Academy of Accounting and Financial Studies Journal (Print ISSN: 1096-3685; Online ISSN: 1528-2635)

Research Article: 2021 Vol: 25 Issue: 5

Using A Cash Flow Model to Predict Future Cash Flow from Historical Cash Flow: Malaysian Perspective

Mazurina Mohd Ali, Universiti Teknologi MARA Selangor

Kamalia Mohamed Ali, Universiti Teknologi MARA Selangor


This research aims to look into the role of historical cash flow in forecasting potential cash flows of Malaysian publicly traded companies. Construction, energy, and property are the industries chosen for this study. The data for this study came from the financial statements of 159 companies from those industries that were published on the Bursa Malaysia website from 2015 to 2019. The statement of profit or loss and cash flow statement are used to collect historical cash flow data. The cash flow model was used, and the three-year lags improve its predictive power in accounting results. This study found that the past one-year cash flows are a significant predictor and optimistic effect on forecasting potential cash flows. Taking all into account, this study will assist company executives in managing cash flows for ongoing operations, monitoring investment strategy, and tracking financing activities to ensure the organization's sustainability and growth. On the other hand, other business stakeholders may use historical cash flows to forecast potential cash flow investment decisions. This study is expected to have implications and benefits for all stakeholders concerned, including academics, professionals, and regulatory agencies.


Historical Cash Flow, Future Cash Flow, Prediction, Malaysia.


The Cash flow analysis is a vital activity since different economic choices are involved. The International Financial Reporting Standard (IFRS) transparency, according to Gordon et al. (2017), offers a system in which financial statements provide adaptability for companies in their classification choices within cash flow statements. The International Accounting Standard Board (IASB) and the Financial Accounting Standard Board (FASB) are interested in flexibility in the designation of cash flows and their ramifications. Financial information can help users of financial statements better forecast potential cash flows.

According to the IASB Conceptual Framework, the primary objective of financial reporting is to provide financial information that is useful to current and prospective investors, lenders, and other decision-makers. This is to provide capital to the company and, in particular, to assist them in determining the reporting entity's potential net cash inflow prospects. For example, investors need details on potential cash flows since the present value of their future cash flows determines the investment's worth. As a result, investors need this level of expertise for investment purposes.

Investors can forecast stock prices when forecasting future cash flows because a company's ability to include cash inflows is reflected in its share valuation. Cash flow forecasting is often used by creditors, suppliers, and workers to assess a company's solvency and liquidity (Rashid, 2018). Furthermore, the cash flow forecast tells the progress of the appraisal determination as well as the manager's and investor's decisions (Nguyen & Nguyen, 2020). The prediction of potential cash flows is a critical symbol of management's use of this form of information to plan future projects. Fully understanding of cash flows are adequate and managing them correctly will aid companies in avoiding crises (Mulenga & Bhatia, 2017). Using cash flow data for the statement of profit or loss and statement of financial position, according to the FASB, would enable users to measure and forecast cash flows.

The financial success of a firm's performance in the construction industry is determined by a number of factors, including the company's cash inflows and outflows. Cash inflows are the amount of cash collected and cumulative investment by a company for a given time span. Insufficient cash flow means no payments to vendors, staff, or crews, as well as no material purchases. Thus, the company can be constrained in its ability to complete on-site assignments, have to make job cuts, or work at a slower pace to balance the amount of cash available. As a consequence, when assessing a company's financial status, the need for cash flow stability and liquidity is important. In other words, cash flow values are critical for analyzing the duration of funds in operations management to determine the investment's duration, as well as for examining cash in funding activities. Accordingly, financial performance can be more precisely calculated, and decision-making can be more efficient (Aris, Anuar, Trofimov, & Sokat, 2019).

It would be helpful to provide a robust energy industry structure that prioritizes decision-making at every level of the global energy system; however, this has not yet been implemented. Even though fossil fuels have historically had significantly lower marginal supply costs, substitute reserves have been required over the last decade and have become more complex and expensive than ever before. In order to meet the increased capital requirements for the replacement of reserves, oil and gas companies keep striving for sufficient-free cash flows from their current income, thus trying to prevent a decline in current assets over the life cycle in order to avoid any possible downturn in future cash flows. Without investment in experimentation to discover alternative reserves to replace oil and gas production, the oil industry would disappear.

However, when oil and gas prices collapse due to poor demand, overproduction, or both, companies are forced to postpone exploration in order to avoid negative cash flows or to prevent already negative cash accounts from being even more negative. A structured investment strategy must verify that capital for the discovery and production of new areas can be derived from operational activities or raised from the investors (Agostinho & Weijermars, 2017).

