Replicating Private Equity Thursday, 4 February, 2016

Author: Stafford

Title: Replicating Private Equity with Value Investing, Homemade Leverage, and Hold-to-Maturity Accounting

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2720479

Abstract:

Private equity funds tend to select relatively small firms with low EBITDA multiples. Publicly traded equities with these characteristics have high risk-adjusted returns after controlling for common factors typically associated with value stocks. Hold-to-maturity accounting of portfolio net asset value eliminates the majority of measured risk. A passive portfolio of small, low EBITDA multiple stocks with modest amounts of leverage and hold-to-maturity accounting of net asset value produces an unconditional return distribution that is highly consistent with that of the pre-fee aggregate private equity index. The passive replicating strategy represents an economically large improvement in risk- and liquidity-adjusted returns over direct allocations to private equity funds, which charge average fees of 6% per year.

Notable quotations from the academic research paper:

"To study the asset selection by private equity funds, author assembles a dataset of public-to-private transactions sponsored by financial buyers, similar to the approach used by Axelson, Jenkinson, Strömberg, and Weisbach (2013). A selection model finds that private equity investors consistently tend to target relatively small firms with low operating cash flow multiples. Additionally, the selected firms tend to be value firms. Interestingly, a firm’s market beta is not a reliable predictor of whether a firm is selected for a going-private transaction. In fact, the average pre-transaction market beta for the public-to-private firms is 1.

Return smoothing is an acute concern for the private investments being considered here, particularly when comparing to the accurately measured risks of replicating portfolios comprised of relatively liquid publicly traded investments. A growing literature challenges the accuracy of the return reporting process for hedge funds, documenting both conditional and unconditional return smoothing, as well as manager discretion in marking portfolio NAVs

In light of the evidence on the importance of return smoothing in altering the measured risk properties of hedge fund returns, special attention is focused on whether the strikingly attractive risk properties of the aggregate PE index could be due to the return reporting process. To investigate how the reporting process can alter inferences about risks, two different accounting schemes are used to report portfolio net asset values from which periodic returns are calculated. The first is the traditional market-value based rule where all holdings are reported at their closing price. Portfolios comprised of stocks with market betas averaging 1, with portfolio leverage of 2x, have measured portfolio betas near 2 under the market-value based accounting rule. The second accounting scheme is based on a hold-to-maturity rule, whereby securities that are intended to be held for long periods of time are measured at cost until they are sold. Over periods where security valuations are increasing on average, this accounting scheme appears to provide a conservative estimate of portfolio value and therefore will perhaps understate leverage. However, an additional feature of this accounting scheme is that it significantly distorts portfolio risk measures by recognizing the profits and losses on the underlying holdings only at the time of sale. Consequently, portfolios with highly statistically significant measured betas near 2 under the market-value reporting rule have measured beta that are statistically indistinguishable from zero under the hold-to-maturity reporting rule. This suggests that the long holding periods of private equity portfolios, combined with conservativism in measuring asset values can effectively eliminate a majority of the measured risk.

Overall, the results push against the view that private equity adds value relative to passive portfolios of similarly selected public equites. The mean returns can be matched in a variety of ways in passive portfolios with firms sharing the characteristics of those selected for private equity portfolios. The critical difference appears to be in the marking of the portfolios and the resulting estimates of portfolio risk.

A strategy that simply selects low EBITDA multiple firms and rebalances to equal-weights each month will match the mean reported private equity return before fees. This portfolio is tilted towards small firms relative to a value-weighted portfolio and consists only of value firms, two characteristics that are both related to subsequent returns and to the empirical selection criterion that appears to be used when publicly traded firms are targeted by private equity investors. Interestingly, this portfolio does not make use of leverage to match the mean private equity return.

A popular belief about private equity is summarized in the following anonymous quote: “there are some things you simply cannot do as a public firm that you can do as a private firm.” This is likely to be true. Firms are likely to benefit from the active operating and financial management provided by private equity investors. At the same time, it appears that private equity investors overpay for the opportunity to provide these services.

The private equity structure – here viewed to be the combination of a value stock selection criterion, long holding periods, conservative net asset value accounting, and active management at the portfolio companies, including increased leverage – can mostly be reproduced with a passive portfolio strategy."


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Quantpedia introduces Quantconferences portal Tuesday, 2 February, 2016

We have launched a new portal Quantconferences.com - a brand new directory for quantitative finance and algorithmic trading conferences.

