Relationship between Portfolio Diversification and Financial Performance of Large Enterprises in Kisumu County, Kenya

This study intended to explore the relationship between portfolio diversification and the financial performance of large businesses in Kisumu County, Kenya. The research questions of the study were; what is the relationship between stock and bond and the financial performance of large enterprises in Kisumu County, Kenya? The study was anchored on Modern Portfolio. A descriptive survey research design was adopted for the study. The statistical procedures of Yamane (1973) were subsequently employed to acquire a sample size of 225 out of a population of 1283 large enterprises; a random sampling procedure was adopted to facilitate the process. The research instrument was a document analysis guide. The study adopted both descriptive and inferential statistics for data analysis. Descriptive statistics involves the use of frequency, mean and standard deviation. The relationship between portfolio diversification and the financial performance of major enterprises in Kisumu County was explored using Pearson’s correlation and regression analysis. Data were presented using tables and figures. The researcher utilised regression analysis to

design was adopted for the study. The statistical procedures of Yamane (1973) were subsequently employed to acquire a sample size of 225 out of a population of 1283 large enterprises; a random sampling procedure was adopted to facilitate the process. The research instrument was a document analysis guide. The study adopted both descriptive and inferential statistics for data analysis. Descriptive statistics involves the use of frequency, mean and standard deviation. The relationship between portfolio diversification and the financial performance of major enterprises in Kisumu County was explored using Pearson's correlation and regression analysis. Data were presented using tables and figures. The researcher utilised regression analysis to specifically evaluate the null hypothesis. The results indicated that stock investment was positively related to financial performance. (β= 0.172, p-value=0.025< 0.05) of large enterprises in Kisumu County. Moreover, the findings corroborated the existence of a causal link between bond investment and financial performance (β= 3.2, p-value=0.001 < 0.05 of large enterprises in Kisumu County. Financial performance was found to benefit greatly from portfolio diversification (β= 4.875, p-value=0.023 < 0.05) of large enterprises. Furthermore, portfolio diversity accounts for 72.1% of the variance in financial performance across major businesses. The study recommends that business owners and managers diversify their investment portfolios across asset classes to mitigate risks and capitalise on opportunities in a variety of market conditions. This study recommends further investigation of the obstacles large enterprises face when diversifying their portfolios.

INTRODUCTION
Diversification refers to the practice of spreading investments across multiple asset classes to reduce the overall risk of a portfolio (Jain & Jain, 2021;Hestbaek & Joensen, 2020). The ultimate goal of diversification is to strike an optimal balance between risks and returns by investing in a variety of assets that are not highly correlated with each other (Estrada, 2020). Diversification can help investors achieve their long-term investment goals by reducing the impact of market volatility on their returns (Estrada, 2020). Portfolio diversification can involve investing in stocks, bonds, real estate, commodities, and other asset classes, as well as using other investment vehicles like mutual funds and exchange-traded funds (ETFs) (DiLallo, 2021). One of the key benefits of portfolio diversification is that it can help investors achieve higher returns with lower risk than investing in individual assets (Hestbaek & Joensen, 2020).
Portfolio diversification allows investors to absorb shocks during market downturns, leverage growth opportunities in different sectors, and provide stability during volatile times by balancing risks (Aristei & Lugo, 2020). The goal of portfolio diversification is to achieve higher returns with lower risk than investing in individual assets (Jain & Jain, 2021). Market Portfolio Theory (MPT) suggests that investors can reduce portfolio risk by holding a diversified portfolio of assets that are not highly correlated with each other (Amenc, 2020). Additionally, diversification can also help investors to achieve their long-term investment goals by reducing the impact of market volatility on their returns (Jain & Jain, 2021). Diversification, according to Cernas (2011), is a portfolio management strategy involving the aggregation of diverse assets to reduce the overall portfolio risk. Daud et al. (2009) argued that firms with diversified portfolios have comparatively better financial performance.
Large corporations in Kenya's agriculture, automotive, construction, energy, insurance, manufacturing, technology, and telecommunications industries are vital to the country's economy. The financial success of these companies in Kenya is on par with their counterparts in other African nations, although they contribute significantly to employment and input provision. The formal sector, which is dominated by major corporations yet accounts for only 16.4% of the 840,600 new employments created annually, is reported to account for only 2% of the national economy. Given that 40% of the country's population lives in poverty due to a lack of job possibilities, this is a worrying scenario. Large businesses in Kisumu County generate only 1.3% of total revenues and employ only 5125 people, which is insufficient to meet the urgent demand for employment development. Large companies, who benefit from economies of scale, are expected to invest in activities like market research, innovation, and productivity enhancement; thus, this finding comes as a surprise. Portfolio diversity, which includes stock, bond, and real estate investments, has been shown to improve financial outcomes for major organisations, but studies have shown conflicting effects. There is also a considerable gap in our understanding of the impact of portfolio diversity on the financial performance of large organisations in Kisumu County, Kenya, as most prior research has concentrated on large firms listed on stock exchanges. Addressing this gap, this study aimed to offer light on potential solutions for improving the financial outcomes of major firms in Kisumu County, Kenya by examining the connection between portfolio diversity and financial performance. Thus, the researchers in this study set out to determine if and how diversified portfolios affected the monetary outcomes of large companies in Kisumu County, Kenya. To achieve these objectives, the following hypotheses were tested:

