Accrued Payroll: Definition, Accounting, Journal Entry, Example, Meaning

Companies pay their employees after predefined intervals. However, accounting requires them to recognize any liability incurred for those expenses regardless of the payment. Therefore, companies use accrued payroll to track it.

What is Accrued Payroll?

Accrued payroll is a fundamental concept in accounting that represents the accumulated amount of employee compensation earned but not yet paid by a company as of the end of an accounting period. It includes various components such as wages, salaries, bonuses, commissions, benefits, and payroll taxes that employees have earned but have not received in cash or check.

The accrual of payroll occurs because of the time lag between when employees perform work and when they receive their compensation. This time difference is common in many businesses, especially those with regular pay periods such as weekly, bi-weekly, or monthly. From an accounting perspective, accrued payroll gets recorded as a liability on the company's balance sheet.

What is the accounting for Accrued Payroll?

Accrued payroll accounting involves recognizing the wages, salaries, bonuses, benefits, and taxes employees have earned but not yet received as a liability. After every accounting period, an adjustment records the accrued payroll expense and increases the accrued payroll liability. This adjustment ensures that the income statement accurately reflects the expenses incurred during the period, regardless of the payment.

The accounting process for accrued payroll helps businesses maintain accurate financial statements by reflecting the true obligations and expenses related to employee compensation. It also facilitates effective cash flow management and budgeting by ensuring that payroll expenses are properly recorded and accounted for in the appropriate periods.

What is the journal entry for Accrued Payroll?

The journal entry for accrued payroll involves recording an increase in salaries and wages expenses. This expense includes all labor-related costs that a company bears. On the other hand, it also increases the accrued payroll liability. The journal entry is as follows.

Dr	Salaries expense
Cr	Accrued payroll

The above journal entry for accrued payroll only recognizes labour-related expenses incurred. However, it falls under the accrued category because the company has not paid for it yet. Once the company compensates its workers, it must reduce the liability using the following journal entry.

Dr	Accrued payroll
Cr	Cash or bank

Example

At the end of January, Green Co. calculates its total salaries and wages expenses to be $5,000. At the time of the calculation, the has incurred the cost and must record it using the following journal entry.

Dr	Salaries expense	$5,000
Cr	Accrued payroll	$5,000

After five days, Green Co. pays all its employees through cash. The company records this transaction as follows.

Dr	Accrued payroll	$5,000
Cr	Cash	$5,000

What is the importance of Accrued Payroll?

Accrued payroll ensures that financial statements accurately reflect the company's financial position by recognizing the liabilities associated with employee compensation that have been earned but not yet paid. It helps present a true and fair view of the company's obligations and expenses at the end of an accounting period.

Secondly, accrued payroll is crucial for effective cash flow management and budgeting. By recording accrued payroll expenses, businesses can plan and budget for future cash outflows related to employee compensation more accurately. It allows companies to allocate resources efficiently, anticipate financial commitments, and avoid cash flow shortages or surprises.

Conclusion

Accrued payroll is an account that records labour-related expenses that a company has incurred but not yet paid. It appears as a liability on the balance sheet until the company compensates its workers. On the other hand, it also increases the expenses for costs incurred. Accrued payroll is crucial in accurately reporting expenses and liabilities.

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Volatility Spillover Between Developing Markets

Volatility spillover refers to the transmission of volatility shocks from one market or asset to another, leading to increased volatility in the receiving market. These spillovers can occur within the same asset class or across different asset classes. For instance, a sudden increase in volatility in one stock market may trigger similar movements in other stock markets around the world. Similarly, volatility shocks in the currency market can spill over into the equity market.

Reference [1] investigates the volatility spillover effect between the Nigerian exchange rate and the exchange rates of the BRICS countries. The authors pointed out,

This study focuses mainly on examining the volatility spillover between the economies of Nigeria and the BRICS nations, using MGARCH time series models; VECH, DBEKK and CCC. Thus, to study some features of good volatility modeling on FTS. It is shown that not all series are stationary since trend components exist which must be transformed prior to modeling. These trend components have been appropriately handled, having noted that some periods pose more threats than the others. In addition, risky periods are spread out at random and a certain degree of autocorrelation exists in the series, implying that big changes are likely to follow big changes and small to follow small, which is called volatility clustering. The result of the VECH model shows that all parameters are significant at 5% level (p< 0.05) and this clearly indicates that there are positive effects of ER shocks in Nigeria on the ERV of BRICS markets. In addition, the VECH model was able to capture volatility spillover (own and across) with both parameters are on negative directions for Nigerian market, suggesting a causal relationship between past volatility shocks of Nigeria and current volatility in the BRICS markets (which clearly revealed that Nigeria has better advantage in being with the BRICS nation).

