nep-mst New Economics Papers
on Market Microstructure
Issue of 2021‒01‒25
five papers chosen by
Thanos Verousis

  1. Pricing spread option with liquidity adjustments By Kevin Shuai Zhang; Traian Pirvu
  2. How Do Principal Trading Firms and Dealers Trade around FOMC Statement Releases? By ; James Collin Harkrader
  3. Analysis and Design of Markets for Tradable MobilityCredit Schemes By Siyu Chen; Ravi Seshadri; Carlos Lima Azevedo; Arun P. Akkinepally; Renming Liu; Andrea Araldo; Yu Jiang; Moshe E. Ben-Akiva
  4. Trading on short-term path forecasts of intraday electricity prices By Tomasz Serafin; Grzegorz Marcjasz; Rafal Weron
  5. Imprecise and Informative: Lessons from Market Reactions to Imprecise Disclosure By Cookson, J. Anthony; Moon, S. Katie; Noh, Joonki

  1. By: Kevin Shuai Zhang; Traian Pirvu
    Abstract: We study the pricing and hedging of European spread options on correlated assets when, in contrast to the standard framework and consistent with imperfect liquidity markets, the trading in the stock market has a direct impact on stocks prices. We consider a partial-impact and a full-impact model in which the price impact is caused by every trading strategy in the market. The generalized Black-Scholes pricing partial differential equations (PDEs) are obtained and analysed. We perform a numerical analysis to exhibit the illiquidity effect on the replication strategy of the European spread option. Compared to the Black-Scholes model or a partial impact model, the trader in the full impact model buys more stock to replicate the option, and this leads to a higher option price.
    Date: 2021–01
  2. By: ; James Collin Harkrader
    Abstract: This FEDS Note examines how different types of market participants transact in the Treasury market in the periods immediately following statement releases at the conclusion of Federal Open Market Committee (FOMC) meetings. We compare intermediation patterns following scheduled statement releases with those following an unscheduled statement release.
    Date: 2020–12–31
  3. By: Siyu Chen; Ravi Seshadri; Carlos Lima Azevedo; Arun P. Akkinepally; Renming Liu; Andrea Araldo; Yu Jiang; Moshe E. Ben-Akiva
    Abstract: Tradable mobility credit (TMC) schemes are an approach to travel demand management that have received significant attention in the transportation domain in recent years as a promising means to mitigate the adverse environmental, economic and social effects of urban traffic congestion. In TMC schemes, a regulator provides an initial endowment of mobility credits (or tokens) to all potential travelers. In order to use the transportation system, travelers need to spend a certain amount of tokens (tariff) that could vary with their choice of mode, route, departure time etc. The tokens can be bought and sold in a market that is managed by and operated by a regulator at a price that is dynamically determined by the demand and supply of tokens. This paper proposes and analyzes alternative market models for a TMC system (focusing on market design aspects such as allocation/expiration of credits, rules governing trading, transaction costs, regulator intervention, price dynamics), and develops a methodology to explicitly model the disaggregate behavior of individuals within the market. Extensive simulation experiments are conducted within a departure time context for the morning commute problem to compare the performance of the alternative designs relative to congestion pricing and a no control scenario. The simulation experiments employ a day to day assignment framework wherein transportation demand is modeled using a logit-mixture model and supply is modeled using a standard bottleneck model. The paper addresses a growing and imminent need to develop methodologies to realistically model TMCs that are suited for real-world deployments and can help us better understand the performance of these systems and the impact in particular, of market dynamics.
    Date: 2021–01
  4. By: Tomasz Serafin; Grzegorz Marcjasz; Rafal Weron
    Abstract: We introduce a profitable trading strategy that can support decision-making in continuous intraday markets for electricity. It utilizes a novel forecasting framework, which generates prediction bands from a pool of path forecasts or approximates them using probabilistic price forecasts. The prediction bands then define a time-dependent price level that, when exceeded, indicates a good trading opportunity. Results for the German intraday market show that, in terms of the energy score, our path forecasts beat a well performing similar-day benchmark by over 25%. Moreover, they provide empirical evidence that the increased computational burden induced by generating realistic price paths is offset by higher trading profits. Still, the proposed approximate method offers a reasonable trade-off - it does not require generating path forecasts and yields only slightly lower profits.
    Keywords: Intraday electricity market; Probabilistic forecast; Path forecast; Prediction bands; Energy score; Trading recommendations
    JEL: C22 C32 C51 C53 Q41 Q47
    Date: 2020–12–30
  5. By: Cookson, J. Anthony; Moon, S. Katie; Noh, Joonki
    Abstract: Imprecise language in corporate disclosures can convey valuable information on ?firms' fundamentals during uncertain times. To evaluate this idea, we develop a novel measure of linguistic imprecision based on sentences marked with the \weasel tag" on Wikipedia. For a 10-week window following the 10-K disclosure, we ?nd that the use of imprecise language in 10-Ks predicts 1) positive and non-reverting abnormal returns, 2) improvements to stock liquidity, 3) greater intensities of insider and informed buying, and 4) higher news sentiment. These fi?ndings are the strongest when the fi?rm disclosures are more forward looking, and for fi?rms with greater idiosyncratic volatility. Taken together, our fi?ndings imply that the imprecise language in 10-Ks contains new information on positive but yet immature prospects of future cash flow.
    Date: 2020–12–07

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