Forecasting Forex: theoretical methods, empirical analysis and responsibilities
I want to share with you the research I did behind my Master Thesis about forecasting Forex rates.
Forecasting Forex: theoretical methods, empirical analysis and responsibilities
If you landed here it is because you are interested in forecasting Forex prices. You are not the only one and I will show you how to start understanding different methods aiming to forecasting Forex rates.
As you can read on my resume, this is the final task of the Master degree in Economics and Finance and it is strictly linked to the previous project work “Is technical analysis profitable? A critique within Forex market” I shared with you.
I originally wrote my Undergraduate Thesis about Forex market, in conclusion of the Economics and Commerce degree. At that time, I did a wide research about main features of currencies trading and now my Master Thesis consists of a quantitative study about forecasting Forex prices, including a chapter about responsibilities for the financial analyst.
Abstract
The purpose of this research is to dress the part of a professional financial analyst, from the beginning to the end.
I choose to study predictability in Foreign Exchange market, since I want to discuss three methods about forecasting Foreign Exchange market prices and to know if I could obtain profitable information that can be offered by a financial analyst to his clients.
My idea is to study in the first chapter Artificial Neural Networks, Support Vector Machines and Technical Analysis by a theoretical point of view, concentrating on what is necessary for the analysis of predictability in Foreign Exchange market prices. I want to highlight that this Thesis is written in combination with the project work for “International Financial Markets” course, whose results relating to profitability of Technical Analysis become part of this experiment for my Thesis. Of course I brighten in which way the two experiments can be integrated.
In the second chapter, after a clear explanation about each detail regarding the entire framework of my experiment, I continue with the practical examination of these methods, widely detailing choices and problems occurred during the analysis.
I explain if and how is possible to compare results from ANNs, SVMs, and TA, because it is not easy the way it looks. Not only is interesting to get a profitable strategy as an experiment result, but I think that clearing up why some strategies may not work is even more remarkable.
After a broad quantitative analysis, the third and last chapter brings the reader to the law of financial markets, because I desire to show a deep research concerning the role of a financial analyst, in particular about laws and self-regulation in Italy and Europe. Moreover, I illustrate a variety of disclaimers used in practice by financial analysts and I justify if they really protect the analyst or his clients. Strictly related to my purpose is the analysis of responsibilities for the financial analyst, giving a clear sight on the difference about two categories of clients: proximate third party and distant third party.
The natural conclusion is a reunification of quantitative and law sides, because, behaving like a financial analyst, I ask myself if should I publish the results of the different tested strategies, giving my detailed reasons and opinions about this important choice that may lead to the significant consequences I showed, both for investors and myself.
Table of contents:
ABSTRACT
INTRODUCTION
1 THEORETICAL METHODS
1.1 Artificial Neural Networks
1.1.1 Artificial Neural Networks in FOREX market
1.1.2 Testing Artificial Neural Networks
1.2 Support Vector Machines
1.2.1 Support Vector Machines in FOREX market
1.2.2 Testing Support Vector Machines
1.3 Technical Analysis
1.3.1 “Is Technical Analysis profitable? A critique within FOREX”
1.3.2 Applying previous results to this framework
2 EMPIRICAL ANALYSIS
2.1 Empirical approach
2.1.1 Defining the framework
2.1.2 The Random Walk
2.1.3 Data snooping for robust control
2.2 Results
2.2.1 Artificial Neural Networks
2.2.2 Support Vector Machines
2.2.3 Technical Analysis
3 RESPONSIBILITIES
3.1 Financial Analyst
3.1.1 Legislation and regulation in Italy and Europe
3.1.2 Disclaimers
3.2 Responsibilities for financial analysts
3.2.1 Publishing information and data
3.2.2 Financial analysts and lawsuits
3.2.3 Should I publish my results?
CONCLUSION
BIBLIOGRAPHY
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