scholarly journals Fair Value of Earnouts: Valuation Uncertainty or Cookie Jar Reserve?

2021 ◽  
Author(s):  
Andrew Ferguson ◽  
Wei Hu ◽  
Peter Lam
Keyword(s):  
Fair Value ◽  
Valuation Uncertainty

Fair value's effects on closed-end funds' discounts and premia: is level 3 the sole perpetrator?

2020 ◽  
Vol 46 (8) ◽  
pp. 1001-1022 ◽  
Author(s):  
Steve Fortin ◽  
Ahmad Hammami ◽  
Michel Magnan
Keyword(s):  
Relevant Information ◽  
Fair Value ◽  
Content Type ◽  
Level 3 ◽  
Closed End Funds ◽  
Level 1 ◽  
Value Hierarchy ◽  
Valuation Uncertainty ◽  
The Impact ◽  
Level 2

PurposeThis study examines the long-term link between fair valuation uncertainty and discounts/premia in closed-end funds. This study argues that, in exploring the close-end funds puzzle, prior research generally omits to consider the uncertainty surrounding the measurement of funds' financial disclosure, as reflected in the fair value hierarchy, when investment specialty differs across funds.Design/methodology/approachRegressions were employed to explore how the fair value hierarchy affects closed-end funds' discounts/premia when investment specialty differs. The authors also examine the effects pre- and post-2012 to explore if that relationship changes due to the additional disclosure requirements enacted at the end of 2011.FindingsThe authors find that the three levels of the fair value hierarchy have effects that vary according to a fund's specialty. For equity specialized funds, Level 3 significantly increases discounts and decreases premia, suggesting the impact of valuation uncertainty that underlies Level 3 estimates; this relationship disappears (decreases in severity) for premia (discount) experiencing funds post-2012. In contrast, Level 1 and Level 2 do not have any significant effect on discounts or premia except that post-2012, Level 2 begins to display discount decreasing effects. For bond specialized funds, no significant association was noted between premia and any of the fair value levels except that post-2012, Level 3 begins to display premium increasing effects. However, results are different for discounts. The authors note that Level 1 valuations significantly increase discounts, but only post-2012; Level 2 valuations significantly decrease discounts (pre- and post-2012), consistent with such estimates incorporating unique and relevant information; and Level 3 valuations do not have a significant effect on discounts.Originality/valueThe results of this study revisit prior evidence and indicate that results about the effects of fair value measurement and the closed-end funds' puzzle are sensitive to the period length being considered and the investment specialty of the fund. The authors also note that additional disclosure regarding Level 3 valuation inputs decreases market concern for valuation uncertainty and increases the liquidity benefits of investing in Level 3 carrying funds.

Prudent Valuation - Guidelines and Sound Practices

2016 ◽  
Author(s):  
Umberto Cherubini ◽  
◽  
Marco Bianchetti ◽  
Keyword(s):  
Financial Institutions ◽  
Fair Value ◽  
Double Counting ◽  
Technical Standard ◽  
Simplified Approach ◽  
The Core ◽  
The Common ◽  
Valuation Uncertainty ◽  
Different Sources ◽  
The Eu

The EU Capital Requirement Regulation (CRR) [8] and of EBA Regulatory Technical Standard for prudent valuation [15], published on Jan. 1st, 2014 and Jan. 28th, 2016, respectively, constitute the EU Prudent Valuation Framework. The CRR, art. 34, requires to Institutions a prudent valuation of positions measured at fair value and the deduction of the resulting Additional Valuation Adjustments (AVAs) from the Common Equity Tier One (CET1) capital. The art. 105 disciplines the AVAs intended to achieve an appropriate level of certainty in prudent value. The EBA RTS [15] allow two approaches to prudent valuation. The simplified approach, applicable by small financial institutions (with total absolute fair-valued assets and liabilities below EUR 15 billions), prescribes a very simple total AVA equal to 0.1% of the total fair value. The core approach, compulsory for institutions above the EUR 15 billion threshold, prescribes the calculation of 9 AVAs, referring to different sources of valuation uncertainty, as the excess of valuation adjustments required to achieve the prudent value with 90% level of confidence. Five out of nine AVAs include a 50% weight to take diversification into account and avoid double counting effects. Those positions for which a change in their fair value affects only partially the CET1 may be partially excluded from the AVAs calculation.

Fair-Value

Controlling ◽  
2003 ◽  
Vol 15 (3-4) ◽  
pp. 209-210
Author(s):  
Reinhard Heyd
Keyword(s):  
Fair Value

Investigation of Timing Anomalies in the Russian Stock Market in the Post-Crisis Period

2019 ◽  
Vol 12 (3) ◽  
pp. 37-47
Author(s):  
I. Ya. Lukasevich
Keyword(s):  
Stock Market ◽  
Information Technologies ◽  
Real Data ◽  
Weak Form ◽  
Fair Value ◽  
Presidential Decree ◽  
Day Of The Week ◽  
Russian Stock Market ◽  
Economic Growth Rates ◽  
Global And Local

The implementation of the May presidential decree aimed at Russia’s joining the top five global economies and achieving economic growth rates above the world’s average while maintaining macroeconomic stability requires a highly developed and efficient stock market ensuring the accumulation of capital and its deployment in the most promising and productive sectors of the economy.The subject of the research is timing anomalies in the Russian stock market in 2012–2018. The relevance of the research is due to the information inefficiency of the Russian stock market and its imperfections leading to significant price deviations from the «fair» value of assets and depriving investors of the opportunity to form various strategies for deriving additional revenues not related to fundamental economic factors and objective processes occurring in the global and local economies and the economy of an individual business entity. Based on the trend analysis of the Broad Market USD Index (RUBMI), the paper demonstrates a methodology for simulating the analysis of price anomalies on large arrays of real data using statistical data processing methods and modern information technologies. The paper concludes that though the Russian stock market lacks even the weak form of efficiency, such well-known timing anomalies as the “day-of-the-week” effect and the “month” effect have not been observed in the recent years. Therefore, investors could not use these anomalies to derive regular revenues above the market average.

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