arXiv research

Study uses LLMs to optimize VC exit timing after IPO.

Study predicts startup outcomes like funding, patenting, IPOs using machine learning.

Within the Private Equity (PE) market, the event of a private company undertaking an Initial Public Offering (IPO) is usually a very high-return one for the investors in the company. For this reason, an effective predictive model for the IPO event is considered as a valuable tool in the PE market, an endeavor in which …

Predicting the exit (e.g. bankrupt, acquisition, etc.) of privately held companies is a current and relevant problem for investment firms. The difficulty of the problem stems from the lack of reliable, quantitative and publicly available data. In this paper, we contribute to this endeavour by constructing an exit predi…

Biotech IPOs in Q1 2021: advanced degrees, clinical trials, and IP key.

This study examines how ChiNext IPOs' initial returns are influenced by regulation regime changes.

The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki S…

Study finds billing codes at IPO boost digital health companies' financial performance.

Social media hype can misprice IPO stocks, leading to short-term gains but long-term losses.

We consider the problem of evaluating the quality of startup companies. This can be quite challenging due to the rarity of successful startup companies and the complexity of factors which impact such success. In this work we collect data on tens of thousands of startup companies, their performance, the backgrounds of t…

Study shows registration regime improves IPO pricing efficiency in China.

Analyzes first exit times in a modified Barndorff-Nielsen and Shephard model.

Paper shows equivalence between two alignment methods and introduces a new algorithm.

Study finds dividend policy has no significant effect on IPO stock prices.

New method accurately reconstructs Russell 3000 index, revealing crowded portfolios.

A new method to value IPOed companies.

Paper analyzes venture capital exit decisions under inconsistent preferences.

This research examines relationship between staging of Venture Capital (VC) investments and social feedback visible in publicly available data on the Web. We address the question of Venture Capital investment sensitivity to performance and prospects of new venture, given as likelihood of obtaining future financing, ava…

Study examines strategic exit timing in uncertain competition.

New method controls mean exit time in stochastic systems using machine learning and quasipotential.

Based on Markvorsen and Palmer's work on mean time exit and isoperimetric inequalities we establish slightly better isoperimetric inequalities and mean time exit estimates for minimal submanifolds of $N\times\mathbb{R}$. We also prove isoperimetric inequalities for submanifolds of Hadamard spaces with tamed second fund…

Study of a generalized geometric Brownian motion with varying entry and exit rates.

The purpose of this article is to compute the expected first exit times of Brownian motion from a variety of domains in the Euclidean plane and in the hyperbolic plane.

Developed policy gradient methods for stochastic control with exit time, outperforming traditional techniques in share repurchase pricing.

On December 16, Zynga, the well-known social game developing company went public. This event is following other recent IPOs in the world of social networking companies, such as Groupon, Linkedin or Pandora to cite a few. With a valuation close to 7 billion USD at the time when it went public, Zynga has become the bigge…

IPO Finance Agent evaluates LLMs on SpaceX IPO due diligence, surpassing Finance Agent v2.

We apply the theory of continuous time random walks to study some aspects of the extreme value problem applied to financial time series. We focus our attention on extreme times, specifically the mean exit time and the mean first-passage time. We set the general equations for these extremes and evaluate the mean exit ti…

E$^2$CM uses class means for efficient early exits in neural networks.

Mean exit times concentrate near equators and minimal hypersurfaces in high dimensions.

Study shows submanifolds can't be immersed in certain spaces.

We prove explicit upper and lower bounds for the $L^1$-moment spectra for the Brownian motion exit time from extrinsic metric balls of submanifolds $P^m$ in ambient Riemannian spaces $N^{n}$. We assume that $P$ and $N$ both have controlled radial curvatures (mean curvature and sectional curvature, respectively) as view…

Investors optimize liquid staking decisions in LSP and AMM protocols.

IPO Finance Agent extends Finance Agent v2 for SpaceX S-1 filings, improving accuracy and cost-efficiency.

Unified ML approach for SDEs in bounded domains.

Enhances early-exit neural networks for anytime classification.

We study theoretical and empirical aspects of the mean exit time of financial time series. The theoretical modeling is done within the framework of continuous time random walk. We empirically verify that the mean exit time follows a quadratic scaling law and it has associated a pre-factor which is specific to the analy…

Even in the face of deteriorating and highly volatile demand, firms often invest in, rather than discard, aging technologies. In order to study this phenomenon, we model the firm's profit stream as a Brownian motion with negative drift. At each point in time, the firm can continue operations, or it can stop and exit th…

On December 16th, 2011, Zynga, the well-known social game developing company went public. This event followed other recent IPOs in the world of social networking companies, such as Groupon or Linkedin among others. With a valuation close to 7 billion USD at the time when it went public, Zynga became one of the biggest …

This paper introduces early exits in neural networks for faster inference.

This paper proposes and analyses a new multilevel Monte Carlo method for the estimation of mean exit times for multi-dimensional Brownian diffusions, and associated functionals which correspond to solutions to high-dimensional parabolic PDEs through the Feynman-Kac formula. In particular, it is proved that the complexi…

Optimizes liquidity withdrawal timing for AMM LPs to balance fees and impermanent loss.

Optimal exit strategies of CPT gamblers in unfair gambles

Classifies domains critical for heat content and exit-time moments.

In the domain of technology startups, biotechnology has often been considered as specific. Their unique technology content, the type of founders and managers they have, the amount of venture capital they raise, the time it takes them to reach an exit as well as the technology clusters they belong to are seen as such un…

This paper investigates sufficient conditions for a Feynman-Kac functional up to an exit time to be the generalized viscosity solution of a Dirichlet problem. The key ingredient is to find out the continuity of exit operator under Skorokhod topology, which reveals the intrinsic connection between overfitting Dirichlet …

Deep RL model optimizes pedestrian evacuation in multi-exit scenarios.

By appealing to renewal theory we determine the equations that the mean exit time of a continuous-time random walk with drift satisfies both when the present coincides with a jump instant or when it does not. Particular attention is paid to the corrections ensuing from the non-Markovian nature of the process. We show t…

Motivated by the industry practice of pairs trading, we study the optimal timing strategies for trading a mean-reverting price spread. An optimal double stopping problem is formulated to analyze the timing to start and subsequently liquidate the position subject to transaction costs. Modeling the price spread by an Orn…