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This paper estimates the carry embedded in listed IBIT options and compares it with the carry embedded in matched CME bitcoin futures. Put-call parity recovers an implied forward on the ETF; BlackRock's daily holdings file maps each ETF…
The Foreign Exchange (Forex) is a large decentralized market, on which trading analysis and algorithmic trading are popular. Research efforts have been focusing on proof of efficiency of certain technical indicators. We demonstrate,…
Modeling wind speed is one of the key element when dealing with the production of energy through wind turbines. A good model can be used for forecasting, site evaluation, turbines design and many other purposes. In this work we are…
In financial trading, return prediction is one of the foundation for a successful trading system. By the fast development of the deep learning in various areas such as graphical processing, natural language, it has also demonstrate…
We derive a simple relation for estimating the relative emittance growth in x and y due to intrabeam scattering (IBS) in electron storage rings. We show that IBS calculations for the ATF damping ring, when using the formalism of…
The large integration of variable energy resources is expected to shift a large part of the energy exchanges closer to real-time, where more accurate forecasts are available. In this context, the short-term electricity markets and in…
The paper investigates the effect of the label green in bond markets from the lens of the trading activity. The idea is that jumps in the dynamics of returns have a specific memory nature that can be well represented through a self-exciting…
The development of reinforced learning methods has extended application to many areas including algorithmic trading. In this paper trading on the stock exchange is interpreted into a game with a Markov property consisting of states,…
We empirically analyze the scaling properties of daily Foreign Exchange rates, Stock Market indices and Bond futures across different financial markets. We study the scaling behaviour of the time series by using a generalized Hurst exponent…
This paper is to explore the possibility to use alternative data and artificial intelligence techniques to trade stocks. The efficacy of the daily Twitter sentiment on predicting the stock return is examined using machine learning methods.…
Predicting the trend of Bitcoin, a highly volatile cryptocurrency, remains a challenging task. Accurate forecasting holds immense potential for investors and market participants dealing with High Frequency Trading systems. The purpose of…
In finance, the weak form of the Efficient Market Hypothesis asserts that historic stock price and volume data cannot inform predictions of future prices. In this paper we show that, to the contrary, future intra-day stock prices could be…
This paper introduces Targeted Function Balancing (TFB), a covariate balancing weights framework for estimating the average treatment effect of a binary intervention. TFB first regresses an outcome on covariates, and then selects weights…
Extreme Value Theory (EVT) is one of the most commonly used approaches in finance for measuring the downside risk of investment portfolios, especially during financial crises. In this paper, we propose a novel approach based on EVT called…
Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network…
A number of inhibitory and excitatory factors regulate the beating of the heart. Consequently, the inter-beat intervals (IBIs) are not constant but vary around a mean value, even in the absence of external factors like exercise or stress.…
In todays global economy, accuracy in predicting macro-economic parameters such as the foreign the exchange rate or at least estimating the trend correctly is of key importance for any future investment. In recent times, the use of…
The Foreign Exchange market is a significant market for speculators, characterized by substantial transaction volumes and high volatility. Accurately predicting the directional movement of currency pairs is essential for formulating a sound…
We analyze the Bombay stock exchange (BSE) price index over the period of last 12 years. Keeping in mind the large fluctuations in last few years, we carefully find out the transient, non-statistical and locally structured variations. For…
We introduce a new machine learning approach to detect value-relevant foreign information for both domestic and multinational companies. Candidate foreign signals include lagged returns of stock markets and individual stocks across 47…