According to Bergmann et al. (2020), growth threats in the real estate sector are understudied, posing a challenge to company survival. The authors highlight the impact of material selection in terms of external and project risk for the development of the real estate. In sum, resource prices and changing regulations have shown the highest risks, while the cash flow model showed that conventional materials perform slightly better although the uncertainties in the calculations are similar. The findings further contributed to risk management and decision-making for real estate projects by giving visibility into the discussion and analysis of the financial efficiency of sustainable construction materials and design that may be essential to disruptive innovations. In general, the study presents a model that integrates the environmental and long-term cash flow assessment of real estate projects, thereby increasing management flexibility.

The ability of an organization to generate future cash flows is critical when making decisions for various stakeholders. Indeed, predictions of potential cash flows play a vital role in financial prediction and financial analysis (Kliestik et al., 2020).

Construction is a high-risk industry, but it is also one of the most important in any economy. While liquidity is the most valuable resource for construction firms, cash flow prediction seeks to assess the distribution of project expenditure and revenue. Poor cash flow adversely affects company profitability and simultaneously the ability to meet project deadlines. The construction industry operates in a highly competitive environment and, without proper governance, contractors cannot survive. Therefore, contractors are encouraged in tender bids to introduce low-profit margins to compete within the industry and this, in turn, impacts the liquidity of the company. Previous research has also found that a lack of liquidity is a major issue that results in the failure of construction projects and the bankruptcy of construction companies. Various studies on cash flow management have shown that construction managers are more concerned with contract sums relating to site costs and fixed costs than with benefit. As such, this might describe why only a third of medium to large businesses make profits even though they experience low turnovers and capital (Adjei et al., 2018).

Malaysia has reported a significant decrease in project execution and deliverable performance due to poor time management and cost efficiency issues (Omopariola et al., 2019). In Malaysia, several researchers have argued that cost variance, rather than time variance, is the source of many problems (e.g. Sankar & Kumar, 2018). However, the results of the current study have shown a significant positive relationship between cash flows and firm performance (Adjei et al., 2018). Contractors with proxies for financial difficulties, inadequate contractor experience, lack of contractor experience, shortage of site workers, and incorrect preparation and contractor scheduling are the reasons projects could not be completed within the stipulated budget and timeline. The problem of cost overruns poses a significant threat to the development of the construction industry in Malaysia (Aris et al., 2019).

As previously stated, finding new energy resources is essential if we are to buy time to develop efficient and sustainable alternatives to fossil fuels. While fossil fuels historically had comparatively small production cost, replacing the necessary reserves over the last century is now more complicated and costly than ever. As a result, in order to meet the increasing capital needs for the replacement of reserves, energy firms continue to aim for adequate cash flow from their current profits to prevent an existence decrease in cash flows and prevent potential reduction in future cash flows. The energy market would vanish if no investment were made in a platform for new reserves to replace oil and gas exploration (Agostinho & Weijermars, 2017).

Nonetheless, when oil and gas prices fall due to slow development or oversupply, or both, businesses either be forced to halt development in order to prevent negative cash flows or to keep cash accounts that have been negatively impacted from spiralling deeper into debt. A sustainable investment portfolio must therefore ensure that the resources for exploration and the development of new sectors can either be obtained from investments or produced by shareholders (Yan Lianyong & Shanna, 2020). Since there is limited research on the prediction of future cash flows in the construction, energy, and property industries in Malaysia, the current study will provide the most recent data, especially on construction, energy, and property industries.

In Malaysia, only a small amount of research has been done to forecast potential cash flows in the construction, energy, and property industries. As a result, the current study would focus on the following research question: Do historical cash flows have a significant predictive power in forecasting potential cash flows in Malaysian publicly traded firms. This study will include the most up-to-date information, especially in the construction, energy, and property development sectors, which are considered responsive and at high risk of cash flow.

The rest of this paper is presented as follows. Section 2 contains the literature review. Section 3 defines the research methodology. Section 4 elaborates on the study's findings, while Section 5 presents the study's conclusions.

Literature Review

The primary purpose of financial statements is to forecast future cash flows. The relevant information is provided to users within and outside the business by forecasting cash flows. Any economic decision denotes a comprehensive choice among various options for achieving the target. As a result, each choice necessitates the presumption that the future will be better served.

