Understanding Behavioural Biases and their Impact on Mutual Fund Investment Decisions: A Systematic Literature Review
Pooled investments, or mutual funds, offer investors economies of scale from inexpensive and diversified portfolios that are frequently distinguished by fund style. They also give investors access to liquidity. The present study is descriptive in nature and it critically surveys the literature on behavioural biases of retail investors and fund managers and impact of the same on their investment decisions and risk taking. The study points out that both herding and window dressing occurs, and fund manager also displays home bias and overconfidence, which lead to increased risk taking and turnover. The disposition effect and performance related incentive fee cause manager to further increase risk.
Introduction
According to SPIVA Year-End Report for 2023, a whopping 74 per cent of actively managed mid and small-cap funds failed to outperform their benchmark indices (Exhibit 1). The report thus posed a serious question about the effectiveness of the actively managed funds.
Indians exhibit a higher level of bias since the Indian financial market is considerably less established (Quddus, 2022). The institutional context of the Indian Mutual Fund business is unique and relatively unexplored. The present study is focussed towards understanding the behavioural biases and its impact on mutual fund investment decisions.
Literature Reviews on Behavioural Biases and Investment Decisions
In case of behavioural finance, theories argue that stock prices can be influenced by psychological and emotional factors. Investment decisions are also influenced by risk perception and are significantly positively related to one another. The perception of risk is significantly positively impacted by herding, disposition effect, and blue-chip bias. However, overconfidence has a significant positive impact on investment decision, but not on risk perception (Almansour, 2023). Eight major biases which can affect investment decisions can be categorised in the following manner:
Table 1: Selected literature reviews on behavioural biases and its impact on mutual fund investment decisions
| SI. No. | Reference | Biases | Major findings | Impact on Investment Decision |
|---|---|---|---|---|
| 1 | (Odean, 1999) | Disposition | Disposition bias is estimated as a difference between the fraction of realized gains and fraction of realized losses. Rapid winner liquidation may be associated with subpar fund performance. | An investor or fund manager may have a tendency to cling onto losing equities for an extended period of time, while selling winning stocks fast. Investors thus make a mistake of choosing high front-end load funds and overestimate anticipated holding periods. |
| 2 | (Candraningrat I. R., 2018) | Framing | Investors who are given positive information framing will predict stock prices higher than investors given negative information framing. | An investor with narrow framing bias does not pay attention to the overall effect of the judgement of buying and selling the assets. |
| 3 | (Alexander Puetz, 2011) | Overconfidence | Overconfident investors subsequently trade more which showcases the false beliefs related to their abilities. | The fund manager trades frequently or prefers speculative stock, which leads to poor performance. |
| 4 | (Massa, 2006) | Home or Local | Investors prefer geographic proximity as it offers familiarity and low cost for acquisition of information. | Fund managers may prefer the stock of companies which are geographically close to his or her home. This leads to an exposure of locally managed mutual funds without putting any importance on its performance and cost. |
| 5 | (Kartasova, 2014) | Snake Bite | This causes fear to take risks that prevents investors from profit lock which may affect investment return. | Fund managers may weigh their decision more heavily towards the events of recent past. |
| 6 | (Koch, 2017) & (Kumar & Jarwal, 2022) | Herding | Out of a sample of 2700 funds between 1989 and 2009, it was identified that only leading funds outperform over several subsequent quarters. In a recent study, herding bias is a short run phenomenon and herding is more prevalent in developing nations during crisis period. | The pervasiveness of herding bias among fund managers is more prevalent in the events of economic crisis and bubbles. |
| 7 | (Ormos & Timotity, 2016) | Anchoring | It causes investors to rely on immediate and recent price changes. | Fund managers put emphasis on first piece of information while making decisions. |
