The study constructs models for SOFR term rates using futures data.
problem Disruption of the LIBOR market and lack of liquid SOFR derivatives.
method Dynamic arbitrage-free models using historical SOFR futures prices.
result Shadow-rate extension needed for zero-boundary term rates.
New method for pricing SOFR futures options, solving both American and Asian exercise styles.
problem Lack of pricing models for SOFR futures options post-LIBOR transition.
method Developed a new version of the GIT method to solve semi-analytically.
result Obtained option prices, exercise boundaries, and Greeks for American and Asian options.
The paper models SOFR and EFFR dynamics, reconciling diffusive and piecewise paths.
problem Updating interest rate models for SOFR, which is becoming a key benchmark.
method Calibrates a model to SOFR and EFFR futures prices, reconciling diffusive and piecewise paths.
result The model reflects key empirical features of SOFR dynamics and reconciles diffusive and piecewise paths.
We develop a new method to price SOFR futures contracts considering convexity, skew, and smile.
problem Analyzing and pricing SOFR futures contracts with convexity, skew, and smile adjustments.
method A perturbative formalism based on a time-ordered exponential series to solve the backward-Kolmogorov diffusion PDE.
result An analytic pricing formula for SOFR futures contracts that incorporates convexity, skew, and smile adjustments.
Examines SOFR derivatives pricing and hedging post-LIBOR discontinuation.
problem Pricing and hedging of SOFR derivatives post-LIBOR discontinuation.
method One-factor model based on Vasicek's equation for overnight interest rates dynamics.
result Arbitrage-free pricing and hedging of SOFR derivatives instruments.
Develops a statistical model for SOFR term structure in incomplete markets.
problem Incomplete liquidity and completeness in SOFR derivatives market.
method Statistical model incorporating macroeconomic factors and jumps in SOFR rates.
result Model is well-suited for risk management and derivatives pricing.
Paper examines pricing and hedging for cross-currency swaps referencing backward-looking rates.
problem Pricing and hedging cross-currency swaps with backward-looking rates.
method Uses interest rate and currency futures for hedging, analyzes arbitrage-free multi-curve setting.
result Explicit pricing and hedging results for CCBS with backward-looking rates.
Study on collateral currency impact in differential swaps valuation.
problem Impact of collateral currency on differential swap valuation and risk management.
method Replication using futures, explicit pricing and hedging strategies.
result Choice of collateral currency can introduce additional risk exposures.
Model estimates LIBOR rates and finds COVID-19 spread spike due to credit risk.
problem Estimating LIBOR rates and understanding the factors affecting them.
method Developed a joint model for various LIBOR-related rates and used it to decompose spreads.
result Credit risk mainly caused the spike in LIBOR-OIS spread during the COVID-19 onset, with equal contributions from credit and funding-liquidity risks on average.
AXI assesses bank funding costs transparently, improving loan pricing and reducing financial risk.
problem Lack of credit-sensitive funding benchmarks after LIBOR transition.
method AXI aggregates unsecured funding transactions across maturities, producing a daily credit spread.
result AXI correlates with financial conditions and market stress, reducing funding risk and offering spread discounts.
Improved model for SOFR, SONIA, and ESTR caplets pricing.
problem Accurate pricing of options on backward-looking rates.
method Extended Turfus and Romero-Bermúdez model to include smile and skew.
result Simple effective variance formulae for caplet pricing.
Alternative perspective on mean-field LIBOR market model, maintaining practicality and applicability.
problem Maintaining practicality and applicability of mean-field LIBOR market model.
method Embedding mean-field model in a classical setup, controlling term rate variances over large time horizons.
result Framework can be directly applied to model term rates from SOFR, ESTR, or other nearly risk-free overnight rates.
This paper models short rates with jumps using PDEs.
problem Capturing jumps and spikes in interest rates.
method PDE approach for pricing interest rate derivatives.
result Established Feynman-Kač representation and derived solutions.
Abstract framework for cross-currency interest rate contracts.
problem Handling cross-currency markets with collateral and incompleteness.
method Developed a general HJM framework for abstract market indices.
result Enabled simultaneous description of multiple currency interest rate products.
This work models overnight rates with jumps and discontinuities, extending classical short-rate models.
problem Capturing the jump behavior and discontinuities in overnight rates for accurate modeling.
method Developed a term structure modeling framework based on overnight rates, accommodating stochastic discontinuities.
result Simple specifications can capture the jump behavior of overnight rates, and explicit valuation formulas are provided.
