Financial Econometrics: An Example-Based Handbook

Anokye Mohammed Adam, Ph.D.
University of Cape Coast, Cape Coast, Ghana

Peterson Owusu Junior
Department of Business Administration, Westend University College, Accra, Ghana

Series: Economic Issues, Problems and Perspectives
BISAC: BUS001010




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Financial modelling – and for that matter, quantitative finance – is a very crucial area of study for the decision makers to make informed and robust choices in matters of interest to the growth and survival of their organisations. Thus, the skills and knowledge (at least, in this book) must be possessed by every finance professional; risk analysts, quantitative analysts, asset and portfolio managers, compliance officers, Forex and Contract for Difference (CFD) traders, etc. Econometric and statistical models employed in financial modelling are too many to be captured under this course. The econometric models captured in this book are for the purposes of fostering understanding, appreciation, and the reality of the mathematics beneath the topics in econometrics. Broadly speaking, this book covers the various facets of regression models in this important field. Diagnostics on the linear regression model, Logit and Probit (Categorical Dependent Variable Models), Stationary and Non-Stationary Time Series, Cointegration and Error Correction Models (ECM), Autoregressive Distributed Lag (ARDL) Models, forecasting with ARIMA and Vector Autoregression (VAR) models, Panel Data Regression Models, and finally Asset Price/Return Volatility: ARCH and GARCH Models are illustrated for easy comprehension. (Imprint: Nova)


Chapter 1. Financial Modelling (pp. 1-24)

Chapter 2. Linear Regression Models (pp. 25-40)

Chapter 3. Regression Diagnostics (pp. 41-98)

Chapter 4. Categorical Variable Models (pp. 99-124)

Chapter 5. Stationary and Non-Stationary Time Series (pp. 125-200)

Chapter 6. Dynamic Models II (pp. 201-256)

Chapter 7. Panel Data Regression Models (Pooling and Panel Estimation) (pp. 257-290)

Chapter 8. Asset Price and Return Volatility (pp. 291-314)


About the Authors

Index (pp. 327)

