The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Introductory Econometrics for Finance
Abstract
A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Co-integration and error correction: representation, estimation and testing
Engle, R. F., & Granger, C. W. J. (1987) · Econometrica · doi:10.2307/1913236 · Cited by 32,007
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
The pricing of options and corporate liabilities
Black, F., & Scholes, M. (1973) · Journal of Political Economy · doi:10.1086/260062 · Cited by 29,074
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
On Persistence in Mutual Fund Performance
Carhart, M. M. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03808.x · Cited by 17,283
STATISTICAL ANALYSIS OF COINTEGRATION VECTORS
Johansen, S. (1988) · Journal of Economic Dynamics and Control · doi:10.1016/0165-1889(88)90041-3 · Cited by 17,027
Cited by
Bouktif, S., Fiaz, A., Ouni, A., & Serhani, M. (2018) · Energies · doi:10.3390/en11071636 · Cited by 915
Bridging the divide in financial market forecasting: machine learners vs. financial economists
Hsu, M.-W., Lessmann, S., Sung, M.-C., Ma, T., & Johnson, J. E. V. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.05.033 · Cited by 195
A real-time passenger flow estimation and prediction method for urban bus transit systems
Zhang, J., Shen, D., Tu, L., Zhang, F., Xu, C., Wang, Y., Tian, C., Li, X., Huang, B., & Li, Z. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2686877 · Cited by 130
Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index
Vo, N., & Ślepaczuk, R. (2022) · Entropy · doi:10.3390/e24020158 · Cited by 39
Gunay, S., & Kaskaloglu, K. (2022) · Research in International Business and Finance · doi:10.1016/j.ribaf.2022.101773 · Cited by 36
Metadata
- Authors
- Brooks, C.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2019-03-18
- OpenAlex
- W1492362433
- Cited by
- 3,657
- References
- 23
- FWCI
- 80.60
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Introductory Econometrics for Finance. https://app.cochat.ai/papers/10.1017/9781108524872
- The paper
- Brooks, C. (2019). Introductory Econometrics for Finance. Cambridge University Press eBooks. https://doi.org/10.1017/9781108524872
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
