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 article examines arbitrage investment in a mispriced asset when the mispricing follows the Ornstein-Uhlenbeck process and a credit-constrained investor maximizes a generalization of the Kelly criterion. The optimal differentiable and threshold policies are derived. The optimal differentiable policy is linear with …
We extend the theory of asymmetric information in mispricing models for stocks following geometric Brownian motion to constant relative risk averse investors. Mispricing follows a continuous mean--reverting Ornstein--Uhlenbeck process. Optimal portfolios and maximum expected log--linear utilities from terminal wealth f…
Study confirms mispricing in sportsbooks but finds data issues affect results.
problem Mispricing and inefficiency in online sportsbooks.
method Replication using Wikipedia buzz factor metric and backtesting.
result Data quality issues affect betting results; only one strategy remains profitable.
Develops a framework for identifying mispriced assets through attention factors for statistical arbitrage.
problem Identifying mispriced assets in statistical arbitrage trading.
method Uses conditional latent factors learned from firm characteristic embeddings to identify time-series signals and form a trading strategy.
result Achieves an out-of-sample Sharpe ratio above 4 on the largest U.S. equities over a 24-year period.
Repo dealers' market power affects bond prices by up to 2 percentage points.
problem Market power of repo dealers impacts bond prices and liquidity.
method Proprietary data on repo and reverse-repo trades analyzed.
result Market power of repo dealers accounts for 0.5-1.3 percentage points of bond yield deviation.
We find stationary distributions in a financial model with trends and mean-reversion.
problem Financial markets with competing trends and mean-reversion.
method Analytical derivation of stationary distributions in various noise and feedback regimes.
result The distributions are unimodal Gaussians in small noise, small feedback limits, but can be bimodal for stronger trends.
Novel pairs trading strategy for cointegrated cryptocurrencies using copulas.
problem Identifying profitable trading opportunities in cointegrated cryptocurrency pairs.
method Linear and non-linear cointegration tests, correlation coefficient, copula families, back-testing.
result The strategy outperforms buy-and-hold trading strategies in profitability and risk-adjusted returns.
New COS method formula improves option pricing accuracy.
problem Determining the optimal truncation range for COS method.
method Derive new formula using Markov's inequality to ensure convergence.
result New formula leads to more accurate option pricing.
Factor Engine simplifies financial factor computation and analysis in Python.
problem Efficient computation and analysis of financial factors.
method Modular, extensible Python library with decorators, integrates with data science ecosystem.
result Mispricing factors computed by Factor Engine and Stata implementation are highly similar.
GIFsentiment predicts stock market returns and investor sentiment from social media GIFs.
problem Understanding investor sentiment in the stock market.
method Constructing a sentiment index from social media GIFs and analyzing its correlation with market returns and volume.
result GIFsentiment positively predicts stock market returns and negatively predicts returns for up to four weeks.
Social media hype can misprice IPO stocks, leading to short-term gains but long-term losses.
problem Mispricing of IPO stocks due to social media hype.
method Analysis of investor emotions on StockTwits and Twitter.
result High pre-IPO enthusiasm leads to higher short-term returns but lower long-term returns.
Polymarket users exploit mispriced assets for profit.
problem Arbitrage opportunities in prediction markets.
method Empirical analysis using on-chain historical order book data.
result 40 million USD of profit extracted from arbitrage opportunities.
We introduce and study a non-equilibrium continuous-time dynamical model of the price of a single asset traded by a population of heterogeneous interacting agents in the presence of uncertainty and regulatory constraints. The model takes into account (i) the price formation delay between decision and investment by the …
Study quantifies model risk in cyber insurance, affecting premium pricing.
problem Model risk and risk sensitivity in cyber insurance pricing.
method Robust estimators for model parameters and dependence analysis.
result Robust estimation improves tail index and joint loss model accuracy.
In this work we consider three problems of the standard market approach to pricing of credit index options: the definition of the index spread is not valid in general, the usually considered payoff leads to a pricing which is not always defined, and the candidate numeraire one would use to define a pricing measure is n…
The study examines stock splits and their effects on companies, managers, and shareholders.
problem Misunderstandings and confounding factors around stock splits and their impacts.
method Selected database analysis of nine recent events, examining market impact, trading volume, and shareholder base.
result Stock splits enhance trading volume, increase shareholder base, and improve market liquidity.
Improved financial market calibration reveals large excess volatility.
problem Large excess volatility in financial markets.
method Extended Chiarella model to handle long-term value drifts, calibrated on multiple asset classes.
result Large excess volatility (factor ≈ 4 for stock indices) and bimodal mispricing distribution.
Study finds cryptoasset markets inefficient due to capital reallocation frictions.
problem Inefficiency in cryptoasset markets due to capital reallocation frictions.
method Examined investments with dominant and secondary risk factors, derived equilibrium restrictions, and tested empirically.
result Empirical results strongly reject necessary equilibrium restrictions, indicating market inefficiency.
