Pa ge 1 Pa ge 59 American Journal of Financial Technology and Innovation (AJFTI) A Study on Impact of Risk Tolerance on Mutual Fund Investors Shubham Sharma1*, Vinod Negi1 ISSN: 2837-4738 (Online) Volume 3 Issue 1, Year 2025 DOI: https://doi.org/10.54536/ajfti.v3i1.4531 https://journals.e-palli.com/home/index.php/ajfti Article Information ABSTRACT Received: February 05, 2025 Accepted: March 10, 2025 Published: April 24, 2025 This study investigates the impact of risk tolerance on mutual fund investment behavior in Himachal Pradesh, India using information gathered from 450 respondents in the districts of Kangra, Una, and Hamirpur, the study uses regression analysis to look into the connection between mutual fund investments and risk tolerance. The results indicate that risk tolerance and mutual fund investing have a statistically significant and substantially favourable connection. With standard deviations indicating some variation in respondents’ risk preferences, descriptive statistics show a higher-than-average risk tolerance and investment activity. The results of the regression analysis indicate that variations in risk tolerance account for 70% of the variance in mutual fund investment behavior. The findings show that respondents who have higher risk tolerance are more inclined to invest in mutual funds, underscoring the importance of risk tolerance in financial decision-making. In order to promote wise mutual fund investing practices, financial advisors and policymaker can benefit greatly from the study’s observations, which emphasize the significance of comprehending behavioral trends in investing. Keywords Investor Decision Making, Mutual Fund Investment, Risk Tolerance INTRODUCTION The market offers a wide variety of financial assets, from traditional real estate and bank deposits to the newest and most trendy capital market offerings like shares and mutual funds. According to various studies among the many investing options available, mutual funds have grown in popularity over the past several years (Meyer & Uhr, 2024). An individual investor is a person who buys stocks not for an organization but for their own account. Compared to large investors like insurance firms, pension funds etc., individual investors usually trade in considerably smaller numbers. Individual investors’ investment activity occurs in the background of institutional investors’ activities (Karthikeyan et al., 2012). Given the lesser magnitude of their ownership and the resulting voting power, there is every chance that their interest could be impacted. A crucial part is played by individual investors in maintaining the financial market’s smooth operation and making sure money is placed in the most capable hands. A growing field of finance called “behavioral finance” is very interested in individual investors’ ability to take risks. From this angle, behavioral finance emphasizes the personal traits, psychological traits or other, that influence standard financial and investing behaviors of investors (Bikas et al., 2012). A mutual fund is created when several people pool their extra money and give it to a reputable organization to administer, according to the Association of Mutual Funds in India. A mutual fund is essentially a tool for risk diversification, and each fund has a different risk profile. This study aims to determine investors’ risk tolerance when making mutual fund investments. Mutual funds invest in companies that are growth-oriented and capable of generating long-term financial gains. These funds pay out a lower yearly dividend to unit investors. Income funds offer high returns on investment (Chawla, 2014). According to the Association of Mutual Funds in India, there are numerous funds available for investors to invest in, including funds specifically focused on real estate investing with an emphasis on returns. Investments in which the entire corpus is devoted to a particular sector are referred to as sector-based funds. Likewise, funds referred to as index funds may focus on companies that are part of an index. Investment funds that focus on debt securities are known as debt funds. Balanced funds are also established to satisfy the combined benefit of capital appreciation and yearly growth since growth and income are the two components of any investment’s return. Mutual funds that only invest in units of other mutual funds are referred to as funds of funds, which is another kind of mutual fund. The purpose of mutual funds is to provide investors with tax exemptions. Traditional financial models have predominantly upheld the conceptual connection between risk tolerance and investment decisions, frequently presuming that investors act rationally. Expected Utility Theory (EUT) is a prominent framework for elucidating the connection between risk tolerance and risk-taking behaviour. Experts advise that individuals should concentrate their evaluations on outcomes that yield the highest profits. The anticipated utility theory posits that individuals, irrespective of the circumstances, act rationally and consistently choose certain risks over others. (Hemrajani et al., 2021). Research indicates a high correlation between financial behaviour and financial risk tolerance. Possessing a greater number of equities correlates with enhanced 