Is AI Taking Over the Work of Financial Analysts?

Question

Task: Within 1200 words (about five pages), and drawing from a variety of sources, essay on the topic "Are financial analysts' jobs being replaced by artificial intelligence and machine learning"?

Answer

The current financial analysis essay discusses the function of financial analysts, including their involvement in a variety of financial planning, analysis, and decision-making processes. Financial analysts must create a variety of budgets and forecasts as part of financial planning in order to estimate the financial health of a project or business well in advance of the year's beginning and compare actual performance to the predicted numbers to analyse overall financial performance.

In the present period, a modernised business world is expanding quickly due to technological improvement. The employment of artificial intelligence in many business operations has developed into a cornerstone for achieving organisational performance, according to the research of essay writing services on financial analysis essays. Machine learning and AI have assumed a central role in corporate organisations around the world due to the increasing relevance of accurate and timely data (Jordan & Mitchell, 2015). Artificial intelligence has presented enticing possibilities to handle activities with greater accuracy and in real-time in the financial sector (O'Leary, 2013). It is true that financial analysts' jobs have been largely replaced by machines thanks to artificial intelligence (AI), which allows robots to perform tasks that would otherwise need physical labour. The primary duty of a financial analyst, as described in this essay on financial analysis, is to evaluate the suitability of any project or company based on its financial performance. The analysis calls for extensive professional skills (Adhikari & Agrawal, 2014). Other industries are integrating their business operations with AI, not just the financial industry, particularly when it comes to analysing the financial success of the organisation overall or a specific project.

Artificial intelligence enables the speedy completion of all calculations, analyses, and other associated tasks that previously required human experts in more conventional situations (via automated processes) (Krollner, Vanstone & Finnie, 2010). Due to manual interaction, the reports produced in the conventional analysis process had a larger likelihood of error; however, with the use of tools incorporating artificial intelligence, the likelihood of error has almost been eliminated. As a result, the reports generated by AI tools are thought to be more accurate. According to research on financial analysis essay, during the past few years, virtually every industry, including manufacturing and marketing, has witnessed a tremendous increase in the use of robots, digital assistants, and other smart equipment (Dirican, 2015). The role of financial analysts has been impacted by AI's ability to make it fairly convenient to simulate human thought processes and behaviour by utilising a variety of learning algorithms (Kou, Peng & Wang, 2014).

Financial analysts could enter a new world where their routine work will be taken over by machines, and they will need to conceive of analytics strategies in novel ways due to the availability of affordable hardware and high-level software as well as numerous revolutionary AI technologies like the Internet of Things, Big Data, Cloud, etc. (Sohangir, Wang, Pomeranets & Khoshgoftaar, 2018).

Although it is true that artificial intelligence has replaced the work that financial analysts once did, this does not mean that their position in an organisation has been eliminated as a result of AI. Instead, AI has aided financial analyst roles by giving them correct data in real-time so they can perform the in-depth analysis component (Baldwin, Brown & Trinkle, 2006).

One of the primary applications of machine learning algorithms in the financial analysis process outlined in the financial analysis essay is their capacity to evaluate huge amounts of transactional data and to identify questionable transactions, or transactions with high-risk scores, in real-time (Arnold, 2018). When artificial intelligence was not yet a concept, financial analysts still performed these tasks manually using tools like advanced Excel and other analytics tools, but because of manual intervention, the data results could not be as accurate as needed to make informed decisions, and these tasks also required more time to complete (Daniels & Caron, 2009). Human experts' incapacity to analyse the data and create the report in real-time frequently prevented their reports from serving their primary function. The inaccuracy of the input and the delay in its creation for analysis can result in a hazy analysis that causes firms to make bad decisions (Cath, Wachter, Mittelstadt, Taddeo & Florida, 2018).

Without a doubt, technology is essential for automating the everyday activities of financial analysts and for identifying data trends in enormous datasets, ensuring that financial analysts retain their importance in businesses (Soufian, Forbes & Hudson, 2014). The real truth, as mentioned in this article on financial analysis, is that the function of the financial analyst is expanding and that they will be given more responsibility—responsibilities that robots cannot carry out using logic and algorithms. Instead of wasting time collecting data from various sources for financial research, time will now be spent on high-end tasks, including in-depth data analysis, exercising rational judgement based on data supplied by AI tools, and evaluating quantitative algorithms (Bertone? che & Knight, 2001). The ability of humans to make decisions still outweighs that of AI. Additionally, it is acknowledged in this example of a financial analysis essay that quantitative models are generally more advanced than human experts, but it is undeniable that they are better able to identify arbitrary data, such as future trends based on microeconomic and macroeconomic conditions, which are not taken into account when using artificial intelligence tools for financial analysis. Additionally, when results are ambiguous and highly subjective to a higher degree of unpredictability, AI, machine learning, and big data demonstrate less effectiveness (Richins, Stapleton, Stratopoulos & Wong, 2017).

