Three essays on the psychology of investment and financial markets

Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

Treatment intensification and risk factor control: toward more clinically relevant quality measures.

BACKGROUND: Intensification of pharmacotherapy in persons with poorly controlled chronic conditions has been proposed as a clinically meaningful process measure of quality. OBJECTIVE: To validate measures of treatment intensification by evaluating their associations with subsequent control in hypertension, hyperlipidemia, and diabetes mellitus across 35 medical facility populations in Kaiser Permanente, Northern California. DESIGN: Hierarchical analyses of associations of improvements in facility-level treatment intensification rates from 2001 to 2003 with patient-level risk factor levels at the end of 2003. PATIENTS: Members (515,072 and 626,130; age >20 years) with hypertension, hyperlipidemia, and/or diabetes mellitus in 2001 and 2003, respectively. MEASUREMENTS: Treatment intensification for each risk factor defined as an increase in number of drug classes prescribed, of dosage for at least 1 drug, or switching to a drug from another class within 3 months of observed poor risk factor control. RESULTS: Facility-level improvements in treatment intensification rates between 2001 and 2003 were strongly associated with greater likelihood of being in control at the end of 2003 (P < or = 0.05 for each risk factor) after adjustment for patient- and facility-level covariates. Compared with facility rankings based solely on control, addition of percentages of poorly controlled patients who received treatment intensification changed 2003 rankings substantially: 14%, 51%, and 29% of the facilities changed ranks by 5 or more positions for hypertension, hyperlipidemia, and diabetes, respectively. CONCLUSIONS: Treatment intensification is tightly linked to improved control. Thus, it deserves consideration as a process measure for motivating quality improvement and possibly for measuring clinical performance.