THEORETICAL FRAMEWORK
This study was guided by the Modern Portfolio Theory.

Modern Portfolio Theory
Modern Portfolio Theory holds that risk-averse investors may build portfolios that maximise anticipated return at a given market risk. This theory emphasises that investments are inherently risky and that there cannot be a reward without a commensurate risk assumed. Given a choice between two investment options with similar returns, a rational investor who is assumed to be risk averse would prefer the one with the least risk associated with the return, which means an investor who prefers higher expected returns must assume higher risks and the opposite is also true. Thus, a completely negatively linked portfolio reduces portfolio risk.
However, depending on risk appetite, investors will assess each trade-off differently. Markowitz (1952) proposed (MPT) as the foundation of finance and investment choices. He thought that most investors desire to be cautious and take the minimum feasible risk to maximise the return-torisk ratio (Veeneya, 2006). Diversifying into many equities reduces portfolio volatility (Markowitz, 1959). Modern Portfolio Theory states that a single stock's risk and return are inadequate. MPT builds asset portfolios based on returns, risks, and covariance or correlations to maximise risk-return.
MPT states that each projected return is comprised of multiple future events and is hence dangerous, but diversification may optimise this risk-return connection (Fabozzi, Gupta & Markowitz, 2002). Efficient portfolios meet these two characteristics. At the same risk, no other portfolio will outperform (Markowitz, 1959). Inefficient portfolios may increase anticipated returns without increasing risk or decrease risk with the same expected return (Markowitz, 1991).

Relationship between Stock Investment and Financial Performance
Ali and Azman (2021)  Kioko and Ochieng (2020) examined how portfolio variety affects Nairobi Securities Exchange-listed investment firms that invested in bonds, stocks, mutual funds, and real estate. Portfolio, Black-Litterman, and CAPM theories formed the framework. Descriptive research. This census surveyed five NSE-listed investment firms. NSE and investing business websites provided secondary data. 2014-2019 data. Diagnostic tests and multiple linear regression models were inferential, mean, median, and standard deviation descriptive. Mutual funds have low bond returns. Equities and property yielded more returns than other investments by comparison. Research showed equity investments improved investment company financial performance. Only Nairobi Securities Exchangelisted investment businesses were investigated, excluding numerous significant enterprises.

Relationship between Bond Investment and Financial Performance
According to Li et al. (2020), financial stress affected Chinese corporate bond performance. The author did a study that used 2007-2018 Cox proportional hazard data. The research indicated financial crisis affects speculative-grade corporate bonds more than investment-grade bonds. Financial stress affects longer-term bonds, according to a study. The study's limited global applicability was bad.
Abugri and Adu (2021)  Hortaçsu, Syverson, and Werbach (2017) examined US corporate bond ratings and pricing. Bond prices were studied after rating adjustments. 1986-2014 event study data. Bond rating changes significantly affect corporate bond prices, depending on direction, according to studies. Bond offering size and issuer credit quality affect the market response, according to studies. Interest rate effects on bond prices were neglected.

Knowledge Gap
Stock investing and financial performance have not been conclusively linked in the research.  Hailu and Tassew (2018), and Hassan (2017) found no significant negative relationship between investment in bonds, real estate and ROA. However, Kioko and Ochieng' (2020) found a negative impact of bond investment on the financial performance of investment firms listed in the NSE but a significant positive impact on real estate and stock investment. Most of these studies were conducted outside Kenya, creating a contextual gap. Portfolio diversification and financial performance studies often ignore emerging markets and locals like Kisumu County. Thus, portfolio diversification's effects on financial performance in Kisumu County, Kenya, may be unknown.

