###### Abstract
Economic and cultural systems, involvement in financial issues, wealth, attitude to risk and many other factors influence behavioural patterns. This means that the results of studies on financial markets can not necessarily be extrapolated to other markets; in fact, all cultural environments need special attention. What is more, international, and intercultural comparisons are necessary for understanding the degree to which these environments are specific. There is a relative wealth of studies contained within the literature on well-developed financial markets and the behaviour of their investors, while studies on less-developed markets are sparser. Teheran Stock Exchanges of investors on the Tehran Stock Exchange (TSE) are gaining increasingly more attention in the literature. Indeed, one can find studies focusing on the following: IPOs (Initial Public Offering) [6], confirmation of the existence of these effects [7; 8], correlation of personality characteristics with conservatism and availability biases [9], targeting of a deeper understanding of individual investment decisions and portfolios [10; 11; 12]; demonstration of the correlation between overconfidence and trading volume [13]; and an examination of intuitive thinking [14] and mental accounting [15]. However, these studies mostly report the existence of these effects but do not explain interactions between cognitive biases. This paper fills this gap by examining bundles of cognitive biases evident in the behaviour of Iranian stock exchange investors. It delivers further insight to the international community with regard to this niche financial market. An important aspect of studies on cognitive biases and investors' behaviour beyond the cultural environment is the research methodology. The most common stream of research focuses on analysing stock prices and volumes and drawing conclusions on psychological attitudes and failures indirectly by assuming the behavioural patterns (e.g., [16]). Such studies usually examine time series and their correlations and co-integration (e.g., [17]). The second, much more infrequent stream of research concentrates on surveying investors in the market directly. Our research method develops this direct approach by examining investors' behavioural attitudes and such profile metrics as gender, age, investment amount, and portfolio experience. Individual data require adequate quantitative analytics. This study proposes the use of unsupervised learning methods, such as clustering and dimension reduction, which enable a more detailed analysis of investors' profiles to be conducted. This methodology may reveal which cognitive biases occur either jointly or separately, and whether personal and professional concerns have a significant role to play in their occurrence. Contributions: This study fills a research gap and proposes a few contributions in behavioural economics and finance:It uses the joint analysis of cognitive biases observed among stock market investors to derive investors' behavioural profiles;  
It examines bundles of cognitive biases present among TSE investors;  
It provides methodological solutions based on individual data using unsupervised learning methods better to understand bundles of cognitive biases and investors' profiles. The remainder of the paper is as follows. Section 2 presents the literature review on seven analysed cognitive biases, Section 3 gives a summary of the study design, Section 4 describes details of the quantitative analysis, Section 5 discusses the results, and Section 6 provides the conclusions.