The impact of VXY and EM-VXY on the implied volatility of ATM option premiums for the USD/MXN exchange rate on the CBOE

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Daniel García Luna Romero
José Ricardo Salazar Garza
Lucio Alán Luis Zatarain
Jesús Alberto Zavala Durón


A series of econometric tests is proposed to study the impact of the VXY and EM-VXY indices on the implicit volatility of at-the-money options of the USD/MXN exchange rate and the premiums on their call and put options. The objective is to determine if these indicators can predict future changes in implied volatility and be used as entry or exit flags in investment and hedging strategies. Additionally, the volatility index (VIX), the USD/MXN exchange rate, and the Mexican Federal Treasury Certificates and London Interbank Offered Rate rates are included as complementary variables. Results show that although the EM-VXY, VIX, and the exchange rate are statistically significant for implicit volatility modeling, they do not have a predictive power that allows them to be used as entry or exit indicators. None of the variables are significant for modeling the premiums in call and put options. This research contributes to the filtering of instruments that, despite their design, may not contribute to the understanding of markets in emerging countries, such as Mexico. Future studies can extend this methodology to other exchange rates, trying different combinations of rates.


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García Luna Romero, D., Salazar Garza, J. R., Luis Zatarain, L. A., & Zavala Durón, J. A. (2023). The impact of VXY and EM-VXY on the implied volatility of ATM option premiums for the USD/MXN exchange rate on the CBOE. The Anáhuac Journal, 23(2), 38–67.
Biografía del autor/a

Daniel García Luna Romero, Universidad de Monterrey (UDEM), Mexico

Daniel García Luna Romero was born and raised in Monterrey, Mexico. Daniel has earned a Master’s Degree in Business Administration (MBA), a Specialty Degree in Finance and a Bachelor’s degree in Mechatronics Engineering from Universidad de Monterrey (UDEM), graduating with honors (Cum-Laude) in both Master and Baccalaureate studies. After driving the digitalization of the finance and quality departments in transnational companies belonging to the steel and manufacturing industries through roles such as Data Analyst, Data Engineer and Data Science Coordinator, Daniel is currently leading the digital transformation of the Internal Audit Department of Grupo FEMSA, a Mexican multinational beverage and retail company, as the Analytics Manager of its Internal Audit’s Center of Excellence.

José Ricardo Salazar Garza, Universidad de Monterrey (UDEM), Mexico

José Ricardo Salazar Garza is full-time professor at Universidad de Monterrey (UDEM) and International Professor at ESAN University in Lima, Peru. Subdirector of Foreign Exchange Operations at Vector Casa de Bolsa, with extensive experience in handling Financial Derivatives Instruments and Risk  anagement. He also served as the Brand Director of BMW Galería and Finance Director in different companies in Monterrey.
Currently, he is a Financial Advisor for the business group Dealcenter. With 19 years of experience in the educational sector, he has been the Academic Director for the Departments of Economics, Accounting, and Finance. He teaches at both the postgraduate and undergraduate levels, focusing on finance-related subjects, and regularly conducts classes in Mexico and Peru. Among the courses he teaches are Derivatives Market, Business Valuation, and Stock Market Finance, among others.
He is also a professor in the Corporate Finance diploma program, where he teaches Instruments and Financial Operations. He holds a Master’s degree in Finance from ITESM, a Doctorate in Administration from the Autonomous University of Nuevo León, and has completed diploma programs at the New York Institute of Finance
and the Institute of Stock Market Studies in Madrid.

Lucio Alán Luis Zatarain, Universidad de Monterrey (UDEM), Mexico

Lucio Alán Luis Zatarain graduated from Mechanical Engineering back in 2014, from the Universidad Autónoma de Nuevo León, with certifications in supply chain and effective negotiation. Postgraduate studies in International Finance and a Master’s in Business Administration from the Universidad de Monterrey. He has worked in different sectors such as Home Appliances, Automotive and Healthcare, developing commodity and category strategies for global strategic sourcing. Wide experience in
commercial negotiations, contract management, supplier development, cost savings and new product introduction. He currently holds a Global Procurement Manager role in Becton Dickinson, a Fortune 500 company in the Healthcare industry.