1 Himachal Pradesh University Business School, Shimla, India * Corresponding author’s e-mail: shubhamsharma061997@gmail.com Pa ge 60 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 financial risk tolerance, according to Halissos and Bertaut (1995). Finke and Huston (2003) assert that individuals more inclined to embrace financial risks possess a greater proportion of equities compared to those who are risk- averse. This aligns with the findings of Hariharan et al. (2000), which indicated that those with greater risk tolerance prefer investing in stocks rather than risk-free assets. This study aims to examine the risk tolerance levels of mutual fund investors. The purpose of the present study is to know about risk tolerance level of mutual fund investors while investing in mutual funds. LITERATURE REVIEW The study by Jain et al. (2023) investigates the mediating effect of risk perception on the link between heuristic biases and decision-making among individual stock investors in India’s National Stock Exchange. The study employs Partial Least Square Structural Equation Modelling (PLS–SEM) on survey data from 432 investors, revealing that risk perception partially mediates the relationship between overconfidence, availability bias, gamblers’ fallacy, anchoring bias, and investment decision- making. The study offers insightful information about behavioral biases among capital market participants, with the acknowledged limitation of concentrating only on heuristic biases and failing to acknowledge the possible influence of other factors on individual equity investors. With implications for equity investing decisions, the study by Deka et al. (2023) investigates the calibration and assessment of the link between behavioral biases and risk perceptions among Indian retail investors. The study uses EFA, CFA, and AMOS-based SEM for factor extraction, validity evaluation, and path analysis using a structured questionnaire with 438 samples. The study demonstrates a noteworthy correlation between investor risk perception and ESG consciousness, validates the substantial influence of risk perception on equity investing decisions, and connects certain biases to perceived risk. Interestingly, biases and risk perception have a positive association that is moderated by higher ESG consciousness. Behera et al. (2022) The study highlights how crucial it is to assist investors who are experiencing emotional distress in order to keep money in the stock market. It suggests developing a process for producing knowledge in order to improve investors’ cognitive abilities and create the best possible risk-bearing capacity. Mahdzan (2021) This study examines how 260 working adults in Kuala Lumpur, Malaysia-mostly MBA students-make judgments about investing in mutual funds based on their financial literacy. An increasing degree of investing literacy is correlated with higher income and occupational levels. Nonetheless, the likelihood of investing in mutual funds is not greatly impacted by risk tolerance. Hemrajani et al. (2021) investigated the influence of psychological factors on individual investors’ financial risk tolerance and risk-taking behaviour. The researcher investigated the influence of psychological factors on individual investors’ financial risk tolerance and risk-taking behaviour. The study demonstrated a substantial correlation between emotional intelligence and impulsiveness with financial risk tolerance and financial risk-taking behaviour. The findings emphasized the importance of psychological factors in determining an individual’s financial risk tolerance and financial risk-taking behaviour. Financial risk tolerance is a complex mechanism that entails more than just psychological consideration. Upadhayay (2020) did a study on the influence of behavioural finance on individual investing decisions in Ahmedabad. The study was descriptive and conducted in Ahmedabad city, which consists of six zones: north, south, west, east, central, and new west. Primary data was gathered from 1,233 respondents. The results indicated that investors aged 18-28 constitute 45.1% of the overall sample, with post-graduates providing the most responses. Ogunlusi and Obademi (2019) examined the influence of behavioural finance on investment decision-making through a specific investment in Nigeria. The researcher distributed 200 questionnaires to respondents from four surveyed investment banks, of which 180 were returned. The enquiries focused on the demographic characteristics of respondents, heuristics, and prospect theory, utilising a descriptive research design for the study. The findings indicated a substantial influence of behavioural finance on investing decisions. Raut et al. (2018) assessed the conduct of individual investors in stock market trading. The research utilised structural equation modelling (SEM) to analyse data gathered from a nationwide survey involving 396 individual investors. This study examined the elements influencing individual investors’ investment decision-making behaviour to determine the efficiency of the Indian financial market and the rationality of investor decisions. The results indicated that investors were markedly affected by herding, information cascades, anchoring, representativeness, and overconfidence, although