REIT Momentum and Characteristic-Related REIT Returns

Recent evidence confirms that in factor-model examinations of the cross-section of REIT returns, REIT momentum emerges as the dominant driver. Acknowledging the importance of momentum, the current study explores whether and how REIT return patterns are linked to the underlying characteristics of the REITs themselves, in the manner of Daniel and Titman’s (Journal of Finance 52(1):1–33, 1997, Journal of Portfolio Management 24(4):24–33, 1998) characteristics model. Over the period 1993 through 2009, we find that after controlling for momentum, book-to-market, institutional ownership, and illiquidity are all strongly associated with REIT returns while size and analyst coverage are not. We further extend prior research by examining the influence of changes in interest rate cycles on REIT returns, and find that the characteristic-return relationships are heavily influenced by interest rates.     

Discussion of “Investor recognition and stock returns”

Lehavy and Sloan (2008, Review of Accounting Studies) note that prior studies find that earnings and cash flows explain only a small portion of the cross-sectional variation in stock return. This motivates them to investigate empirically the ability of a behavioral model of capital market equilibrium proposed by Merton (1987, Journal of Finance, 42, 483–510) to explain the remaining variation in stock returns. Their primary findings show that security value is, as predicted, increasing in investor recognition of the security and that investor recognition is incremental to and more important than cash flows in explaining the cross-sectional variation of stock returns. While the research question is intriguing and well motivated, a number of methodological limitations may limit the reliability of the findings/interpretations. In this paper, I first evaluate the motivation and potential contribution of the Lehavy and Sloan (2008) study. I then outline methodological limitations underlying the study and offer ways of overcoming them. In the final section, I state my conclusions.     

Insider trading and firm-specific return volatility

Roll (J Financ 43:541–566, 1988) argues that firm-specific stock return volatility may result either from informed trading or from noise trading that is unrelated to information. In this paper we provide evidence that insider purchases are inversely related to the idiosyncratic volatility of stocks. We also find that stock idiosyncratic volatilities are generally inversely related to future 6- and 12-month returns. Our results are primarily driven by the timing of insider sales rather than insider purchases. The results are consistent with an information-based explanation of firm-specific return volatility.     

Correction note for ��The large-maturity smile for the Heston model��

The papers (Forde and Jacquier in Finance Stoch. 15:755?C780, 2011; Forde et al. in Finance Stoch. 15:781?C784, 2011) study large-time behaviour of the price process in the Heston model. This note corrects typos in Forde and Jacquier (Finance Stoch. 15:755?C780, 2011), Forde et al. (Finance Stoch. 15:781?C784, 2011) and clarifies the proof of Forde et al. (Finance Stoch. 15:781?C784, 2011, Proposition 2.3).     

Public pension fund ownership and firm performance

Equity ownership by public pension funds (PPFs) is widely used in the literature (see, e.g., Cremers and Nair 2005; Dittmar and Mahrt-Smith 2007) as a measure of the strength of shareholder monitoring/governance. This paper raises caution on such practices by illustrating an inverted-U shape relationship between PPF ownership and firms’ future performance, measured by stock returns and operating performance: during 1985–2005, future performance first increases, then declines in aggregate equity ownership by PPFs. Our results suggest that PPFs’ presence is consistent with shareholder value maximization when they have moderate influence on firm management, whereas excessive PPF ownership may facilitate PPF managers’ pursuits of political interests and destroy shareholder value. Therefore, it is important to impose an upper bound to PPF ownership when measuring the strength of shareholder monitoring/governance.     

What is behind the magic of O-Score? An alternative interpretation of Dichev’s (1998) bankruptcy risk anomaly

Using Ohlson’s (J Account Res 18(1):109–131, 1980) measure of bankruptcy risk (O-Score), Dichev (J Fin 53(3):1131–1147, 1998) documents a bankruptcy risk anomaly in which firms with high bankruptcy risk earn lower than average returns. This study first demonstrates that the negative association between bankruptcy risk and returns does not generalize to an alternative measure of bankruptcy risk. Then, by examining the nine individual components of O-Score, I find that funds from operations (FFO) is the only component that is associated with returns. Furthermore, I show that the return-predictive power of FFO is due to cash flows from operations. Taken as a whole, this study provides evidence that Dichev’s bankruptcy risk anomaly is a manifestation of investors’ under (over)-pricing of cash flows (accrual) component of earnings, i.e., the accrual anomaly documented by Sloan (Account Rev 71(3):289–316, 1996).     