Kriging predicts futures prices by accounting for trends and bid-ask spreads.
problem Predicting futures prices with trends and bid-ask spreads.
method Bayesian Kriging technique to model term structure.
result Kriging accurately predicts futures prices with embedded trends and bid-ask spreads.
Study reveals dynamic linkage between Peanut and Soybean Oil futures markets.
problem Exploring interdependence between Peanut and other agricultural commodities in Chinese futures market.
method Constructed multivariate linear regression models and used VAR and DCC-EGARCH models for dynamic relationships. Applied MLP, CNN, and LSTM neural networks for price prediction.
result Significant dynamic linkage between Peanut and Soybean Oil futures markets through DCC-EGARCH, limited influence from other futures markets through VAR model.
Proposes a new VIX futures trading strategy based on term structure modeling.
problem Optimizing VIX futures trading based on term structure.
method Assumes VIX futures term structure follows a Markov model. Uses a deep neural network to model the functional dependence between VIX futures curve, positions, and expected utility.
result Backtests show reasonable portfolio performance and optimal long/short positions.
Derives pricing formulas for perpetual futures contracts.
problem Ensuring fair pricing of perpetual futures contracts without expiration.
method Explicit expressions derived for various types of perpetual contracts, including linear, inverse, and quantos futures.
result Futures price is the risk-neutral expectation of the spot price sampled at a random time reflecting funding payments.
Hidden Markov model predicts profitable statistical arbitrage in Shanghai crude oil futures.
problem Statistical arbitrage opportunities in international crude oil futures markets.
method Hidden Markov model for cointegration spread, mean-reverting regime-switching process.
result Statistical arbitrage strategies involving Shanghai crude oil futures are profitable.
Calibrates carbon futures option pricing using high-frequency data.
problem Estimating equity and variance risk premia for carbon futures options.
method Multifactor stochastic volatility framework with jumps, employing indirect inference.
result Provides insights into carbon futures and option dynamics.
Futures trading is the core of futures business, and it is considered as one of the typical complex systems. To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from the Shanghai Futures Exchange to construct futures trading networks,…
The paper analyzes the pricing of a new compute futures asset.
problem Uncertainty in AI adoption and pricing of compute capital.
method An asset-pricing framework for compute futures, including synthetic futures pricing.
result Preliminary evidence suggests a positive compute risk premium.
Study improves prediction of commodity futures using multi-factor model.
problem Improving accuracy in predicting commodity futures prices.
method State-space functional regression model incorporating yield curve dynamics.
result Functional regression model outperforms Schwartz-Smith model in estimating short-end of futures curve.
Study examines how arbitrage between ETF and futures affects market liquidity during crashes.
problem Impact of arbitrage between leveraged ETF and futures on market liquidity during market crashes.
method Artificial market simulations to investigate liquidity changes in L-ETF and futures markets.
result Arbitrage trading affects liquidity supply from one market to another during market crashes.
Model prices commodity futures and index options.
problem Deriving accurate prices for derivative contracts on commodity futures and indices.
method Stochastic local volatility model for commodity futures.
result Model accurately recovers prices of derivative claims.
We consider portfolio optimization in futures markets. We model the entire futures price curve at once as a solution of a stochastic partial differential equation. The agents objective is to maximize her utility from the final wealth when investing in futures contracts. We study a class of futures price curve models wh…
Predicts short-term futures contract direction using neural networks and order flow data.
problem Challenges in predicting short-term directional movement of futures contracts.
method Engineering features from technical analysis, order flow, and order-book data; training a Tabnet neural network.
result Achieved an accuracy of 0.601 in predicting directional change on the Silver Futures Contract.
This study analyzes the correlation structure of global agricultural futures markets using RMT.
problem Understanding the complex correlation structure of global agricultural futures markets.
method Random Matrix Theory (RMT) applied to analyze correlation coefficients and eigenvalues.
result The correlation structure is asymmetric and right skewed, with significant eigenvalues indicating market effects and commodity groups.
Paper builds a supervised learning model for Chinese futures price prediction.
problem Predicting the trend of Chinese futures prices accurately.
method Supervised learning model designed for futures price movement classification.
result The model meets accuracy requirements for classifying futures price movements.
Study optimizes funding rates for cryptocurrency perpetual futures to maintain price alignment.
problem Maintaining alignment between perpetual future prices and target values in cryptocurrency markets.
method Developed replicating portfolios and path-dependent funding rates using path-dependent infinite-horizon BSDEs and arbitrage pricing theory.
result Appropriate funding rate design can keep perpetual future prices aligned with target values.
Surveying nonparametric inference with shape constraints, past and future.
problem Statistical inference under shape constraints.
method Historical overview and future directions.
result Outlook on future research directions.
