East African tech experts identify machine learning challenges.
problem Machine learning research needs in East African tech industry.
method 46 interviews with tech professionals.
result Concrete machine learning problems identified.
On-device research index
arXiv research
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.
169,051 papers · 148 categories
Trend · papers per month
48 results for “tech ventures”
Geoeconomic analysis of venture capital portfolios reveals key emerging tech domains and countries.
problem Quantifying geoeconomic power and technological sovereignty through venture capital data.
method Economic complexity methods applied to venture capital portfolios and RVA metrics.
result Cloud Computing, Cybersecurity Tools, and Medtech have the highest concentration of specialization among high-GCI countries.
Analyzes how venture investment strategies have evolved over time in different sectors.
problem Understanding changes in venture investment strategies across sectors over time.
method Applied PCA and TCA to analyze a dataset of 52,000 startups and 110,000 funding rounds.
result There has been a shift in venture investment towards lower-tech sectors and a rise in accelerator investments.
Study uses web search data to analyze tech startups growth.
problem Analyzing growth dynamics of tech startups.
method Utilized Google Trends data for 241 US-based tech startups.
result Web search traffic correlates positively with tech startup growth.
Designed to compete with fiat currencies, bitcoin proposes it is a crypto-currency alternative. Bitcoin makes a number of false claims, including: solving the double-spending problem is a good thing; bitcoin can be a reserve currency for banking; hoarding equals saving, and that we should believe bitcoin can expand by …
Dual risk models are popular for modeling a venture capital or high tech company, for which the running cost is deterministic and the profits arrive stochastically over time. Most of the existing literature on dual risk models concentrated on the optimal dividend strategies. In this paper, we propose to study the optim…
The dual risk model is a popular model in finance and insurance, which is often used to model the wealth process of a venture capital or high tech company. Optimal dividends have been extensively studied in the literature for a dual risk model. It is well known that the value function of this optimal control problem do…
Paper analyzes venture capital exit decisions under inconsistent preferences.
problem Time-inconsistent preferences in venture capital exit timing.
method Modeling four types of venture capitalists with varying levels of inconsistency.
result Time-inconsistent venture capitalists exit earlier than consistent ones.
We describe Venture, an interactive virtual machine for probabilistic programming that aims to be sufficiently expressive, extensible, and efficient for general-purpose use. Like Church, probabilistic models and inference problems in Venture are specified via a Turing-complete, higher-order probabilistic language desce…
Investment strategy depends on many factors for venture capital funds.
problem Finding the optimal portfolio size for venture capital funds.
method Analyzes various factors affecting fund returns and optimal portfolio size, starting with basic assumptions and increasing complexity.
result Investment strategy depends on many factors, not a one-size-fits-all formula.
In this theoretical paper, I propose creation of a venture bank, able to multiply the capital of a venture capital firm by at least 47 times, without requiring access to the Federal Reserve or other central bank apart from settlement. This concept rests on obtaining default swap instruments on loans in order to create …
Enhances VC startup success predictions using graph augmented time series models.
problem Challenges in predicting startup success due to limited financial data and subjective forecasts.
method Integrates inter-company relationships into time series analysis using GraphRAG.
result Significantly outperforms previous models in startup success predictions.
Develops a deep learning framework to predict future tech directions for high-tech companies.
problem Difficult task in predicting future R&D trends for high-tech companies due to complexity and variety of factors.
method Deep Technology Forecasting (DTF) framework with three components: PCR, CTR, and DTT neural network.
result DTF framework precisely predicts future tech emphasis of companies using hybrid factors.
Study examines tech stocks' reactions to Facebook data leak scandal.
problem Impact of Facebook data leak scandal on U.S. tech stocks.
method Clustering method to identify related companies, CAR to measure impact.
result Overall tech sector showed no adverse impact, but Facebook's performance was negatively affected.
