Author:
Fatouros Georgios,Makridis Georgios,Soldatos John,Ristau Petra,Monferrino Vittorio
Abstract
AbstractRisk assessment is of high importance when it comes to trading, investments, and other financial activities, as poor risk monitoring could lead to inefficient investments, loss of capital, and penalties by regulatory authorities. Thus, robust risk models, capable of yielding real-time results, are valuable assets for investment banking. This chapter introduces a financial tool that can provide risk assessment on Forex portfolios in (near) real-time and pre-trade analysis at rest. Financial risk is measured in terms of both Value at Risk and the Expected Shortfall, with the respective models utilizing not only statistical but also deep learning techniques that achieve accurate results. Moreover, the proposed application, based on state-of-the-art data management technologies, provides real-time risk assessments, utilizing the latest market data. These features along with the provided pre-trade analysis make this solution a valuable tool for practitioners in high frequency trading (HFT) and investment banking in general.
Publisher
Springer International Publishing
Reference23 articles.
1. Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2007). Journal of international Economics, 73(2), 251.
2. Mengle, D. L., Humphrey, D. B., & Summers, B. J. (1987). Economic Review 73, 3.
3. Kearns, M., & Nevmyvaka, Y. (2013). High frequency trading: New realities for traders, markets, and regulators.
4. Bredin, D., & Hyde, S. (2004). Journal of Business Finance & Accounting, 31(9–10), 1389.
5. Préfontaine, J., Desrochers, J., & Godbout, L. (2010). The Analysis of comments received by the BIS on principles for sound liquidity risk management and supervision. International Business & Economics Research Journal (IBER), 9(7). https://doi.org/10.19030/iber.v9i7.598