Akgiray, V. (1989). Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts. Journal of Business, 55–80. Retrieved from
Alexander, C. (2008). Market Risk Analysis, Practical Financial Econometrics (Vol. II). West Sussex, United Kingdom: Wiley.
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Ebens, H. (2001). The distribution of realized stock return volatility. Journal of Financial Economics, 61(1), 43–76. Retrieved from
Appiah-Kusi, J., & Menyah, K. (2003). Return predictability in African stock markets. Review of Financial Economics, 12(3), 247–270.
Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297.
Asiedu, E. (2002). On the determinants of foreign direct investment to developing countries: is Africa different? World Development, 30(1), 107–119. Retrieved from
Baddeley, M., & Barrowclough, D. (2009). Running regressions : a practical guide to quantitative research in economics, finance and development studies. Cambridge [u.a.] : Cambridge Univ. Press.
Bai, J., & Ng, S. (2004). A PANIC Attack on Unit Roots and Cointegration. Econometrica, 72(4), 1127–1177.
Baltagi, B. H. (2005). Econometric Analysis of Panel Data. Wiley.
Baltagi, B. H., & Kao, C. (2000). Nonstationary panels, cointegration in panels and dynamic panels: A survey. Syracuse University Center for Policy Research Working Paper, (16). Retrieved from =1808022.
Baltagi, B. H., & Wu, P. X. (1999). Unequally spaced panel data regressions with AR (1) disturbances. Econometric Theory, 15(06), 814–823.
Banerjee, A. (1999). Panel Data Unit Roots and Cointegration: An Overview. Oxford Bulletin of Economics and Statistics, 61(S1), 607–629.
Bhargava, A., Franzini, L., & Narendranathan, W. (1982). Serial correlation and the fixed effects model. The Review of Economic Studies, 49(4), 533–549.
Binder, M., Hsiao, C., & Pesaran, M. H. (2005). Estimation and inference in short panel vector autoregressions with unit roots and cointegration. Econometric Theory, 21(04), 795–837.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Bollerslev, T. (1987). A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return. The Review of Economics and Statistics, 69(3), 542–47. Retrieved from
Breitung, J., & Meyer, W. (1994). Testing for unit roots in panel data: are wages on different bargaining levels cointegrated? Applied Economics, 26(4), 353–361.
Brooks, C. (2008). Introductory Econometrics for Finance (2 edition). Cambridge England ; New York: Cambridge University Press.
Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society. Series B (Methodological), 149–192. Retrieved from
Chang, Y. (2002). Nonlinear IV unit root tests in panels with cross-sectional dependency. Journal of Econometrics, 110(2), 261–292.
Chang, Y. (2004). Bootstrap unit root tests in panels with cross-sectional dependency. Journal of Econometrics, 120(2), 263–293.
Chu, S.-H., & Freund, S. (1997). Volatility estimation for stock index options: a GARCH approach. The Quarterly Review of Economics and Finance, 36(4), 431–450. Retrieved from 6900447.
Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20(2), 249–272.
Choi, I. (2002). Combination Unit Root Tests for Cross-Sectionally Correlated Panels. Mimeo, Hong Kong University of Science and Technology.
Cryer, J. D., & Chan, K.-S. (2008a). Models for Nonstationary Time Series. Time Series Analysis: With Applications in R, 87–107. Retrieved from /chapter/10.1007/978-0-387-75959-3_5.
Cryer, J. D., & Chan, K.-S. (2008b). Models For Stationary Time Series. Time Series Analysis: With Applications in R, 55–85. Retrieved from /content/pdf/10.1007/978-0-387-75959-3_4.pdf.
Cryer, J. D., & Chan, K.-S. (2008c). Time series regression models. Time Series Analysis: With Applications in R, 249–276. Retrieved from
Cryer, J. D., & Kellet, N. (1986). Time series analysis (Vol. 286). Springer. Retrieved from
DeJong, D. N., & Whiteman, C. H. (1991). Reconsidering “trends and random walks in macroeconomic time series.” Journal of Monetary Economics, 28(2), 221–254.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431.
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: Journal of the Econometric Society, 1057–1072.
Dimson, E. (1979). Risk measurement when shares are subject to infrequent trading. Journal of Financial Economics, 7(2), 197–226. Retrieved from
Dunning, J. H. (2001). The eclectic (OLI) paradigm of international production: past, present and future. International Journal of the Economics of Business, 8(2),
173–190. Retrieved from /13571510110051441.
Edwards, S. (2001). Capital mobility and economic performance: Are emerging economies different? National bureau of economic research. Retrieved from
Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987–1007.
Engle, R. F., & Lee, G. (1999). A long-run and short-run component model of stock return volatility. Cointegration, Causality, and Forecasting: A Festschrift in Honour of Clive WJ Granger, 475–497.
Engle, R. F., & Ng, V. K. (1993). Measuring and testing the impact of news on volatility. The Journal of Finance, 48(5), 1749–1778. Retrieved from
EViews. (2015). EViews User Guide. IHS Global Inc.
Fama, E. (1965). The behavior of stock market prices. Journal of Business, 38, 34–105.
Fisher, R. A. S. (1938). Statistical methods for research workers (7th ed., rev. and enl). Edinburgh Oliver and Boyd. Retrieved from
Fossati, S. (2013). Unit root testing with stationary covariates and a structural break in the trend function. Journal of Time Series Analysis, 34(3), 368–384.
