Design of a microscopic model adapted to emerging financial markets
the case of the Moroccan financial market
DOI:
https://doi.org/10.59051/joaf.v13i1.514Keywords:
Adaptive Markets Hypothesis (AMH), Agent-Based Model (ABM), Degree of time-varying market efficiency, Efficiency Market Hypothesis (EMH), stylized factsAbstract
Objective: The aim of of this article is to design a microscopic model, under the Adaptive Market Hypothesis (AMH), which can explain the formation of equilibrium prices and the market efficiency dynamics of the Moroccan financial market.
Methods: Our model combines investor behavior and market microstructure. To validate the model, we performed simulations under two scenarios. The first scenario integrates the two compartments of the model. The second scenario only examines the impact of the microstructure.
Results: Numerical simulations show that the model is robust to the facts observed in the Moroccan financial market.
Originality / Implications : This is the first model developed under the AMH approach which considers the specificity of emerging financial markets such as the Moroccan financial market. The model has important implications for both regulatory policies and the construction of investment strategies.
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Almudhaf, F., Aroul, R. R., & Hansz, J. A. (2020). Are markets adaptive? Evidence of predictability and market efficiency of lodging/resort reits. International Journal of Strategic Property Management, 24(2), 130‑139. https://doi.org/10.3846/ijspm.2020.11547
Arthur, W. B., Holland, J. H., LeBaron, B., Palmer, R., & Tayler, P. (1996). Asset pricing under endogenous expectations in an artificial stock market. The economy as an evolving complex system II, 27.
Box, G. E., & Pierce, D. A. (1970). Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. Journal of the American statistical Association, 65(332), 1509‑1526.
Challet, D., Chessa, A., Marsili, M., & Zhang, Y.-C. (2001). From minority games to real markets.
Chiarella, C., & Iori, G. (2002). A simulation analysis of the microstructure of double auction markets*. Quantitative finance, 2(5), 346‑353.
Chiarella, C., Iori, G., & Perelló, J. (2009). The impact of heterogeneous trading rules on the limit order book and order flows. Journal of Economic Dynamics and Control, 33(3), 525‑537.
Cont, R. (1999). Modeling economic randomness : Statistical mechanics of market phenomena. in: M. Batchelor & LT Wille (Eds.) Statistical Physics on the eve of the 21st century, Singapore: World Scienti.
Cont, R. (2001). Empirical properties of asset returns : Stylized facts and statistical issues. Quantitative Finance, 1(2), 223‑236. https://doi.org/10.1080/713665670
Cross, R., Grinfeld, M., Lamba, H., & Seaman, T. (2005). A threshold model of investor psychology. Physica A: Statistical Mechanics and its Applications, 354, 463‑478.
El Oubani, A., & Lekhal, M. (2021). An agent-based model of financial market efficiency dynamics. Borsa ̇Istanbul Review. https://doi.org/10.1016/j.bir.2021.10.005
Farmer, J. D., & Joshi, S. (2002). The price dynamics of common trading strategies. Journal of Economic Behavior & Organization, 49(2), 149‑171.
Ghazani, M. M., & Araghi, M. K. (2014). Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency : Evidence from the Tehran stock exchange. Research in International Business and Finance, 32, 50‑59. https://doi.org/10.1016/j.ribaf.2014.03.002
Ghazani, M. M., & Ebrahimi, S. B. (2019). Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency : Evidence from the crude oil prices. Finance Research Letters, 30, 60‑68. https://doi.org/10.1016/j.frl.2019.03.032
Ghoulmie, F., Cont, R., & Nadal, J.-P. (2005). Heterogeneity and feedback in an agent-based market model. Journal of Physics: Condensed Matter, 17(14), S1259‑S1268. https://doi.org/10.1088/0953-8984/17/14/015
Giardina, I., & Bouchaud, J.-P. (2003). Bubbles, crashes and intermittency in agent based market models. The European Physical Journal B-Condensed Matter and Complex Systems, 31(3), 421‑437.
Guillaume, D. M., Dacorogna, M. M., Davé, R. R., Müller, U. A., Olsen, R. B., & Pictet, O. V. (1997). From the bird’s eye to the microscope : A survey of new stylized facts of the intra-daily foreign exchange markets. Finance and stochastics, 1(2), 95‑129.
Hall, A. D., & Hautsch, N. (2006). Order aggressiveness and order book dynamics. Empirical Economics, 30(4), 973‑1005.
Iori, G. (2002). A microsimulation of traders activity in the stock market : The role of heterogeneity, agents’ interactions and trade frictions. Journal of Economic Behavior & Organization, 49(2), 269‑285.
Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics letters, 6(3), 255‑259.
Kim, J. H. (2009). Automatic variance ratio test under conditional heteroskedasticity. Finance Research Letters, 6(3), 179‑185. https://doi.org/10.1016/j.frl.2009.04.003
Kirman, A., & Teyssiere, G. (2002). Microeconomic models for long memory in the volatility of financial time series. Studies in Nonlinear Dynamics & Econometrics, 5(4).
Konté, M. A. (2011). A link between random coefficient autoregressive models and some agent based models. Journal of Economic Interaction and Coordination, 6(1), 83‑92.
LeBaron, B. (1999). Evolution and time horizons in an agent based stock market. Available at SSRN 218309.
LeBaron, B. (2006). Agent-based computational finance. Handbook of computational economics, 2, 1187‑1233.
Lekhal, M., & El Oubani, A. (2020). Does the Adaptive Market Hypothesis explain the evolution of emerging markets efficiency ? Evidence from the Moroccan financial market. Heliyon, 6(7), e04429.
Lim, K.-P., & Brooks, R. (2011). The evolution of stock market efficiency over time : a survey of the empirical literature. Journal of Economic Surveys, 25(1), 69‑108. https://doi.org/10.1111/j.1467-6419.2009.00611.x
Lo, A. W. (2004). The adaptive markets hypothesis. The Journal of Portfolio Management, 30(5), 15‑29.
Lo, A. W. (2005). Reconciling Efficient Markets with Behavioral Finance : The Adaptive Markets Hypothesis. Journal of Investment Consulting, 7(2), 21‑44.
Lux, T., & Marchesi, M. (2000). Volatility clustering in financial markets : A microsimulation of interacting agents. International journal of theoretical and applied finance, 3(04), 675‑702.
McLeod, A. I., & Li, W. K. (1983). Diagnostic checking ARMA time series models using squared-residual autocorrelations. Journal of Time Series Analysis, 4(4), 269‑273. https://doi.org/10.1111/j.1467-9892.1983.tb00373.x
Shahid, M. N., Coronado, S., & Sattar, A. (2019). Stock market behaviour : Efficient or adaptive ? Evidence from the Pakistan Stock Exchange. 26.
Zovko, I. I., & Farmer, J. D. (2002). The power of patience : A behavioural regularity in limit-order placement. Quantitative finance, 2(5), 387.
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