Decision-makers, according to Umoren & Umoffong (2018), must generally face the consequences of their decisions. Anticipating future cash flows is a crucial part of the decision-making process because it can decide the options and assessment process results. Since cash must be available when needed, cash flow is known as the "cornerstone" of a company's business management. As a result, a company's cash management capabilities are vital to its long-term survival and growth. Consequently, by predicting future cash flows, managers can assist in the foreseeing of possible financial issues. Forecasting cash flow also helps the company to have a clearer view of its cash situation, enabling it to make appropriate improvements in debt reduction, acquisitions, and cost repayment (Noury et al., 2020).

According to Sarraf (2019), an analyst is interested in a company's cash flow because historical cash flows are assumed to affect potential cash flows.In other words, the study aims to forecast future cash flow expansion to provide a straightforward predictor of the company's future cash flows. To make an informed decision about investment portfolios, fund managers or experts may calculate the return on their stock holdings. This calculation is essential to determine which securities to purchase, hold, or sell, as well as when to buy or sell them (Jiang & Jia, 2020).

Furthermore, a company's desire to pay dividends is mirrored in its capacity to produce potential cash flows. Predicting a company's cash flow when it sells shares is essential when making financial decisions because it shows the company's potential to pay dividends in the future. Additionally, various stakeholders' decision-making processes rely on a company's ability to understand future cash flows. In terms of financial analysis and investment research, estimating potential cash flows is a significant task (Soboleva et al., 2018).

As a result, when combined with other data, Vietnamese Accounting Standard No. 24 (VAS 24) has agreed that cash flow from operating activities would help and enable users to forecast future cash flows (Nguyen & Nguyen, 2020). On the other hand, since forecasting future cash flows is so important, some researchers have advocated for the visibility of cash flow prediction to help investors and analysts predict future cash flow dividend streams. As a consequence, they have agreed to compare future cash flows with actual cash flows to provide more useful data for investment decision-making.

Predicting a client's or customer's bankruptcy problems helps borrowers avoid misery and terrible debts, as Shamsudin & Kamaluddin (2015) point out in their lending decisions. There are a few telltale signs that a company is having financial difficulties. As a result, cash flows are one of the most important financial indicators of a financial crisis. Creditors and other stakeholders will receive an early warning alert of a bankruptcy if cash flow is reduced. Longevity is also measured by a company's ability to generate a healthy long-term cash flow, with inflows exceeding outflows over time. Companies may live for a limited time by deferring loan payments or allocating funds wisely. In the long run, though, companies must also collect enough cash to meet their needs, as debt repayment failure is the most common cause of bankruptcy (Lee & Kim, 2019).

Since it is essential to investigate potential cash flow prediction in order to detect a deterioration in a company's financial situation, a reliable prediction of financial problems using a suitable and valid approach is a major concern. Mulenga & Bhatia (2017) assert that historical cash flow is a better predictor of future cash flows, which has been scientifically proven by the Financial Accounting Standard Board (FASB). Previous research finds mixed evidence on which measure in terms of historical earnings or historical cash flows as a superior indicator of potential cash flows from 1989 to 2015, according to Nallareddy et al. (2020). They discovered, however, that historical cash flows are a better indicator per year.

Nonetheless et al. (2018) examine past cash flows and earnings to forecast potential operating cash flows of Nigerian money deposit banks. between 2011 and 2016. They employed OLS regression techniques, and the main findings showed that past earnings can forecast future operating cash flows better than past cash flows.

Agana et al. (2016) investigated the comparative predictive ability of variables in earnings and operating cash flows for future operating cash flows in a developed economy to support their point. As a proxy for potential operating cash flows, current operating cash flows were inverted as predictors over the previous one, two, and three years of earnings and operating cash flows. The findings revealed that forecasting potential operating cash flows requires a thorough understanding of historical earnings and operating cash flows. However, they have distinct predictive powers for future cash flows, with historical earnings having a superior comparative predictive potential. As a result, the analysis came to the conclusion that historical earnings are a better indicator of potential cash flow of transactions than historical cash flow of transactions.

Stakeholder Theory

The stakeholder theory is a view of capitalism that emphasizes the interconnected relationships between a business and its customers, suppliers, staff, investors, societies, and other stakeholders (Freeman et al., 2020). Stakeholder theory refers to groups of people who are involved in a company's success and are motivated by its goals, operations, or activities.

