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.
Alpha2 discovers logical formulaic alphas using deep reinforcement learning.
AlphaCFG discovers alpha factors using grammar-guided search.
Paper proposes a new REINFORCE algorithm for mining formulaic alpha factors with reduced variance.
Hybrid ML ensemble predicts market risk and generates alpha.
Enhances genetic programming for stock alpha discovery with warm start and structural constraints.
We propose a novel interpretation of the collapsed variational Bayes inference with a zero-order Taylor expansion approximation, called CVB0 inference, for latent Dirichlet allocation (LDA). We clarify the properties of the CVB0 inference by using the alpha-divergence. We show that the CVB0 inference is composed of two…
Paper proposes a new framework to mine synergistic formulaic alphas for better stock trend forecasting.
AlphaLogics mines market logic to generate interpretable alpha factors.
Study uses ML to predict currency and bond returns from news sentiment.
A new tensorial metric describes geometry in 4D space.
We describe the underlying probabilistic interpretation of alpha and beta divergences. We first show that beta divergences are inherently tied to Tweedie distributions, a particular type of exponential family, known as exponential dispersion models. Starting from the variance function of a Tweedie model, we outline how…
AlphaEval evaluates alpha mining models efficiently and comprehensively.
FactorMiner discovers financial alpha factors with low redundancy.
AlphaForge mines and dynamically combines alpha factors for better investment performance.
This work extends alpha-beta divergences to complex data and finds closed-form solutions.
Paper reviews the evolution of alpha from human insight to AI-powered systems.
Proposes a novel evolutionary model for stock price prediction.
We investigate a new geometric flow which consists of a coupled system of the Ricci flow on a closed manifold M with the harmonic map flow of a map phi from M to some closed target manifold N with a (possibly time-dependent) positive coupling constant alpha. This system can be interpreted as the gradient flow of an ene…
Forecast-to-fill strategy generates durable alpha in gold futures.
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…
T-KAN improves HFT LOB forecasting with learnable splines.
TLRS improves predictive power of mined formulaic alpha factors.
Alpha-GPT mines new trading signals with human-AI interaction.
We give an explicit algorithm and source code for extracting expected returns for stocks from expected returns for alphas. Our algorithm altogether bypasses combining alphas with weights into "alpha combos". Simply put, we have developed a new method for trading alphas which does not involve combining them. This yields…
Alpha-R1 uses LLMs to reason about economic factors and news for better alpha screening.
We propose a framework for constructing factor models for alpha streams. Our motivation is threefold. 1) When the number of alphas is large, the sample covariance matrix is singular. 2) Its out-of-sample stability is challenging. 3) Optimization of investment allocation into alpha streams can be tractable for a factor …
We compute the analytic expression of the probability distributions F{FTSE100,+} and F{FTSE100,-} of the normalized positive and negative FTSE100 (UK) index daily returns r(t). Furthermore, we define the alpha re-scaled FTSE100 daily index positive returns r(t)^alpha and negative returns (-r(t))^alpha that we call, aft…
In terms of the stock exchange returns, we compute the analytic expression of the probability distributions F{DAX,+} and F{DAX,-} of the normalized positive and negative DAX (Germany) index daily returns r(t). Furthermore, we define the alpha re-scaled DAX daily index positive returns r(t)^alpha and negative returns (-…
Alpha-GPT 2.0 integrates human insights into AI-driven investment research.
It is well known that combining multiple hedge fund alpha streams yields diversification benefits to the resultant portfolio. Additionally, crossing trades between different alpha streams reduces transaction costs. As the number of alpha streams increases, the relative turnover of the portfolio decreases as more trades…
RiskMiner discovers formulaic alphas using MCTS for better performance.
Internal crossing of trades between multiple alpha streams results in portfolio turnover reduction. Turnover reduction can be modeled using the correlation structure of the alpha streams. As more and more alphas are added, generally turnover reduces. In this note we use a factor model approach to address the question o…
A nonnegative number d_infinity, called asymptotic dimension, is associated with any metric space. Such number detects the asymptotic properties of the space (being zero on bounded metric spaces), fulfills the properties of a dimension, and is invariant under rough isometries. It is then shown that for a class of open …
We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications typically there is insufficient history to compute a sample covariance matrix (SCM) for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted) regression ove…
DCMIX learns channel importance for high content imaging.
EFS uses LLMs to optimize sparse portfolios by evolving alpha factors.
Study uses LLMs to categorize financial tweets, revealing useful sentiment signals.
Unified convergence analysis of alpha-SVRG under strong convexity.
New methods for tuning alpha in Gibbs posteriors improve speed and accuracy.
This paper introduces a variational approximation framework using direct optimization of what is known as the {\it scale invariant Alpha-Beta divergence} (sAB divergence). This new objective encompasses most variational objectives that use the Kullback-Leibler, the R{é}nyi or the gamma divergences. It also gives access…
An explicit expression is obtained for the sectional curvature in the plane spanned by two stationary flows, cos(k, x) and cos(l, x). It is shown that for certain values of the wave vectors k and l the curvature becomes positive for alpha > alpha_0, where 0 < alpha_0 < 1 is of the order 1/k. This suggests that the flow…
The weak variance-alpha-gamma process is a multivariate Lévy process constructed by weakly subordinating Brownian motion, possibly with correlated components with an alpha-gamma subordinator. It generalises the variance-alpha-gamma process of Semeraro constructed by traditional subordination. We compare three calibrati…
MarketSenseAI uses AI to select stocks with 10-30% excess alpha.
We give a simple explicit formula for turnover reduction when a large number of alphas are traded on the same execution platform and trades are crossed internally. We model turnover reduction via alpha correlations. Then, for a large number of alphas, turnover reduction is related to the largest eigenvalue and the corr…
AlphaSAGE mines diverse alphas via GFlowNets, overcoming RL issues.
We give an explicit algorithm and source code for extracting equity risk factors from dead (a.k.a. "flatlined" or "hockey-stick") alphas and using them to improve performance characteristics of good (tradable) alphas. In a nutshell, we use dead alphas to extract directions in the space of stock returns along which ther…
PPO optimizes LLM-generated alpha weights for better trading performance.
The paper presents methods to improve uncertainty calibration in Bayesian Neural Networks.