Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Health investment complementarities under competing risks

Applying the competing--risks model to multi--cause mortality,this paper provides a theoretical and empirical investigation of the positive complementarities that occur between disease--specific policy interventions. We argue that since an individual cannot die twice, competing risks imply that individuals will not waste resources on causes that are not the most immediate, but will make health investments so as to equalize cause--specific mortality. However, equal mortality risk from a variety of diseases does not imply that disease--specific public health interventions are a waste. Rather, a cause--specific intervention produces spillovers to other disease risks, so that the overall reduction in mortality will generally be larger than the direct effect measured on the targeted disease. The assumption that mortality from non--targeted diseases remains the same after a cause--specific intervention under--estimates the true effect of such programs, since the background mortality is also altered as a result of intervention. Analyzing data from one of the most important public health programs ever introduced, the Expanded Program on Immunization (EPI) of the United Nations, we find evidence for the existence of such complementarities, involving causes that are not biomedically, but behaviorally, linked.

Biaixos informatius als mercats de valors

[cat] L'article presenta els resultats d'unes proves empíriques que mostren com en la informació econòmica a la premsa escrita poden haver-hi biaixos sistemàtics. Les empreses de sectors regulats son més actives informativament la qual cosa es tradueix en un major protagonisme en la premsa econòmica especialitzada. La primera prova empírica consisteix en una comprovació del protagonisme de les empreses de l'Ibex 35 i del Dow Jones a la premsa general i la econòmica d'Espanya i els Estats Units respectivament En la segona es fa una anàlisi de la informació del periòdic econòmic Expansión. L'existència de biaixos informatius sistemàtics indueix a qüestionar-se la hipòtesi de racionalitat en els mercats financers.

Optimal capital structure: a trade-off model and its empirical testing

In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

The measurement of ice velocity, mass balance and thinning-rate on Johnsons Glacier, Livingston Island, South Shetland Islands, Antarctica

A network of twenty stakes was set up on Johnsons Glacier in order to determine its dynamics. During the austral summers from 1994-95 to 1997-98, we estimated surface velocities, mass balances and ice thickness variations. Horizontal velocity increased dow nstream from 1 m a- 1 near the ice divides to 40 m a- 1 near the ice terminus. The accumulation zone showed low accumulation rates (maximum of 0,6 m a- 1 (ice)), whereas in the lower part of the glacier, ablation rates were 4,3 m a- 1 (ice). Over the 3-year study period, both in the accumulation and ablation zones, we detected a reduction in the ice surface level ranging from 2 to 10 m from the annual ve rt ical velocities and ice-thinning data, the mass balance was obtained and compared with the mass balance field values, resulting in similar estimates. Flux values were calculated using cross-section data and horizontal velocities, and compared with the results obtained by means of mass balance and ice thinning data using the continuity equation. The two methods gave similar results.