Fowler, D. J., & Rorke, C. H. (1983). Risk measurement when shares are subject to infrequent trading: Comment. Journal of Financial Economics, 12(2), 279–283. Retrieved from _3a2_3ap_3a279-283.htm.
Frankel, J. A., & Rose, A. K. (1995). A Panel Project on Purchasing Power Parity: Mean Reversion Within and Between Countries (Working Paper No. 5006). National Bureau of Economic Research. Retrieved from
Greene, W. (2002). Alternative panel data estimators for stochastic frontier models. Unpublished Manuscript (Septemebr 1, 2002), Department of Economics, New York University. Retrieved from /publication/228708841_Alternative_panel_data_estimators_for_stochastic_frontier_models/links/004635180450c6d253000000.pdf.
Groen, J. J. J., & Kleibergen, F. (2003). Likelihood-Based Cointegration Analysis in Panels of Vector Error-Correction Models. Journal of Business & Economic Statistics, 21(2), 295–318.
Gujarati, P. D. (2011). Econometrics by Example. Houndmills, Basingstoke, Hampshire ; New York: Palgrave Macmillan.
Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal, 3(2), 148–161.
Harris, R. D. F., & Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics, 91(2), 201–226.
Hendry, D. F., & Mizon, G. E. (1978). Serial Correlation as a Convenient Simplification, Not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England. The Economic Journal, 88(351), 549–563.
Hsiao, C. (1986). Analysis of Panel Data (Econometric Society Monographs). Retrieved April 26, 2017, from
Hsiao, C. (2014). Analysis of panel data. Cambridge university press. Retrieved from
Hurlin, C., & Mignon, V. (2007, July). Second Generation Panel Unit Root Tests. Retrieved from
Hyndman, R., Koehler, A. B., Ord, J. K., & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach (2008 edition). Berlin: Springer.
Im, K. S., Pesaran, M. H., & Shin, Y. (1997). Testing for Unit Roots in Heterogeneous Panels. Mimeo, University of Cambridge.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R (1st ed. 2013, Corr. 6th printing 2016 edition). New York: Springer.
Jaspersen, F. Z., Aylward, A. H., & Knox, A. D. (2000). Risk and Private Investment: Africa Compared with Other Developing Areas. In Investment and risk in Africa (pp. 71–95). Springer. Retrieved from
Jörg Breitung. (2001). The local power of some unit root tests for panel data. In Nonstationary Panels, Panel Cointegration, and Dynamic Panels (Vol. 15, pp. 161–177). Emerald Group Publishing Limited. Retrieved from
Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1), 1–44.
Kohler, U., & Kreuter, F. (2005). Data Analysis Using Stata. Stata Press.
Korkpoe, C. H., & Owusu Junior, P. (2016). Volatility Comparison of the GSE All Share Index Returns using Student t- and Normal-GARCH models. African Journal of Management Research, University of Ghana Business School, 24.
Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we
that economic time series have a unit root? Journal of Econometrics, 54(1-3), 159–178. Retrieved from /030440769290104Y.
Larbi-Siaw, O., & Lawer, P. A. (2015). Determinants of Bank Deposits in Ghana: A Cointegration Approcah. Asian Journal of Economics and Empirical Research, 2(1), 1–7.
Larsson, R., Lyhagen, J., & Löthgren, M. (2001). Likelihood-based cointegration tests in heterogeneous panels. Econometrics Journal, 4(1), 109–142.
Levin, A., & Lin, C. (1993). Unit Root Tests in Panel Data: Asymptotic and Finite Sample Properties. Mimeo, University of California, San Diego.
Levin, A., Lin, C.-F., & James Chu, C.-S. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24.
Lo, A., & Craig MacKinlay, A. (1990). An econometric analysis of nonsynchronous trading. Journal of Econometrics, 45(1-2), 181–211. Retrieved from
Lo, A. W., & MacKinlay, A. C. (1990). When are contrarian profits due to stock market overreaction? Review of Financial Studies, 3(2), 175–205. Retrieved from
Lütkepohl, H., & Xu, F. (2012). The role of the log transformation in forecasting economic variables. Empirical Economics, 42(3), 619–638. Retrieved from
Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61(S1), 631–652.
Malkiel, B. G. (1999). A Random Walk Down Wall Street: Including a Life-cycle Guide to Personal Investing. Norton.
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. Retrieved from tb00373.x/abstract.
McCoskey, S., & Kao, C. (1998). A residual-based test of the null of cointegration in panel data. Econometric Reviews, 17(1), 57–84. /07474939808800403.
McCoskey, S., & Kao, C. (1999). Testing the Stability of a Production Function with Urbanization as a Shift Factor. Oxford Bulletin of Economics and Statistics, 61(S1), 671–690.
McManus, P. A. (2011, October 7). Introduction to Regression Models for Panel Data Analysis: Workshop in Methods. Indiana University.
Michener, R. (2003). Notes on logarithms Ron Michener Revised January 2003. Retrieved from
Mijiyawa, A. (2015). What Drives Foreign Direct Investment in Africa? An Empirical Investigation with Panel Data. African Development Review, 27(4), 392–402. Retrieved from
Miller, M. H., Muthuswamy, J., & Whaley, R. E. (1994). Mean Reversion of Standard & Poor’s 500 Index Basis Changes: Arbitrage-induced or Statistical Illusion? The Journal of Finance, 49(2), 479–513.
Mlambo, C., & Biekpe, N. (2005). Thin trading on African stock markets: Implications for market efficiency testing. Investment Analysts Journal, 34(61), 29–40.