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 …
The Chicago Board Options Exchange (CBOE) Volatility Index, VIX, is calculated based on prices of out-of-the-money put and call options on the S&P 500 index (SPX). Sometimes called the "investor fear gauge," the VIX is a measure of the implied volatility of the SPX, and is observed to be correlated with the 30-day real…
This paper presents a new model for pricing financial derivatives subject to collateralization. It allows for collateral arrangements adhering to bankruptcy laws. As such, the model can back out the market price of a collateralized contract. This framework is very useful for valuing outstanding derivatives. Using a uni…
We study a dynamic portfolio optimization problem related to convergence trading, which is an investment strategy that exploits temporary mispricing by simultaneously buying relatively underpriced assets and selling short relatively overpriced ones with the expectation that their prices converge in the future. We build…
In light of the power problems of statistical tests and undisciplined use of alpha-based statistics to compare models, this paper proposes a unified set of distance-based performance metrics, derived as the square root of the sum of squared alphas and squared standard errors. The Bayesian investor views model performan…
Trend and Value are pervasive anomalies, common to all financial markets. We address the problem of their co-existence and interaction within the framework of Heterogeneous Agent Based Models (HABM). More specifically, we extend the Chiarella (1992) model by adding noise traders and a non-linear demand of fundamentalis…
A new deep learning model improves asset pricing predictions.
problem Improving asset pricing models for better predictions.
method Pseudo-Siamese Network (SNAP) for conditional asset pricing.
result The SNAP model outperforms benchmarks in out-of-sample prediction and Sharpe ratio.
Study shows cognitive load impacts financial market efficiency, especially for less sophisticated investors.
problem Cognitive load's effect on financial market information processing.
method Developed a theoretical framework and tested it with exogenous disclosure complexity variation.
result Cognitive load significantly impairs price discovery, particularly for less sophisticated investors.
Agent maximizes utility with pathwise constraint on portfolio value.
problem Maximizing utility with a pathwise constraint on portfolio value.
method Max-plus decomposition for supermartingales, Black-Scholes-Merton model.
result Explicit form of optimal terminal wealth and process involved.
The paper models insurance market dynamics under uncertainty and financial frictions.
problem Modeling insurer behavior under uncertainty and financial frictions.
method Dynamic equilibrium model of insurance market with competitive insurers maximizing shareholder value.
result Investment can lead to lower insurance prices and negative loadings under certain conditions.
A new method uses preference relations to reconcile contradictory trading signals from multiple securities.
problem Difficulty in exploiting multiple pairs trading signals due to contradictions.
method Proposes a portfolio construction method based on preference relation graphs to reconcile contradictory signals.
result Portfolios based on preference relations exhibit robust returns even with high transaction costs and improve with more securities considered.
This paper analyzes arbitrage opportunities in Polymarket's NBA markets.
problem Underexplored market microstructure and high-frequency pricing efficiency in decentralized prediction markets.
method Systematic empirical analysis of algorithmic arbitrage using over 75 million limit order book snapshots.
result Microstructural efficiency is profound, with single-market anomalies rare and combinatorial inefficiencies more frequent.
The modelling of financial markets presents a problem which is both theoretically challenging and practically important. The theoretical aspects concern the issue of market efficiency which may even have political implications \cite{Cuthbertson}, whilst the practical side of the problem has clear relevance to portfolio…
Paper proposes a new trading strategy using corporate event detection from news articles.
problem Predicting stock movements based on corporate events from news articles.
method Bi-level event detection model: low-level for token-level event identification, high-level for article-level event identification.
result The proposed strategy outperforms existing models in stock prediction metrics.
Study improves machine learning for long-term financial portfolio management.
problem Machine learning precision declines with long-term data.
method Data augmentation using multiple time scales and learning data.
result Generalization performance can be maintained for long-term tasks.
PolySwarm uses a swarm of LLMs to predict and arbitrage prediction markets.
problem Real-time prediction market trading and latency arbitrage inefficiencies.
method PolySwarm employs a swarm of 50 diverse LLMs, Bayesian combination, and risk-controlled execution.
result Swarm aggregation outperforms single-model baselines in prediction tasks.
Neural network model improves longevity risk assessment.
problem Systematic mispricing of longevity risk in linear models.
method Hybrid-Lift framework combining Hierarchical LSTM networks and Mean-Bias Correction.
result Hybrid-Lift outperforms Li-Lee framework by 17.40% in Sweden and 12.57% in West Germany.
Dynamic-weight AMMs outperform traditional CEX rebalancing in tokenized funds, especially on L2s.
problem Improving asset allocation efficiency in decentralized finance (DeFi) protocols.
method Block-level arbitrage analysis and long-term performance benchmarks on two live pools.
result Dynamic-weight AMMs can achieve performance comparable to or better than traditional CEX rebalancing, especially on Layer 2 (L2) networks.
Unified market making controls risk, arbitrage, and volatility surfaces.
problem Market making risk, arbitrage, and volatility surface consistency.
method Constrained RL and stochastic control for risk-sensitive execution and hedging.
result Agent achieves positive P&L with zero calendar and butterfly violations.
The paper develops a filtering framework for estimating hazard rates with jumps in financial and insurance applications.
problem Estimating hazard rates with unobservable change-points in financial and insurance contexts.
method Continuous-time filtering framework using progressive enlargement of filtration, stochastic differential equations, and sensitivity analysis.
result Explicit formula for survival probability conditional on partial information.
Model shows liquidity stress crossover in market dynamics.
problem Identifying genuine market instabilities in agent-based models.
method Applied Bouchaud's phase-diagram method to a continuous-double-auction model.
result Emergent liquidity-stress crossover with specific tipping point parameters.
An interacting Black-Scholes model for option pricing, where the usual constant interest rate r is replaced by a stochastic time dependent rate r(t) of the form r(t)=r+f(t) dW/dt, accounting for market imperfections and prices non-alignment, was developed in [1]. The white noise amplitude f(t), called arbitrage bubble,…