METHODOLOGY
The study adopted a descriptive survey design because it involved collections of quantitative information that could be tabulated along a continuum in numerical form, such as financial performance (Sileyew, 2019).

Target Population
The target population for the study were employees in large enterprises licensed and registered by the County Government of Kisumu as of June 30 2020. In the study, large enterprises were defined as those whose annual turnover is more than five million, employ at least 10 staff, and are operating within an office space of over 300 square feet, which was adopted from the criteria for the classification of business according to size for trade license billing by the County Government of Kisumu. According to the records held by the business licensing and registration department of the County Government of Kisumu, there are 1283 large enterprises licensed and registered by the County Government as of June 30 , 2020. Population distribution was as shown in Table 1.

Description of the Sample and Sampling Procedures
The study adopted Yamane's (1973) statistical formulae to obtain a sample size of 225 out of a population of 1283, as shown in the following sub-section. However, simple random sampling at 17.537% for each type of business was adopted to distribute the sample size to each category proportionately as shown in Table 1.  (2020) The sample size of this study was based on Yamane's 1973 formulae, as shown below: Where; n is the sample size, N is the population size (1283), and e is the level of precision (0.05). The desired sample size for the students thus comprised 225 respondents. = 225÷1238 = 0.17537 = 17.37%

Description of Research Instruments
The study relied heavily on a document analysis guide as its primary method of data collection. Archives, annual reports, rules, and policy documents are all examples of the types of textual materials that can be analysed through a process called "document analysis" (Busetto et al., 2020). The document analysis guide targeted audited annual financial reports to extract quantitative data that were used in calculating ROA, which was an indicator of financial performance. Quantitative data was obtained from annual financial reports of the 225 large enterprises sampled and which had invested in bonds and shares in Kisumu County; for a period of five years to extract net income and total assets at the end of each financial year, the ratio between the two figures was then used to calculate return on assets (ROA) Data on ROA covering 5 years from 2016-2020. Independent variables were measured by the extent of their investment to total assets.

Inferential Statistics
Linear regression was used to represent the relationship between a set of explanatory variables and a response variable. Multiple linear regressions seek to conclude the nature of that relationship. Each value of the dependent variable y, financial performance of big firms in Kisumu County, Kenya, was correlated with some value of the independent variable x, portfolio diversification. The following regression model was chosen after using regression analysis, specifically multiple linear regression analysis: FP = β0 + β1SINV + β2BINV + ε Where; FP = Financial Performance, SINV = Stock Investment, BINV = Bond Investment, β0 = Intercept of the equation, β1, β2; Beta Coefficients for SINV and BINV respectively, ε; Random error term

Financial Performance of Large Enterprises
This study obtained the performance of large enterprises in terms of return on assets (ROA) using a document analysis guide. The researcher was able to obtain data from 198 firms due to the availability of data; this was a reliable response to derive the conclusion. The descriptive statistics for the ROA of large enterprises in Kisumu County, Kenya, are shown in Table 2.

