Investors’ preference towards risk: evidence from the Taiwan stock and stock index futures markets

We apply the stochastic dominance (SD) tests proposed by Linton et al. (2005) and Davidson and Duclos (2000) for risk averters and risk seekers to examine investors’ preferences with respect to the Taiwan stock index and its corresponding index futures. We find that there is no first‐order SD relationship between Taiwan spot and futures. However, for second‐ and third‐order SD, we find that spot dominates futures for risk averters whereas futures dominates spot for risk seekers. The implication is that to maximize their expected utilities, risk averters prefer to buy stocks, whereas risk seekers prefer long index futures.     

The volume–volatility relationship and the opening of the Korean stock market to foreign investors after the financial turmoil in 1997

This paper investigates the stock volatility–volume relation in the Korean market for the period 1995–2001. Previous research examined the impact of liberalization on the Korean stock market up to the period before the financial turmoil in 1997 although the crucial measures of the liberalization were introduced after the crisis under the International Monetary Fund program. One of the major features of the reformation was the financial opening to foreign investors. In this study the ‘total’ trading volume is separated into the domestic investors’ and the foreign investors’ volume. By doing this the information used by two different groups of traders can be separated. Further, in addition to the absolute value of the returns and their squares we use the conditional volatility from a GARCH-type model as an alternative measure of stock volatility. The following observations, among other things, are noted about the volume–volatility causal relationship. First, for the entire period there is a strong bidirectional feedback between volume and volatility. In most cases this causal relationship is robust to the measures of volume and volatility used. Second, volatility is related only to ‘domestic’ volume before the crisis whereas after the crisis a bidirectional feedback relation between ‘foreign’ volume and volatility begins to exist. In other words, ‘foreign’ volume tends to have more information about volatility in recent years, which suggests the increased importance of ‘foreign’ volume as an information variable.      

How does beta explain stochastic dominance efficiency?

Stochastic dominance rules provide necessary and sufficient conditions for characterizing efficient portfolios that suit all expected utility maximizers. For the finance practitioner, though, these conditions are not easy to apply or interpret. Portfolio selection models like the mean–variance model offer intuitive investment rules that are easy to understand, as they are based on parameters of risk and return. We present stochastic dominance rules for portfolio choices that can be interpreted in terms of simple financial concepts of systematic risk and mean return. Stochastic dominance is expressed in terms of Lorenz curves, and systematic risk is expressed in terms of Gini. To accommodate for risk aversion differentials across investors, we expand the conditions using the extended Gini.     

SAMPLING ERROR IN FIRST ORDER STOCHASTIC DOMINANCE

This study analyzes the standard method of testing for first order stochastic dominance from a statistical viewpoint and applies a boundary crossing algorithm to approximate the resulting error probabilities. Error probabilities can be estimated even when the two distributions are not equal. This approach, which is useful when large sample simulations are not feasible, helps clarify some of the unusual results obtained by Kroll and Levy in an earlier study.     

Optimal portfolio choice in the bond market

We consider the Merton problem of optimal portfolio choice when the traded instruments are the set of zero-coupon bonds. Working within a Markovian Heath–Jarrow–Morton model of the interest rate term structure driven by an infinite-dimensional Wiener process, we give sufficient conditions for the existence and uniqueness of an optimal trading strategy. When there is uniqueness, we provide a characterization of the optimal portfolio as a sum of mutual funds. Furthermore, we show that a Gauss–Markov random field model proposed by Kennedy [Math. Financ. 4, 247–258(1994)] can be treated in this framework, and explicitly calculate the optimal portfolio. We show that the optimal portfolio in this case can be identified with the discontinuities of a certain function of the market parameters.     

Stochastic dominance as an approach to uncertainty in cost accounting

Presently textbook treatment of the topic of uncertainty in cost accounting never goes beyond the notions of mean and variance and the maximization of expected utilities. Because the application of these models requires artificial assumptions about either loss functions or utility functions, students are often left wondering how practical probabilistic models are afterall. This paper suggests that stochastic dominance be used to supplement the current textual material on uncertainty. Since these models are easy to implement in a cost accounting context, the class can devote more time to accounting issues in the context of uncertainty rather than get lost in decision theory. Three models of stochastic dominance are discussed here: the first order, the second order, and the third order stochastic dominance. All the necessary assumptions about each model are stated, and each model is accompanied by a numerical example.     

Bootstrapping a distance test for stochastic dominance analysis

A major impediment to measuring portfolio performance under stochastic dominance has been the lack of test statistics for orders of stochastic dominance above first degree. In this article, the Bootstrap method, introduced by Efron (1979), is used to estimate critical values for distance statistics in order to test the null hypothesis of no dominance, under second- and third-degree stochastic dominance, for several samples of stock returns. These test statistics, suggested by Whitmore (1978), are analogous to the Kolmogorov-Smirnov distance statistics that can be used to test for first-degree stochastic dominance. Stochastic dominance is shown to accurately assess portfolio performance of sample distributions when the population distributions are controlled and Bootstrap statistics are employed in the analysis. In addition, second- and third-degree stochastic dominance analysis of the smallfirm January anomaly indicates that, over the 23-year time period 1964 to 1986, small firms statistically dominate a diversified market index in only one calendar year.     

