June 17, 2016 @ 10:30 am – 12:00 pm
Auditorio Paraninfo. Claustro San Agustín. Universidad de Cartagena.

A systematic view on price based trading strategies
A. Christian Da Silva*, Dunn Capital; Fernando Ferreira, USP; Ju-Yi Yen, University of Cincinnati
We study trading strategies that use historical price data to predict future asset performance. Important and well known examples are short-term or long-term reversal cite{Bondt1989}, momentum and trend-following cite{JT1993,BP}. A distinction between these strategies is the extension of historical data used to predict the future. In particular, short-term reversal appears for portfolios which are build using historical data up to one month. Trend-following and momentum are generally implemented using few months to one year and long-term reversal uses few years of historical data.
We study such strategies by assuming that the asset log-returns $x_{i}$ are Gaussian random variables with drift $mu$, variance $V$ and autocorrelation $rho$ cite{FSY}. We further assume to be able to trade proportional to a simple moving average ($m(T)$) with $T$ terms and calculate the exact expression for the average performance and its variance cite{FSY}.
Empirically we identify the different regimes (from short-term reversal to long-term reversal and beyond) by presenting the Sharpe ratio of our strategy applied to 120 years of the DJIA as a function of $T$.

11:00am–11:30am (Spanish):
An Application of Extreme Value Theory for Measuring Financial Risk in the Uruguayan Pension Fund
Guillermo Magnou*, SURA
Traditional methods for financial risk measures adopts normal distributions as a pattern of the financial return behavior. Assessing the probability of rare and extreme events is an important issue in the risk management of financial portfolios. In this paper, we use Peaks Over Threshold (POT) model of Extreme Value Theory (EVT), and General Pareto Distribution (GPD) which can give a more accurate description on tail distribution of financial losses. The EVT and POT techniques provides well established statistical models for the computation of extreme risk measures like the Return Level, Value at Risk and Expected Shortfall. In this paper we apply this technique to a series of daily losses of AFAP SURA over an 18-year period (1997-2015), AFAP SURA is the second largest pension fund in Uruguay with more than 310,000 clients and assets under management over USD 2 billion.
Our major conclusion is that the POT model can be useful for assessing the size of extreme events. VaR approaches based on the assumption of normal distribution are definitely overestimating low percentiles (due to the high variance estimation), and underestimate high percentiles (due to heavy tails). The absence of extreme values in the assumption of normal distribution underestimate the Expected Shortfall estimation for high percentiles. Instead, the extreme value approach on POT model seems coherent with respect to the actual losses observed and is easy to implement.

11:30am–12:00am (Spanish):
Empirical Approach to the Heston Model Parameters on the Exchange Rate USD / COP
Carlos Grajales*, Universidad de Antioquia; Santiago Medina, Universidad Nacional de Colombia
This work proposes an empirical calibration of the Heston stochastic volatility model for the exchange rate USD / COP. The parameter estimation is done by developing an algorithm that performs simulated trajectories for the exchange rate under
Heston model and looking for matching probability distributionof simulated paths with the probability distribution that comes from the real exchange rate. The calibration is achieved by using both two-sample KS test and Nelder Mead simplex direct search. At the end, the results show that although achieving multiple optima parameter values depending on an initial vector parameter is posible, one of these could be chosen according to financial market information. The ongoing suggested open problems that come with the underlying dynamics presented will be related with
derivatives and risk measures valuation

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