| 8 | (Wang, 2012) | Window-dressing | It was found that 9.4% of almost 54,000 transactions in the sample are based on window dressing. The paper also suggests that past poor performance leads to window dressing because of increased employment risk and window dressed fund enjoys subsequent cash inflows which in turn suggests that investors are misled by it. | Fund managers undertake cosmetic adjustments to the portfolio just before the declaration date in order to make it more attractive to the investors. |
Source: Author\'s Compilation from various literature
Research Methodology
The study is descriptive in nature and to address the research objective, a secondary survey has been applied using \"Google Scholar\", \"Semantic Scholar\" and \"Bielefeld Academic Search Engine (BASE)\". To study about behavioural biases and their impact on Mutual Fund investment decisions, a literature review has been undertaken along with bibliometric analysis. \"Behavioural Biases\", \"Investment Decisions\", \"Mutual Funds Investment\" and \"Actively Managed Funds\" were considered to be the keywords for downloading and fetching relevant publications for this purpose. A total of 52 research works have been downloaded after removing the duplicates in \"Zotero\". Uncertainty of not choosing a relevant paper has been corrected by adopting three stage strategy which are database searching, abstract study, and citation checking. \"Research Rabbit\", which is an AI powered tool, has been used to check for similar papers to ensure that the downloaded papers are specific towards the objective of the study. A network analysis has been undertaken using VOS viewer on downloaded papers based on \"Title\", \"Keywords\" and \"Abstract\" data. The papers were downloaded and fetched last on $25^{th}$ May 2024, therefore any publication after the above-mentioned date has not been taken into consideration. Also, 9 Scopus indexed research papers out of a total of 52 selected research works were selected (Refer Table 2) based on their number of citation and recency to understand behavioural biases and its impact on mutual fund investment decision making.
Analysis and Findings
a. Bibliometric Analysis
An analysis has been carried out to identify the repeatedly used keywords or phrases in the title or abstract of the papers. The analysis of the keywords highlights that there exists a uniform pattern in the selection of keywords used, especially in the title and the abstract. Out of the total 1235 terms or phrases, 103 met the threshold limit of 4 minimum number of occurrences. For each of these 103 terms, a relevance score has been calculated. The most relevant terms have been selected based on this score. By default, in VOS viewer, 60 per cent of the terms been selected which comes to 62. Major 6 clusters were formed. These clusters have been depicted below by the network formed by applying \"Association Strength\" method of \"Normalization\". The clusters with their constituents have been tabulated as follows:
Table 2: Cluster and its Constituents
| Cluster Number | Total Items | Four Major Items in the Cluster | Links | Total Link Strength | Occurences |
|---|---|---|---|---|---|
| 1 | 15 | Analysis Behaviour Behavioural Bias Fund Manager | 41 38 36 46 | 281 315 467 393 | 14 20 20 34 |
| 2 | 12 | Equity Fund Manager Herd Behaviour Heuristic Investment Decision Making | 10 10 13 24 | 73 35 46 265 | 4 5 4 15 |
| 3 | 11 | Disposition Effect Equity Mutual Fund Overconfidence Professional Investor | 15 31 27 24 | 92 99 223 81 | 5 5 16 5 |
| 4 | 9 | Mutual Fund Investor Mistake Psychology Application | 27 18 38 19 | 134 258 225 82 | 8 13 12 5 |
| 5 | 8 | Evidence Herding Trading Stock Price | 41 23 29 21 | 257 268 217 115 | 13 14 13 5 |
| 6 | 5 | Market Member Pension Fund Trustee Option | 46 6 6 6 | 563 96 132 115 | 26 4 6 5 |
(Source: VOS viewer \"Network Visualization\")
b. Impact on Retail Investors
Investors who view their investment portfolio to serve various purposes exhibit different behaviour in their use of individual stock versus mutual funds. It has been observed that investors pay less attention to hidden management costs and are more attentive to obvious fees like front-end loads. Investors who stay in less affluent and less educated societies or have such neighbours tend to select high expense funds. Investors who are busy more likely to choose mutual funds than individual equities, and households with higher levels of personal and professional responsibilities and less free time are more likely to choose mutual funds.