Stochastic dominance analysis of Asian hedge funds

We employ the stochastic dominance approach that utilizes the entire return distribution to rank the performance of Asian hedge funds as traditional mean-variance and CAPM approaches could be inappropriate given the nature of non-normal returns. We find both first-order and higher-order stochastic dominance relationships amongst the funds and conclude that investors would be better off by investing in the first-order dominant funds to maximize their expected wealth. By investing in higher-order dominant funds, risk-averse investors can maximize their expected utilities but not their wealth. In addition, we find the common characteristic for most pairs of funds is that one fund is preferred to another in the negative domain whereas the preference reverses in the positive domain. We conclude that the stochastic dominance approach is more appropriate compared with traditional approaches as a filter in hedge fund selection. Compared with traditional approaches, the SD approach, not only is assumption free, but also provides greater insights to the performance and risk inherent in a hedge fund's track record.     

Insider trading in an equilibrium model with default: a passage from reduced-form to structural modelling

We study, in the framework of Back [Rev. Financial Stud. 5(3), 387–409 (1992)], an equilibrium model for the pricing of a defaultable zero coupon bond issued by a firm. The market consists of a risk-neutral informed agent, noise traders, and a market maker who sets the price using the total order. When the insider does not trade, the default time possesses a default intensity in the market’s view as in reduced-form credit risk models. However, we show that, in equilibrium, the modelling becomes structural in the sense that the default time becomes the first time that some continuous observation process falls below a certain barrier. Interestingly, the firm value is still not observable. We also establish the no expected trade theorem that the insider’s trades are inconspicuous.      

Macro information environment change and the quality of management earnings forecasts

The 1990s were characterized by substantial increases in the performance of and investor reliance on financial analysts. Because managers possess superior private information and issue forecasts to align investors’ expectations with their own, we predict that managers increased the quality of their earnings forecasts during the 1990s in order to keep pace with the improved forward-looking information provided by financial analysts, upon which investors increasingly relied. Using a sample of 2,437 management earnings forecasts, we document an increase in management earnings forecast precision, management earnings forecast accuracy, and managers’ tendency to explain earnings forecasts in 1993–1996 relative to 1983–1986. Given that these forecast characteristics are linked to greater informativeness and credibility, we also document that the information content of management earnings forecasts, as measured by the strength of share price responses to forecast news, increased in 1993–1996 relative to 1983–1986. As expected, the increased information content of management forecasts primarily occurred for firms covered by financial analysts.

Coherent Distortion Risk Measures and Higher-Order Stochastic Dominances

Abstract

We show that the only coherent distortion risk measure that is consistent with respect to 3-convex order and hence with stochastic dominance of order 3 is the expected value, thus generalizing previous results of Hurlimann and solving a problem posed by Yamai and Yoshiba.     

Bonds versus stocks: Investors’ age and risk taking

It has become increasingly popular to advise investors to relocate their funds from a primarily stock portfolio to a primarily bond portfolio as they get older. However, the well-known decision rules such as mean–variance or stochastic dominance rules are unable to explain this common practice. Almost stochastic dominance (ASD) and almost mean–variance (AMV) approaches are used to examine the dominance of stock and bond portfolios. ASD and AMV rules unambiguously support the popular practice of advising higher stock to bond ratio for long investment horizons. Hence, we provide an explanation to the practitioners’ recommendation within the expected utility paradigm.     

Order submission behaviors and opening price behaviors: evidence from an emerging market

Recent studies document that mutual funds demonstrate an overnight information advantage over foreign investors in Taiwan, a fast emerging market. However, this inequality contradicts the documented foreign investors’ growing market dominance and information advantage. Motivated by the inconsistency, we apply intraday data to examine the linkage between investors’ order submission behaviors and the opening price behaviors of the top net-trade stocks of professional institutional investors. We find that mutual funds exhibit a more persistent and aggressive trading pattern than foreign investors. The order submission behavior of aggressive individuals, following closely mutual funds’ trades, mainly drives the observed informational differences.     

In which financial markets do mutual fund theorems hold true?