contagion exhibited little effects. Chaudhary (2025) studies how overconfidence, loss aversion and perception of risk affect investment decisions. The findings of the research reveal that risk perception significantly impacts investment decision with individual perceiving higher risk displaying a greater propensity to invest in high-risk assets. Deepa (2018) studied the investors’ behavioural approach toward mutual fund investment in the Tirupur district of Tamil Nadu. The researcher used an explorative research design. The researcher took a sample size of 400 and applied different types of sampling techniques like simple random, cluster and convenience sampling to source required information from the defined geographical regions of the study. The researcher found that 74.30 per cent of the mutual fund investors were men, 34.50 per cent of investors were graduates, and the study results indicated that 61 per cent of investors have expressed a very high degree of awareness of the performance of mutual funds. The factors which affect the investors for investing in mutual funds were features Pa ge 61 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 like minimum initial investment (68%), ownership pattern of the scheme (66.80%) and availability of professional financial advisor (64.8%). The relationship between logical decision-making and behavioral biases among Indian individual investors is investigated by (Kumar & Goyal ,2018). Applying statistical procedures like t-test, ANOVA, and Fisher’s LSD test, 386 valid responses to a structured questionnaire that was collected between May and October 2015 are used. According to the study, although most investors make logical decisions, behavioral biases might appear at different phases of the process. Moreover, disparities in income and gender influence the ability to make logical decisions; in India, men investors are more prone to herding prejudice and overconfidence. The results imply that people can make better investing decisions if they are conscious of their biases. Nithya (2017) investigated how individual investors in the Coimbatore district of Tamil Nadu perceive the behaviour surrounding mutual fund investment decisions. The primary conclusion of the study indicated that most investors exhibit a reduced risk appetite when engaging in the mutual fund market. The investment in mutual funds is primarily shaped by the active involvement of factors specific to the fund, as well as broader economic and various other investment considerations. Pinjisakikool (2017) investigated the influence of personality factors on households’ financial risk tolerance and financial conduct. The analysis included psychological and economic data, encompassing the Big Five personality factors that may affect financial conduct. The research included data from 4,026 individuals in the DNB (De Nederlandsche Bank) household survey and demonstrated that all five major personality factors were positively correlated with financial risk tolerance and affect risk tolerance. Mark (2017) performed an exploratory investigation of the investment behaviour of investors in Hong Kong and Mainland China. Key features such as demographic, psychological, and societal factors were examined. Customer data from 2012 to 2014 was collected. The researcher employed regression analysis as a statistical instrument. This research collected 142,496 samples from financial service providers registered on the Hong Kong Stock Exchange, comprising 87,057 samples from Mainland Chinese investors and 55,439 from Hong Kong investors. The researcher determined that the three most critical factors—age, income level, and investing experience—affect investment behaviour; income level exerts a positive influence, whereas investment experience negatively impacts the quantity of fund shares held by investors. Deb and Singh (2016) investigate the impact of risk perception on the investment behaviour of bank workers in Tripura regarding mutual funds. The general risk perception among bank personnel has been classified as moderate. The research demonstrated an inverse correlation between risk perception and the amount invested in mutual funds. Rahmawati et al. (2015) examined the factors influencing the risk tolerance of individual investors. The author reached the conclusion that men exhibit lower levels of risk aversion compared to women. Investors with a solid education tend to embrace risk more readily, while those with fewer financial resources often exhibit lower risk tolerance. Finding important determinants of investor preferences for financial goods is the goal of the research by Kalra et al. (2012) The classification and regression tree (CART) methodology was utilized by them with a sample of 377 individual investors. It was discovered that psychographic factors were important indicators for high-risk investment goods, although socioeconomic and demographic factors were important indicators for low- risk investments. The report recommends that financial service companies take these factors into account in order to customize their marketing tactics and build customer confidence. The comprehension of Indian investor behavior is improved by this empirical contribution. Walia and Kiran (2009) conducted an analysis of investors’ risk perception regarding mutual fund services. The study revealed that investors’ understanding and their positive outlook on market volatility affect their choice to pursue risky investments. Objective To study the impact of risk tolerance on mutual fund investors while investing in mutual funds. MATERIALS AND METHODS This study used descriptive research design. The target population for this study are those people who invest in mutual funds. This study is based in Himachal Pradesh, a hilly state in India. For the purpose of this study top three district of Himachal Pradesh according to their literacy level have been taken. These top 3 districts are Hamirpur, Una and Kangra (Indian Census, 2011). In the present study non probability sampling (Purposive and Convenience sampling) is used. The sample size for the study is 450 which further divided into the 3 district according to their population proportion. So lastly 273 responses are from Kangra district, 94 from Una and 83 respondents are from Hamirpur district. Regression analysis used in this study to analyze the data related to risk tolerance level of mutual fund investors. There are number of reasons for choosing Himachal Pradesh as research area The first reason for taking Himachal Pradesh for study is that Himachal Pradesh stood first among all the states in SDG 8 i.e., Decent Work and Economic Growth. SDG 8 promotes sustained economic growth. But despite being in first position in SDG 8, Himachal Pradesh has to work more in the sector of social security. The percentage of regular wage/ salaried employees in the non-agriculture sector without any social security benefit is 39.1 per cent (NITI Aayog Reports SDG India Index 2020-2021) and the target for 2030 is to bring it down to 0 per cent, so mutual fund investment can help to provide social security to employees because mutual contains various retirement funds with minimum risk as compare to other market instruments. Pa ge 62 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 Progression rate of investors in Himachal Pradesh is good as there was 7,48,583 investors in Himachal Pradesh in 2023 which is increased to 10,93,311(As per BSE data) till August 2024 which is 46.05% increase in the rare of investors and Himachal Pradesh has 16,300 crore Asset Under Management (AUM) in Mutual Fund till August 2024 (As per data of Association of Mutual Funds in India). For this research Individuals are selected from the chosen districts belonging to the age group of 18- 49 (as per RBI National Strategy for Financial Education 2020-2025 there is 57% of the population who cross the minimum threshold score which includes components like Financial Knowledge, Financial Behaviour and Financial attitude of financial literacy), who are investors of mutual fund schemes will be selected as sampling unit for the study. Research Instruments 5 items are used to measure risk tolerance which were adapted from Goyal et al., (2023). The reliability of these items came 0.791. Whereas for mutual fund investment 4 items were used which were adapted from Ogunlusi and Obademi (2019) and the reliability for these items were 0.833. For Risk Tolerance Following Items are Used on 7 Points Likert Scale 1. Investing is too difficult to understand for me 2. I am more comfortable putting my money in a bank A/c than in the mutual fund 3. When, I think of the Word “risk” the term loss comes to mind immediately 4. Making money in stock and mutual fund based on luck 5. In term of Investing, safety is more important than return. And for Mutual Fund Investment Following Items were Used on 7 Points Likert Scale 1. My investment in mutual funds has demonstrated better results than expected. 2. My investment in mutual funds has shown consistent cash flow growth. 3. My investment in mutual funds carries lower risk compared to the overall market. 4. My investment in mutual funds offers a high degree of safety Hypothesis H0 There is no impact of Risk tolerance of investor on Mutual Fund Investment. Ha There is an impact of Risk tolerance of investor on Mutual Fund Investment Data Analysis and Results For this study the data is collected from three district of Himachal Pradesh i.e. Kangra, Una and Hamirpur and data 450 sample were gathered from these districts to know the risk tolerance level of mutual fund investors in Himachal Pradesh, a hilly state in India. For analysing the impact of risk tolerance on mutual fund investor, regression analysis is conducted and the result of the same are given below: Regression Analysis Table 1: R Square Analysis Model Summaryb M od el R R S qu ar e A dj us te d R S qu ar e St d. E rr or of th e E st im at e R S qu ar e C ha ng e F C ha ng e D f1 D f2 Si g. F C ha ng e D ur bi n W at so n 1. 