use of dummy variable for demonetization period.
result Demonetization led to an upward trend in Indian stock market and strengthened the Indian currency (decreased foreign exchange rate).
We have presented a novel technique of detecting intermittencies in a financial time series of the foreign exchange rate data of U.S.- Euro dollar(US/EUR) using a combination of both statistical and spectral techniques. This has been possible due to Continuous Wavelet Transform (CWT) analysis which has been popularly a…
Study lead-lag relationships in foreign exchange markets using three approaches.
problem Lack of research on lead-lag relationships in foreign exchange markets.
method Three approaches: lagged correlations, lagged partial correlations, and Granger causality.
result Statistically significant lead-lag relationships found in some exchange rate pairs.
Graph learning improves FXRP and FXSA with significant statistical arbitrage gains.
problem Improving FXRP and FXSA with complex multi-currency and interest rate relationships.
method Two-step graph learning approach: first, edge-level regression on spatiotemporal graph; second, stochastic optimization with constraints and risk-adjusted return maximization.
result Graph-learning method achieves higher information and Sortino ratios than benchmarks.
Modeling CDS and FX devaluation effects for emerging markets.
problem Risk of dramatic FX devaluation during default events in emerging markets.
method Reduced form framework for credit risk with explicit FX dynamics, including a default-driven jump.
result Perceived risks of devaluation can induce significant basis spreads between domestic and foreign CDS quotes.
Study shows CCLs have minimal impact on most trades but can affect some.
problem Impact of counterparty credit limits on everyday trading prices.
method Analyzed high-quality data from a foreign exchange spot market and developed a new trading model.
result CCLs had little impact on most trades but can have major impact in specific scenarios.
Model shows triangular arbitrage key to cross-currency correlations in forex markets.
problem Understanding cross-currency correlations in forex markets.
method Agent-based model of market interactions.
result Triangular arbitrage is primary driver of cross-currency correlations.
The paper analyzes elicitability of return risk measures and their scoring functions.
problem Elicitability of return risk measures and their scoring functions.
method Dual representation results for convex and geometrically convex return risk measures, axiomatic characterizations of Orlicz premia, and construction of strictly consistent scoring functions.
result Orlicz premia are the only elicitable return risk measures under different sets of conditions.
Two methods are proposed to filter correlations in DCC-GARCH residuals for foreign exchange rates.
problem Filtering correlations in DCC-GARCH residuals for accurate foreign exchange rate prediction.
method Two approaches: estimating correlation matrix as a parameter and using eigenvalue decomposition.
result The DCC-GARCH residual can be almost independent using these methods.
Dynamic functional time-series methods improve forecast accuracy for foreign exchange implied volatility surfaces.
problem Forecasting implied volatility surfaces in foreign exchange markets.
method Dynamic functional principal component analysis and multivariate functional time-series methods.
result Dynamic univariate functional time-series method shows the greatest improvement in forecast accuracy.
Study forecasts volatility and risk in electricity markets using matrix-HAR models.
problem Forecasting volatility and risk in electricity markets.
method Constructed a parsimonious matrix-HAR type model to estimate realized covariation and risk premia in electricity markets.
result Inclusion of longer time horizons and renewable generation information improves forecasts.
New concept of illiquidity linked to credit risk, using Jarrow & Turnbull's analogy.
problem Understanding illiquidity in financial markets, especially with credit risk.
method Introduces a constraint-based notion of illiquidity, using Jarrow & Turnbull's foreign exchange analogy.
result A new mathematical framework for understanding illiquidity in financial markets.
We analyze high-resolution foreign exchange data consisting of 20 million data points of USD-JPY for 13 years to report firm statistical laws in distributions and correlations of exchange rate fluctuations. A conditional probability density analysis clearly shows the existence of trend-following movements at time scale…
Machine learning models predict EUR/USD currency direction with 58.52% accuracy.
problem Predicting the directional movement of EUR/USD in the Foreign Exchange market.
method Comparative analysis of machine learning models, including decorrelated and non-decorrelated feature sets, and meta-estimators.
result 58.52% accuracy for one-day ahead forecasts.
The study finds flaws in methods used to estimate foreign exchange option prices.
problem Flaws in estimating foreign exchange option prices.
method Provided counterexamples of popular FX option interpolation methods.
result Popular FX option interpolation methods fail in certain scenarios.
FX spreads reduced with Last Look option, affecting market equilibrium.
problem Impact of Last Look option on FX market spreads and equilibrium.
method Assumed risk-neutral brokers, analyzed with and without Last Look option.
result Last Look option reduces spreads, can lead to market coexistence or survival of one venue.
The study examines relationships between assets in foreign exchange markets using new measures.
problem Quantifying relationships between assets in non-stationary markets.
method Developed transformation equations for means and covariances under changing numeraire.
result Partial correlations between assets remain invariant under numeraire change.
Paper develops a new framework for analyzing certainty equivalents and dynamic risk premia using Malliavin calculus and Wiener chaos analysis.
problem Limitations of Arrow-Pratt approximation for arbitrary sequences of vanishing risks.
method Develops a new framework based on Malliavin calculus and Wiener chaos analysis, combining Itô calculus, the Clark--Ocone representation, and the Wiener chaos decomposition.
result Establishes a unified framework linking expected utility theory, stochastic analysis, and Wiener chaos expansions, revealing higher-order certainty equivalents and dynamic risk premia.
This paper compares traditional econometric and contemporary machine/deep learning techniques for forecasting foreign exchange rates.
problem Accurate prediction of foreign exchange rates for investment purposes.
method Multivariate time series analysis using Vector Auto Regression, Support Vector Machine, and Recurrent Neural Networks.
result Contemporary machine/deep learning techniques outperform traditional econometric methods in forecasting foreign exchange rates.