In essence, there exists a spillover of volatilities between the Nigerian exchange rate and the exchange rate markets of the BRICS countries. The authors also offer economic explanations based on bilateral relations between these nations.

This paper demonstrates that seemingly unrelated markets can be interconnected and display lead-lag relationships. Such relationships are important in the design of trading and risk management systems, such as statistical arbitrage.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Ibrahim, M. K., Tasi’u, M. and Dikko, H. G., A study on the volatility spillover between Nigerian and BRICS  economies using multivariate GARCH models, FUDMA JOURNAL OF SCIENCES, 8(2), 170 - 179.

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Marginal Social Benefit: Definition, Cost, Formula, Equation, Meaning, Example

In decision-making, especially about economics or community projects, it's important to think about how choices impact everyone, not just a few.

There's a specific factor that helps measure this impact, showing how decisions can affect the whole society - which is known as Marginal Social Benefit (MSB).

It's crucial for businesses to understand the concept of MSB, as it can help them make more informed and responsible choices for their operations and strategies.

What is Marginal Social Benefit?

Marginal social benefit refers to the total gain appreciated by society when a product is consumed, accounting for both its direct benefits to consumers and its wider impacts on the environment and society.

Essentially, it combines the immediate satisfaction that users get with the broader societal and environmental costs or gains.

For instance, if consuming a product brings additional benefits to the community, like improved public health, then the marginal social benefits exceed the benefits that just the consumers themselves experience.

On the flip side, if the consumption of a product leads to negative outcomes, like pollution, the overall benefit to society is less than what the individual consumers perceive as their personal gain.

In simple words, marginal social benefit is all about considering the "bigger picture" and not just individual gains.

How Marginal Social Benefit Works

Imagine someone buys a bike and uses it instead of a car.

This decision doesn't just benefit the bike rider by saving money on gas - it also helps everyone else by reducing traffic and pollution. Marginal social benefit is like looking at this bigger picture.

It checks how one person's choice to buy and use something can be good for other people too. If the choice leads to nice things for others, like cleaner air, then the benefit is big.

But if it causes problems, like noise or waste, then the benefit isn't as great. It's about seeing how one action can ripple out and touch the community.

For a bigger picture like a business or an organization, this concept is important to consider when deciding on what products or services to offer.

By taking into account the potential impacts on society and the environment, companies can make more informed decisions that not only benefit themselves but also contribute positively to the world around them.

Equation for Marginal Social Benefit

The formula of marginal social benefit is quite simple

Marginal Social Benefit = External Benefits + Marginal Private Benefit

Where,

• External Benefits: These are the positive effects that are enjoyed by others in society as a result of an individual's consumption or production choices.
• Marginal Private Benefit: This refers to the personal gain or benefit experienced by the individual consumer.

In short, marginal social benefit takes into account not only the immediate benefits for individuals but also the potential benefits for society as a whole.

Conclusion

Social impact should be a major concern not only for individuals but also for businesses and organizations. By considering the concept of marginal social benefit, we can make more conscious choices that not only benefit ourselves but also contribute positively to society. It's good for both personal gains as well as the greater good.

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Predicting Realized Volatility Using Skewness and Kurtosis

Realized volatility refers to the actual volatility experienced by a financial asset over a specific period, typically computed using historical price data. By calculating realized volatility, investors and analysts can gain insights into the true level of price variability in the market, which can be valuable for risk management, portfolio optimization, and trading strategies. Realized volatility is often used in conjunction with implied volatility to assess the accuracy of market forecasts and to adjust trading strategies accordingly.

Reference [1] examines whether realized volatility can be forecasted. Specifically, it studies whether realized skewness and kurtosis can be used to forecast realized volatility. The authors pointed out,

Given the important role of volatility forecasts accuracy in optimal portfolio designs, this study provides strong evidence that realized kurtosis is most useful when one to 22 day ahead forecasts are of interest by taking large and diverse set of data of 452 listed firms at PSX, and thus could assist in improving asset allocation decisions. Thus, the standard HAR model and its extensions containing realized kurtosis predicts the expected realized volatility as a linear function of yesterday’s realieed volatility and its mean over prior week and month as well as yesterday’s realieed kurtosis. Therefore, it is concluded that stocks’ own realieed kurtosis carries meaningful information for stocks’ future volatilities.

