Mihály Ormos

Association between affective temperaments and season of birth in a general student population

BACKGROUND Several studies indicate a significant association between birth season and personality and neuropsychiatric disorders. The aim of our present study was to investigate the association between affective temperaments and season of birth in a nonclinical sample. METHODS 366 university students completed the standardized Hungarian version of the Temperament Evaluation of Memphis, Pisa, Paris and San Diego-Auto-questionnaire (TEMPS-A). Ordinary Least Squares regression was applied to explain the relationship between TEMPS-A subscale and birth season of the respondents. RESULTS We found a significant association between temperament scores and birth season in the case of the Hyperthymic, Cyclothymic, Irritable and Depressive temperaments, while no significant results emerged for the Anxious temperament. LIMITATIONS The relatively small sample size, especially in the case of seasonal and monthly subsamples limits generalization of our results. CONCLUSIONS Our results support the evidence that there is a strong association between season of birth and personality, extending the results to affective temperaments as well. Furthermore, our results are in line with clinical observations concerning the seasonal variation of onset and hospitalization due to affective episodes. This is especially important, since affective temperaments are conceived as the subaffective and subclinical manifestations of major and minor affective disorders indicating a risk for the development of these disorders and also exerting a possible pathoplastic effect, thus our results also have clinical significance.

Entropy-Based Financial Asset Pricing

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return – entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

Non-Parametric and Semi-Parametric Asset Pricing

We find that the CAPM fails to explain the small firm effect even if its non-parametric form is used which allows time-varying risk and non-linearity in the pricing function. Furthermore, the linearity of the CAPM can be rejected, thus the widely used risk and performance measures, the beta and the alpha, are biased and inconsistent. We deduce semi-parametric measures which are non-constant under extreme market conditions in a single factor setting; on the other hand, they are not significantly different from the linear estimates of the Fama-French three-factor model. If we extend the single factor model with the Fama-French factors, the simple linear model is able to explain the US stock returns correctly.

Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading

We implement a market microstructure model including informed, uninformed and heuristic-driven investors, which latter behave in line with loss-aversion and mental accounting. We show that the probability of informed trading (PIN) varies significantly during 2008. In contrast, the probability of heuristic-driven trading (PH) remains constant both before and after the collapse of Lehman Brothers. Cross-sectional analysis yields that, unlike PIN, PH is not sensitive to size and volume effects. We show that heuristic-driven traders are universally present in all market segments and their presence is constant over time. Furthermore, we find that heuristic-driven investors and informed traders are disjoint sets.

Generalized Asset Pricing: Expected Downside Risk-Based Equilibrium Modelling

We introduce an equilibrium asset pricing model, which we build on the relationship between a novel risk measure, the Expected Downside Risk (EDR) and the expected return. On the one hand, our proposed risk measure uses a nonparametric approach that allows us to get rid of any assumption on the distribution of returns. On the other hand, our asset pricing model is based on loss-averse investors of Prospect Theory, through which we implement the risk-seeking behaviour of investors in a dynamic setting. By including EDR in our proposed model unrealistic assumptions of commonly used equilibrium models - such as the exclusion of risk-seeking or price-maker investors and the assumption of unlimited leverage opportunity for a unique interest rate - can be omitted. Therefore, we argue that based on more realistic assumptions our model is able to describe equilibrium expected returns with higher accuracy, which we support by empirical evidence as well.

What Managers Think of Capital Structure and How They Act: Evidence from Central and Eastern Europe

Abstract This paper analyzes the capital structure and the choice of financing alternatives across a broad sample of Central and Eastern European companies. Our investigation is built on two methods: the first concentrates on capital structure decisions through quantitative information applying panel regression for the period 2005–2008 to allow a closer look at the strength of the pecking order and static tradeoff theories; and the second extends the analysis with a qualitative questionnaire on the explicit and latent preferences behind financing policy. The same set of randomly selected 498 firms that fairly represent size classes and countries by the weight of their economic performance are investigated. The CFOs’ answers reflect a pecking order driven behavior, with a limited role for the target leverage ratio; this is confirmed by the estimated coefficients of the panel regression.