New method for off-policy evaluation in POMDPs using future-dependent value functions.
problem Curse of horizon in off-policy evaluation for POMDPs.
method Develops future-dependent value functions and minimax learning method.
result PAC result and Bellman completeness for the proposed OPE estimator.
Hierarchical graph learning for calendar spread strategies in commodity futures markets
problem Developing machine-learning methods for calendar spread strategies in commodity futures markets
method Proposing a hierarchical graph learning approach
result Outperforming benchmark models in both prediction and trading performance
We apply the formalism of the continuous time random walk (CTRW) theory to financial tick data of the bond futures transacted in Korean Futures Exchange (KOFEX) market. For our case, the tick dynamical behaviors of the returns and volatility for bond futures are treated particularly at the long-time limit. The volatili…
Study shows post-COVID commodity futures returns and volatility changed for different products.
problem Analyzing how the pandemic affected Chinese commodity futures markets.
method Empirical analysis of commodity futures returns and cointegration before and after the pandemic.
result Post-COVID, some commodity futures returns increased significantly, while others saw higher volatility.
This paper uses Monte Carlo simulation to value quality options in agricultural futures contracts.
problem Valuation of quality options in agricultural futures to prevent manipulation and improve hedging performance.
method Monte Carlo simulation with antithetic variables for efficiency.
result Demonstrates a method to estimate the value of quality options in agricultural futures contracts.
We study a stochastic control approach to managed futures portfolios. Building on the Schwartz 97 stochastic convenience yield model for commodity prices, we formulate a utility maximization problem for dynamically trading a single-maturity futures or multiple futures contracts over a finite horizon. By analyzing the a…
Perpetual futures offer leverage without maturity, with prices influenced by funding rates.
problem Understanding and pricing perpetual futures with funding rates.
method Derive no-arbitrage prices and bounds in markets with trading costs. Empirically analyze deviations and Sharpe ratios of implied arbitrage strategies.
result Implied arbitrage strategies in crypto markets yield high Sharpe ratios, indicating significant pricing inefficiencies.
The study examines how global economic policy uncertainty affects crude oil futures volatility.
problem Predicting crude oil futures volatility using global economic policy uncertainty.
method Established single-factor and two-factor models under the GARCH-MIDAS framework, tested with rolling-window and fixed-span specifications.
result GEPU changes have stronger predictive power than the GEPU index for crude oil futures volatility.
The paper analyzes gold, oil, and bitcoin futures volatility and basis.
problem Understanding the volatility and basis of gold, oil, and bitcoin futures.
method Contract-by-contract analysis of spot and futures prices, trading volume, and open interest data.
result Trading volume positively affects volatility in all three assets, while open interest has a possible negative effect.
Study measures risk spillovers between US and China's agricultural futures markets.
problem Interconnectedness and risk transmission in agricultural futures markets.
method TVP-VAR-DY model with quantile method.
result CBOT corn, soybean, and wheat are primary risk transmitters; DCE corn and soybean are main receivers.
A new GNN model predicts stock trends by learning historical and future correlations.
problem Limited improvement in stock trend prediction models due to ignoring future patterns.
method DishFT-GNN framework that trains a teacher and student model to capture historical and future data correlations.
result State-of-the-art performance on real-world datasets.
We utilize the symmetric thermal optimal path (TOPS) method to examine the dynamic interaction patterns between the VIX and VIX futures markets. We document that the VIX dominates the VIX futures more in the first few years, especially before the introduction of VIX options. We further observe that the TOPS paths show …
Fair market valuations ignore future worker profits in employee-owned firms.
problem Ignoring future worker profits in fair market valuations for employee-owned firms.
method Analyzing property rights and residual claimants in employee-owned firms.
result Fair market valuations are inappropriate for employee-owned firms.
Study examines liquidation, leverage, and optimal margin requirements in Bitcoin futures markets.
problem Understanding and optimizing margin requirements in Bitcoin futures markets.
method Empirical analysis using generalized extreme value theory and BitMEX data.
result Margin requirements need to be significantly higher to reduce daily margin calls.
Multivariate time series forecasting is an important yet challenging problem in machine learning. Most existing approaches only forecast the series value of one future moment, ignoring the interactions between predictions of future moments with different temporal distance. Such a deficiency probably prevents the model …
Study optimal futures trading strategies for assets with multiscale central tendency price model.
problem Optimal dynamic trading of futures with multiscale central tendency price model.
method Derive no-arbitrage futures prices, solve HJB equations for optimal strategies.
result Optimal trading strategies depend on asset parameters and futures risk premia.