Briefly, the author extended the HAR-RV model to incorporate realized skewness and kurtosis. They found that realized kurtosis is most useful when forecasting one to 22 days ahead.

Note that this study was conducted in the Pakistan stock market, but the research framework can be applied to any stock market and asset class.

Let us know what you think in the comments below or in the discussion forum.

References

[1]  Seema Rehman, Role of realized skewness and kurtosis in predicting volatility, Romanian Journal of Economic Forecasting, 27(1) 2024

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Expansionary Monetary Policy: Definition, Meaning, Effects, Benefits, Pros and Cons

In today's economy, the role of expansionary monetary policy is like a helping hand during tough times. Imagine a situation where jobs are hard to find, businesses struggle to grow, and people are spending less.

In such scenarios, having the right tools to start growth and encourage spending is crucial. Expansionary monetary policy serves as one of these essential tools.

It helps ensure that the economy doesn't stay down for too long, making it an important aspect of financial health and stability.

What is Expansionary Monetary Policy?

Expansionary policy is basically boosting an economy when it's moving slowly. It's all about encouraging more spending and activity - this can be done in two main ways.

One way is by making it cheaper for people and businesses to borrow money, aiming to get them to spend and invest more.

Another approach involves the government stepping in, spending more itself, or giving tax breaks, hoping to spark more economic activity.

The goal here is to keep the economy from slipping too much, trying to avoid big slowdowns or recessions.

However, this strategy isn't without its challenges - it can lead to higher prices for things as demand goes up. So, while it's aimed at reducing joblessness and keeping the economy lively, it has to be managed carefully to not let prices climb too high.

How Expansionary Monetary Policy Works

Expansionary monetary policy is a method used by central banks to jump-start the economy.

The central bank lowers interest rates, making it cheaper for people and businesses to borrow money. When borrowing costs less, people are more likely to take out loans for big purchases or to start and expand businesses.

Businesses might use the extra funds to hire more workers or buy new equipment. All this activity pumps more money into the economy, encouraging growth.

However, it's a delicate balance because too much spending can lead to higher prices for goods and services.

How to Implement Expansionary Monetary Policy

Here's how central banks can implement expansionary monetary policy

1. Lower interest rates: By lowering interest rates, central banks make it less expensive for people and businesses to borrow money - this encourages more spending and investment.
2. Increase the money supply: Central banks can also increase the amount of money in circulation by buying government bonds or other securities from commercial banks. This gives those banks more money to lend out at lower interest rates.
3. Cut reserve requirements: Banks are required to keep a certain amount of money in reserve, but central banks can reduce this requirement to allow them to lend out more money.

How does Expansionary Monetary Policy Affect the Economy?

Expansionary monetary policy can have several effects on the economy, here are some of the main ones

1. Increases Economic Growth: By making it easier and cheaper to borrow money, expansionary monetary policy encourages more spending and investment, leading to overall economic growth.
2. Reduces Unemployment: With more spending and investment, businesses are likely to hire more workers which can help reduce unemployment rates.
3. Boosts Stock Market: Lower interest rates make stocks a more attractive investment option, leading to an increase in stock prices.
4. Inflation: As mentioned earlier, expansionary monetary policy can lead to inflation if too much money is injected into the economy. Banks must carefully monitor and adjust their policies to avoid excessive inflation rates.

Conclusion

Expansionary monetary policy is a powerful tool used by central banks to stimulate economic growth. However, it has its limitations and must be carefully managed to avoid negative effects such as inflation. Even though it has its risks, it is an essential tool in stabilizing and supporting the overall health of the economy.

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Is Pairs Trading Still Profitable?

Pairs trading involves identifying two related securities, typically stocks, that have historically exhibited a strong correlation in price movements. Traders then look for deviations from this historical relationship, buying the underperforming security while simultaneously selling the outperforming one. The goal is to profit from the convergence of prices back to their historical relationship. Pairs trading can be implemented using various metrics to measure the relationship between securities, such as cointegration or correlation coefficients.

