Francisco Guijarro

Stock market trading rule based on pattern recognition and technical analysis

This work provides empirical evidence which confronts the Efficient Market Hypothesis.This work introduces a new definition of the flag pattern.The results show that the trading rule can beat the market.The European market is more inefficient than the US market. This work presents empirical evidence which confronts the classical Efficient Market Hypothesis, which states that it is not possible to beat the market by developing a strategy based on a historical price series.We propose a risk-adjusted profitable trading rule based on technical analysis and the use of a new definition of the flag pattern. This rule defines when to buy or sell, the profit pursued in each operation, and the maximum bearable loss. In order to untie the results from randomness, we used a database comprised of 91,307 intraday observations from the US Dow Jones index. We parameterized the trading rule by generating 96 different configurations and reported the results of the whole sample over 3 subperiods. In order to widen its validity we also replicated the analysis on two leading European indexes: the German DAX and the British FTSE. The returns provided by the proposed trading rule are higher for the European than for the US index, which highlights the greater inefficiency of the European markets.

A goal programming approach to estimating performance weights for ranking firms

This paper proposes several goal programming (GP) models for estimating the performance measure weights of firms by means of constrained regression. Since some single-criterion performance measures are usually in conflict, we propose two opposed alternatives for determining multiple-criterion performance: the first is to calculate a consensus performance that reflects the majority trend of the single-criterion measures and the other is to calculate a performance that is biased towards the measures that show the most discrepancy with the rest. GP makes it possible to model both approaches as well as a compromise between the two extremes. Using two case studies reported in the literature and introducing another one examining non-financial companies listed in Ibex-35, we compare our proposal with other methods such as CRITIC and a modified version of TOPSIS. In order to improve the comparisons a Montecarlo simulation has been performed in all three case studies. Scope and purpose: The study falls into the area of multiple-criteria analysis of business performance. Firms are obliged to report a vast amount of financial information at regular intervals, and for this there is a wide range of performance measures. Multicriteria performance is calculated from the single-criterion measures and is then used to draw up rankings of firms. As a complement to the other multicriteria methods described in the literature, we propose the use of GP for implementing two quite different strategies: overweighting the measures in line with the general trend or overweighting the measures that conflict with the rest. Besides the use of Spearmans correlation, we introduce two other measures for comparing the solutions obtained.

Mixed valuation methods: a combined AHP-GP procedure for individual and group multicriteria agricultural valuation

This paper introduces a new assessment method classification, in which a third procedure, mixed valuation, is jointly included with the traditional economic and non-economic methodologies. The paper considers a case of multiple actors (from a previous work by the same authors—Aznar et al. (Estudios de Economía Aplicada, 25(2):389–409, 2007), in which a new technique for multicriteria agriculture valuation (MAVAM) was proposed. The method is specifically designed for situations in which scarce information about the elements being compared (quantified or not) is available. It works in individual and group decision making contexts and attempts to both obtain and incorporate the objective information associated with the tangible aspects of the problem and the subjective knowledge associated with the human factor into the valuation process. It combines two of the most extended multicriteria decision making techniques: the Analytic Hierarchy Process (AHP) and Goal Programming (GP). The first of these enables tangible and intangible information stemming from known elements to be collected by using pairwise comparisons; the second allows the scarce information available and the personal approach to the valuation to be included in the valuation process. The proposed methodology is illustrated by means of its application to a case of individual and group valuation of an agricultural asset in the La Ribera district, Valencia (Spain).

Estimating Regression Parameters with Imprecise Input Data in an Appraisal Context

Traditional valuation models, such as capitalization or comparative, share the common principle of using exact information in their calculations. However, in the professional field, it is difficult to find situations characterized by the wealth and precision of the information available. Within the professional context, it is usually necessary to carry out estimates on some of the explanatory variables of pricing, even though consciously introducing an important degree of subjectivity. The model proposed in this paper, which uses the goal programming optimization technique, is capable of dealing with imprecise information, since it allows to consider intervals to define the values of the explanatory variables. Additionally, this paper presents and demonstrates several propositions that increase the informative capacity of the model presented.