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…
A scenario in which regulators take the drastic step of requiring coverage of all venture bank investment loans using interbank borrowed funds is considered. In this scenario, a minimal amount of default insurance is used, such that Tier 1 and 2 capital requirements are still met. To do this, the default insurance perc…
Study uses LLMs to optimize VC exit timing after IPO.
problem Optimal exit timing after IPO is crucial but not well studied.
method Uses LLMs to analyze financial data and market signals.
result LLMs can improve VC exit timing and generate better returns.
Beyond Picking Winners: Correlation-Driven Tail Risk in Venture Capital Portfolio Constructionq-fin.PM
Proposes a new framework to manage venture capital portfolio risk by focusing on deal-level correlations.
problem Managing venture capital portfolio risk, especially extreme outcomes.
method Gaussian-copula-based framework that learns deal-level dependence from observed joint success frequencies.
result Correlation amplifies extreme upside outcomes, shifting portfolio distribution toward heavier right tails.
When an insurance note is also a derivative a serious problem arises because a derivative must be fulfilled immediately. This feature of derivatives prevents claims processing procedures that screen out ineligible claims. This, in turn, creates a perverse incentive for insured holders of notes to commit acts that resul…
The paper categorizes four types of scale-up: smart, dumb, forced, and fumbled.
problem Growing ventures in size and maintaining efficiency.
method Identifying modularity and speed as key factors, categorizing four types of scale-up.
result Modularity and speed are crucial for successful scale-up.
We study a practical optimization problems for venture capital investments and/or Research and Development (R&D) investments. The first problem is that, given the amount of the initial investment and the reward function at the initial public offering (IPO) market, the venture capitalist wants to maximize overall discou…
The Tech Decouplingq-fin.ST
Tech sector decouples from non-tech sectors post-2015, predicting economic growth.
problem Understanding the relationship between technology and economic growth.
method ARIMA modeling, stationarity tests, data wrangling, exploratory data analysis.
result The technology sector decouples from non-technology sectors post-2015 and predicts economic growth.
The paper uses deep learning to detect asset price bubbles in tech stocks.
problem Detecting financial asset price bubbles using deep learning.
method Deep learning techniques applied to call option prices for financial asset bubbles detection.
result The proposed deep learning algorithm provides a theoretical foundation for positive and continuous stochastic asset price processes.
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…
Study analyzes climate-tech investments across 14 sectors.
problem Accelerating climate-tech innovation in nascent value chains.
method Analysis of 4,172 firms and 12,929 investments over 15 years.
result Only 15% of firms develop end products, 59% support them, and 26% develop services.
We study ranking quantilized mean-field games to select top-performing agents.
problem Selecting top-performing agents in competitive scenarios.
method Developed two formulations: target-based and threshold-based, and provided analytic and semi-explicit solutions.
result Analytic and semi-explicit solutions for quantilized mean-field consistency conditions.
The paper analyzes game theory in convertible contracts during liquidity events.
problem Optimizing payments in convertible contracts during liquidity events.
method Defined a general model for games, showed non-existence of pure strategy Nash equilibria, developed algorithms for computing equilibria.
result Optimum pure strategy Nash equilibria exist when all contracts are of the same type (SAFE).
This paper evaluates investment risks in LATAM AI startups using DCF method.
problem Unique challenges and risks faced by LATAM tech startups.
method Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) metrics; Discounted Cash Flow (DCF) method.
result Developed a ranking of emerging powers in Latin America for tech startup investment.
Corporate venture capital is in the midst of a renaissance. The end of 2015 marked all-time highs both in the number of corporate firms participating in VC deals and in the amount of capital being deployed by corporate VCs. This paper explores, rather than defines, how these firms find success in the wake of this sudde…
Study compares sentiment spillover networks from news and social media in tech companies.
problem Understanding how sentiment information flows between companies through news and social media.
method Network-based transfer entropy method to measure and compare sentiment spillover.
result News shows stronger information flow among tech companies after COVID-19.
Business-cycles and Cash-on-Market: Pre-money Startup Valuation in the Macroeconomic Environmentq-fin.GN
Business cycles affect startup valuations, both directly and indirectly.
problem How do business cycles impact startup valuations?
method Structural Equation Model approach using a dataset of 1,089 venture capital investments.
result Business cycles impact startup valuations both directly and indirectly.