It contains links to majority of quant finance events in one place. Portal offers opportunity to search a detailed list of events:
http://quantconferences.com/ScreenByEvent

or screen our database for keynote speakers to see which conferences they will attend:
http://quantconferences.com/ScreenBySpeaker
http://quantconferences.com/ScreenBySpeaker/Detail/3346 (Emanuel Derman as an example)

You are most welcome to visit our new project. Let us know if you are missing any event in our list and we will add it there.

The QUANTPEDIA & QUANTCONFERENCES Team

FX Liquidity Risk and Carry Trade Returns Thursday, 28 January, 2016

A new related paper has been added to:

#5 - FX Carry Trade

Authors: Abankwa, Blenman

Title: FX Liquidity Risk and Carry Trade Returns

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2662955

Abstract:

We study the effects of FX liquidity risk on carry trade returns using a low-frequency market-wide liquidity measure. We show that a liquidity-based ranking of currency pairs can be used to construct a mimicking liquidity risk factor, which helps in explaining the variation of carry trade returns across exchange rate regimes. In a liquidity-adjusted asset pricing framework, we show that the vast majority of variation in carry trade returns during any exchange rate regime can be explained by two risk factors (market and liquidity risk) in the FX market. Our results are further corroborated when the hedge liquidity risk factor is replaced with a non-tradable innovations risk factor.

Notable quotations from the academic research paper:

"Academic research used to ignore liquidity. The theory assumed frictionless markets which are perfectly liquid all of the time. This paper takes the opposite view. We argue that illiquidity is a central feature of the securities and financial markets. This paper provides a comprehensive study that links liquidity risk to carry trade returns and provides an explanation of why currency investors should consider and manage FX liquidity risk.  The paper contributes to the international fi nance and empirical asset pricing literature in three major perspectives.

This is the first study to investigate the e ffects of liquidity risk on carry trade returns across exchange rate regimes, using a low-frequency market-wide liquidity measure constructed from daily transaction prices. The possibility of using a low-frequency (LF) liquidity measure circumvents the restricted and costly access of intraday high-frequency (HF) data. Not only is access to HF data limited and costly, it is also subjected to time-consuming handling, cleaning, and fi ltering techniques.

Second, we show that FX liquidity risk can be gleaned from the low-frequency market-wide liquidity measure, which helps in explaining the variation of carry trade returns in an asset pricing framework.

Third, we fi nd that liquid and illiquid G10 currencies behave di erently toward liquidity risk for all regimes. Whereas liquid currencies such as the JPY and EUR are not that sensitive to liquidity risk, illiquid currencies such as the AUD and NZD are highly sensitive to liquidity risk. Liquid currencies have negative liquidity betas whereas illiquid currencies show positive liquidity betas. This also substantiates the finding by Mancini, Ranaldo, and Wrampelmeyer (2013) that negative liquidity beta currencies act as insurance or liquidity hedge, whereas positive liquidity beta currencies expose currency investors to liquidity risk."


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The Betting Against Beta Anomaly: Fact or Fiction? Wednesday, 20 January, 2016

A new related paper has been added to:

#77 - Beta Factor in Stocks

Authors: Buchner, Wagner

Title: The Betting Against Beta Anomaly: Fact or Fiction?

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2703752

Abstract:

This paper suggests an alternative explanation for the recently documented betting against beta anomaly. Given that the equity of a levered firm is equivalent to a call option on firm assets and option returns are non-linearly related to underlying stock returns, linear CAPM-type regressions are generally misspecified. We derive theoretical expressions for the pricing error and analyze its magnitude using numerical examples. Consistent with the empirical findings of Frazzini and Pedersen (2014), our pricing errors are negative, increase with leverage, and become economically significant for higher levels of firm leverage.

Notable quotations from the academic research paper:

"In this paper, we suggest a possible alternative explanation for the betting against beta phenomenon. We propose that the betting against beta phenomenon is due to pricing errors, which arise given that the CAPM does not take non-linearities in stock returns into account. Our rationale is as follows. As highlighted by the classic Black-Scholes-Merton model of corporate debt and equity valuation, the equity of a levered firm is equivalent to a call option written on the underlying value of the firm’s assets. As is known, option returns are highly skewed and non-linearly related to the returns of the underlying. Therefore, linear CAPM-type regressions of equity returns may suffer from model misspecification. Using the Black-Scholes-Merton model, we derive expressions for the model pricing error under the standard CAPM and analyze its magnitude using numerical examples.

