Sawtooth Software: The Survey Software of Choice

Nasim Dehghan Hardoroudi

Nasim Dehghan Hardoroudi

Nasim is a doctoral candidate in Management Science at Aalto University School of Business. She holds Master of Science in Quantitative Methods in Economics and Management Science. Her bachelor degree is in Applied Mathematics.

Nasim is experienced in risk management, portfolio optimization and mathematical modeling. She has developed high skills in various mathematical and statistical softwares.

Nasim’s doctoral dissertation is about advances on portfolio choice. She has been working on this topic under the supervision of Professor Markku Kallio. In her dissertation, she proposes a mixed integer linear programming (MILP) model for the well-known cardinality constrained portfolio optimization problem which is a mixed integer quadratic programming (MIQP) one. The proposed formulation can be solved by standard MILP solvers much faster than the MIQP problem. She also studies the second order stochastic dominance (SSD) constrained portfolio optimization model in her dissertation. In addition, she also works on higher order stochastic dominance efficiency tests and developes some new tests in collaboration with her supervisor.

In one of her research project, in collaboration with Professor Markku Kallio, Professor Merja Halme and Professor Elias Rantapuska, she assesses private individuals’ interest in structured instruments in competition with different types of index funds which will help banks to have a better understanding of their customers with different preferences. To this end, they design a questionnaire containing the proposed products which are chosen internationally to allow comparative studies in other countries. After collecting the respondents’ answers, they use conjoint analysis to identify the importance of the attributes and estimate a utility function for the proposed products of the bank.

Nasim is not only good at quantitative analysis but also in painting, calligraphy and interior design.

Research Results

A short summary of our findings in the article:

The main target of our research was to assess private investors’ interest in simple and transparent structured instruments in competition with different types of index funds. The results of our study will help banks to have a better understanding of their customers with different preferences, and develop proper products to avoid the possible negative long-term effect of the reputation of complex structured products.

To this end, we have designed a questionnaire containing the proposed products which are chosen internationally to allow comparative studies in other countries. We compared six types of structured instruments and five alternative index funds relating to stocks, bonds, commodities and real estates. The questionnaires were distributed among 8713 members of the Finnish Shareholders Association (FSA). After collecting the respondents’ answers (301 of them responded), we used choice based conjoint (CBC) analysis as the research method for preference measurement among the members of the target group. The outcome concerning simple structured instruments is as follows:

  • In the competition among five index funds and four simple structured products, the market share of the structured products indicates that strong demand exists.
  • The demand of structured instruments is highly sensitive to bank charges.
  • The risk- return trade-off is such that some risk of negative return is acceptable given a gain in expected return; i.e., risky instruments are preferred to less risky ones securing the initial funds invested, given that the risks of a negative return are reasonable small and compensated by higher expected return.
  • Statistical analysis reveals characteristics among investors - in particular, age and investment wealth - explain the attitude towards different types of instruments.

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Lighthouse Studio is our flagship software for producing and analyzing online and offline surveys. It contains modules for general interviewing, choice-based conjoint, adaptive choice-based conjoint, adaptive choice analysis, choice-value analysis, and maxdiff exercises.

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