The mutual fund theorem (MFT) is considered in a general semimartingale financial market S with a finite time horizon T, where agents maximize expected utility of terminal wealth. The main results are:

Real-time market microstructure analysis: online transaction cost analysis

Motivated by the practical challenge in monitoring the performance of a large number of algorithmic trading orders, this paper provides a methodology that leads to automatic discovery of causes that lie behind poor trading performance. It also gives theoretical foundations to a generic framework for real-time trading analysis. The common acronym for investigating the causes of bad and good performance of trading is transaction cost analysis Rosenthal [Performance Metrics for Algorithmic Traders, 2009]). Automated algorithms take care of most of the traded flows on electronic markets (more than 70% in the US, 45% in Europe and 35% in Japan in 2012). Academic literature provides different ways to formalize these algorithms and show how optimal they can be from a mean-variance (like in Almgren and Chriss [J. Risk, 2000, 3(2), 5–39]), a stochastic control (e.g. Guéant et al. [Math. Financ. Econ., 2013, 7(4), 477–507]), an impulse control (see Bouchard et al. [SIAM J. Financ. Math., 2011, 2(1), 404–438]) or a statistical learning (as used in Laruelle et al. [Math. Financ. Econ., 2013, 7(3), 359–403]) viewpoint. This paper is agnostic about the way the algorithm has been built and provides a theoretical formalism to identify in real-time the market conditions that influenced its efficiency or inefficiency. For a given set of characteristics describing the market context, selected by a practitioner, we first show how a set of additional derived explanatory factors, called anomaly detectors, can be created for each market order (following for instance Cristianini and Shawe-Taylor [An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, 2000]). We then will present an online methodology to quantify how this extended set of factors, at any given time, predicts (i.e. have influence, in the sense of predictive power or information defined in Basseville and Nikiforov [Detection of Abrupt Changes: Theory and Application, 1993], Shannon [Bell Syst. Tech. J., 1948, 27, 379–423] and Alkoot and Kittler [Pattern Recogn. Lett., 1999, 20(11), 1361–1369]) which of the orders are underperforming while calculating the predictive power of this explanatory factor set. Armed with this information, which we call influence analysis, we intend to empower the order monitoring user to take appropriate action on any affected orders by re-calibrating the trading algorithms working the order through new parameters, pausing their execution or taking over more direct trading control. Also we intend that use of this method can be taken advantage of to automatically adjust their trading action in the post trade analysis of algorithms.     

An Asymptotic Expansion Approach to Currency Options with a Market Model of Interest Rates under Stochastic Volatility Processes of Spot Exchange Rates

This paper proposes an asymptotic expansion scheme of currency options with a libor market model of interest rates and stochastic volatility models of spot exchange rates. In particular, we derive closed-form approximation formulas for the density functions of the underlying assets and for pricing currency options based on a third order asymptotic expansion scheme; we do not model a foreign exchange rate’s variance such as in Heston [(1993) The Review of Financial studies, 6, 327–343], but its volatility that follows a general time-inhomogeneous Markovian process. Further, the correlations among all the factors such as domestic and foreign interest rates, a spot foreign exchange rate and its volatility, are allowed. Finally, numerical examples are provided and the pricing formula are applied to the calibration of volatility surfaces in the JPY/USD option market.     

A Recursive Scheme for Perpetuities with Random Positive Interest Rates. II: The Impenetrable Wall

In some former contributions, the authors investigated actuarial quantities with stochastic interest rates. In a first model, the randomness is modelled by means of an ordinary Wiener process, and as a consequence negative interest rates are possible. A second model provides a tool to avoid these negative interest rates, which can be necessary in particular situations. This paper wants to present an alternative solution to the problem of negative interest rates. This new model will be implemented to the case of an annuity certain and of a perpetuity.     

Pricing growth-rate risk

We characterize the compensation demanded by investors in equilibrium for incremental exposure to growth-rate risk. Given an underlying Markov diffusion that governs the state variables in the economy, the economic model implies a stochastic discount factor process S. We also consider a reference growth process G that may represent the growth in the payoff of a single asset or of the macroeconomy. Both S and G are modeled conveniently as multiplicative functionals of a multidimensional Brownian motion. We consider the pricing implications of parametrized family of growth processes G ^ε , with G ⁰=G, as ε is made small. This parametrization defines a direction of growth-rate risk exposure that is priced using the stochastic discount factor S. By changing the investment horizon, we trace a term structure of risk prices that shows how the valuation of risky cash flows depends on the investment horizon. Using methods of Hansen and Scheinkman (Econometrica 77:177–234, 2009), we characterize the limiting behavior of the risk prices as the investment horizon is made arbitrarily long.     

Is gold good for portfolio diversification? A stochastic dominance analysis of the Paris stock exchange

This paper aims to assess the role of gold quoted in Paris in the diversification of French portfolios from 1949 to 2012 using the stochastic dominance (SD) approach. The principal advantage of this method is that there is no restriction on the distribution of the returns. Our results show that stock portfolios including gold stochastically dominate those without gold at the second and third orders. This implies that risk-averse investors would be better off by including gold in their stock portfolios to maximize their expected utilities. The study on sub-periods shows that this result holds especially in unstable or crisis times. However, these results do not hold for bond or risk-free portfolios, for which the portfolios without gold dominate those with gold. To check the robustness of our results, our SD analysis of a mixed portfolio (50% stocks, 30% bonds and 20% the risk-free asset) provides results similar to those for portfolios with stocks only, except from 1971 to 1983. Portfolios including gold quoted in London show results similar to those from Paris. The results of mean–variance performance measures confirm the findings of previous studies that gold is good for the diversification of stock portfolios but not for bond portfolios.