Our analysis highlights that the pricing error is negative and becomes economically large as firm leverage increases. That is, consistent with the empirical findings of Frazzini and Pedersen (2014), our theoretical analysis predicts that a portfolio that is long low-beta stocks and short high-beta stocks generates a positive CAPM alpha. However, since the equity is correctly priced under our Black-Scholes-Merton framework, the observed positive alpha is due to the pricing error that is induced by the inadequate linearity assumption of the CAPM. This result questions whether the betting against beta phenomenon is indeed an asset pricing anomaly or whether it is due to the fact that the standard CAPM is an inappropriate setting for analyzing the equity returns of highly levered firms. As the analysis presented in this paper is purely theoretical, our aim here is not to assert that the documented betting against beta phenomenon can fully be attributed to the pricing error that we point out. Such detailed empirical tests are beyond the scope of the present paper. Nonetheless, our findings highlight that care must be taken when we interpret the negative alphas of high-beta stocks as an asset pricing anomaly"


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A Multiples-Based Decomposition of the Value Premium Thursday, 14 January, 2016

A new related paper has been added to:

#26 - Value (Book-to-Market) Anomaly

Authors: Golubov, Konstantinidi

Title: A Closer Look at the Value Premium: Evidence from a Multiples-Based Decomposition

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2702822

Abstract:

We use industry multiples-based market-to-book decomposition of Rhodes-Kropf, Robinson and Viswanathan (2005) to study the value premium. The market-to-value component drives all of the value strategy return, while the value-to-book component exhibits no return predictability in both portfolio sorts and firm-level return regressions controlling for other stock characteristics. Prior results in the literature linking value/glamor to expectational errors and limits to arbitrage hold due to the market-to-value component, whereas the results linking market-to-book to cashflow risk, exposure to investment-specific technology shocks, and analyst’s risk ratings hold only for the unpriced value-to-book. Overall, our evidence points towards the mispricing explanation for the value premium.

Notable quotations from the academic research paper:

"In this paper, we shed further light on the origins of the “value premium” using a market-to-book decomposition proposed by Rhodes–Kropf, Robinson, and Viswanathan (2005) (RRV hereafter) in their study of misvaluation and merger waves. In particular, the market-to-book ratio is decomposed into market-to-value and value-to-book components, where value is an estimate of fundamental value based on industry multiples conditional on a set of observable characteristics. The market-to-value component represents deviation of the stock price from fundamental value implied by long-run industry valuations, and the value-to-book component represents the “expected” industry-specific valuation of the firm’s net assets. The market-to-value component can be further decomposed into firm-specific deviation of the stock price from contemporaneous industry-level valuation, and the deviation of industry-level valuation from its long-run average.

We find that all of the return predictability of the market-to-book ratio is concentrated in the market-to-value component. Over the 1975-2013 period, a long-short portfolio strategy based on the conventionally used market-to-book ratio produces an average return of 1.42% per month (17.04% annualized). The same strategy based on the market-to-value component produces an average return of 1.56% (18.72% annualized), while going long low value-to-book and short high value-to-book stocks produces an average return of 0.27% per month – statistically insignificant. The Sharpe ratios of the market-to-value strategies are also superior to that of the conventional value strategy. Further decomposition of the market-to-value component into firm-level deviations from contemporaneous industry-level valuations and industry-level deviations from long-run averages shows that it is the firm-specific component that drives return predictability.

If high (low) market-to-value stocks are over (under)priced, we should find that investors are negatively (positively) surprised by their earnings announcements following portfolio formation. This is exactly what we find. We also find that high (low) market-to-value stocks experience positive (negative) earnings surprises in the quarters prior to portfolio formation, suggesting that the mechanism by which these stocks become mispriced is investor overextrapolation of positive (negative) news, leading to over (under)valuation that gets corrected over subsequent quarters as the true fundamentals are revealed. These patterns are not there for the value-to-book component.

We then examine the role of limits to arbitrage, such as short sale constraints and noise trader risk, in the sustaining of mispricing (De Long et al. (1990), Shleifer and Vishny (1997), Pontiff (2006)). In the absence of limits to arbitrage, overvaluation should not persist for long periods of time as the rational arbitrageurs trade against the mispricing. We find that the performance of the market-to-value strategy is concentrated in portfolios characterized by short sale constraints, as captured by institutional ownership and the existence of exchange-traded options. Moreover, these differences are largely due to high market-to-value stocks – the ones going into the short leg of the strategy – where short sale constraints are really binding. We also find that the market-to-value strategy returns are largely due to stocks characterized by noise trader risk as captured by idiosyncratic return volatility. Again, these effects are not there for value-to-book: the mispricing-based explanations of the market-to-book effect hold only for the component designed to capture mispricing."


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