Reference [1] examines the profitability of pairs trading in the German market. It investigates four methods for selecting pairs: the Distance Method, Cointegration Method, Copula Method, and Ensemble Method. The author pointed out,

This study revisits well-established pairs trading strategies and applies them to the German stock market, for which – despite its large size and sophisticated trading infrastructure – comprehensive studies are lacking. All standard approaches are tested over the period 2000 through 2023 and its multiple market regimes, complemented by the proposal for an ‘ensemble technique’ that combines the signal of individual methods.

…

Opportunities in the market for basic approaches such as the Distance and Cointegration Method have decreased after the 2008/09 financial crisis. Copula and Ensemble Method provide consistently positive portfolio returns on employed capital over the entire period. Their equivalent performance for committed capital is reduced primarily because of limited trading opportunities. With the Copula Method still the best-performing over the entire period, its advantage over, say, the Distance Method is much less pronounced.

In short, when factoring in transaction costs, pairs trading using the Distance and Cointegration methods becomes unprofitable. However, pairs trading based on the Copula and Ensemble methods remains profitable.

We believe that commonly used pairs selection methods are overused and no longer yield profits. To trade pairs profitably, traders should explore less conventional methods.

It's worth noting that this study examined the German market. It would be interesting to see similar research conducted in other developed markets.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Sascha Wilkens, Pairs Trading in the German Stock Market: There’s Life in the Old Dog Yet, SSRN

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Vertical Analysis vs Horizontal Analysis: What are the Differences, Comparison

Vertical and horizontal analysis provide valuable insights into multiple aspects of a company's financial performance. However, they differ in the way they help analyze financial statements.

What is Vertical Analysis?

Vertical analysis (or common-size analysis) is a financial evaluation method focused on dissecting and comparing individual components within financial statements for a single reporting period. This technique involves representing each line item on a financial statement as a percentage of a critical benchmark, such as total revenue or assets.

By converting financial data into percentages, vertical analysis facilitates a more in-depth examination of the composition and relative significance of different elements within the statements, aiding in detecting trends, relationships, and patterns. Through vertical analysis, analysts and stakeholders gain insights into the proportional contribution of each line item to the overall financial picture.

What is Horizontal Analysis?

Horizontal analysis (or trend analysis) is an analysis technique used to evaluate and compare financial data across multiple periods. It involves examining changes and trends in financial statements, such as income statements, balance sheets, and cash flow statements, over time. The primary focus of horizontal analysis is to assess the direction and magnitude of changes in key financial metrics and line items from one period to another.

Horizontal analysis involves calculating dollar amount changes and percentage changes for each line item on the financial statements in various periods. This analysis helps stakeholders and analysts identify trends, patterns, and fluctuations in performance over time. It provides insights into the changes in revenues, expenses, assets, liabilities, and other financial metrics, allowing for a comprehensive assessment of a company's financial health and performance trajectory.

Vertical Analysis vs Horizontal Analysis: What are the differences?

Vertical and horizontal analysis take different approaches when analyzing financial statements. The differences between the two come from the following areas.

Focus

Vertical analysis focuses on analyzing individual components of financial statements within a single period by expressing each item as a percentage of a critical benchmark, such as total revenue or assets. However, horizontal analysis evaluates changes and trends in financial data across multiple periods by comparing dollar amount changes and percentage changes for each line item between two or more periods.

Time frame

Vertical analysis considers the composition and relative significance of financial statement items within a specific reporting period. In contrast, horizontal analysis considers the direction and magnitude of changes in financial statement items over time, typically comparing data from consecutive or historical periods.

Purpose

Vertical analysis helps assess the proportional contribution of different line items to the overall financial picture and identify trends or patterns within a single period. However, horizontal analysis assists in identifying trends, patterns, and fluctuations in financial performance over time, aiding in understanding the trajectory of financial metrics and evaluating long-term performance.

Calculation

Vertical analysis involves converting financial data into percentages by dividing each line item by a critical benchmark. On the other hand, horizontal analysis measures dollar amount changes and percentage changes for each line item between two or more periods.

Scope

Vertical analysis focuses on analyzing the composition and structure of financial statements vertically, emphasizing the relative importance of different components within a single period. Contrastingly, horizontal analysis analyzes changes and trends in financial statements horizontally, emphasizing the evolution and direction of financial metrics over time.

