×

Cash flow risk management in the property/liability insurance industry: a dynamic factor modeling approach. (English) Zbl 1393.62049

Summary: This study proposes and demonstrates a dynamic factor model that can be empirically carried out by the utilization of a factor-augmented autoregressive technique to explain and forecast the time-varying patterns of cash flows of insurance companies in the United States. A principal component approach is employed in the Factor-Augmented Autoregressive Model (FAARM) to capture the augmented factors that are to be utilized for forecasting. We describe the cash flow statistical model by a dimension-reduction technique that can depict the dynamic patterns of the cash flows of insurance firms and then measure the FAARM model. Results from the first step (principal component analysis) help capture the macroeconomic variables and the variables pertaining to insurance companies’ cash flows, namely, cash flows from investment, underwriting, and risk management activities. Results from the second step offer evidence supporting that the FAARM improves the out-of-sample forecasting accuracy assessed by a forecasted root-mean-squared error (FRMSE). This article presents a set of feasible FAAR models from which an insurance firm can choose one that can be a better fit to the firm corresponding to its specific firm characteristics, such as firm size. Consequently, the chosen FAARM(s) can improve the accuracy of cash flow forecasting and thus can help insurers to manage risk via cash-flow-matching techniques.

MSC:

62P05 Applications of statistics to actuarial sciences and financial mathematics
62H25 Factor analysis and principal components; correspondence analysis
91B30 Risk theory, insurance (MSC2010)
PDF BibTeX XML Cite
Full Text: DOI

References:

