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GMM tests of stochastic discount factor models with useless factors

Journal of Financial Economics 1999 54(1), 103-127
This paper studies generalized method of moments tests for the stochastic discount factor representation of asset pricing models when one of the proposed factors is in fact useless, defined as being independent of the asset returns. Analytic results on asymptotic distributions and simulation results on finite sample distributions both show that (i)the Wald test tends to overreject the hypothesis of a zero factor premium for a useless factor when the model is misspecified, (ii)with the presence of a useless factor, the power of the over-identifying restriction test in rejecting misspecified models is reduced, and in some cases a misspecified model with a useless factor is more likely to be accepted than the true model.

Banking relationship, information reusability, and acquisition loans

Journal of Banking & Finance 2022 138, 106449
We study whether and how banks reuse information across different but related borrowers in financing mergers and acquisitions. We find that stronger prior lending relationships between acquisition loan lenders and acquisition targets are associated with lower spreads and fewer covenant restrictions on acquisition loans. We show that the results are unlikely to be driven by unobservable acquirer, target, or lender characteristics. Consistent with the information asymmetry hypothesis, the effect is stronger when information asymmetry about the target firm is higher. We also find that the result is not driven by the coinsurance effect.

Asymmetric return dynamics and technical trading strategies

Journal of Banking & Finance 2005 29(2), 391-418
We investigate the profitability of technical trading strategies based on an asymmetric reverting property of stock returns. We identify an asymmetry in return dynamics for daily returns on the S&P 500 index. Return dynamics evolve along a positive (negative) unconditional mean after a prior positive (negative) return. The trading strategies based on this asymmetry generate a positive return for buy signals, a negative return for sell signals, and a positive return for the spread between buy and sell signals. Our results imply that the observed asymmetry in return dynamics is the main source of profitability for the implied strategies, thereby corroborating arguments for the usefulness of technical trading strategies.

Day-of-the-week effect in the Taiwan foreign exchange market

Journal of Banking & Finance 2007 31(9), 2847-2865
This study uses stochastic dominance with and without risk-free assets to examine whether trading days can affect patterns of the day-of-the-week effect in the Taiwan foreign exchange market. Our results generally indicate that higher returns appear on the first three days of the week across different trading-day regimes in the Taiwan foreign exchange market, confirming day-of-the-week effect. Allocating part of investors’ assets in risk-free assets is useful in distinguishing returns among weekdays for all currencies.

Idiosyncratic risk does not matter: A re-examination of the relationship between average returns and average volatilities

Journal of Banking & Finance 2004 29(3), 603-621
A recent study by Goyal and Santa-Clara [J. Finance 58 (2003) 975] finds a significantly positive relationship between average stock returns and pre-determined average return volatility measures, while finding no relationship between the average return and its own volatility. The result is interpreted as evidence that idiosyncratic risk matters in asset pricing. We re-examine the issue in extended sample periods and find the proclaimed positive relationship is not substantiated. Our analysis indicates that the above-mentioned positive relationship is mainly driven by the data in the 1990s. The trading strategy suggested by Goyal and Santa-Clara to exploit the return predictability by pre-determined volatility does not yield sustained economic gains.

Asset Pricing Specification Errors and Performance Evaluation

Review of Finance 1999 3(2), 205-232
Many evaluation techniques typically measure performance as deviations of average returns on actively managed funds from those predicted by some asset pricing model. Empirical evidence, however, has so far suggested that all asset pricing models lack empirical support, implying that the models contain mis-specification errors to various degrees. Evaluating mutual fund performance relative to any of these models thus becomes problematic. In this paper, we propose an approach to performance measurement that emphasizes minimizing explicitly the pricing error associated with an asset pricing function which is employed to compute performance measures. This approach is henceforth called the minimum specification-error (MSE) method. We also discuss the statistical properties for implementing MSE performance measure. To demonstrate the significance of the pricing error confounded in evaluation measurement, we contrast our methodology with the Grinblatt and Titman (1989) period weighting approach and with the empirical implementation of Chen and Knez (1996). We find that the greater the pricing error of passive assets, the larger the performance measures. Given the average pricing error generated from a collection of 163 diverse passive portfolios used in this analysis the performance values assigned to a large number of the funds become statistically and economically insignificant.

Two‐Pass Tests of Asset Pricing Models with Useless Factors

Journal of Finance 1999 54(1), 203-235
In this paper we investigate the properties of the standard two‐pass methodology of testing beta pricing models with misspecified factors. In a setting where a factor is useless, defined as being independent of all the asset returns, we provide theoretical results and simulation evidence that the second‐pass cross‐sectional regression tends to find the beta risk of the useless factor priced more often than it should. More surprisingly, this misspecification bias exacerbates when the number of time series observations increases. Possible ways of detecting useless factors are also examined.

Why are excess returns on China’s Treasury bonds so predictable? The role of the monetary system

Journal of Banking & Finance 2012 36(1), 239-248
It is well documented that the time-varying bond excess returns can be explained by predetermined variables such as information in the term structure and macro economic variables. Recent studies suggest that demand and supply of bonds influence bond excess returns. We extend the literature and find that monetary system attributes affect return dynamics in the bond market. By introducing a theoretical model to forecast excess returns on Treasury bonds in the context of China’s unique monetary system, this paper attributes the predicted components of bond excess returns mainly to the inflexible term structures of official interest rates set by China’s central bank.