0.838a .702 .701 .2178 .702 1053.862 1 448 <.001 1.937 a. Predictors: (Constant), Risk Tolerance b. Dependent Variable: Mutual Fund Investment Source: Primary data prepared by author The research reveals a fairly favourable, statistically significant connection (r = 0.838, p < 0.001) between investing in mutual funds and risk tolerance. According to descriptive statistics, respondents’ levels of both variables are marginally higher than average. These findings highlight how risk tolerance affects investing behavior, which makes it a crucial component of research on financial decision-making. According to the data, 70.2% of the diversity in investment patterns may be explained by risk tolerance, which has a considerable impact on mutual fund investing behavior (R2 = 0.702). This suggests that variations in respondents’ risk tolerance account for around 70% of the variation in mutual fund investment behavior. Adjusted R2 is 0.701, This value modifies the R2 statistic to account for the number of predictors and the sample size, so offering a more precise assessment of model fit in the context of multiple predictors. The little disparity between R2 and Adjusted R2 indicates that the model possesses robust and steady explanatory power. Standard Error of the Estimate: Standard Error is 0.2178, This is the mean deviation of the observed data from the regression line. A reduced standard error signifies that the model’s predictions closely align with the actual data points. Change in R² is 0.702, Signifies that the total variance elucidated by the model is attributable only to the independent variable (Risk Tolerance), given that there is a singular predictor in this model. Pa ge 63 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 F Change and Significance (F-test) F = 1053.862, p < 0.001: The F-test evaluates the overall statistical significance of the regression model. The elevated 𝐹-value and its significant p-value demonstrate that the model is well-suited and that Risk Tolerance is a major predictor of Mutual Fund Investment. Durbin-Watson Statistic Durbin-Watson is 1.937 This evaluates autocorrelation in the residuals. A number around 2 signifies the absence of substantial autocorrelation, implying that the residuals are independent, a fundamental assumption of regression analysis. Table 2: Correlation Model Summaryb Mutual Fund Investment Risk Tolerance Pearson Correlation Mutual Fund Investment 1.000 0.838 Risk tolerance 0.838 1.000 Sig. (1-tailed) Mutual Fund Investment - <.001 Risk tolerance .000 - N Mutual fund Investment 450 450 Risk Tolerance 450 450 Source: Primary data prepared by author According to the analysis, there is a 0.838 Pearson association between risk tolerance and mutual fund investment. This shows a somewhat positive connection, indicating that respondents’ investment behavior in mutual funds tends to rise proportionately to their increased risk tolerance. At a 99% confidence level, the correlation’s p-value of less than 0.001 indicates that it is statistically significant (p < 0.01). The observed association is unlikely to have happened by accident, as confirmed by this high level of significance. The statistically substantial and positive association indicates that respondents’ risk tolerance has a considerable impact on their mutual fund investing behavior. An important behavioral tendency among mutual fund investors is the apparent correlation between increased investment activity and higher risk tolerance. These results highlight how the sample population’s risk appetite influences their investment choices. Table 3: ANOVAa Model Sum of Squares df Mean Square F Sig. 1. Regression 50.035 1 50.035 1053.862 <.001b Residual 21.270 448 .047 Total 71.304 449 a. Dependent Variable: Mutual Fund Investment b. Predictors: (Constant), Risk Tolerance Source: Primary data prepared by author Sum of Squares (SS) Regression SS (50.035) This shows how much of the change in the dependent variable (Mutual Fund Investment) can be explained by the change in the independent variable (Risk Tolerance). When the number is high, it means that the model explains a lot of the variation. Residual SS (21.270) This is the change in the dependent variable that the model can’t explain. A better fit of the model is shown by a lower residual SS. Total SS (71.304) This shows how much the dependent variable has changed. The Regression SS and the Residual SS are added together to get this number. What It Means About 50.035 of the total variations (71.304), or 70.2%, can be explained by the model. The other 21.270, or 29.8%, cannot be explained. Types of Freedom (df) This number, df (1), shows how many variables are in the model (Risk Tolerance), residual df (448), which is the number of observations minus the number of variables and the constant, is equal to 448. This is the number of observations minus one, which is 450 - 1 = 449 (450 - 1 = 449). Mean Square (MS) Regression MS (50.035) This is found by dividing Regression SS by Regression df. It shows how much of the difference the model can explain for each predictor. Pa ge 64 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 Residual MS (0.047) This is found by dividing Residual SS by Residual df. It shows the average difference that can’t be explained. What It Means The big difference between the Regression MS (50.035) and the Residual MS (0.047) shows that the model explains a lot more variation than it leaves out. F Statistic That number, 1053.862, is the ratio of the Regression MS to the Residual MS. The other number, 50.035/0.047, is the same thing. If the F-value is high, it means that the model is a lot better at predicting the dependent variable than using the mean as a forecast. How Important (p-value) p<0.001 This means that the regression model is statistically significant as a whole. The independent