c. Impact on Fund Managers or Institutional Investors
It has been identified that sophisticated investors i.e. those who are better informed, have higher income and better experience make good use of mutual funds, whereas behaviourally biased investors buy mutual fund for frequent trading and prefer high expense funds and active funds rather than indexed funds. A study of large sample of US actively managed equity mutual funds during the year 2003-2009 explained that superior past performance boosts managerial overconfidence. The researcher identified inverted U-shaped relationship between fund manager overconfidence and subsequent investment performance.
d. Behavioural Biases in Investment Decisions and Strategies for Mitigation
In recent times, research has focussed on how to reduce investor biases. Some of the studies proposed in these directions are using gamification approach (Dhawan, 2020), or usage of Artificial Intelligence (Chartier, 2021) or agent-based modelling. It was well established that in the future, an investor\'s behaviour would become such an integral part of finance that any financial modelling without it would make the model incorrect (Thaler, 1999). Further, the literatures revealed that investors\' decision gets biased by the form of presentation of financial reporting, pro-forma and GAAP disclosure. Interestingly, one study states that wealthy investors and large institutions do not show behavioural biases while investing as they have information advantage.
One study identified that both top and bottom performing managers showcase 40% increased risk in the second half of the year (relative to minimum risk level) (Hu, 2011). Incentive fee which are related to performance also affects manager behaviour. Research work suggests that effective fee rates are convex over lower ranges of performances. The researchers examined the manager\'s age, average composite SAT score from their undergraduate program, and whether or not they held an MBA to ascertain whether the characteristics of fund managers affect mutual fund performance. Compared to managers who attended less selective undergraduate institutions, mutual fund managers who attended more selective ones performed better. The researchers strongly suggest that stock-picking ability exists. Additionally, the researchers suggest that managers with the \"best\" attributes may outperform the market on average, and that younger managers are more sensitive to performance when it comes to managerial turnover. Studies have demonstrated that there is an enhanced exchange of information between fund managers and the CEO, CFO, and chairman of the company in pre-existing social networks.
Conclusion
Several behavioral biases that fund managers\' face are well shown by empirical research. There is window dressing and herding going on, and the manager exhibits home bias and overconfidence as well, which increases risk-taking and turnover. Managers take on more risk due to the disposition impact and performance-related incentive fees, but they also contribute to somewhat better risk-adjusted performance. The cross-section of fund returns can be effectively explained by both manager and fund characteristics. Risk-taking in reaction to prior performance is convex, even U-shaped; that is, it is lower among mid-ranked managers and higher among both good and poor performers. Nonetheless, it is evident that a solitary time series of returns is typically associated with several managers throughout time, each of whom may possess distinct behavioral biases and attributes.
References:
- Alexander Puetz, S. R. (2011). Overconfidence Among Professional Investors: Evidence from Mutual Fund Managers. Journal of Business Finance & Accounting, 684-712.
- Almansour, B. Y. (2023). Behavioral finance factors and investment decisions: A mediating role of risk perception. Cogent Economics & Finance.
- Candraningrat, I. R. (2018). Influence of Framing Information and Disposition Effect in Decision of Investment: Experimental Study on Investor Behavior at Indonesia Stock Exchange Representative on Denpasar, Bali. International Review of Management and, 59-68.
- Kartasova, G. R. (2014). Influence of \"Snake-Bite\" Effect on Investment Return Rate: Lithuanian Example. Mediterranean Journal of Social Sciences.
- Koch, A. (2017). Herd behavior and mutual fund performance. Management Science, 3849-3873.
- Massa, M. &. (2006). Hedging, familiarity and portfolio choice. The Review of Financial Studies, 633-685.
- Odean, T. (1999). Do Investors Trade Too Much? AMERICAN ECONOMIC REVIEW, 1279-1298.
- Ormos, & Timotity. (2016). Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading. Finance Research Letters, 60-66.
- Quddus, K. &. (2022). Are professional fund managers less likely to sell winners? Evaluating how attention allocation impacts behavioural biases. IIMB, Management Review, 29-43.
- Wang, X. (2012). Prevalence of Mutual Fund Window Dressing. SSRN Electronic Journal.