Dynamic risk, accounting-based valuation and firm fundamentals

This study extends the accounting-based valuation framework of Ohlson (Contemp Acc Res 11(2):661–687, 1995) and Feltham and Ohlson (Acc Rev 74(2):165–183, 1999) to incorporate dynamic expectations about the level of systematic risk in the economy. Our model explains recent empirical findings documenting a strong negative association between changes in economy-wide risk and future stock returns. Importantly, the model also generates costs of capital that are solely a linear function of accounting variables and other firm fundamentals, including the book-to-market ratio, the earnings-to-price ratio, the forward earnings-to-price ratio, size and the dividend yield. This result provides a theoretical rationale for the inclusion of these popular variables in cost of capital (expected return) computations by the accounting and finance literatures and obviates the need to estimate costs of capital from unobservable (future) covariances. The model also generates an accounting return decomposition in the spirit of Vuolteenaho (J Finance 57(1):233–264, 2002). Empirically, we find that costs of capital generated by our model are significantly associated with future returns both in and out of sample in contrast to standard benchmark models. We further obtain significantly lower valuation errors in out-of-sample tests than traditional models that ignore dynamic risk expectations.     

A comparative study of two models SV with MCMC algorithm

This paper examines two asymmetric stochastic volatility models used to describe the volatility dependencies found in most financial returns. The first is the autoregressive stochastic volatility model with Student??s t-distribution (ARSV-t), and the second is the basic SVOL of Jacquier et al. (J Bus Econ Stat 14:429?C434, 1994). In order to estimate these models, our analysis is based on the Markov Chain Monte-Carlo (MCMC) method. Therefore, the technique used is a Metropolishastings (Hastings in Biometrika 57:97?C109, 1970), and the Gibbs sampler (Casella and George in The Am Stat 46:167?C174, 1992; Gelfand and smith in J Am Stat Assoc 85:398?C409, 1990; Gilks and Wild in 41:337?C348, 1992). The empirical results concerned on the Standard and Poor??s 500 composite Index (S&P), CAC40, Nasdaq, Nikkei and DowJones stock price indexes reveal that the ARSV-t model provides a better performance than the SVOL model on the MSE and the maximum Likelihood function.     

The 52-week high,momentum, and predicting mutual fund returns

George and Hwang (J Finance 59:2145–2176, 2004) have shown that the 52-week high share price carries significant predictive ability for individual stock returns, dominating other common momentum-based trading strategies. Based upon their results and other methods, this paper examines and compares the performance of three momentum trading strategies for mutual funds, including an analogous 1-year high measure for the net asset value of mutual fund shares. Strategies based on prior extreme returns and on fund exposure to stock return momentum are also examined. Results show that all three measures have significant, independent, predictive ability for fund returns. Further, each produces a distinctive pattern in momentum profits, whether measured in raw or risk-adjusted returns, with profits from momentum loading being the least transitory. Nearness to the 1-year high and recent extreme returns are significant predictors of fund monthly cash flows, whereas fund momentum loading is not.     

New empirical evidence on the investment success of momentum strategies based on relative stock prices

This paper provides significant extensions and tests of momentum trading strategies based on relative prices that were first explored by George and Hwang (2004). We develop new momentum strategies based on the ratio of the current stock price to each of five different reference points in past prices: 52-week high, 52-week median, 52-week low, half-year high, and 2-year high. We measure their investment performance on the basis of the Fama and French 3-Factor and Momentum Model (Carhart four-factor model), and further employ the technique of nested trading strategies to measure incremental performance. The strategy based on the ratio of current stock price to its 52-week high price is the most profitable, and its performance is robust when tested over a wide range of financial and economic factors. Our results provide strong new evidence of the investment merits of a momentum trading strategy based on the 52-week high price ratio, and add new weight to challenges to the hypothesis that the stock market is efficient in the semi-strong sense.     

