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.
German FinBERT improves financial text analysis performance.
This paper analyzes financial sentiment using LLMs and FinBERT, improving accuracy with few-shot examples.
FinBERT model identifies key speakers in earnings calls, boosting stock returns.
Study uses FinBERT for financial sentiment analysis to predict stock movement.
Study compares AI models for stock price prediction using financial news.
FinBERT-BiLSTM predicts cryptocurrency prices using sentiment analysis.
Predict stock prices using financial news sentiment analysis.
Proposes a regularization approach to model German power derivative market, identifying significant risk spillovers.
Large language models predict stock market returns better than traditional methods.
Study reveals stylized facts in German bond futures markets.
Framework integrates financial and annual report data for better corporate credit ratings.
FinBERT-XRC model assesses financial report risk, offering transparent explanations.
This study evaluates LLMs for sentiment analysis in stock price prediction.
How does dynamic price information flow among Northern European electricity spot prices and prices of major electricity generation fuel sources? We use time series models combined with new advances in causal inference to answer these questions. Applying our methods to weekly Nordic and German electricity prices, and oi…
Improved crude oil price forecasting using multi-dimensional LLM sentiment signals.
We present a relatively detailed analysis of the persistence probability distributions in financial dynamics. Compared with the auto-correlation function, the persistence probability distributions describe dynamic correlations non-local in time. Universal and non-universal behaviors of the German DAX and Shanghai Index…
Short-term probabilistic forecasting of German electricity imbalance prices.
Detects out-of-distribution sentences in Neural Machine Translation.
Research optimizes a small RES utility's portfolio by dynamically trading in German electricity markets.
Investigates if adding cryptocurrencies to German portfolios diversifies better, finding mixed results.
Hybrid engine analyzes news sentiment for markets in real-time.
The grid integration of intermittent Renewable Energy Sources (RES) causes costs for grid operators due to forecast uncertainty and the resulting production schedule mismatches. These so-called profile service costs are marginal cost components and can be understood as an insurance fee against RES production schedule u…
In the following paper, we analyse the ID-Price in the German Intraday Continuous electricity market using an econometric time series model. A multivariate approach is conducted for hourly and quarter-hourly products separately. We estimate the model using lasso and elastic net techniques and perform an out-of-samp…
Low redispatch prices boost green hydrogen production cost, encouraging electrolyzer siting.
Based on the tick-by-tick stock prices from the German and American stock markets, we study the statistical properties of the distribution of the individual stocks and the index returns in highly collective and noisy intervals of trading, separately. We show that periods characterized by the strong inter-stock coupling…
Study on excess mortality in Germany during 2020-21.
For the first time, we apply the wavelet coherence methodology on biofuels (ethanol and biodiesel) and a wide range of related commodities (gasoline, diesel, crude oil, corn, wheat, soybeans, sugarcane and rapeseed oil). This way, we are able to investigate dynamics of correlations in time and across scales (frequencie…
Recent works have highlighted the strength of the Transformer architecture on sequence tasks while, at the same time, neural architecture search (NAS) has begun to outperform human-designed models. Our goal is to apply NAS to search for a better alternative to the Transformer. We first construct a large search space in…
We investigate the large-volatility dynamics in financial markets, based on the minute-to-minute and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after large volatilities is characterized by a power law, and the exponents usually vary with the strength of the large vo…
We investigate the large-fluctuation dynamics in financial markets, based on the minute-to-minute and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after the large fluctuations is characterized by a power law, and the exponents usually vary with the strength of the lar…
In this paper, we present Neural Phrase-based Machine Translation (NPMT). Our method explicitly models the phrase structures in output sequences using Sleep-WAke Networks (SWAN), a recently proposed segmentation-based sequence modeling method. To mitigate the monotonic alignment requirement of SWAN, we introduce a new …
PreBit predicts Bitcoin price movements using social media and financial data.
One of the findings of the recent literature is that the 2008 financial crisis caused reduction in international diversification benefits. To fully understand the possible potential from diversification, we build an empirical model which combines generalised autoregressive score copula functions with high frequency dat…
These are notes of a talk I gave in a seminar at the University of Pennsylvania summarizing results in the Habilitation by Jost Eschenburg on "Freie isometrische Aktionen auf kompakten Lie-Gruppen mit positiv gekruemmten Orbitraeumen". Due to the fact that it is published in a not easily accesible journal (and is writt…
Paper models and forecasts intra-day electricity price spreads.
The study uses neural networks to classify and predict coronavirus data.
THieF improves day-ahead electricity price prediction accuracy by reconciling hourly and block forecasts.
The article prices exchange options using variance gamma-like models.
Paper proposes a new method for probabilistic electricity price forecasting.
This paper contributes to the literature on international stock market comovements and contagion. The novelty of our approach lies in application of wavelet tools to high-frequency financial market data, which allows us to understand the relationship between stock markets in a time-frequency domain. While major part of…
This paper has been submitted to the Proceedings of the Australian-German Workshop on Differential Geometry in the Large held at the mathematical research institute MATRIX in Creswick, Victoria, Australia, Feb.2-Feb.14, 2019. We describe and discuss 2 important open problems in Sasaki geometry.
Based on the tick-by-tick price changes of the companies from the U.S. and from the German stock markets over the period 1998-99 we reanalyse several characteristics established by the Boston Group for the U.S. market in the period 1994-95, which serves to verify their space and time-translational invariance. By increa…
We determine the distribution of size and growthrates of German business firms in 1987-1997. We find a log-normal size distribution. The distribution of growth rates has fat tails. It can be fitted to an exponential in a narrow central region and is dominated by finite-sample-size effects far in its wings. We study the…
A quantitative check of weak efficiency in US dollar/German mark exchange rates is developed using high frequency data. We show the existence of long term return anomalies. We introduce a technique to measure the available information and show it can be profitable following a particular trading rule.
Study combines sentiment analysis with traditional models for better S&P 500 trading.
Optimal energy trading strategy for intraday markets using Hawkes processes.
Ordinal regression falls between discrete-valued classification and continuous-valued regression. Ordinal target variables can be associated with ranked random variables. These random variables are known as order statistics and they are closely related to ordinal regression. However, the challenge of using order statis…
The goal of this modern presentation, followed by an English translation from the German, is to make available some parts of Lie's very systematic mathematical thought which deserve to join the contemporary literature, and above all also, to be read.