Jesús Alberto Zavala Durón, Universidad de Monterrey (UDEM), Mexico

Jesús Alberto Zavala Durón graduated as a Public Accountant from the Universidad Autónoma de Nuevo León (UANL), with a Specialization in Finance and a Master’s degree in Administration (MBA) from the Universidad de Monterrey (UDEM). He has held different positions focused on the administrative area. Currently, he is in charge of the administration, finance, and tax areas of Inmobiliaria 78, a subsidiary company of Grupo FEMSA, and is also a member of the real estate acquisition committee of both Inmobiliaria 78 and Cadena Comercial OXXO, both subsidiary companies of Grupo FEMSA.


Avendaño Cruz, S. & Mata Hernández, J.M. (2021). Pronóstico del tipo de cambio USD MXN durante el COVID-19 con métodos de suavización y descomposición. Revista Enfoques. Ciencia Política y Administración Pública, 19 (34), 1-15.

Banco de México (n.d.). Certificados de la Tesorería de la Federación. Secretaría de Hacienda y Crédito Público, Banco de México, 1-8.

Black, F. & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81 (3), 637.

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, vol. 31 (3), 307-327.

Breusch, T.S. & Pagan, A.R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47 (5), 1287–1294.

D’Agostino, G., Di, E., Enrique F., Marques, S., Reif, S., & García, J.(2013). Volatilidad implícita en opciones. El rol de la fórmula de Black and Scholes y la posibilidad de cálculo sin asumir un modelo determinado. Revista de Investigación en Modelos Financieros, 1 (1). pdf

Engle, R.F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50 (4), 987-1007.

Fassas, A.P. & Siriopoulos, C. (2021). Implied volatility indices - A review. Quarterly Review of Economics and Finance, 79, 303-329.

Fleming, J., Ostdiek, B. & Whaley, R.E. (1995). Predicting stock market volatility: A new measure. Journal of Futures Markets, 15 (3), 265-302.

ICE (2023) LIBOR, ICE Benchmark Administration. ICE NYSE.

İskenderoglu, O. & Akdag, S. (2020) Comparison of the effect of Vix fear index on stock exchange indices of developed and developing countries: The G20 case. South East European Journal of Economics and Business, 15 (2), 105-121.

JP Morgan, Reuters, (1996) RiskMetrics-Technical Document.

Latané, H.A. & Rendleman Jr., R.J. (1976). Standard deviations of stock price ratios implied in option prices. (Papers and Proceedings of the Thirty-Fourth Annual Meeting of the American Finance Association Dallas, Texas December 28-30, 1975) The Journal of Finance, 31 (2), 369-381.

Liao, S., Chen, J. & Ni, H. (2021). Forex trading volatility prediction using Neural Network Models. arXiv:2112.01166 [q-fin.ST], 1-21.

Lorenzo Alegría, R.M. (1996). La volatilidad: modelización en la valoración de opciones y estimadores. Investigaciones Europeas de Dirección y Economía de la Empresa, 2 (1), 59-83.

Mushtaq, R. (2011). Testing time series data for stationarity.

Normand, J. & Sandilya, A. (2006). Introducing the JPMorgan VXY & EM-VXY. JPMorgan.

Olden, J.D. & Jackson, D.A. (2002). Illuminating the “black box”: A randomization approach for understanding variable contributions in artificial neural networks. Ecological Modelling, 154 (1/2), 135-150.

Pilbeam, K. & Langeland, K.N. (2015). Forecasting exchange rate volatility: GARCH models versus implied volatility forecasts. International Economics and Economic Policy, 12 (1), 127-142.

Roberts, S.W. (2000). Control Chart Tests Based on Geometric Moving Averages. Technometrics, 42 (1), 97-101.

Solís, S. & Muñoz, L. (2019). Volatilidad del tipo de cambio en México: ¿Síntoma de la enfermedad holandesa? Gestión y estrategia, 55, 75-89.

Whaley, R.E. (2009). Understanding the VIX. Journal of Portfolio Management, 35 (3), 98-106.

White, K.J. (1992). The Durbin-Watson Test for Autocorrelation in Nonlinear Models. The Review of Economics and Statistics, 74 (2), 370-373.