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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.

168,657 papers · 148 categories

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491317 · May 202619922001200920172026
48 results for Alpha Log-Det

The paper develops divergences for Gaussian processes and RKHS settings.

problem Estimating divergences in infinite-dimensional spaces.
method Formulations of Alpha Log-Det divergences, continuity in norm, laws of large numbers, consistent estimation from finite samples.
result Infinite-dimensional divergences can be estimated from finite-dimensional versions with dimension-independent sample complexities.

The study examines averages of Laplacian determinants over large genus moduli spaces.

problem Analyzing averages of determinants of Laplacians over large genus moduli spaces.
method Examined the moduli space of hyperbolic surfaces with the Weil-Petersson metric, showing decay rates and approaching constants for specific functions.
result Found a universal constant E and decay rates for expected values of determinants over large genus moduli spaces.

DAGMA learns DAGs faster and more accurately using log-determinant acyclicity.

problem Learning directed acyclic graphs from data efficiently and accurately.
method DAGMA uses M-matrices and log-determinant acyclicity to optimize DAG learning.
result DAGMA achieves faster and more accurate DAG learning compared to existing methods.

Local index theorem for cofinite hyperbolic Riemann surfaces derived from computational perspective.

problem Deriving the local index theorem for cofinite Riemann surfaces.
method Using Ahlfors' variational formulas and projection formulas, deriving integral formulas for variations of determinants.
result Explicit integral formulas for variations of logdetΔn\log\detΔ_n and logdetNn\log \det N_n.

For a smooth strictly plurisubharmonic function uu on a open set ΩCnΩ\subset\mathbb{C}^{n} and FF a C1C^{1} nondecreasing function on R+\mathbf{R}^{*}_{+}, we investigate the complex partial differential equations Δglogdet(uijˉ)=F(det(uijˉ))glogdet(uijˉ)g2,Δ_{g}\log\det(u_{i\bar j})=F(\det(u_{i\bar j}))\Vert\nabla_{g}\log\det(u_{i\bar j})\Vert_{g}^{2}, whe…

2017-07-10abs ↗pdf ↗

Alpha2 discovers logical formulaic alphas using deep reinforcement learning.

problem Discovering interpretable formulaic alphas for better trading strategies.
method Formulating alpha discovery as program construction, using deep reinforcement learning to navigate the search space.
result Empirical experiments show Alpha2 identifies diverse, logical, and effective alphas improving trading strategy performance.

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…

2017-08-09abs ↗pdf ↗

Paper proposes a new framework to mine synergistic formulaic alphas for better stock trend forecasting.

problem Mining alphas separately ignores their combined performance, leading to suboptimal models.
method Proposes a reinforcement learning-based framework that optimizes the mining of synergistic formulaic alpha sets.
result Demonstrates higher returns in stock trend forecasting compared to previous approaches.

Alpha-R1 uses LLMs to reason about economic factors and news for better alpha screening.

problem Challenges in data-driven investment strategies due to signal decay and regime shifts.
method Reinforcement learning trained on 8B parameters to evaluate alpha relevance under changing market conditions.
result Empirically outperforms benchmark strategies and shows improved robustness to alpha decay.

New method estimates log-determinant using trace powers, avoiding classical limitations.

problem Estimating log-determinant of large matrices efficiently and accurately.
method Interpolating moment-generating function and its derivative at zero using trace powers.
result No continuous estimator using finite moments can be uniformly accurate over unbounded conditioning.

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 …

2014-06-13abs ↗pdf ↗

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…

2010-04-07abs ↗pdf ↗

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 (-…

2010-04-07abs ↗pdf ↗

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…

2014-04-03abs ↗pdf ↗

RiskMiner discovers formulaic alphas using MCTS for better performance.

problem Mining formulaic alphas without considering structural information and alpha correlations.
method Formulates alpha mining as an MDP and solves it with a risk-seeking MCTS.
result Our method outperforms state-of-the-art benchmarks and achieves the most profitable results.

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…

2014-05-31abs ↗pdf ↗

Enhances genetic programming for stock alpha discovery with warm start and structural constraints.

problem Overwhelming search space and computational burden in traditional genetic programming for alpha factor discovery.
method Proposes a new GP framework with warm start and structural constraints to enhance search performance and interpretability.
result Superior out-of-sample prediction results and higher portfolio returns compared to benchmarks.

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…

2015-01-22abs ↗pdf ↗

Unified convergence analysis of alpha-SVRG under strong convexity.

problem Analyzing the convergence of alpha-SVRG in strongly convex environments.
method Unified convergence rate expression for alpha-SVRG under fixed learning rate, demonstrating faster convergence than SGD and SVRG.
result alpha-SVRG has a faster convergence rate compared to SGD and SVRG under suitable choice of alpha.

AlphaEval evaluates alpha mining models efficiently and comprehensively.

problem Lack of systematic evaluation for alpha mining models.
method Unified, parallelizable evaluation framework assessing predictive power, stability, robustness, financial logic, and diversity.
result AlphaEval achieves evaluation consistency comparable to comprehensive backtesting, providing more comprehensive insights and higher efficiency.