Stock Investment and Financial Performance
This study sought to find out the relationship between stock investment and the financial performance of large enterprises in Kisumu County, Kenya. Descriptive statistics were obtained, as shown in Table 3. Thereafter, Pearson's correlation and simple linear regression were conducted, and the findings were presented in subsequent Tables.   County exhibited a degree of stability and were not subject to significant fluctuations. Since this study focuses on the relationship between stock investment and financial performance, the findings of this table alone do not provide direct insights into that relationship. Further analysis, such as correlation and regression, had to be undertaken to assess the nature and strength of the relationship between stock investment and financial performance. The outcomes are presented in Tables 4, 5,.6, and 7.  (2023) In Table 4, which shows the correlation between stock investment and financial performance, there is a strong positive correlation of 0.862 between the two variables. The correlation is statistically significant at the 0.012 level, indicating a highly significant relationship. Consequently, simple linear regression analysis was conducted as shown in the succeeding Tables 5, 6, and 7.  (2023) Table 5 provides the model summary for the relationship between stock investment and financial performance. The coefficient of determination (R-squared) is 0.744, indicating that 74.4% of the variance in financial performance can be explained by stock investment. The adjusted R-squared, which takes into account the number of predictors in the model, is 0.739. The standard error of the estimate is 0.817, reflecting the average distance between the actual financial performance values and the predicted values from the regression model.  Table 6 presents the analysis of variance (ANOVA) for the regression model. The regression model accounts for a significant amount of variance in financial performance, as evidenced by the large F-statistic of 444.482 and a p-value of 0.011, indicating a highly significant relationship. The F-statistic calculated is 444.482, which is much larger than the critical F-value of 10.12796448 at a 0.05 significance level. The pvalue of 0.011 also confirms the statistical significance. Therefore, we can conclude that the relationship between stock investment and financial performance is highly significant.  (2023) In Table 7, the regression coefficients are shown. The constant term is 13.115, indicating the expected value of financial performance when stock investment is zero. The coefficient for stock investment is 4.875, indicating that for every unit increase in stock investment, financial performance is expected to increase by 4.875 units. Both coefficients are statistically significant at the 0.05 significance level, suggesting a strong relationship between stock investment and financial performance. In Table 7, the regression coefficients are provided, allowing us to establish a complete model for the relationship between stock investment and financial performance. The formula for this model can be written as: Y (Financial Performance) = 13.115 + 4.875 * X1 (Stock Investment) In this model, the constant term (13.115) represents the expected value of financial performance when stock investment is zero. The coefficient for stock investment (4.875) indicates that, for every unit increase in stock investment, financial performance is expected to increase by 4.875 units. Both coefficients are statistically significant at the 0.001 level, further supporting the strong relationship between stock investment and financial performance.

Relationship between Stock Investment and Financial Performance
The first hypothesis was; H1: There is no significant relationship between stock investment and the financial performance of large enterprises in Kisumu County, Kenya. The correlation analysis shows a strong positive correlation between stock investment and financial performance, with a Pearson's correlation coefficient (r) of 0.862. This indicates a high degree of association between stock investment and financial performance. The correlation is statistically significant at a significance level of 0.012, suggesting that the relationship is not due to random chance.
The regression analysis further supports the significant relationship. The regression coefficient for stock investment is 4.875, indicating that for every unit increase in stock investment, there is an expected increase of 4.875 units in financial performance. The regression model explains 74.4% of the variance in financial performance, as indicated by the R-square value of 0.744.
In conclusion, there is a strong and significant positive relationship between stock investment and the financial performance of large enterprises in Kisumu County, Kenya. Increasing stock investment is likely to contribute to improved financial performance.

Bond Investment and Financial Performance
This study sought to find out the relationship between bond investment and the financial performance of large enterprises in Kisumu County, Kenya. Descriptive statistics were obtained, as shown in Table 8. Thereafter, Pearson's correlation and simple linear regression were conducted, and the findings were presented in the succeeding Tables.  (2023) The descriptive statistics for bond investment in large enterprises in Kisumu County, Kenya, revealed that the average bond investment ranges from 0.036 to 0.042, with standard deviations ranging from 0.007 to 0.010 across different financial years. These findings provide an overview of the bond investment levels in the region during the study period.  Table 9 indicates a significant positive relationship (r = 0.777, p < 0.05) between bond investment and the financial performance of large enterprises in Kisumu County. This suggests that as bond investment increases, there is a tendency for financial performance to improve. Therefore, the findings do not support the study's null hypothesis (H1) that there is no significant relationship between bond investment and financial performance.  (2023) Table 10 shows that bond investment explains approximately 60.4% (R-squared = 0.604) of the variation in financial performance among large enterprises in Kisumu County. The adjusted Rsquared of 0.593 accounts for the number of predictors in the model. The standard error of the estimate (0.957) indicates the average distance between the predicted and actual financial performance values. These findings suggest that bond investment is a significant predictor of financial performance in the studied enterprises.  Table 11 indicates that the regression model, which includes bond investment as a predictor, is statistically significant (F = 70.39, p < 0.05). The regression sum of squares (1.450) represents the amount of variation in financial performance explained by the bond investment. This further supports the finding that bond investment has a significant impact on the financial performance of large enterprises in Kisumu County.  The findings provide robust evidence to support the study's alternate hypothesis. They indicate a significant positive relationship between bond investment and financial performance in large enterprises in Kisumu County, Kenya. These results highlight the importance of bond investment as a potential driver of financial performance and provide valuable insights for policymakers and investors in the region.