An ANP framework for property pricing combining quantitative and qualitative attributes

This paper presents a new comparative methodology for the valuation of urban properties based on the Analytic Network Process (ANP), with the twin objective of overcoming the drawbacks found in classical urban valuation methods and enhancing the current set of tools available for the appraiser. The ANP enables to tackle contexts in which scant information is available, qualitative variables are considered and, unlike the Analytic Hierarchy Process, interdependences among variables are present, all very common situations in professional valuation practice, so this study proposes its application to the field of urban valuation. To illustrate the new proposal, a real case study is put forward alongside four different models for solving it, with the aim of analysing the varying accuracy of each model. It may be concluded that the more information taken into account in relation to the interdependences between criteria and alternatives, the greater the accuracy of the results.

Ranking Spanish savings banks: A multicriteria approach

Business rankings in general, and those referring to savings banks in particular, are usually based on a single criterion, so that rankings vary according to the criterion used. This paper proposes a multicriteria methodology based on goal programming that considers simultaneously the different dimensions involved in savings bank performance. An analysis of the Spanish savings banks reveals that credit risk is the most important performance dimension of these financial institutions, followed by profitability and productivity.

Modelling aesthetic variables in the valuation of paintings: an interval goal programming approach

The economic valuation of works of art is a decisive subject in the general field of valuation. Unlike in other areas of valuation, the explanatory power of the directly observable and quantifiable variables is very low, therefore, aesthetic criteria must be used to obtain valuation models with a greater explanatory power. Frequently, these aesthetic criteria are not always precise, and experts usually express them as an interval of values. This paper describes different valuation models that use the goal programming optimisation method to include explanatory variables of the closing price in the form of intervals of values. We have also modelled the possibility that an expert can determine the relevance of each observation in the formation of the valuation function depending on the degree of precision with which the variables have been defined.

Credit risk management: A multicriteria approach to assess creditworthiness

Abstract Credit risk management is a key issue for any company at anytime, but is especially important in the case of the banking industry. This fact is more than evident in times of financial crises, when financial institutions can suffer high losses due to unpaid credits. For this reason, international financial supervisors and authorities have forced banks to monitor their credit risk and this risk is a variable that is constantly under the scrutiny of all financial agents in the international markets. There are currently several methodologies that aim to predict the default probability of debtors. Many of them use logit analysis to discriminate among debtors. New methodologies make use of neural networks or multicriteria methods. This paper presents a new proposal based on goal programming, which allows the judgement of experts to be incorporated into the model, as suggested by the Basel Committee. Our approach combines the objective information of financial variables with the subjective judgement of experts about the different relevance of these variables, so observing the Basel Committee guidelines.

The curvature of the tracking frontier: A new criterion for the partial index tracking problem

Index tracking aims to select portfolios that imitate the behavior of a stock index. A tracking strategy is referred to as partial when the tracking portfolio is solely formed by a subset of stocks, so enabling a substantial cost reduction in comparison with full tracking. Three criteria are usually employed in the literature when building the tracking portfolio: tracking error variance, excess return and tracking portfolio variance. This paper considers a new parameter for use with the above: frontier curvature. This criterion is not defined for a particular portfolio, but for all the portfolios that define the tracking frontier. The main implication is that a manager can satisfy different investment profiles with the same subset of stocks. The manager will therefore reduce transaction costs as all the portfolios on the frontier contain the same stocks.

A dynamic trading rule based on filtered flag pattern recognition for stock market price forecasting

We propose an automatic and dynamic trading rule based on flag pattern recognition.The strategy does not depend on the ability of the trader to guess the best configuration of the trading rule.We include several filters for the trades, one of them considering the EMA indicator in short and medium timeframes.The trading rule is applied on a large intraday database for the DJIA index.We can conclude that our proposal is far superior to the previous flag pattern strategies as regards both profitability and risk. In this paper we propose and validate a trading rule based on flag pattern recognition, incorporating important innovations with respect to the previous research. Firstly, we propose a dynamic window scheme that allows the stop loss and take profit to be updated on a quarterly basis. In addition, since the flag pattern is a trend-following pattern, we have added the EMA indicator to filter trades. This technical analysis indicator is calculated both for 15-min and 1-day timeframes, which enables short and medium terms to be considered simultaneously. We also filter the flags according to the price range on which they are developed and have limited the maximum loss of each trade to 100 points. The proposed methodology was applied to 91,309 intraday observations of the DJIA index, considerably improving the results obtained in the previous proposals and those obtained by the buy & hold strategy, both for profitability and risk, and also after taking into account the transaction costs. These results seem to challenge market efficiency in line with other similar studies, in the specific analysis carried out on the DJIA index and is also limited to the setup considered.