Morgan, J. P. (1996, December 17). RiskMetrics TM Technical Document. Retrieved January 11, 2016, from
Moon, H., & Perron, B. (2004). Testing for a unit root in panels with dynamic factors. Journal of Econometrics, 122(1), 81–126.
Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347–370. Retrieved from
Ng, S., & Perron, P. (1995). Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag. Journal of the American Statistical Association, 90(429), 268–281. Retrieved from /10.1080/01621459.1995.10476510.
Ng, S., & Perron, P. (1996). The exact error in estimating the spectral density at the origin. Journal of Time Series Analysis, 17(4), 379–408. Retrieved from
Ng, S., & Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69(6), 1519–1554. Retrieved from
Ng, S., Perron, P., & others. (2001). A note on the selection of time series models. Discussion Pa. Retrieved from /datastream/PDF/download/citation.pdf.
O’Connell, P. G. J. (1998). The overvaluation of purchasing power parity. Journal of International Economics, 44(1), 1–19. 00017-2.
Oh, K.-Y. (1996). Purchasing power parity and unit root tests using panel data. Journal of International Money and Finance, 15(3), 405–418.
Pafka, S., & Kondor, I. (2001). Evaluating the RiskMetrics Methodology in Measuring Volatility and Value-at-Risk in Financial Markets. Physica A: Statistical Mechanics and Its Applications, 299(1-2), 305–310.
Pagan, A. R., & Schwert, G. W. (1990). Alternative models for conditional stock volatility. Journal of Econometrics, 45(1), 267–290. Retrieved from
Papell, D. (1997). Searching for stationarity: Purchasing power parity under the current float. Journal of International Economics, 43(3-4), 313–332.
Parramore, K., & Watsham, T. (2004). Mathematical foundations of risk management. Retrieved from
Perron, P., & Ng, S. (1996). Useful modifications to some unit root tests with dependent errors and their local asymptotic properties. The Review of Economic Studies, 63(3), 435–463. Retrieved from
Pedroni, P. (2000). Fully Modified OLS for Heterogeneous Cointegrated Panels. Retrieved from 15004-2.
Pedroni, P. (2001). Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics, 83(4), 727–731.
Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 20(03), 597–625.
Pesando, J. (1979). On the Random Walk Characteristics of Short- and Long-Term Interest Rates in an Efficient Market. Journal of Money, Credit and Banking, 11(4), 457–66. Retrieved from _3a1979_3ai_3a4_3ap_3a457-66.htm.
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621–634.
Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79–113.
Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. Retrieved from /75/2/335.short.
Phillips, P. C., & Durlauf, S. N. (1986). Multiple time series regression with integrated processes. The Review of Economic Studies, 53(4), 473–495.
Phillips, P. C., & Moon, H. R. (2000). Nonstationary panel data analysis: an overview of some recent developments. Econometric Reviews, 19(3), 263–286.
Quah, D. (1992). The relative importance of permanent and transitory components: identification and some theoretical bounds. Econometrica: Journal of the Econometric Society, 107–118.
Quah, D. (1994). Exploiting cross-section variation for unit root inference in dynamic data. Economics Letters, 44(1-2), 9–19.
Rao, C. R. (1952). Advanced statistical methods in biometric research. Retrieved from
Rossi, B. (2006). Are exchange rates really random walks? Some evidence robust to parameter instability. Macroeconomic Dynamics, 10(01), 20–38. Retrieved from
Rossi, B. (2013, November 14). Are exchange rates predictable? Retrieved from
Rothenberg, T. J., & Stock, J. H. (1997). Inference in a nearly integrated autoregressive model with nonnormal innovations. Journal of Econometrics, 80(2),
269–286. Retrieved from /S0304407697000407.
Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607.
Samuelson, P. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6.
Scholes, M., & Williams, J. (1977). Estimating betas from nonsynchronous data. Journal of Financial Economics, 5(3), 309–327. Retrieved from /article/eeejfinec/v_3a5_3ay_3a1977_3ai_3a3_3ap_3a309-327.htm.
SAS. (1999). SAS/STAT User’s Guid. Sas Institute Inc., Cary, NC. USA.
Stock, J. H., & Watson, M. W. (2006). Forecasting with many predictors. Handbook of Economic Forecasting, 1, 515–554. Retrieved from /science/article/pii/S1574070605010104.
Stock, J. H., & Watson, M. W. (2003). Introduction to econometrics (Vol. 104). Addison Wesley Boston. Retrieved from
Taylor, M. P., & Sarno, L. (1998). The behavior of real exchange rates during the post-Bretton Woods period. Journal of International Economics, 46(2), 281–312.
Torres-Reyna, O. (2007). Panel data analysis fixed and random effects using Stata (v. 4.2). Data & Statistical Services, Princeton University. Retrieved from
Tsay, R. S. (2013). An introduction to analysis of financial data with R (Vol. 861). Hoboken, New Jersey : Wiley: John Wiley & Sons.
Tsay, R. S. (2010). Analysis of Financial Time Series (Third Edition). Hoboken, New Jersey: John Wiley & Sons, Inc.
Wooldridge, J. M. (2002). Econometric Analysis of Cross Section and Panel Data. MIT Press.
Wu, Y. (1996). Are real exchange rates nonstationary? Evidence from a panel-data test. Journal of Money, Credit and Banking, 28(1), 54–63.

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