Relationship between Bond Investment and Financial Performance
The second hypothesis was; H2: There is no significant relationship between bond investment and the financial performance of large enterprises in Kisumu County, Kenya. The correlation analysis reveals a moderate positive correlation between bond investment and financial performance, with a Pearson's correlation coefficient (r) of 0.777. This suggests a moderate association between bond investment and financial performance. The correlation is statistically significant at a significance level of 0.001*, indicating that the relationship is not due to chance.
The regression analysis confirms the significant relationship. The regression coefficient for bond investment is 3.200, indicating that for every unit increase in bond investment, there is an expected increase of 3.200 units in financial performance. The regression model explains 60.4% of the variance in financial performance, as indicated by the R-square value of 0.604.
In conclusion, there is a significant positive relationship between bond investment and the financial performance of large enterprises in Kisumu County, Kenya. Increasing bond investment is likely to contribute to improved financial performance.

Portfolio Diversification and Financial Performance
The purpose of this research was to examine whether or not diversified portfolios led to better financial results for large businesses in Kisumu County, Kenya. Descriptive statistics were obtained, as shown in Table 13. Thereafter, Pearson's correlation and simple linear regression were conducted, and the findings were presented in successive Tables.  (2023) Table 13 displays the descriptive statistics for portfolio diversification in large enterprises in Kisumu County, Kenya. It indicates that the mean portfolio diversification ranged from 0.072 to 0.085, with corresponding standard deviations ranging from 0.019 to 0.025 across different financial years. These statistics provide an overview of the average portfolio diversification levels and the variability around the mean during the study period.  Table 14 displays the correlation analysis findings for portfolio diversification and financial performance. The correlation analysis between portfolio diversification and financial performance reveals a strong positive relationship, with a correlation coefficient of 0.849. The p-value of less than 0.023 indicates that this correlation is statistically significant. These findings do not support the null hypothesis (H4) that there is no significant relationship between portfolio diversification and financial performance in large enterprises in Kisumu County, Kenya.    Table 16 displays the analysis of variance, which reveals that the regression model, which includes portfolio diversification as a predictor, is statistically significant (F = 285.5, p = 0.021). The regression sum of squares (3.780) indicates the amount of variation in financial performance explained by portfolio diversification. The degrees of freedom for the regression and residual are 1 and 3, respectively. These findings further support the conclusion that portfolio diversification significantly contributes to explaining the observed variation in financial performance.  (2023) In Table 17, the regression coefficients show that portfolio diversification has a significant positive effect on financial performance. The unstandardised coefficient for portfolio diversification (4.875) indicates that for every unit increase in portfolio diversification, financial performance is predicted to increase by 4.875 units. The t-value of 16.88 and the significance level of p < 0.05 confirm the statistical significance of this relationship. In conclusion, the findings of this study provide strong evidence to support the existence of a significant positive relationship between portfolio diversification and financial performance in large enterprises in Kisumu County, Kenya. Portfolio diversification explains a substantial proportion of the variation in financial performance, as demonstrated by the high R-square value. The analysis of variance and regression coefficients further support the conclusion that portfolio diversification has a significant impact on financial performance. These findings highlight the importance of considering portfolio diversification as a strategic factor in enhancing financial performance for businesses in Kisumu County.

Relationship between Portfolio Diversification and Financial Performance
H3: Large firms in Kisumu County, Kenya, benefit from portfolio diversification. Portfolio diversity and financial performance have a Pearson's correlation coefficient (r) of 0.849. Portfolio diversification strongly affects financial performance. At 0.001* significance, the correlation is not random.
Regression analysis confirms significance. Portfolio diversification increases financial performance by 4.875 units per unit. R-square = 0.721 indicates that the regression model explains 72.1% of financial performance variance.
Overall, portfolio diversity improves the financial performance of major firms in Kisumu County, Kenya. Portfolio diversification may boost financial success.
Based on the revised data, stock investment, bond investment, and portfolio diversification all positively affect the financial performance of large firms in Kisumu County, Kenya. Diversifying investments and devoting resources to different investment kinds may improve financial performance.

Relationship between Stock Investment and Financial Performance of Large Enterprises
This study found that stock investment improves the financial performance of large firms in Kisumu County, Kenya. The correlation analysis shows a strong correlation coefficient of 0.862. Table 5 shows that stock investment explains 74.4% of financial performance variation. The regression model's statistical significance is confirmed by the ANOVA's large F-statistic and p-value below 0.05. The regression coefficients reveal that stock investment increases financial performance by 4.875 units. These data suggest that major firms in Kisumu County, Kenya, benefit from stock investment. Stock investing improves financial performance. These findings show that regional firms' financial success depends on stock investment.