The implied intra-day probability of informed trading

The paper develops a methodology for estimating the intra-day probability of informed trading for NYSE stocks, implied by the specialist’s quotes and depths. The time series pattern of our measure (PROBINF) in an intra-day analysis around earnings announcements is consistent with previous findings and with expectations regarding informed trading. Moreover, we find that PROBINF exhibits a strong and robust relationship with PIN, the level of insider trading and with measures of the price impact of trades. Our methodology complements the one developed in Easley et al. (J Financ 51(3):811–833, 1996a, J Financ 51(4):1405–1436, b), as it can be used to measure short term changes in informed trading and information asymmetry around events such as merger and acquisition announcements, share repurchases, stock splits, dividend announcements and index additions and deletions.     

A note on the condition of no unbounded profit with bounded risk

As a corollary to Delbaen and Schachermayer’s fundamental theorem of asset pricing (Delbaen in Math. Ann. 300:463–520, 1994; Stoch. Stoch. Rep. 53:213–226, 1995; Math. Ann. 312:215–250, 1998), we prove, in a general finite-dimensional semimartingale setting, that the no unbounded profit with bounded risk (NUPBR) condition is equivalent to the existence of a strict sigma-martingale density. This generalizes the continuous-path result of Choulli and Stricker (Séminaire de Probabilités XXX, pp. 12–23, 1996) to the càdlàg case and extends the recent one-dimensional result of Kardaras (Finance and Stochastics 16:651–667, 2012) to the multidimensional case. It also refines partially the second main result of Karatzas and Kardaras (Finance Stoch. 11:447–493, 2007) concerning the existence of an equivalent supermartingale deflator. The proof uses the technique of numéraire change.     

The optimal-drift model: an accelerated binomial scheme

We introduce the optimal-drift model for the approximation of a lognormal stock price process by an accelerated binomial scheme. This model converges with order o(1/N), which is superior compared to today??s benchmark methods. Our approach is based on the observation that risk-neutral binomial schemes converge to the lognormal limit independently of the choice of the drift parameter. We verify the improved order of convergence by an asymptotic expansion of the binomial distribution function. Further, we show that the above result on drift invariance implies weak convergence of the binomial schemes suggested by Tian (in J. Futures Mark. 19, 817?C843, 1999) and Chang and Palmer (in Finance Stoch. 11, 91?C105, 2007).     

Option hedging for small investors under liquidity costs

Following the framework of Çetin et al. (Finance Stoch. 8:311–341, 2004), we study the problem of super-replication in the presence of liquidity costs under additional restrictions on the gamma of the hedging strategies in a generalized Black–Scholes economy. We find that the minimal super-replication price is different from the one suggested by the Black–Scholes formula and is the unique viscosity solution of the associated dynamic programming equation. This is in contrast with the results of Çetin et al. (Finance Stoch. 8:311–341, 2004), who find that the arbitrage-free price of a contingent claim coincides with the Black–Scholes price. However, in Çetin et al. (Finance Stoch. 8:311–341, 2004) a larger class of admissible portfolio processes is used, and the replication is achieved in the L ² approximating sense.     

Is financial reporting shaped by equity markets or by debt markets? An international study of timeliness and conservatism

We hypothesize debt markets—not equity markets—are the primary influence on “association” metrics studied since Ball and Brown (1968 J Account Res 6:159–178). Debt markets demand high scores on timeliness, conservatism and Lev’s (1989 J Account Res 27(supplement):153–192) R ², because debt covenants utilize reported numbers. Equity markets do not rate financial reporting consistently with these metrics, because (among other things) they control for the total information incorporated in prices. Single-country studies shed little light on debt versus equity influences, in part because within-country firms operate under a homogeneous reporting regime. International data are consistent with our hypothesis. This is a fundamental issue in accounting.     

