Investigating the Impact of Order Flow Imbalance and Information Asymmetry on Treasury Bill Price Changes

Document Type : Research Paper

Authors

1 Assistant Prof., Department of Finance, Faculty of Accounting and Financial Sciences, College of Management, University of Tehran, Tehran, Iran.

2 MSc. Student, Department of Finance, Faculty of Accounting and Financial Sciences, College of Management, University of Tehran, Tehran, Iran.

Abstract

Objective
The information-based model is one of the prevalent frameworks in the market microstructure literature, examining trader behavior in the presence of information asymmetry and its subsequent impact on price formation. Information asymmetry significantly contributes to market inefficiency, manifesting in traders' transactions and orders. Informed traders, possessing knowledge of an asset's intrinsic value through access to comprehensive market information, engage in high-volume transactions and orders to maximize their informational advantages. These value-relevant orders influence the actions of other market participants and consequently affect market prices. Given the critical role of information asymmetry and its effects on traders' order behavior, the study of orders—rather than mere transactions—has gained prominence. Analyzing traders' behavioral patterns through their order prices, volumes, and types provides a clearer understanding of the price effects resulting from market participants' decisions. Considering the price impact of orders and the significance of the secondary market for Islamic treasury bills as a pivotal tool in the central bank's monetary policy and government financing, this study aims to investigate the price effects of order flow on the price fluctuations of Islamic treasury bills in the market.
 
Methods
In this article, according to the price effect of orders in the market, the order flow imbalance variable that shows the changes in supply and demand volume in the first line of the order book has been used. Therefore, the vector autoregressive model has been used to investigate the effect of order flow imbalance on treasury bill price changes. Therefore, to check the price effect of orders, 17 symbols of treasury bills in the over-the-counter market from 2021 to September 2023, which had the most trading days compared to other treasury bills, were used. Therefore, in this research by using the vector autoregressive model and analyzing it through the impulse response function, the effect of order flow imbalance on price changes is investigated in three categories of treasury bills with different maturities to investigate the impact of information asymmetry on orders.
 
Results
According to the findings obtained in this research, the order flow imbalance variable in long-term maturity treasury bills had a greater effect on price changes. Moreover, based on the analyses conducted using the impulse response function, in the event of a shock, the effect of order flow imbalance in long-term maturity treasury bills will remain for extended periods and affect price changes. However, the magnitude of the shock's effect on price changes is much greater than that of the order flow imbalance variable.
 
Conclusion
Therefore, it can be concluded that in long-term maturity treasury bills, the effect of information asymmetry in the order flow is greater than the other bills and can lead to price volatility. Hence, traders should pay more attention to the supply and demand volume of orders and other factors to prevent potential losses.

Keywords

Main Subjects

References

 
Akbari Roshan, M., Ebadi, J. & Mohamadi, S. (2021). Expanding an Information-Based Model Based on Inside and Outside Private Information. Journal of Economic Research (Tahghighat- E- Eghtesadi), 56(2), 205-255. (in Persian)
Asghari, E., Abbasian Fredoni, M. M. & Naslmosavi, S. (2020). The Impact of Investor Sentiments on Stock Market Liquidity. Journal of Accounting Advances, 12(1), 1-27. (in Persian)
Barakchian, S.M. & Seyedsalehi, M. H. (2022). The Effects of Order Flow Imbalance on Stock Prices in Tehran Stock Exchange. Journal of Financial Management Perspective, 12(40), 9 - 27. (in Persian)
Bertsimas, D. & Lo, A. W. (1998). Optimal control of execution costs. Journal of Financial Markets, 1(1), 1-50.
Bissoondoyal-Bheenick, E., Brooks, R. & Do, HX. (2019). Asymmetric relationship between order imbalance and realized volatility: Evidence from the Australian market. International Review of Economics & Finance, 62, 309–320.
Brandt, M.W. & Kavajecz, K.A. (2003). Price Discovery in the U.S. Treasury Market: The Impact of Orderflow and Liquidity on the Yield Curve. The Journal of Finance, 59, 2623-2654.
Cont, R., Cucuringu, M. & Zhang, C. (2023). Cross-Impact of Order Flow Imbalance in Equity Markets. Quantitative Finance, 1–21.
Cont, R., Kukanov, A. & Stoikov, S. (2014). The price impact of order book events. Journal of financial econometrics, 12(1), 47-88.
Copeland, T. E. & Galai, D. (1983). Information Effects on the Bid-Ask Spread. The Journal of Finance, 38(5), 1457–1469.
Easley, D. & O’Hara, M. (1992). Time and the Process of Security Price Adjustment. The Journal of Finance, 47(2), 577–605.
Fleming, M. J. & Remolona, E. M. (1999). Price Formation and Liquidity in the U.S. Treasury Market: The Response to Public Information. Journal of Finance, 54(5), 1901–1915.
Fleming, M. J. (2001). Measuring Treasury Market Liquidity. FRB of New York Staff Report.
Fleming, M.J., Nguyen, G.H. & Ruela, F. (2023). Tick Size, Competition for Liquidity Provision, and Price Discovery: Evidence from the US Treasury Market. Management Science, 886.
Fleming, M. J., Mizrach, B. & Nguyen, G. (2017). The Microstructure of a U.S. Treasury ECN: The BrokerTec Platform. Journal of Financial Markets, 40, 2-22.
Fleming, M. J., Nguyen, G., Engle, R. & Ghysels, E. (2019). Liquidity and Volatility in the U.S. Treasury Market. Journal of Econometrics, 217(2), 207-229.
Hamayeli Mehrabani, T. & Mehrara, M. (2021). Simulating and Estimating Trade Probability Based on Informed Trading in Tehran Stock Exchange. Financial Management Strategy, 9(3), 17-40. (in Persian)
Handa, P. & Schwartz, R. (1996). Limit Order Trading. Journal of Finance, 51(5), 1835–1861.
Hashemi, G. & Eivazlou, R. (2023). Order Imbalance and Stock Price Realized Volatility in Tehran Stock Exchange and Iran Farabourse. Financial Management Strategy, 11(3), 29-50. (in Persian)
Kyle, A. S. (1985). Continuous Auctions and Insider Trading. Econometrica, 53(6), 1315–1335.
Lin, H., Lo, I. & Qiao, R. (2021). Macroeconomic news announcements and market efficiency: Evidence from the U.S. Treasury market. Journal of Banking & Finance, 133, 106252.
Namaki, A., Abbasian, E. & Shafiei, E. (2022). Analyzing of Systemic Risk Contributions of Tehran Stock Exchange Companies by Complexity Approach. Journal of financial Management strategy, 10(36), 91-112. (in Persian)
Nazarpour, M. N. & Sadraei, M. H. (2017). Identification and Ranking of Islamic Treasury Bills' Risks in Iran's Securities Market. Scientific Journal of "Islamic Finance Researches" (IFR), 6(2), 133-166. (in Persian)
Pasquariello, P. & Vega, C. (2007). Informed and Strategic Order Flow in the Bond Markets. Review of Financial Studies, 20(6), 1975-2019.
Rastegar, M. A. & Saedi Far, K. (2017). Optimal Execution Strategy: An Agent-based Approach. Financial Research Journal, 19(2), 262-239. (in Persian)
Vega, C. & Miller, C.S. (2009). Market Microstructure Division of International Finance. Board of Governors of the Federal Reserve System, Springer, New York, 5392–5404.
Financial Research Journal
Volume 26, Issue 2
2024
Pages 447-475

Files

Share

How to cite

Statistics