variable (Risk Tolerance) helps to predict the dependent variable (Mutual Fund Investment) by a large amount. Table 4: Coefficientsa Model Unstandardized B Coefficients Std. Error Standardized Coefficient Beta t Sig. Collinearity Statistic 1. (Constant) 0.860 .091 9.435 <.001 Tolerance VIF Risk tolerance 0.767 .024 .838 32.463 <.001 1.00 1.00 a. Dependent Variable: Mutual Fund Investment Source: Primary data prepared by author It is projected that the dependent variable (Mutual Fund Investment) will have a value of 0.860 when the independent variable (Risk Tolerance) is 0. The starting point for investing in mutual funds is 0.860 units (on the scale used in the model), even if the person has no risk tolerance. t = 9.435, Sig. < 0.001: The constant is statistically significant, which means it makes the model more useful. Risk Tolerance (independent variable) Unstandardised B = 0.767: This means that Mutual Fund Investment goes up by 0.767 units for every unit increase in Risk Tolerance, which is the same scale as the dependent variable. In Other Words, Risk Tolerance Has a Big and Positive Effect on Mutual Fund Investments Beta = 0.838: This is the standardised coefficient, which lets you compare variables that are recorded on different scales. A lot of the model’s variation can be explained by the fact that Risk Tolerance has a big positive effect on Mutual Fund Investment. t = 32.463, Sig. < 0.001: Risk Tolerance is a very good indicator of Mutual Fund Investment, as shown by the very high t-value and significant p-value. Tolerance and VIF Statistics for Collinearity Tolerance = 1.00 and VIF = 1.00 are statistics that show multicollinearity, or how much two different factors are linked to each other. There are no problems with multicollinearity if both the Tolerance value and the VIF (Variance Inflation Factor) value are close to 1. There is no need to worry about multicollinearity in this model because there is only one independent variable. Overall Meaning and Risk There is a strong and statistically significant link between tolerance and investing in mutual funds. In raw units, the unstandardised coefficient (B=0.767) shows how the link works, and the standardised coefficient (β=0.838) shows how strong the effect is. Since There are no Problems with Multicollinearity, the Model is Strong Since the difference between R2 and Adjusted R2 is minimal, the model’s explanatory power is strong and stable. The analysis confirms that Risk Tolerance significantly influence Mutual Fund Investment. So, we reject the null hypothesis i.e. There is no impact of Risk tolerance of investor on Mutual Fund Investment and Accept Alternative Hypothesis There is an impact of Risk tolerance of investor on Mutual Fund Investment. Findings The regression analysis indicates a robust and statistically significant positive association between risk tolerance and mutual fund investment behaviour (r = 0.838, p < 0.001). This indicates that when an individual’s risk tolerance escalates, their propensity to invest in mutual funds correspondingly increases, demonstrating a direct impact of risk tolerance on investing choices. The R² score of 0.702 signifies that roughly 70.2% of the variance in mutual fund investment behaviour is attributable to risk tolerance. This underscores that risk tolerance significantly influences mutual fund investment behaviour among the study group from Himachal Pradesh. The Adjusted R² value of 0.701 validates the model’s robustness, considering sample size and predictors, indicating a steady and dependable model fit. The F-statistic of 1053.862 (p < 0.001) indicates that the total regression model is statistically significant, affirming that risk tolerance is a primary predictor of mutual fund investment behaviour. The t-value for Risk Tolerance (32.463, p < 0.001) underscores that risk tolerance is a highly significant determinant affecting mutual fund investments, exerting a substantial positive influence. Pa ge 65 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 investors in investment decision-making. International Journal of Financial Studies, 10(1), 21. https://doi. org/10.3390/ijfs10010021 Chawla, D. (2014). An empirical analysis of factors influencing investment in mutual funds in India. Global Business Review, 15(3), 493–503. https://doi. org/10.1177/0972150914535136 Chaudhary, M. K. (2025). Impact of Risk Perception, Overconfidence Bias and Loss Aversion on Investment Decision-Making. American Journal of Financial Technology and Innovation, 3(1), 14–22. https://doi.org/10.54536/ajfti.v3i1.4061 Finke, M. S., & Huston, S. J. (2003). Undefined. Journal of Family and Economic Issues, 24(3), 291–303. https://doi. org/10.1023/a:1025499322428 Goyal, K., Purohit, S., & Shukla, S. (2023). The direct and indirect effects of financial socialization and psychological characteristics on young professionals’ personal financial management behavior. International Journal of Bank Marketing, 41(7), 1550–1584. https:// doi.org/10.1108/ijbm-09-2022-0419 Haliassos, M., & Bertaut, C. C. (1995). Why do so few hold stocks? The Economic Journal, 105(432), 1110. https://doi.org/10.2307/2235407 Hemrajani, A., Kumar, R., & Sharma, P. (2021). Retail investors’ financial risk tolerance and risk-taking behavior: The role of psychological