2252. Harnessing Accounting Data for Profitability Forecasts and Robust Portfolio Construction
Invited abstract in session FA-6: Risk Management, stream Financial Management and Accounting.
Friday, 8:45-10:15Room: H9
Authors (first author is the speaker)
| 1. | Lukas Benjamin Heidbrink
|
| Chair for Quantitative Accounting & Financial Reporting, Bielefeld University |
Abstract
Forecasting the financial performance of companies and markets is the subject matter of a variety of research papers. Measuring the accuracy of forecasts, however, does not take the level of profitability into account. Rather, it measures the predictability of profitability. This is why accuracy is considered a measure of robustness.
Typically, accruals are known to increase risk and decrease reliability. Particularly, discretionary accruals cause lower forecasting ability. As such, the proposed model maximizes earnings yield while restricting the level of discretionary accruals, as well as short-term and long-term out-of-sample forecasting errors, resulting in a robust, low-risk portfolio that is highly predictable. Limiting the iterative forecasting error of future operating cash flows induces robustness, and limiting the share of discretionary accruals in profit reduces overall risk.
With a slight modification, this model also allows for the identification of natural hedging strategies, in accordance with IFRS regulations. Given a company's financial assets and liabilities, the model identifies suitable shares for a macro-hedge, minimizing downside risk in the company's portfolio.
Keywords
- Accounting
- Forecasting
Status: accepted
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