Equilibrium model with default and dynamic insider information

We consider an equilibrium model à la Kyle–Back for a defaultable claim issued by a given firm. In such a market the insider observes continuously in time the value of the firm, which is unobservable by the market makers. Using the construction in Campi et al. (http://hal.archives-ouvertes.fr/hal-00534273/en/, 2011) of a dynamic three-dimensional Bessel bridge, we provide the equilibrium price and the insider’s optimal strategy. As in Campi and Çetin (Finance Stoch. 11:591–602, 2007), the information released by the insider while trading optimally makes the default time predictable in the market’s view at the equilibrium. We conclude the paper by comparing the insider’s expected profits in the static and dynamic private information case. We also compute explicitly the value of the insider’s information in the special cases of a defaultable stock and a bond.     

The equity premium: a deeper puzzle

Traditional pre-1929 consumption measures understate the extent of serial correlation in the US annual real growth rate of per capita consumption of non-durables and services due to measurement limitations in the construction of their major components. Under alternative measures proposed in this study, the serial correlation of consumption growth is \(0.42\) for the \(1899\) – \(2012\) , contrary to the estimate of \(-0.15\) under the traditional measures. This new evidence implies that the class of economies studied by Mehra and Prescott (J Monet Econ 15(2):145–161, 1985) generates a negative equity premium for reasonable risk aversion levels, thus, further exacerbating the equity premium puzzle.     

Quantitative error estimates for a least-squares Monte Carlo algorithm for American option pricing

We prove new error estimates for the Longstaff–Schwartz algorithm. We establish an $O(\log^{\frac{1}{2}}(N)N^{-\frac{1}{2}})$ convergence rate for the expected L ² sample error of this algorithm (where N is the number of Monte Carlo sample paths), whenever the approximation architecture of the algorithm is an arbitrary set of L ² functions with finite Vapnik–Chervonenkis dimension. Incorporating bounds on the approximation error as well, we then apply these results to the case of approximation schemes defined by finite-dimensional vector spaces of polynomials as well as that of certain nonlinear sets of neural networks. We obtain corresponding estimates even when the underlying and payoff processes are not necessarily almost surely bounded. These results extend and strengthen those of Egloff (Ann. Appl. Probab. 15, 1396–1432, 2005), Egloff et al. (Ann. Appl. Probab. 17, 1138–1171, 2007), Kohler et al. (Math. Finance 20, 383–410, 2010), Glasserman and Yu (Ann. Appl. Probab. 14, 2090–2119, 2004), Clément et al. (Finance Stoch. 6, 449–471, 2002) as well as others.     

Are intraday reversal and momentum trading strategies feasible? An analysis for German blue chip stocks

The success of trading strategies that lead to abnormal excess returns based on annual/monthly investment periods has recently declined significantly. We adopt the original frameworks of De Bondt and Thaler (J Finance 40(3):793–808, 1985) and Jegadeesh and Titman (J Finance 48(1):65–91, 1993) to an intraday reversal as well as momentum strategy scheme based on 5-min stock returns. We analyze 16 reversal and momentum strategies each with ranking and holding periods of 60, 120, 180 or 300 min (reversal strategies) and 15, 30, 45 or 60 min (momentum strategies) from a retail investor’s perspective. We find no indications for momentum in stock prices but strong indications for reversals. Our results are furtherly robust regarding to market adjustment, portfolio sizes and skipping periods between ranking and holding periods. Our results show that the returns of the reversal strategies are statistically significant, however, yet too small to be economically significant. Our results also confirm the efficiency on the stock markets.

     

Portfolio allocation using multivariate variance gamma models

In this paper, we investigate empirically the effect of using higher moments in portfolio allocation when parametric and nonparametric models are used. The nonparametric model considered in this paper is the sample approach; the parametric model is constructed assuming multivariate variance gamma (MVG) joint distribution for asset returns.We consider the MVG models proposed by Madan and Seneta (1990), Semeraro (2008) and Wang (2009). We perform an out-of-sample analysis comparing the optimal portfolios obtained using the MVG models and the sample approach. Our portfolio is composed of 18 assets selected from the S&P500 Index and the dataset consists of daily returns observed from 01/04/2000 to 01/09/2011.