The stakeholder theory, according to Al-Attar & Maali (2017), can be linked to Freeman's workshop in 1984, which created a modern conceptual paradigm for organizations to address the needs and benefits of stakeholders. This theory aims to optimize profits and increase company resources for the good of all stakeholders. Some scholars have noted that the objectivity of the stakeholder hypothesis can vary depending on the constituents, which can lead to inconsistencies. When it comes to a business's cash flow, all parties are able to participate. In reality, the cash flow architecture alone enables stakeholders to make short- and long-term investment decisions. If a company's cash flow is weak, it may scare away potential investors and put current investors in jeopardy (Amayreh & Castaneda, 2019).

In the context of this study, this theory clarifies that management has a responsibility to predict what will happen to cash flows and ensure that the organization has sufficient capital to thrive. As a result, a lack of consistent funds could jeopardize the project's entire lifespan. Furthermore, in the construction, energy, and property industries, predicting cash flows is vital to assisting management in forecasting a surplus or deficit in the coming months. For example, if the company's earnings are expected to fall over the next three months, it would be ideal if management might decide to buck the trend.

Previous studies established cash flow estimation as a criterion for calculating potential cash surpluses or shortfalls, according to Omopariola, Windapo, Edwards, and Thwala (2019). Construction projects that catch the interest of key stakeholders and take full advantage of the growth opportunity are more prevalent in companies with a productive cash flow analysis. The creation of an accurate financial forecast that can be attributed to actual on-site development and the associated expenditure outlays is the goal of cash flow analysis.

Furthermore, property development has always been a highly cyclical market, and developers are often plagued by cash flow issues. Property construction necessitates a large initial investment as well as recurring cash outflows for operations. Except for the fact that some or all projects can be sold before they are built, developers often run into cash flow problems before the development starts to sell, particularly if the real estate market is slowing down during construction. Several developers are also facing bankruptcy due to prolonged negative cash flows. Furthermore, a business that is experiencing rapid growth could experience cash flow issues. As a company grows, it incurs higher labour costs, such as higher rent for additional rooms, increased marketing expenses, and increased capital spending for new equipment, machinery, and so on. Extra funds may be consumed in addition to maintaining a higher inventory ratio.

Since the coronavirus outbreak, the property industry, which is known for its "high leverage and high turnover," has faced various strategic and operational challenges. To speed up the economic recovery, a series of programmes (such as fiscal relief and monetary easing policies) are expected to be implemented. The coronavirus broke out without notice at the end of 2019 and spread rapidly. Since then, the pandemic has engulfed companies, adding to the already-increasing problems they face. As a result of this disaster, it is critical for property developers to set up the correct cash management system to ensure successful overall planning and sufficient cash flow to avoid capital shortages and a possible debt crisis. As a result, forecasting potential cash flows in the real estate sector is crucial.

Energy companies may put their cash flow to good use in a number of ways. Until operating costs or financing changes, cash flow is the gap between income and cash flows investment. As a result, businesses can use cash flow to make acquisitions, repay loans, produce profits, buy back equity shares, and increase the accumulated cash balance. Firms may use additional funds for investments, acquisitions, dividends, share repurchases, or to increase cash balances when they borrow additional funds, issue new share capital, or sell current resources. Due to the long-term nature of economic decisions and the constraints imposed by short-term resource constraints, companies often increase their capital reserves during times of increasing energy prices in order to have money available to invest in the coming years. There are two aspects of financial data that are worth noting. Owing to the depreciation of past and present tangible funding, as well as the desertification of oil reserves, net income is initially considerably lower than cash flow. Second, certain investment decisions are deducted as expenditures for cash flow and gross profit, such as experimentation and research and development costs.

The energy industry's investment is a large-scale undertaking, so it's important to estimate capital expenditure for the current and future periods. Discount rates have an effect on cash flows every year, so determining the discount rate is critical. The larger the receivables, the tighter the year-end sales and the higher the cash flows. The lower the receivables, on the other hand, the higher the financial gains and the greater the cash flows. The valuation is also focused on present value and uses accounting data to analyze the cash inflow and outflow to arrive at an economic value that is completely objective. The conclusion implicitly implies that the investment project's cash flow will remain constant, ignoring the importance of growth potential. Organizations are cash flow machines from the viewpoint of investors, with detailed financial performance and profitability elements that are influenced by management decisions that must, without a doubt, produce positive shareholder returns (Yan et al., 2020).


Data Collection

The target population of this study is the public listed companies in Malaysia, which are from the construction, energy, and property industries. The target respondents should have comprehensive data historical cash flows. The data were collected from their annual reports from the year 2015 to 2019, taken from the Bursa Malaysia website.