Future financial analysts' ability to perform their jobs effectively will be largely dependent on their ability to continuously learn new patterns, analyse data, and offer distinctive financial services. The future of artificial intelligence and machine learning in business organisations will be shaped by insights regarding the accuracy, timeliness, predictions, and other elements. The aforementioned explanation of the financial analysis essay can be used to draw the conclusion that, despite the fact that artificial intelligence has simply automated regular duties for financial analysts, this has not led to the eradication of their areas of responsibility. Instead, there has been a certain expansion in the job of the financial analyst. With the help of AI, simple tasks may now be automated, freeing up financial analysts to focus on higher-level tasks like data analysis and critical activity judgement (Benninga, 2014). In order to instal and operate the technologies in the business processes, human intelligence will always be needed. It would be more accurate to draw the conclusion from the readings discussed above for the financial analysis essay that pairing financial analysts with machines will enable both of them to flourish in different areas, which will lead to digital transformation in the field of financial analysis (Benninga, 2014).

References:

Risk, Return, and Capital Asset Pricing Model Assignment Sample

Introduction

The CEO of SysConsult International commissioned this essay. Analysis of potential investments in Logical IT and Safeworth Grocery is the goal. The research of finance assignment makes the assumption that a one-year Treasury note will earn 5% over the following year, with Logical IT's beta being 1.70 and Safeworth Grocery's beta being 0.60. Table 1 below contains an examination of potential return rates for the two businesses under various economic scenarios.

Relationship between Risk and Rate of Return

General Rule

As a general rule, more risks are linked to greater potential rewards, whereas greater safety is linked to greater potential losses. A straightforward and common sense principle of companies seeking to acquire capital governs this connection. It is best to describe the situation by presuming that there is no such link. In this universe, regardless of volatility, all investments would yield the same rate of return. Therefore, there wouldn't be any incentives for investors to fund risky businesses or projects. In other words, only a select few businesses would be able to access the money from possible investors, as people would not want to take the chance of their money disappearing for no apparent reason.

In the real world, businesses have the opportunity to raise more money by providing investors with greater returns. Companies can either guarantee investors a portion of their income through dividend payments, or they can show that they will grow quickly, allowing investors to sell their shares at a profit. Potential investors have a cause to participate in businesses with high performance volatility thanks to incentives like these. Investors typically base their judgements on a comparison of potential returns and risks, choosing the market's optimum ratio. Investors are also influenced by their own level of risk tolerance, as some people may be unable to take a large risk of financial loss, regardless of how lucrative an investment could be.

Not a Direct Relationship

It should be noted that risk and return do not directly correlate. Bigger risks entail higher potential profits, where "potential" is the essential concept. A person must be willing to embrace the potential that they could lose some or all of the money they invest if they wish to fast expand their wealth. Two concrete examples—trading in penny stocks and cryptocurrencies—can be used to demonstrate this. Bitcoin and other cryptocurrencies are frequently linked to great profits. Figure 1 shows that if an investor had bought in October 2020 and sold in December 2020, their investment would have more than doubled.

Figure 1. Bitcoin-USD exchange rates between October 2020 and December 2020(Yahoo Finance, 2021)

Although purchasing Bitcoins may seem appealing, due to the extreme volatility of the exchange rates, it is not necessarily a safe investment. If investors had chosen to invest at the start of June 2021, as shown in Figure 2 below, they may have lost more than 40% of their money. Investors may also be higher at risk of losing money due to government laws against cryptocurrencies, low transaction and keeping security, and other factors. Twelve nations, including China and Russia, have outlawed cryptocurrency, indicating that further nations may do the same. Due to all of these factors, investors must be willing to risk the possibility of substantial losses in exchange for the potential for big profits.

Penny stocks are another illustration of the connection because they are regarded as high-risk investments because of the extreme share price volatility. Outside of the major stock exchanges, a small group of investors trade these equities at extremely low rates. As a result, if a substantial investor decides to buy shares, the stock price will increase significantly, giving other investors the chance to sell the stock at a premium. But these investments are frequently non-liquid, suggesting that nobody might desire to buy these equities. Additionally, the stock prices would decrease dramatically if a big investor decides to sell shares, which will result in losses.

Calculating the Expected Rate of Return

Definition and Formula

The anticipated rate of return is the value at which investors can expect a given probability distribution of probable returns. In other words, it is the result of adding the probability of all conceivable outcomes together. Given the probability distribution of outcomes, it may be seen as the typical return rate an investor should anticipate from an investment. An investor can determine if a stock is performing well or poorly using the expected rate of return as a benchmark. The expected rate of return is calculated using the following formula:

Where:
• E(R) = Expected Rate of Return
• Rn = Return Rate in case of n
• Pn = Probability of n occurring

Calculations

According to the estimates, Safe worth Grocery has the lowest predicted rate of return, while Logical IT has the best.

Calculating Standard Deviation

Definition and Formula

A measure of variability called standard deviation shows how much the actual data may deviate from the expected value in standard units. To put it another way, the standard deviation is a metric that shows how volatile a stock is predicted to be over a specific time frame. The following is the standard deviation formula:

Where:

• Rt = observed return rate
• R = expected return rate

Calculations

According to the estimates, Logical IT has the largest standard deviation, indicating that its stock is the most volatile.

