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.
Study examines tech stocks' reactions to Facebook data leak scandal.
The paper uses deep learning to detect asset price bubbles in tech stocks.
ChatGPT predicts stock trends from Twitter sentiment, showing positive effects.
The paper uses data science to predict stock trends of Amazon, Apple, Google, and Microsoft.
Study uses xLSTM in DRL for better stock trading performance.
Based on 46 in-depth interviews with scientists, engineers, and CEOs, this document presents a list of concrete machine research problems, progress on which would directly benefit tech ventures in East Africa.
Technological change and innovation are vitally important, especially for high-tech companies. However, factors influencing their future research and development (R&D) trends are both complicated and various, leading it a quite difficult task to make technology tracing for high-tech companies. To this end, in this pape…
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…
This paper considers a statistical signal processing problem involving agent based models of financial markets which at a micro-level are driven by socially aware and risk- averse trading agents. These agents trade (buy or sell) stocks by exploiting information about the decisions of previous agents (social learning) v…
Tech sector decouples from non-tech sectors post-2015, predicting economic growth.
Market valuation duration is 175 years, but drops to 46 years during crises.
Study analyzes climate-tech investments across 14 sectors.
This paper evaluates investment risks in LATAM AI startups using DCF method.
Study of historic stock returns distributions, highlighting asymmetry and outliers.
Study compares sentiment spillover networks from news and social media in tech companies.
Study finds 'Dragon Kings' in stock market volatility during major economic crises.
Mirzakhani obtained the asymptotic growth, when , of the number of curves in the mapping class group orbit of some given simple curve and with length at most . Years later she extended this result from simple to arbitrary curves. Here we give a short and relative low-tech argument showing how to derive t…
Cryptocurrencies are increasingly correlated with traditional financial markets.
Tool uses text mining to define innovative tech fields from abstracts.
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…
Study uses web search data to analyze tech startups growth.
Margin trading and short selling boost green tech innovation in China.
Geoeconomic analysis of venture capital portfolios reveals key emerging tech domains and countries.
Abstracts discuss a common framework for constructing homology theories.
Deep learning models are growing, posing new mathematical challenges.
Cryptocurrencies use blockchain tech for secure transactions, offering new research opportunities.
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…
This paper presents a pre-processing and a distance which improve the performance of machine learning algorithms working on independent and identically distributed stochastic processes. We introduce a novel non-parametric approach to represent random variables which splits apart dependency and distribution without losi…
We present a methodology for clustering N objects which are described by multivariate time series, i.e. several sequences of real-valued random variables. This clustering methodology leverages copulas which are distributions encoding the dependence structure between several random variables. To take fully into account …
The hidden Markov model (HMM) is a generative model that treats sequential data under the assumption that each observation is conditioned on the state of a discrete hidden variable that evolves in time as a Markov chain. In this paper, we derive a novel algorithm to cluster HMMs through their probability distributions.…
The paper tackles financial market dynamics with new tech-driven data.
Paper combines regularization and pruning to reduce FLOPs in DNNs.
In recent years, China, the United States and other countries, Google and other high-tech companies have increased investment in artificial intelligence. Deep learning is one of the current artificial intelligence research's key areas. This paper analyzes and summarizes the latest progress and future research direction…
We analyze the sectoral dynamics of startup venture financing. Based on a dataset of 52000 start-ups and 110000 funding rounds in the United States from 2000 to 2017, and by applying both Principal Component Analysis (PCA) and Tensor Component Analysis (TCA) in sector space, we visualize and measure the evolution of th…
Lie groups applied to tech progress in economic growth.
A study shows that a fine-tuned model's directional accuracy in financial forecasting is largely due to chance, not skill.
This study finds ESG rating disagreement reduces corporate productivity, especially in certain types of firms.
RegTech improves compliance and risk management through tech solutions.
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 …
REST framework predicts stock trends by considering stock-specific and related-stock events.
Geography effect is investigated for the Chinese stock market including the Shanghai and Shenzhen stock markets, based on the daily data of individual stocks. The Shanghai city and the Guangdong province can be identified in the stock geographical sector. By investigating a geographical correlation on a geographical pa…
In dialogues, an utterance is a chain of consecutive sentences produced by one speaker which ranges from a short sentence to a thousand-word post. When studying dialogues at the utterance level, it is not uncommon that an utterance would serve multiple functions. For instance, "Thank you. It works great." expresses bot…
EarnMore uses masked stock representations to train RL agents for customizable stock pools efficiently.
New methods resolve conflicting treatment effect estimates in health tech assessments.
Effective utilization of photovoltaic (PV) plants requires weather variability robust global solar radiation (GSR) forecasting models. Random weather turbulence phenomena coupled with assumptions of clear sky model as suggested by Hottel pose significant challenges to parametric & non-parametric models in GSR conversio…
A simple and elegant arrangement of stock components of a portfolio (market index-DJIA) in a recent paper [1], has led to the construction of crossing of stocks diagram. The crossing stocks method revealed hidden remarkable algebraic and geometrical aspects of stock market. The present paper continues to uncover new ma…
Graham's formula simplifies stock valuation for growth stocks.
It seems to be very unlikely that all relevant information in the stock market could be fully encoded in a geometrical shape. Still,the present paper will reveal the geometry behind the stock market transactions. The prices of market index (DJIA) stock components are arranged in ascending order from the smallest one in…