[1] Adam, T., Capital expenditures, financial constraints, and the use of options, Journal of Financial Economics, 92, 2, 238-251, (2009)
[2] Almeida, H.; Campello, M.; Weisbach, M. S., The cash flow sensitivity of cash, Journal of Finance, 59, 1777-1804, (2004)
[3] Alonso, A.; García-Martos, C.; Rodríguez, J.; Sánchez, M., Seasonal dynamic factor analysis and bootstrap inference: application to electricity market forecasting, Technometrics, 53, 137-151, (2011)
[4] Alti, A., How sensitive Is investment to cash flow when financing Is frictionless?, Journal of Finance, 58, 707-722, (2003)
[5] Ang, A.; Sherris, M., Interest rate risk management: developments in interest rate term structure modeling for risk management and valuation of interest-rate-dependent cash flows, North American Actuarial Journal, 1, 2, 1-26, (1997) · Zbl 1080.60507
[6] Azcue, P.; Muler, N., Optimal investment strategy to minimize the ruin probability of an insurance company under borrowing constraints, Insurance: Mathematics and Economics, 44, 26-34, (2009) · Zbl 1156.91391
[7] Bakshi, G.; Chen, Z.; Mehra, R., Handbook of Investments: Equity Premium, Cash flow risk, discounting risk, and the equity premium puzzle, 377-400, (2007), North-Holland, Amsterdam
[8] Ballotta, L.; Haberman, S., Investment strategies and risk management for participating life insurance contracts, (2009)
[9] Bates, T.; Kahle, K.; Stúlz, R., Why do US firms hold so much more cash than they used to?, Journal of Finance, 64, 1985-2021, (2009)
[10] Belviso, F.; Milani, F., Structural factor-augmented VARs SFAVARs and the effects of monetary policy, B.E. Journal of Macroeconomics, 6, 3, 1-46, (2006)
[11] Bolton, P.; Chen, H.; Wang, N., A unified theory of Tobin’s q, corporate investment, financing, and risk management, Journal of Finance, 66, 1545-1578, (2011)
[12] Born, P.; Lin, H.-J.; Wen, M.; Yang, C. C., The dynamic interactions between risk management, capital management, and financial management in the U.S. property/liability insurance industry, Asia-Pacific Journal of Risk and Insurance, 4, 2-17, (2009)
[13] Cummins, J. D.; Weiss, M. A.; Dionne, G., Handbook of Insurance, Analyzing firm performance in the insurance industry using frontier efficiency and productivity methods, 795-861, (2000), Kluwer, Norwell, MA
[14] Cummins, J. D.; Tennyson, S.; Weiss, M. A., Consolidation and efficiency in the U.S. life insurance industry, Journal of Banking & Finance, 23, 325-357, (1999)
[15] Cummins, J. D.; Xie, X., Mergers and acquisitions in the US property-liability insurance industry: productivity and efficiency effects, Journal of Banking & Finance, 32, 1, 30-55, (2008)
[16] Fairley, W., Investment income and profit in property-liability insurance: theory and empirical results, Bell Journal of Economics, 10, 192-210, (1979)
[17] Forni, M.; Hallin, M.; Lippi, M.; Reichlin, L., The Generalised Dynamic Factor Model: One Sided Estimation and Forecasting. ULB Institutional Repository 2013/10129, (2005), Université Libre de Bruxelles, Brussels
[18] Franklin, S. B.; Gibson, D. J.; Robertson, P. A.; Pohlmann, J. T.; Fralish, J. S., Parallel analysis: A method for determining significant principal components, Journal of Vegetation Science, 6, 1, 99-106, (1995)
[19] García-Martos, C.; Rodríguez, J.; Sánchez, M., Forecasting electricity prices by extracting dynamic common factors: application to the Iberian market, IET Generation, Transmission & Distribution, 6, 11-20, (2012)
[20] Geweke, J.; Aigner, Dennis J.; Goldberger, Arthur S., Latent Variables in Socio-Economic Models, The dynamic factor analysis of economic time series, 365-383, (1977), North-Holland, Amsterdam
[21] Giannone, D.; Reichlin, L.; Sala, L., Monetary policy in real time, NBER Macroeconomics Annual, 19, 161-200, (2004)
[22] Hylleberg, S.; Engle, R.; Granger, C.; Yoo, B., Seasonal integration and cointegration, Journal of Econometrics, 44, 215-238, (1990) · Zbl 0709.62102
[23] Iyengar, G.; Ma, A. K. C., Cash flow matching: A risk management approach, North American Actuarial Journal, 13, 3, 370-378, (2009)
[24] Kapetanios, G.; Marcellino, M., A comparison of estimation methods for dynamic factor models of large dimension, (2004)
[25] Keown, A. J.; Martin, J. D.; Petty, J. W., Foundations of Finance: The Logic and Practice of Financial Management, (2007), Prentice Hall, New York
[26] Lin, H. J.; Wen, M.; Yang, C. C., Effects of risk management on cost efficiency and cost function of the U.S. property & liability insurers, North American Actuarial Journal, 15, 4, 487-498, (2011)
[27] (2009)
[28] Rochet, J.-C.; Villeneuve, S., Liquidity management and corporate demand for hedging and insurance, Journal of Financial Intermediation, 20, 303-323, (2011)
[29] Sargent, T. J.; Sims, C. A.; Sims, C. A., New Methods in Business Cycle Research: Proceedings from a Conference, Business cycle modeling without pretending to have too much A-priori economic theory, (1977), Federal Reserve Bank of Minneapolis, Minneapolis
[30] Shin, H.; Stulz, R. M., Shareholder wealth and firm risk. dice center working paper 2000–19, (2000)
[31] Stock, J. H.; Watson, M. W., Macroeconomic forecasting using diffusion indexes, Journal of Business and Economic Statistics, 20, 147-162, (2002)
[32] Stock, J. H.; Watson, M. W., Implications of dynamic factor models for VAR analysis, (2005)
[33] Stock, J. H.; Watson, M. W.; Elliott, G.; Granger, Clive W. J.; Timmermann, A., Handbook of Economic Forecasting, 1, Forecasting with many predictors, 515-554, (2006), Elsevier, Amsterdam
[34] Stock, J. H.; Watson, M. W.; Castle, J.; Shephard, N., The Methodology and Practice of Econometrics: Festschrift in Honor of D. F. Hendry, Forecasting in dynamic factor models subject to structural instability, 173-230, (2009), Oxford University Press, Oxford
[35] Subrahmanyam, M. G.; Tang, D. Y.; Wang, S. Q., Credit default swaps and corporate cash holdings, (2014)
[36] Watson, M. W., Comment on monetary policy in real time by giannone, reichlin, and sala, NBER Macroeconomics Annual, 19, 216-221, (2004)
[37] Wen, M.; Born, P., Firm-level analysis of the effects of net investment income on underwriting cycles: an application of simultaneous equations, Journal of Insurance Issues, 28, 1, 14-32, (2005)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.