Conclusion

Vertical and horizontal analysis are two methods of analyzing financial statements to identify trends. The former focuses on comparing individual components for a single period by establishing a benchmark. On the other hand, horizontal analysis looks at the same line items over various periods for comparison. The differences between the two come from their focus, time frame, purpose, calculation, and scope.

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Risk Management for Bull Put Spread Strategy

A bull put spread is a type of options strategy used by investors who anticipate a moderate rise or at least stability in the price of the underlying asset. In this strategy, the investor sells a put option with a higher strike price while simultaneously buying a put option with a lower strike price, both with the same expiration date.

If the price of the underlying asset remains above the higher strike price at expiration, both options expire worthless, and the investor keeps the premium received. However, if the price falls below the lower strike price, the investor may incur losses, which are limited to the difference between the two strike prices minus the net premium received. Overall, the bull put spread strategy is used to capitalize on a bullish or neutral market outlook with limited risk.

Reference [1] examines the effectiveness of stop losses in bull put spreads. This is achieved through Monte Carlo simulation, which is conducted in an idealized setting using theoretical asset and option prices. Although the simulation may not perfectly reflect real-world conditions, it provides valuable insights and intuitions regarding the effectiveness of different stop-loss strategies. The author pointed out,

While all three strategies with strict exit variants show a clearly (exponentially) positive development, an (almost) total loss has completely destroyed the variant with no exit strategy. Since a (near) total loss event practically erodes the entire investment, a realistic chance of recovery is no longer possible. Seen from this perspective, it becomes much clearer, much more so than could be seen from the computations of average returns, that implementing a bull put spread strategy in the setting we chose (using the available investment to the full) proves fatal without a strict exit strategy.

Upon reviewing the results presented in Table 4.12, we notice some counterintuitive findings.

• Firstly, the strategy proves profitable only during periods of low volatility;
• Conversely, it incurs losses when volatility is high, even during a bull market. (We believe that we have insights into why it loses money in a bull market, but we leave this to the readers).
• The implementation of stop losses enhances the strategy's performance.

The author’s conclusion emphasizes the importance of common-sense principles and best practices in portfolio management, such as capital preservation and minimization of the risks of ruin. These objectives can be achieved through the implementation of stop losses.

We note, however, that the risks of ruin can also be minimized by eliminating the tail risks. This is our preferred solution.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Gerhard Larcher, The Art of Quantitative Finance Vol.1, Trading, Derivatives and Basic Concepts, 2023, Springer

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Direct Listing: Definition, Advantages, Disadvantages, Meaning, Example, vs. IPO

When it comes to a company going public, there are two main ways to do it: through an initial public offering (IPO) or through direct listing.

While IPOs have long been the traditional route for companies looking to become publicly traded, direct listings have gained popularity in recent years.

It's more common for well-established companies with a strong financial standing to choose direct listings over IPOs. By understanding how direct listings work, business owners and investors alike can make informed decisions about the best path for their company.

What is Direct Listing?

A direct listing, also known as a direct public offering (DPO), is a process in which a company lists its existing shares on a stock exchange without allocating new shares or raising additional capital.

Essentially, it allows a private company to become publicly traded without going through the traditional IPO process.

Most of these companies have different goals than the companies that go public through an IPO.

While IPOs are primarily used to raise capital, direct listings are typically done for other reasons such as providing liquidity for existing shareholders or increasing brand visibility.

It's beneficial for liquidity and employee morale, as employees are given the opportunity to sell their shares on the public market.

How Direct Listings Work

Direct listings involve a company's existing shareholders selling their shares directly to the public, bypassing the underwriters or banks that are typically involved in an IPO.

This means that there is no initial pricing of the company's stock and no lock-up period for investors.

In an IPO, underwriters work with the company to determine the price of its stock and then sell it to investors at that price. With direct listings, the market determines the initial stock price through supply and demand.

Additionally, there is no lock-up period for investors, meaning they can buy and sell shares of the company immediately without any restrictions.

This is different from an IPO where the company's insiders and pre-IPO shareholders are typically restricted from selling their shares for a certain period of time after the initial public offering.

Advantages of Direct Listings

One major advantage of direct listings is that it can save companies millions of dollars in underwriting fees.

This is because the company does not need to pay any fees to investment banks or underwriters for their services in determining the initial stock price and selling the shares to investors.

Direct listings also allow companies to have more control over the pricing of their stock, as it is determined by market demand rather than through negotiations with underwriters.