Gordon et al. (2017) suggested the stratified random sampling technique. This sampling technique was chosen in this study because it is most efficient in differentiating information based on various population strata. The stratified random sampling technique is also known to differ in parameters.

Stratified random sampling in this study includes segregation and followed by a random selection of annual reports from each organization. The data drawn from each organization can either be proportionate or disproportionate stratified random sampling. Generally, disproportionate sampling is more comfortable and straightforward in collecting data (Amayreh & Castaneda, 2019).

In addition, the stratified random sampling design is also more efficient because, in terms of the sample size, each data from the financial statement is better represented and more valuable, and the information can be obtained from each organization.

The companies listed on the Bursa Malaysia website between 2015 and 2019 make up the study's sample. Before being admitted, companies must have prepared accurate financial reports such as revenue statements, balance sheets, and a statement of cash flow. Furthermore, the companies had to have been operational for at least 12 months prior to submission. Nonetheless, the reason for excluding entities with fiscal years ending in December is that equal numbers can be kept. The survey includes 159 companies Table 1. Since they are big businesses with high prices, these firms are at a high risk. If cash flows can be forecast in these sectors, it is critical and therefore avoidable. This might put current and future projects in jeopardy due to a lack of stable funding over their lifespan.

Table 1 Summary of Industries
Industry Number of Companies Percentage (%)
Construction 46 29
Energy 21 13
Property 92 58
Total 159 100

Hypothesis Development

According to the International Accounting Standard Board (IASB) IAS 7, the "Cash Flow Statement" describes that past cash flows are often used as an indicator of numbers, pacing, and estimation of potential cash flows (Nguyen & Nguyen, 2020). In a recent analysis, Efayena (2015) found that cash flow from operations has greater predictive power of future cash flow than earnings, and Farshadfar, Chew Ng, & Brimble (2008) discovered that cash flow from operations has greater predictive power in predicting future cash flow of 323 companies listed on the Australian stock exchange between 1992 and 2004. Their findings were found to be comparable to Habib (2010). As a result, the research hypothesis is as follows:

H1: Historical cash flows have a significant predictive power in forecasting potential cash flows in Malaysian publicly traded firms.

Cash Flow Model

Since previous research has shown that yearly cash flow lags are a good indicator of future cash flows, this study would look at how well year-long cash flow lags forecast future cash flows in Malaysian publicly traded firms. The cash flow model is used to make this prediction as shown below:

CFOt = α0+ α1CFOt- 1 + α2 CFOt- 2 + α3 CFOt- 3 + μ


CFOt = Cash flow from operations for year t,

CFOt-1 = Cash flow from operations for year t-1

CFOt-2, = Cash flow from operations for year t-2

CFOt-3 = Cash flow from operations for year t-3

α0, α1, α2, α3 = Unknown parameters

μ = Error term

The total cash flow of payments as reported in the annual t-i cash flow statements, as specified by CFOt-i, is used to calculate the yearly cash flow lags. The concept of cash flow indicators was also calculated by Agana et al. (2016) in their research. Yearly cash flow lags are estimated to serve a stronger relation with potential cash flows, whereas subsequent cash flow lags are anticipated to have cumulative predictive capacity. Furthermore, if they have predictive capabilities, they could be seen in the model.


Based on Table 2, there are 159 cash flow records in total for each company. This model consists of four variables: Cash Flow 2016, Cash Flow 2017, Cash Flow 2018, and Cash Flow 2019. Besides, there is no missing value in all variables. The median is the best at measuring central tendency; thus, on average, the companies have good historical cash flows in predicting future cash flows since the median for each variable range from RM2 million to RM16 million.

Table 2 Descriptive Statistics of the Cash Flow Model
  CFO (2016) CFO (2017) CFO (2018) CFO (2019)
N Valid 159 159 159 159
Missing 0 0 0 0
Mean 36804163.11 39218383.81 73794361.35 80089117.81
Median 8040000.00 14046107.00 2769483.00 15141000.00
Std. Deviation 139233077.203 192148216.552 253459462.569 220403976.008
Variance 19385849787503264.000 36920937123998888.000 64241699165925672.000 48577912640025536.000

Based on Table 3 above, the R-squared value of 0.187. Therefore, the independent variables (Cash Flow 2018, Cash Flow 2017, and Cash Flow 2016) explain 18.70% of the variability of the dependent variable (Cash Flow 2019), while the remaining 81.30% is explained by other factors. Besides, the Durbin-Watson value (1.923) also shows the existence of an autocorrelation.

