A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
In power systems, an asset class is a group of power equipment that has the same function and shares similar electrical or mechanical characteristics. Predicting failures for different asset classes is critical for electric utilities towards developing cost-effective asset management strategies. Previously, physical ag…
We investigate connectedness within and across two major groups or assets: i) five popular cryptocurrencies, and ii) six major asset classes plus two commonly employed risk factors. Granger-causality tests uncover six direct channels of causality from the elements of the mainstream assets/risk factors group to digital …
Generating realistic asset-class scenarios from time series and curves
Study examines cryptocurrency volatility factors using high-frequency data.
We solve a version of the optimal trade execution problem when the mid asset price follows a displaced diffusion. Optimal strategies in the adapted class under various risk criteria, namely value-at-risk, expected shortfall and a new criterion called "squared asset expectation" (SAE), related to a version of the cost v…
Foundation models improve on econometric benchmarks for forecasting volatility, but vary widely across models.
RL agents outperform baselines in asset allocation.
The kind of realized mission inflows the sensitivity to risk. Among other factors, the risk results from decision about liquid assets investment level and liquid assets financing. The higher the risk exposure, the higher the level of liquid assets. If the specific risk exposure is smaller, the more aggressive could be …
Study uses BSDEs to price European options in markets with multiple defaults.
It is essential to incorporate the impact of investor behavior when modeling the dynamics of asset returns. In this paper, we reconcile behavioral finance and rational finance by incorporating investor behavior within the framework of dynamic asset pricing theory. To include the views of investors, we employ the method…
The study assesses music as an investment asset class using discounted cashflow models.
Geometric approach combines asset returns and investor views for better portfolio optimization.
Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the order book. The invariant has been tested on different markets and different asset classes. In all cas…
Examines how central bank policies affect stock markets and asset prices.
Optimizes asset allocation with illiquid assets using MPC.
Clusters asset classes to identify lead-lag relationships in market regimes.
This paper examines momentum spillover across multiple asset classes using only pricing data.
This paper reviews the economic and theoretical foundations of insolvency risk measurement and capital adequacy rules. The proposed new measure of insolvency risk is constructed by disentangling assets, debt and equity at the micro-prudential firm level. This new risk index is the Firm Insolvency Risk Index (FIRI) whic…
We study the impact of central clearing of over-the-counter (OTC) transactions on counterparty exposures in a market with OTC transactions across several asset classes with heterogeneous characteristics. The impact of introducing a central counterparty (CCP) on expected interdealer exposure is determined by the tradeof…
The Split-Session Cluster GARCH model captures tail heterogeneity in overnight and intraday returns.
Investors prioritize ESG in crypto-assets, showing higher exposure than traditional assets.
The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We define two characteristic quantities of an optimal portfolio, namely, minimal investment ris…
Enhances financial market valuation and trading algorithms using distributional value functions.
The paper optimizes stock portfolios with constraints based on performance attribution.
We take a look the changes of different asset prices over variable periods, using both traditional and spectral methods, and discover universality phenomena which hold (in some cases) across asset classes.
New proposed models are often compared to state-of-the-art using statistical significance testing. Literature is scarce for classifier comparison using metrics other than accuracy. We present a survey of statistical methods that can be used for classifier comparison using precision, accounting for inter-precision corre…
Diversified risk parity strategies outperform equally-weighted portfolios in various asset universes.
Develops a dynamic latent-factor model for high-dimensional asset characteristics.
Paper proves existence and uniqueness of solutions to PIDEs in Bessel spaces for option pricing.
This paper provides formulas for minimum cost super-hedging in a multi-asset binomial market.
New model analyzes dynamic correlations in stock returns.
We present an overview of the broad class of financial models in which the prices of assets are Lévy-Ito processes driven by an -dimensional Brownian motion and an independent Poisson random measure. The Poisson random measure is associated with an -dimensional Lévy process. Each model consists of a pricing kerne…
Study proposes a new approach for deep hedging using artificial market simulations.
Modified CTGAN-Plus-Features method optimizes asset allocation with CVaR constraint.
Predicts asset return distributions using LSTM and quantile regression.
We show that shortfall risks of American options in a sequence of multinomial approximations of the multidimensional Black--Scholes (BS) market converge to the corresponding quantities for similar American options in the multidimensional BS market with path dependent payoffs. In comparison to previous papers we conside…
The occurrence of aftershocks following a major financial crash manifests the critical dynamical response of financial markets. Aftershocks put additional stress on markets, with conceivable dramatic consequences. Such a phenomenon has been shown to be common to most financial assets, both at high and low frequency. It…
Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACV…
An efficient conditioning technique, the so-called Brownian Bridge simulation, has previously been applied to eliminate pricing bias that arises in applications of the standard discrete-time Monte Carlo method to evaluate options written on the continuous-time extrema of an underlying asset. It is based on the simple a…
We explore a decomposition in which returns on a large class of portfolios relative to the market depend on a smooth non-negative drift and changes in the asset price distribution. This decomposition is obtained using general continuous semimartingale price representations, and is thus consistent with virtually any ass…
During the last few years, there has been an interest in comparing simple or heuristic procedures for portfolio selection, such as the naive, equal weights, portfolio choice, against more "sophisticated" portfolio choices, and in explaining why, in some cases, the heuristic choice seems to outperform the sophisticated …
A new portfolio model DEWSP improves Sharpe ratio by 0.24% to 5.15%.
Quantum computing speeds up asset pricing models exponentially.
Study optimal portfolio selection with Recovery Average Value at Risk, showing better control over liabilities.
Paper tackles dynamic portfolio optimization using quantum and quantum-inspired methods.
Dynamic rule-based investment strategies outperform static ones in pension schemes.
Investigates cross-impact kernels for financial asset prices.
We study the properties of nonlinear Backward Stochastic Differential Equations (BSDEs) driven by a Brownian motion and a martingale measure associated with a default jump with intensity process . We give a priori estimates for these equations and prove comparison and strict comparison theorems. These results ar…