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.
VGRSI uses price visibility graphs to generate profitable trading signals.
High-frequency financial data of the foreign exchange market (EUR/CHF, EUR/GBP, EUR/JPY, EUR/NOK, EUR/SEK, EUR/USD, NZD/USD, USD/CAD, USD/CHF, USD/JPY, USD/NOK, and USD/SEK) are analyzed by utilizing the Kullback-Leibler divergence between two normalized spectrograms of the tick frequency and the generalized Jensen-Sha…
We find a sharp local maximum in cross-correlation of EUR/USD and BTC/USD pairs, indicating short-term momentum trading.
Paper examines two methods for FX market volatility modeling.
In the forthcoming ISDA Standard Credit Support Annex (SCSA), the trades denominated in non-G5 currencies as well as those include multiple currencies are expected to be allocated to the USD silo, where the contracts are collateralized by USD cash, or a different currency with an appropriate interest rate overlay to ac…
We develop a maximum penalized quasi-likelihood estimator for estimating in a nonparametric way the diffusion function of a diffusion process, as an alternative to more traditional kernel-based estimators. After developing a numerical scheme for computing the maximizer of the penalized maximum quasi-likelihood function…
We propose a mathematical procedure for finding informed traders in ultra-high frequency trading. We wrote it as Vector ARMA and found condition of its stationarity. For the price exposure complied with ARMA(1,2) we proved that underlying asset price difference can be derived as ARMA(1,1) process. For validation of the…
USD algorithm transports distributions with or without mass conservation.
We propose a Genetic Programming architecture for the generation of foreign exchange trading strategies. The system's principal features are the evolution of free-form strategies which do not rely on any prior models and the utilization of price series from multiple instruments as input data. This latter feature consti…
Machine learning models predict EUR/USD currency direction with 58.52% accuracy.
IUS framework predicts EUR/USD exchange rate with improved accuracy.
Achilles predicts Gold vs USD with a profitable trading bot.
We analyze high-resolution foreign exchange data consisting of 20 million data points of USD-JPY for 13 years to report firm statistical laws in distributions and correlations of exchange rate fluctuations. A conditional probability density analysis clearly shows the existence of trend-following movements at time scale…
Stablecoins are unstable, but some are more stable than others.
Study confirms USD/JPY rises at Gotobi days, suggesting trading strategy.
Study compares GARCH, EWMA, and IV models for GBP/USD and EUR/GBP currency pairs.
Study of volume dynamics at market spread in Bitcoin/USD.
This paper proposes a multi-scale Markov-Switching GARCH model for EUR/USD volatility.
The long-term dependence of Bitcoin (BTC), manifesting itself through a Hurst exponent , is exploited in order to predict future BTC/USD price. A Monte Carlo simulation with geometric fractional Brownian motion realisations is performed as extensions of historical data. The accuracy of statistical inferen…
Model predicts majority of countries will prefer BRI over USD by 2020.
Study examines how Trump tariffs and COVID-19 affected financial market efficiency.
Study uses ML to predict currency and bond returns from news sentiment.
Study shows demonetization strengthened Indian currency and stock market.
RL-Exec uses reinforcement learning to optimize BTC-USD liquidation, outperforming traditional methods.
This paper proposes new GARCH models for cryptocurrency volatility, showing skewed distributions improve prediction accuracy.
SVAR-LiNGAM reveals causal order in crypto-asset markets.
Power spectrum densities for the number of tick quotes per minute (market activity) on three currency markets (USD/JPY, EUR/USD, and JPY/EUR) for periods from January 1999 to December 2000 are analyzed. We find some peaks on the power spectrum densities at a few minutes. We develop the double-threshold agent model and …
Reinforcement learning can interact with the environment and is suitable for applications in decision control systems. Therefore, we used the reinforcement learning method to establish a foreign exchange transaction, avoiding the long-standing problem of unstable trends in deep learning predictions. In the system desig…
Study evaluates early-stage cybersecurity firms' performance using Crunchbase data.
This thesis applies entropy as a model independent measure to address three research questions concerning financial time series. In the first study we apply transfer entropy to drawdowns and drawups in foreign exchange rates, to study their correlation and cross correlation. When applied to daily and hourly EUR/USD and…
This paper models yearly exchange rates between USD/KZT, EUR/KZT and SGD/KZT, and compares the actual data with developed forecasts using time series analysis over the period from 2006 to 2014. The official yearly data of National Bank of the Republic of Kazakhstan is used for present study. The main goal of this paper…
A new fuzzy time series method for non-stationary data.
This paper examines autocorrelation in major crypto markets, finding persistent correlations on short time frames.
Study reduces financial dynamics complexity using PCA for NASDAQ, oil, gold, and USD.
Fast, global, and sensitively reacting to political, economic and social events of any kind, these are attributes that social media like Twitter share with foreign exchange markets. The leading assumption of this paper is that information which can be distilled from public debates on Twitter has predictive content for …
Model estimates LIBOR rates and finds COVID-19 spread spike due to credit risk.
Dynamic functional time-series methods improve forecast accuracy for foreign exchange implied volatility surfaces.
Study improves forex forecasting accuracy using machine learning models.
We investigate the statistical properties of the EBS order book for the EUR/USD and USD/JPY currency pairs and the impact of a ten-fold tick size reduction on its dynamics. A large fraction of limit orders are still placed right at or halfway between the old allowed prices. This generates price barriers where the best …
We present a novel methodology to determine the fundamental value of firms in the social-networking sector based on two ingredients: (i) revenues and profits are inherently linked to its user basis through a direct channel that has no equivalent in other sectors; (ii) the growth of the number of users can be calibrated…
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…
We address the problem of likelihood based inference for correlated diffusion processes using Markov chain Monte Carlo (MCMC) techniques. Such a task presents two interesting problems. First, the construction of the MCMC scheme should ensure that the correlation coefficients are updated subject to the positive definite…
A non-trivial probability structure is evident in the binary data extracted from the up/down price movements of very high frequency data such as tick-by-tick data for USD/JPY. In this paper, we analyze the Sony bank USD/JPY rates, ignoring the small deviations from the market price. We then show there is a similar non-…
We investigate topology and temporal evolution of the foreign currency exchange market viewed from a weighted network perspective. Based on exchange rates for a set of 46 currencies (including precious metals), we construct different representations of the FX network depending on a choice of the base currency. Our resu…
Extended PELCoV for bivariate Student-t copulas to monitor foreign exchange risk.
Sentiment analysis from news and social media predicts forex market movements.
IPO Finance Agent evaluates LLMs on SpaceX IPO due diligence, surpassing Finance Agent v2.
Using 1-min returns of Bitcoin prices, we investigate statistical properties and multifractality of a Bitcoin time series. We find that the 1-min return distribution is fat-tailed, and kurtosis largely deviates from the Gaussian expectation. Although for large sampling periods, kurtosis is anticipated to approach the G…