Table 3 Model Summary of the Cash Flows Model
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
1 .432a .187 .161 .69113 1.923
a. Predictors: (Constant), CFO (2018), CFO (2017), CFO (2016)
b. Dependent Variable: ResidualCFO

The variables in Table 4 include Cash Flow 2016, Cash Flow 2017, and Cash Flow 2018. Since only one variable (Cash Flow 2018) has a significant value (0.000) < α-value (0.05); therefore, it can be concluded that Cash Flow 2018 contributes to the prediction of future cash flows of Malaysian construction, energy and property industries. As a result, the statistical findings of the cash flow model indicated that the previous one-year cash flow has a substantial effect on potential cash flows (p<0.005).

Table 4 Final Model of Cash Flows
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 7.594 .075   101.253 .000
CFO (2016) -2.684E-10 .000 -.059 -.475 .636
CFO (2017) 1.059E-10 .000 .028 .234 .815
CFO (2018) 1.150E-9 .000 .447 4.114 .000

The cash flow statement may give an indication of how well the company is doing financially. Given these industries are considered in a high-risk category, therefore the past one-year cash flow data would give a better prediction on the future cash flows. To see the company's financial performance in the future would be beneficial to companies as well as the potential investors. It is more accurate if the company could estimate the future performance based on the previous year expenses and income.

This finding may support the optimistic and substantial cash flow for potential investment. Hypothesis is agreed to the extent that the cash flow of a previous one-year is a better predictor for the future cash flows, based on the findings of this analysis. A cash flow prediction forecasts the amount of money that will flow in and out of the company, taking into account all the revenue and expenditures. Many companies' cash flow forecasts are usually for a 12-month term. Therefore, this result may support the assertion that most companies' cash flow forecasts only cover a 12-months span.


This research is expected to have consequences and benefits for all parties involved, including academics, creditors and investors. The forecast model, for example, will be used by creditors to assess their customers' ability to repay debts and borrow sums. Investors who are interested in predicting future returns may also be interested in forecasting future cash flows. This study will contribute to the body of information and previous research on historical cash flows in the prediction of potential cash flows. The results of this study can also be extended to the decision-making processes of other stakeholders, such as business executives. Users of financial statements also will be able to measure and use cash flow modelling data to determine possible cash flows of businesses in terms of predicting projected cash flows, funding, and other results. Government agencies, such as Malaysia's Securities Commission, may use the study's findings to devise legislation and determine what facts can be made available to the general public. Policymakers often play an important role in enacting laws or regulations that favour shareholders and other institutional investors. Thus, via the information management framework, policymakers may monitor the policy of disclosing information to Malaysian publicly listed firms. In other words, they should promote the identification of other achievement metrics, such as cash flow operations as a complementary metric for funding management.

Some limitations may partially influence the research results. With time limitations and no availability of data sources, the following concerns are limited to the current study. First, the results of this study are only limited to Malaysian-listed companies in the construction, energy, and property industries, and the sample in this study further excluded Malaysian companies that are not listed on the website of Bursa Malaysia. Consequently, the results could not extend to the entire selected industry. In addition, the recovery companies were omitted from the study; thus, the research findings could not be used by companies undergoing rehabilitation. Second, this study presumes that the cross-sectional regression analysis operates through businesses in different industries. In other words, each predict model's component will have the same effect on potential cash flows regardless of sector. However, it is indeed likely that the relationship between the explanatory variable and future cash flows differs across sectors, resulting in forecast errors.

This study may be expanded by emulating the methods for investigating data affecting publicly traded firms in other areas. Furthermore, the data sample can be broken down and analyzed by sector. As a whole, this can lead to the development of more sector hypotheses. This study will generate predictive models that are important for studying the Malaysian stock market. Probably, if a business model is used, the predictive model would more likely be more reliable since each firm's data would be evaluated separately. Future research, on the other hand, could be able to test longer data timelines and include suitable prediction models for Malaysian companies. Additionally, the results of this analysis are focused exclusively on a secondary data system. The outcome of a survey to collect data directly from users of financial statements or associated parties can also offer additional validity. Customers of financial statements could use cash flow predictors to predict future cash flows, and further studies may include evidence-based practise. The approximation of the regression model will not be consistent with the cash flow findings because this study used regression analysis to approximate the model for estimating potential cash flows. In other words, a better model can be extracted from a different programme, and if the cash flow data is sufficient, more research can be performed.


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