New methods for tuning alpha in Gibbs posteriors improve speed and accuracy.

problem Inconsistency in Bayesian inference and lack of fast tuning methods for alpha.
method Proposed two data-driven methods: sample-splitting and bootstrapping. Formulated alpha-posteriors for three models.
result Sample-splitting outperforms SafeBayes in speed and accuracy, especially in complex models.

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…

2000-07-09abs ↗pdf ↗

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…

2018-01-26abs ↗pdf ↗

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…

2014-04-20abs ↗pdf ↗

AlphaSAGE mines diverse alphas via GFlowNets, overcoming RL issues.

problem Reward sparsity, inadequate sequential representations, and single optimal mode issues in RL for alphas.
method Structure-aware encoder (RGCN), GFlowNets, dense reward structure.
result Empirically outperforms existing baselines in mining diverse alphas.

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…

2017-09-19abs ↗pdf ↗

PPO optimizes LLM-generated alpha weights for better trading performance.

problem Adapting LLM-generated alphas for varying market conditions.
method Proximal Policy Optimization (PPO) for dynamic alpha weight adjustment.
result PPO-optimized strategy achieves higher Sharpe ratios and smaller drawdowns.

The paper presents methods to improve uncertainty calibration in Bayesian Neural Networks.

problem Uncalibrated Bayesian Neural Networks often lead to overconfidence.
method The paper uses alpha-divergences from Information Geometry for calibration.
result Calibration using alpha-divergences provides better uncertainty estimates and is more efficient.

AlphaForge mines and dynamically combines alpha factors for better investment performance.

problem Inconsistency and inflexibility of fixed factor weights in alpha factor mining.
method Generative-predictive neural network for factor generation and dynamic weight adjustment.
result Demonstrated superior performance in formulaic alpha factor mining and portfolio returns.

In these notes we discuss investment allocation to multiple alpha streams traded on the same execution platform, including when trades are crossed internally resulting in turnover reduction. We discuss approaches to alpha weight optimization where one maximizes P&L subject to bounds on volatility (or Sharpe ratio). The…

2014-06-05abs ↗pdf ↗

Mannheim curves are defined for immersed curves in 3-dimensional sphere S^3 . The definition is given by considering the geodesics of S^3. First, two special geodesics, called principal normal geodesic and binormal geodesic, of S^3 are defined by using Frenet vectors of a curve immersed in S^3. Later, the curve alpha i…

2015-09-17abs ↗pdf ↗

AlphaCFG discovers alpha factors using grammar-guided search.

problem Discovering formulaic alpha factors in finance.
method AlphaCFG uses a grammar-based framework to define and discover alpha factors with syntactic and semantic constraints.
result AlphaCFG outperforms state-of-the-art methods in trading profitability and efficiency.

We present explicit formulas - that are also computer code - for 101 real-life quantitative trading alphas. Their average holding period approximately ranges 0.6-6.4 days. The average pair-wise correlation of these alphas is low, 15.9%. The returns are strongly correlated with volatility, but have no significant depend…

2016-01-05abs ↗pdf ↗

The paper evaluates biased methods for alpha-divergence minimization.

problem The impact of bias on solutions found for alpha-divergence minimization.
method Empirical evaluation of biased methods for alpha-divergence minimization, focusing on bias effects and dimensionality.
result Solutions are biased towards KL-divergence minimizers and require impractical computation in high dimensions to minimize alpha-divergence.

Given a smooth, closed, oriented 4-manifold X and alpha in H_2(X,Z) such that alpha.alpha > 0, a closed 2-form w is constructed, Poincare dual to alpha, which is symplectic on the complement of a finite set of unknotted circles. The number of circles, counted with sign, is given by d = (c_1(s)^2 -3sigma(X) -2chi(X))/4,…

2004-01-15abs ↗pdf ↗

Paper proposes a new REINFORCE algorithm for mining formulaic alpha factors with reduced variance.

problem Mining formulaic alpha factors with interpretability and robustness in volatile markets.
method Developed a novel REINFORCE algorithm with a dedicated baseline and reward shaping.
result Boosts correlation with returns by 3.83% and enhances excess returns compared to existing methods.

In this paper, the geometric meaning of (alpha,beta)-norms is made clear. On this basis, we introduce a new class of Finsler metrics called general (alpha,beta)-metrics, which are defined by a Riemannian metric and an 1-form. These metrics not only generalize original (alpha,beta)-metrics naturally, but also include so…

2012-09-05abs ↗pdf ↗

We discuss investment allocation to multiple alpha streams traded on the same execution platform with internal crossing of trades and point out differences with allocating investment when alpha streams are traded on separate execution platforms with no crossing. First, in the latter case allocation weights are non-nega…

2014-05-19abs ↗pdf ↗

In the present paper we study locally semiflat (we also call them semiintegrable) almost Grassmann structures. We establish necessary and sufficient conditions for an almost Grassmann structure to be alpha- or beta-semiintegrable. These conditions are expressed in terms of the fundamental tensors of almost Grassmann st…

1998-05-22abs ↗pdf ↗

A global twistor correspondence is established for neutral self-dual conformal structures with alpha-surface foliation when the structure is close to the standard structure on S^2 times S^2. We need to introduce some singularity for the alpha-surface foliation such that the leaves intersect on a fixed two sphere. In th…

2007-01-04abs ↗pdf ↗