Relationship between Bond Investment and Financial Performance of Large Enterprises
The findings of this study contribute to the understanding of the relationship between bond investment and financial performance in large enterprises operating in Kisumu County, Kenya.
The results indicate a significant positive relationship between bond investment and financial performance, supported by a correlation coefficient of 0.777 and a p-value of less than 0.05. The descriptive statistics reveal that bond investment levels varied across different financial years, reflecting potential fluctuations in investment patterns.
The model summary further strengthens the relationship by demonstrating that approximately 60.4% of the variation in financial performance can be explained by bond investment. This highlights the importance of bond investment as a predictor of financial performance in large enterprises. The analysis of variance confirms the statistical significance of the regression model, indicating that the bond investment significantly contributes to explaining the observed variation in financial performance. The regression coefficients highlight the positive impact of bond investment, with every unit increase in bond investment resulting in a predicted increase of 3.200 units in financial performance.

CONCLUSIONS OF THE STUDY
This study examined how portfolio diversity affects the financial performance of major firms in Kisumu County, Kenya. According to the study, large firms in Kisumu County, Kenya, with more stock investment, do better financially. Strategic stock investments may improve financial performance, according to the findings. Stock investment is crucial to regional companies' financial performance. These results are similar to Natarajan et al. (2019), who sought to examine the relationship between stock returns and financial performance for firms listed on the Bombay Stock Exchange (BSE) in India. The study concluded that there is a direct relationship between stock returns and financial performance; hence rise in the financial performance of the listed firms increases the stock returns of firms listed at the BSE.
Bond investment affects the financial performance of major firms in Kisumu County, Kenya, according to the findings. Bond investments increase financial performance. This suggests that authorities and investors should use bond financing to boost regional enterprises' financial performance. These results contradict to ones by Kioko and Ochieng (2020) conducted to establish the Effect of Portfolio Diversification on the Financial Performance of Investment Firms Listed in the Nairobi Securities Exchange, where the results revealed a negative and insignificant relationship between mutual Funds' investments and bond investments and return on investments. However, the results of this study are similar to those in research conducted in Turkey by Hanin, Noriza and Mohamad (2017), where it was found that there was a significant relationship between financial profitability and investment in bonds among publicly listed insurance companies in Turkey. In South Africa, Nisra, Peng and Ashraf (2018) found that investment in bonds had a significantly low positive effect on the financial performance of commercial banks in South Africa.

Theory Implication
The investigator recommends analysis and further review of financial theories anchoring portfolio diversification and financial performance, especially with a bias on the contextual framework of large enterprises in Kenya, which may elicit different theoretical underpinnings than large enterprises in developed countries.

Practical Implications
Kisumu County firms might explore stock investment. Diversify your portfolio and stocks. Stock investing strategy should be customised for businesses by qualified financial experts. Actively managing stock investments may help companies prosper.
The study advises Kisumu County lawmakers to enable bond investment. Corporations may acquire bonds with tax incentives. Second, financial institutions and market authorities should raise corporate understanding and education about bond investing risks and advantages. This helps firms determine investment programs. Finally, future studies may disclose how bond investment influences financial performance and other variables that affect significant enterprises' financial success.
Company feasibility and risk assessments should precede real estate investments. This allows riskaverse decision-making. To increase profits, business owners and managers should invest in real estate. Finally, public-private partnerships should support and teach large Kisumu County enterprises to engage in real estate.
Finally, firm executives should diversify their asset classes. This reduces market risks and seizes opportunities. Market research and analysis may help businesses uncover investment opportunities that match their strategy. Portfolio monitoring and rebalancing enhance returns and diversity. Finally, financial advisors and investment consultants may assist organisations in developing effective portfolio diversification plans.

Policy Impact
The study recommends establishing and realigning policy frameworks for bigger Kenyan enterprises' stock market involvement. The researchers' paper advises adjusting government interest rates and maturity periods to attract significant Kenyan corporations to invest in Tbills and T-bonds. Kenya's big four affordable housing plan offers real estate investment incentives. The research also proposes Kisumu County government encourage real estate investment. Streamlining legislation, giving incentives, and developing infrastructure attract investment.

Recommendations for Further Research
This study suggests studying the portfolio diversification difficulties of major firms in Kisumu County, Kenya, to generalise results. Finally, the researcher suggests applying this conceptual framework to stock exchange-listed businesses, which diversify more than non-listed ones, to get new insights.