Novel approaches to drug-placebo difference calculation: evidence from short-term antidepressant drug-trials.

The calculation of antidepressant‐placebo difference (50% − 30% = 20%) in drug trials is based on the postulate that all placebo responders should be ‘automatically’ antidepressant responders, an assumption that has been never been specifically investigated and substantiated. However, some studies show that a clinically significant part of placebo responders are also antidepressant nonresponders. The traditional calculation of antidepressant‐placebo difference seems, therefore, to be wrong because of an inherent fundamental bias resulting in a marked overestimation of the placebo effect. If the mechanism of action of antidepressant and placebo are independent (unrelated) and the randomization results in two identical (homogenous) groups of patients, then the two basic principles by which the evaluation of potentially useful drugs are based on, such as the relationship between antidepressant response and placebo response rates, would also be independent. In this case, only 50% of placebo responders are antidepressant responders (and another 50% of them are antidepressant nonresponders) and the antidepressant‐placebo difference would be 50% − 15% = 35%, instead of 50% − 30% = 20%, as calculated by the traditional method. For real interpretation, decisions that have been made on traditional drug‐placebo difference evaluation should be recalculated and reviewed, not only in major depression but also in other psychiatric and medical disorders where the drug‐placebo difference is in the same magnitude. Copyright

Unravelling the asymmetric volatility puzzle: A novel explanation of volatility through anchoring

This paper discusses a novel explanation for asymmetric volatility based on the anchoring behavioral pattern. Anchoring as a heuristic bias causes investors to focus on recent price changes and price levels, which leads to a belief in continuing trend and mean-reversion, respectively. The empirical results support our theoretical explanation through an analysis of large price fluctuations in the S&P 500 and the resulting effects on implied and realized volatility. These results indicate that asymmetry (a negative relationship) between shocks and volatility in the subsequent period indeed exist. Moreover, contrary to previous research, our empirical tests also suggest that implied volatility is not simply an upward biased predictor of future deviation compensating for the variance of the volatility but rather, due to investors’ systematic anchoring to losses and gains in their volatility forecasts, a co-integrated yet asymmetric over-/under-estimated financial instrument. We also provide results indicating that the medium-term implied volatility (measured by the VIX Index) is an unbiased though inefficient estimation of realized volatility, while in contrast short-term volatility (measured by the recently introduced VXST Index representing the 9-day implied volatility) is also unbiased and yet efficient.

The Case of “Less is More”: Modelling Risk-Preference with Expected Downside Risk

Abstract This paper discusses an alternative explanation for the empirical findings contradicting the positive relationship between risk (variance) and reward (expected return). We show that these contradicting results might be due to the false definition of risk-perception, which we correct by introducing Expected Downside Risk (EDR). The EDR parameter, similar to the Expected Shortfall or Conditional Value-at-Risk, measures the tail risk, however, fits and better explains the utility perception of investors. Our results indicate that when using the EDR as risk measure, both the positive and negative relationship between expected return and risk can be derived under standard conditions (e. g. expected utility theory and positive risk-aversion). Therefore, no alternative psychological explanation or additional boundary condition on utility theory is required to explain the phenomenon. Furthermore, we show empirically that it is a more precise linear predictor of expected return than volatility, both for individual assets and portfolios.

Components of investment grade wine prices

We investigate the fine-wine market from a weak-form efficiency viewpoint using the London International Vintners Exchange index family for the period from January 1993 to February 2010. The autoregressive moving average spectral estimates of variance ratios (VRs) show that the random walk (RW) hypothesis can be rejected regardless of USD or GBP currency denomination and regardless of inflation. The wine returns exhibit large positive autocorrelation, resulting in VRs that are above unity, which indicates that apart from the RW, a stationary component characterizes wine prices. The large stationary component can be associated with the illiquidity of wines and the inefficiency of young wines. The RW component of wine prices is likely to be driven by the market factor. Owing to currency risk, a US wine investor faces a higher risk than his/her UK counterpart, although wines hedge against inflation in both currencies.