Beta and CAPM

Beta vs Standard Deviation

Beta or the standard deviation are two ways to quantify volatility. The standard deviation, as it was discussed in Section 4, is a gauge of a stock's volatility over a specific time period. A stock's price fluctuation in relation to a benchmark is shown by the relative measure of volatility known as beta (for example, ASX200 index). The stock, for instance, will be 20% more volatile than the market if the beta is 1.2. This suggests that the stock should increase by 12% if the market increases by 10%. When predictions regarding the performance of the benchmark index are available, beta is helpful. Higher betas are recommended if the market is anticipated to rise, whereas lower betas are preferred in all other scenarios.

Since it helps to make decisions knowing the forecast for the benchmark, beta is a stronger indicator of risk in this situation for the common shares of the IT company and the supermarket company. According to the ASX200 forecast, there is only a 30% risk of a market recession and a 70% likelihood that the market would grow.

Using Beta for Calculations

The projected rate of return for the two companies under examination can be determined using the beta of the companies. The capital asset pricing model (CAPM) can be used to do that. The CAPM formula is as follows:

Where:

• Rf = risk free rate (treasury note)
• βi = company beta
• E(Rm)= benchmark return rate (ASX200)

Section 1 of the essay provides the betas for Logical IT and Safeworth Groceries as well as the risk-free rate. Section 3.2 of the essay provides the expected rate of return for the ASX200.

Following are the calculations for the two companies under analysis' projected rates of return:

If the cash flows are the same, Logical IT will be valued more because of its larger beta.

Volatility of the Benchmark

It is also vital to take into account how the anticipated return rate will vary if the market becomes unstable. Higher betas indicate that the value will likewise be more variable than projected. For instance, if the projected rate of the ASX200 falls by 5% (to 6%), Logical IT's share price will move more dramatically than Safeworth Groceries'. Following are the calculations:

This indicates how closely tied to market performance the value of Logical IT's shares is.

Portfolio Creation

Portfolio Beta

Putting such a portfolio is essential for protecting investments from threats. Investors want to distribute their capital among a variety of funds, including bonds, shares of small businesses, shares of internationally renowned companies, and shares of well-established foreign corporations. By making investments in various businesses, investors frequently diversify their portfolios. A technique like this helps protect the investor from the potential that the industry won't do well at a certain point in time. When it comes to Logical IT and Safeworth Groceries, investment in the grocery chain provides protection from the market's turbulence and the IT industry's performance.

A portfolio's beta, which is a weighted average of the betas of all the companies in the portfolio, can be used to describe it after it has been constructed. Understanding a portfolio's predicted volatility during the specified period is made easier with the help of the portfolio beta. The following formula is used to determine the portfolio's beta:

Two potential two-share portfolios were taken into account for investment. The first choice is to put $70,000 in Safeworth Groceries and $30,000 in Logical IT. According to this, 30% of the portfolio will presumably be invested in the IT company, and 70% in the grocery company. When it comes to portfolio beta:

The CAPM model can be used to determine the portfolio's anticipated rate of return:

According to the analysis, this option has a little lower risk than the ASX200 index. When the market prediction is unfavorable or fraught with uncertainty, this kind of portfolio may prove advantageous.

Alternatively, you might put $70,00 into Logical IT and 30% into Safeworth Groceries. The predicted rate of return and portfolio beta in this instance will be as follows:

Comparing this type of portfolio to the market benchmark of 11%, larger predicted returns are connected. When the outlook for the market is favourable, a portfolio like this is the ideal choice.

Recommendations

When comparing the two choices listed above, I would choose the second one, in which the IT business receives 70% of the funds and the food company receives 30%. As stated in Section 1 of the current paper, there is only a 30% likelihood of a market recession, thus the projection for the ASX200 index is favourable. Investors may be more risk-tolerant when the market is predicted to grow, so somewhat larger beta values are favoured. By investing in the grocery company in the second scenario, any potential underperformance of Logical IT is compensated for. It is advisable to safeguard the investment from the risk of a recession even though diversifying the portfolio reduced the possible rate of return from 15.2% to 13.22%. The expected returns from Logical IT will dramatically decrease if the market goes into a recession, whereas the expected returns from the grocery store are predicted to be rather steady (see Section 5.3). Additionally, buying in Safeworth Grocery shields funds against Logical IT's underperformance and market volatility.

Although the aforementioned advise seems to be appropriate, the investor ultimately has the last say. The investor's individual risk tolerance should be used as a reference when making investments. The 30% probability of underperformance may be too high for some investors. The first selection from the two-share portfolio is preferred in this situation. This portfolio's beta is only somewhat lower than the market benchmark, which suggests that predicted returns will be roughly average. The investor will also continue to be safe from any potential market turbulence.

Reference List

Orji, C. (2021). Bitcoin ban: These are the countries where crypto is restricted or illegal. EuroNews.

Yahoo Finance. (2021). Bitcoin USD (BTC-USD).