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James T. E. Chapman and Ajit Desai
This paper assesses the usefulness of comprehensive payments data for macroeconomic predictions in Canada. Specifically, we evaluate which type of payments data are useful, when they are useful, why they are useful, and whether machine learning (ML) mode...
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Dean Fantazzini
In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the da...
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Sailesh BHAGHOE,Gavin OOFT
Pág. 1 - 18
JEL. C22; C53; E37.
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Marcial Messmer and Francesco Audrino
We investigate whether Lasso-type linear methods are able to improve the predictive accuracy of OLS in selecting relevant firm characteristics for forecasting the future cross-section of stock returns. Through extensive Monte Carlo simulations, we show t...
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Boris Andreev, Georgios Sermpinis and Charalampos Stasinakis
Ever since the start of the coronavirus pandemic, lockdowns to curb the spread of the virus have resulted in an increased interest of retail investors in the stock market, due to more free time, capital, and commission-free trading brokerages. This inter...
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Jules Clément Mba, Sutene Mwambetania Mwambi and Edson Pindza
Since its inception in 2009, Bitcoin has increasingly gained main stream attention from the general population to institutional investors. Several models, from GARCH type to jump-diffusion type, have been developed to dynamically capture the price moveme...
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Dimitrios Kartsonakis Mademlis,Nikolaos Dritsakis
Pág. 49 - 60
In several financial applications, it is extremely useful to predict volatility with the highest precision. Neural Networks alongside GARCH-type models have been extensively employed in the last decades for estimating volatility of financial indices. The...
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Marek Kwas and Michal Rubaszek
The random walk, no-change forecast is a customary benchmark in the literature on forecasting commodity prices. We challenge this custom by examining whether alternative models are more suited for this purpose. Based on a literature review and the result...
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Monica Defend, Aleksey Min, Lorenzo Portelli, Franz Ramsauer, Francesco Sandrini and Rudi Zagst
This article considers the estimation of Approximate Dynamic Factor Models with homoscedastic, cross-sectionally correlated errors for incomplete panel data. In contrast to existing estimation approaches, the presented estimation method comprises two exp...
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Rim Ammar Lamouchi
Pág. 29 - 34
This paper examines the market efficiency of Saudi Arabia stock exchange market namely Tadawul All Share Index, TASI, for the period from 1998 to 2020. To test the efficiency of stock market, we analyze the dependence structure of stock market index retu...
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