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on Market Microstructure |
| By: | Boudiaf, Ismael Alexander; Scheicher, Martin; Frieden, Immo |
| Abstract: | This paper studies market liquidity in interest rate swaps (IRS) before and during the global tightening of monetary policy. IRS constitute the single largest derivatives segment globally. Banks and Pension Funds extensively rely on IRS to hedge interest rate risk. Hence, providing an understanding of this market and the drivers of market liquidity is a key research question in the current market context. We use price and volume data from around 338.000 trades in the most active long-horizon swap contract denominated in EUR to construct seven liquidity measures. Taking a comprehensive approach, we ap-ply linear regressions to determine the drivers of variation in liquidity. Our liquidity measures are significantly related to monetary policy, market-wide fixed income liquidity, EURIBOR rate volatility and Dealer behaviour. Indicators for generic market stress such as VIX which are often documented in the literature are not strongly connected to IRS trading conditions. JEL Classification: G12, G15 |
| Keywords: | fixed income, liquidity, market structure, swap |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:srk:srkwps:2024147 |
| By: | Vito Alessandro Monaco; Antonio Riva; Luca Sabbioni; Lorenzo Bisi; Edoardo Vittori; Marco Pinciroli; Michele Trapletti; Marcello Restelli |
| Abstract: | In recent years, the popularity of artificial intelligence has surged due to its widespread application in various fields. The financial sector has harnessed its advantages for multiple purposes, including the development of automated trading systems designed to interact autonomously with markets to pursue different aims. In this work, we focus on the possibility of recognizing and leveraging intraday price patterns in the Foreign Exchange market, known for its extensive liquidity and flexibility. Our approach involves the implementation of a Reinforcement Learning algorithm called Fitted Natural Actor-Critic. This algorithm allows the training of an agent capable of effectively trading by means of continuous actions, which enable the possibility of executing orders with variable trading sizes. This feature is instrumental to realistically model transaction costs, as they typically depend on the order size. Furthermore, it facilitates the integration of risk-averse approaches to induce the agent to adopt more conservative behavior. The proposed approaches have been empirically validated on EUR-USD historical data. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.23294 |