factors. FIIB Business Review, 231971452110582. https://doi. org/10.1177/23197145211058274 Reserve Bank of India. (2020). National Strategy for Financial Education 2020-2025 [PDF file]. https:// shorturl.at/aZDzr Reserve Bank of India. (2020). Annual Report 2019-2020 [PDF file]. https://shorturl.at/sEC2A Moscati, I. (2018). The expected utility theory and measurement theory of von Neumann and Morgenstern, 1944–1947. In Measuring utility (pp. 147–162). https:// doi.org/10.1093/oso/9780199372768.003.0010 Nithya, D. (2017). Mutual fund investment decision by individual investors: Behavioural perspectives [Doctoral dissertation]. Sodhganga. Shahnaz, N., Jamil, S., & Abdul Rahman, R. (2021). Investment literacy, risk tolerance, and mutual fund investments: An exploratory study of working adults in Kuala Lumpur. International Journal of Business and Society, 21(1), 111–133. https://doi.org/10.33736/ ijbs.3230.2020 Ogunlusi, O. E., & Obademi, O. (2019). The impact of behavioural finance on investment decision-making: A study of selected investment banks in Nigeria. Global Business Review, 22(6), 1345–1361. https://doi. org/10.1177/0972150919851388 Pinjisakikool, T. (2017). The influence of personality traits on households’ financial risk tolerance and financial behaviour. Journal of Interdisciplinary Economics, 30(1), 32-54. https://doi.org/10.1177/0260107917731034 Rahmawati, R., Sari, N. L., & Hartono, D. (2015). Determinants of the risk tolerance of individual The Standard Error of the Estimate (0.2178) indicates that the predicted mutual fund investment values closely correspond with the observed data, signifying a strong fit of the regression model to the actual data. The Tolerance (1.00) and VIF (1.00) values signify the absence of multicollinearity concerns in the model. The presence of a single independent variable indicates that the model is devoid of potential collinearity issues. The ANOVA table indicates that the regression model significantly accounts for the variance in mutual fund investing behaviour (p < 0.001), hence affirming the critical influence of risk tolerance on investment decisions. Consequences for Financial Decision-Making The study underscores the significance of risk tolerance in shaping investing decisions, rendering it an essential consideration for financial advisors and mutual fund managers in formulating investment strategies. Comprehending the correlation between risk tolerance and investment behaviour might facilitate the customisation of financial products and advisory services to more effectively correspond with investor preferences. The study demonstrates that risk tolerance substantially affects mutual fund investment behaviour. This understanding is significant for legislators, financial planners, and mutual fund providers seeking to stimulate investment activity by addressing investor risk preferences. CONCLUSION This study’s analysis definitively shows that risk tolerance substantially influences mutual fund investment behaviour among the people of Himachal Pradesh. The regression model indicates that risk tolerance explains a substantial proportion of the variance in investment patterns (70.2%), with a positive and statistically significant connection between the two variables. The results indicate that investors with more risk tolerance are more inclined to invest in mutual funds, whilst those with diminished risk tolerance generally refrain from such investments. This highlights the significance of evaluating an individual’s risk profile when examining investment behaviour in financial decision-making. The substantial statistical significance (p < 0.001) of the association indicates that risk tolerance must be regarded as an essential element for comprehending and forecasting mutual fund investments. The study refutes the null hypothesis asserting no effect of risk tolerance on mutual fund investment behaviour and endorses the alternative hypothesis that risk tolerance substantially affects mutual fund investment decisions. These findings can assist financial advisors, policymakers, and fund managers in customising investment strategies and products according to investors’ risk preferences, hence improving investment participation and financial planning. REFERENCES Behera, S., Yadav, M., & Kumar, A. (2022). Examining risk absorption capacity as a mediating factor in the relationship between cognition and neuroplasticity in Pa ge 66 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 59-66, 2025 investors. International Journal of Economics and Financial Issues, 5, 373–378. NITI Aayog. (2020). SDG India Index & Dashboard 2020- 21. https://sdgindiaindex.niti.gov.in/#/ranking SE Ltd-registered investors. (n.d.). BSE (formerly Bombay Stock Exchange) | Live stock market updates for S&P BSE SENSEX, stock price, company news & results. BSE. https://www.bseindia.com/markets/ keystatics/KeyStat_ClientStat.aspx?expandable%20 =4 Walia, N., & Kiran, R. (2012). Understanding the risk anatomy of experienced mutual fund investors. Journal of Behavioral Finance, 13(2), 119–125. https:// doi.org/10.1080/15427560.2012.673517 World Investor Week. (2021, November 22–28). Mutual Funds India | Investment Plans | Tax Saving | Mutual Funds NAV. AMFI. https://www.amfiindia. com/geographical-spreads