New algorithm for quickly deciding on tech innovations to maximize ROI.
problem Maximizing ROI in repeated decision-making for tech innovations.
method Developed a novel algorithm for learning optimal decision-making policies over innovation proposals.
result Algorithm converges to optimal policy with a rate of order .
New algorithm improves knowledge transfer in dynamic decision-making.
problem Utilizing data from existing ventures to improve decision-making in new ventures.
method Proposes Transferred Fitted -Iteration algorithm for estimating optimal action-state function .
result Significantly improved final learning error of function.
Paper uses time series transformers to predict investment success.
problem Optimizing investment sourcing in VC and GC.
method Transformer-based Multivariate Time Series Classifier (TMTSC).
result TMTSC improves decision making in VC and GC investments.
ChatGPT predicts stock trends from Twitter sentiment, showing positive effects.
problem Predicting stock market trends using social media sentiment.
method Used ChatGPT for sentiment analysis of Twitter posts about Microsoft and Google.
result ChatGPT's predictions correlated positively with stock performance.
Study of public and private VC relationships in France using qualitative methods.
problem Understanding interactions between public and private venture capitalists in France.
method Qualitative approach with semi-structured interviews and thematic content analysis.
result Formal or informal relationships between public and private VCs are a 'economico-cognitive' approach to networking and innovation.
To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet w…
Dan Lovallo and Daniel Kahneman must be commended for their clear identification of causes and cures to the planning fallacy in "Delusions of Success: How Optimism Undermines Executives' Decisions" (HBR July 2003). Their look at overoptimism, anchoring, competitor neglect, and the outside view in forecasting is highly …
In this paper will be applied some principles and methods from econophysics in the case of the direct foreign investitions (D.F.I.), particularised for the Greenfield type, and mixed firms of trade and industrial production (Joint Ventures). To this aim will be used some similarities and parallelisms between the mentio…
Matrix factorization was used to generate investment recommendations for investors. An iterative conjugate gradient method was used to optimize the regularized squared-error loss function. The number of latent factors, number of iterations, and regularization values were explored. Overfitting can be addressed by either…
Tool uses text mining to define innovative tech fields from abstracts.
problem Defining scope in dynamic, multidisciplinary tech projects.
method Text mining of Elsevier's Scopus abstracts.
result Tool provides crucial information for tech field definition.
Deep learning helps identify promising startups.
problem Identifying successful startups amidst many.
method Literature review and synthesis of DL-based startup evaluation methods.
result Deep learning shows promise in startup success prediction.
We construct a statistical indicator for the detection of short-term asset price bubbles based on the information content of bid and ask market quotes for plain vanilla put and call options. Our construction makes use of the martingale theory of asset price bubbles and the fact that such scenarios where the price for a…
Mirzakhani extended curve counting from simple to all curves.
problem Counting curves in the mapping class group orbit with length at most L.
method Low-tech argument showing general result from simple curves.
result Derived the asymptotic growth of curves for arbitrary curves.
Predicting startup success using Crunchbase data and deep learning.
problem Predicting startup success in a volatile entrepreneurial ecosystem.
method Novel deep learning model integrating funding metrics, founder features, and industry category.
result Achieved 14 times capital growth and identified high-potential startups.
In a dual risk model, the premiums are considered as the costs and the claims are regarded as the profits. The surplus can be interpreted as the wealth of a venture capital, whose profits depend on research and development. In most of the existing literature of dual risk models, the profits follow the compound Poisson …
Abstracts discuss a common framework for constructing homology theories.
problem Developing homology theories in low-dimensional topology and geometry.
method Uses a common framework since the late 1980s to construct homology theories.
result Indicates the specific nature of the situation dictates the algebraic nature of chain groups.
Deep learning models are growing, posing new mathematical challenges.
problem Mathematical challenges in training, inference, generalization, and optimization of deep models.
method Formal mathematical analysis and communication with mathematicians, statisticians, and computer scientists.
result A set of new mathematical challenges in deep learning.