Furthermore, direct listings can increase brand visibility as they often generate a lot of media attention and investor interest.

This can help attract potential customers and investors to the company.

Disadvantages of Direct Listings

One disadvantage of direct listings is that it can be a riskier option for companies, as there is no guarantee of a successful market debut.

Without underwriters' support, there may not be enough demand for the company's stock, leading to a decrease in share price.

Additionally, without the traditional IPO process, direct listings do not have the same level of regulatory scrutiny and due diligence, which may make some investors hesitant to invest.

Furthermore, direct listings may not be suitable for companies looking to raise capital as they are primarily used for existing shareholders to sell their shares.

IPO vs Direct Listing

Here are some of the noticeable differences between IPOs and direct listings

Sure, I'd be happy to explain the differences between an IPO and a direct listing in a simple way. Let's break it down:

1. How They Raise Money

IPO: In an IPO, a company sells new shares of itself to the public for the first time. This process helps the company raise a lot of money because they're selling parts of the company to investors.

Direct Listing: In a direct listing, the company doesn't sell new shares. Instead, it allows people who already own shares (like employees or early investors) to sell them directly to new investors. The company itself doesn't make money from this sale.

2. Role of Underwriters

IPO: An IPO involves financial experts called underwriters (usually big banks). These underwriters help set the price of the shares, sell them, and guarantee a certain amount of money will be raised.

Direct Listing: There are no underwriters involved in a direct listing. The market determines the price of the shares based on supply and demand when trading starts. This means there's no guaranteed amount of money raised.

3. Pricing of Shares

IPO: In an IPO, the initial price of the shares is decided by the underwriters before they start being sold to the public. This price is based on how much they think the company is worth and how much interest there is from investors.

Direct Listing: In a direct listing, there's no set price before the shares start trading. The opening price is determined on the day of the listing based on the buying and selling orders collected by the stock exchange from investors.

4. Lock-Up Period

IPO: Often in an IPO, there's a "lock-up" period. This means that insiders (like employees and early investors) are not allowed to sell their shares for a certain period after the IPO, usually around six months. This is to prevent the market from being flooded with too many shares all at once.

Direct Listing: There's usually no lock-up period in a direct listing. This means insiders can sell their shares right away if they want to.

Conclusion

Businesses that want to go public have two main options: an IPO or a direct listing. Both involve selling shares to the public - both have their pros and cons. Both have different purposes and outcomes. It's important for businesses to carefully consider their goals and decide which option is best for them.

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A Portfolio Construction Approach Based on Options Implied Density Distributions

An investment portfolio can be constructed by using momentum, minimum-variance, or mean-variance approaches. It involves combining assets in a way that optimizes risk and return. Each approach offers its own trade-offs: momentum strategies may suffer during market reversals, while minimum-variance portfolios may underperform in strongly trending markets. Meanwhile, mean-variance portfolios require assumptions about expected returns and covariances, which may not hold in practice.

Reference [1] introduces a novel portfolio construction technique based on options prices. Essentially, the authors employ sector ETF options to derive implied risk-neutral distributions, which are subsequently transformed into real-world distributions. These real-world distributions are then utilized within a portfolio optimization framework to construct a sector ETF portfolio. They pointed out,

We adopt a comprehensive financial modeling approach to sector investing with ETFs. Significant and robust outperformance is achieved. The comprehensive strategy beats the passive benchmark and simpler active approaches (including pure sector momentum, Minimum-Variance, and Mean-Variance portfolios) in terms of a range of performance measures out-of-sample.

The after-cost outperformance of the comprehensive strategy is more pronounced when the portfolio is rebalanced quarterly or annually to limit portfolio turnover and transaction costs, and in high volatility states, when markets are expected to be least efficient and option prices are expected to be most informative.

Several elements of the methodology stand out as being particularly effective: option-implied probabilities estimated using the Heston model, risk transformation of the risk-neutral distribution, and the use of SD constraints to account for skewness and tail risk.

In short, the article demonstrates that option-implied probability density distributions can be utilized for constructing investment portfolios. The resulting portfolios exhibit favorable risk-adjusted returns.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Thomas Conlon, John Cotter, Illia Kovalenko, Thierry Post, A financial modeling approach to industry exchange-traded funds selection, Journal of Empirical Finance 74 (2023) 101441

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