Term Structure of VIX Futures

VIX futures are financial derivatives that allow traders to speculate on or hedge against future volatility in the stock market, specifically the S&P 500 index. They are based on the CBOE Volatility Index (VIX), which measures market expectations of near-term volatility. Unlike spot VIX, which reflects current market volatility, VIX futures reflect market expectations of volatility at different points in the future. This often leads to a term structure where VIX futures prices can be in contango or backwardation.

Reference [1] proposed a framework to price VIX futures. Essentially, the authors break down the factors affecting VIX futures term structures into two key components: demand and variance risks. They pointed out,

… shocks to the variance and demand factors alter the term structure of VIX futures differently. Assessing the implications of the shocks is useful for exploring risk management strategies based on VIX futures. For instance, a positive shock to the variance factor increases economic uncertainty, and leads investors to expect the impact of the shock to be large but short-lived. Hence, investors tend to hold more short-term VIX futures to hedge against these volatility risks. In contrast, a positive shock to the demand factor directly reduces investor demand for VIX futures, leading futures prices to fall. When investors realize that the demand shock is sustained, they reduce their investment in long-term VIX futures and short long-term VIX futures to deal with the demand risk.

… We find that the jump risk contributes to explaining the conditional mean, variance, and higher-order moments of VIX futures. The parameters pertaining to the investors’ demand and arbitrageurs’ risk aversion are nontrivial in terms of pricing futures and fitting the term structure. We compare the variance and demand factors and find that the former is more important in pricing short-term futures, whereas the latter has a greater effect on long-term futures. In addition, the impulse response analysis suggests that shocks to the variance factor dissipate more quickly over the horizons than shocks to the demand factor.

In short, the VIX futures term structures can be influenced by these demand and variance risks.

This is an important contribution to the research on the pricing of VIX futures as it could help explain why, recently, short-dated VIX futures are in backwardation, while the spot VIX is in contango.

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

References

[1] Yang X. & Huang J., Demand Risks and Term Structure of Volatility Index Futures, Journal of Management Science and Engineering, 2024

Originally Published Here: Term Structure of VIX Futures

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Fixed-Charge Coverage Ratio: Definition, Calculation, Example, Importance

The fixed-charge coverage ratio might sound complicated, but it's just a way to see if a company can pay its regular bills and interest on loans.

Imagine checking if there's enough money to keep the lights on and pay the rent. This ratio helps understand a company's financial health by comparing its earnings to its fixed costs.

It's a handy tool for anyone wanting to see how well a business can handle its debts and other fixed expenses.

What is the Fixed-Charge Coverage Ratio?

The fixed-charge coverage ratio (FCCR) is a way to measure if a company can cover its regular expenses like rent, utilities, and loan payments with its earnings.

It's a useful tool for lenders to check how reliable a company is when it comes to paying its debts.

A high FCCR means the company is in good shape and can handle its fixed charges just with the money it makes. This ratio gives a quick view of a company's financial health.

How Fixed-Charge Coverage Ratio Works

The fixed-charge coverage ratio (FCCR) helps to figure out if a company can handle its regular costs.

To calculate it, the company's earnings before interest and taxes (EBIT) are divided by the total fixed charges.

Fixed charges include things like rent, utilities, and debt payments—basically, the stuff that needs to be paid no matter what. A higher FCCR means the company has enough earnings to cover these charges comfortably.

This ratio is useful for showing if a company is financially stable and can manage its debts without any trouble. It's a handy tool for lenders and investors to see the company’s ability to meet its financial obligations.

Importance of Fixed-Charge Coverage Ratio

Here are some of the key reasons why Fixed-Charge Coverage Ratio is important

1. Measures Financial Health

The Fixed-Charge Coverage Ratio shows if a company can handle its regular expenses with its earnings.

This helps determine if the company is financially stable. A higher ratio means the company is in good shape, making it easier to trust its ability to pay bills and debts.

2. Assists Lenders

Lenders use this ratio to decide if they should give a company a loan. A high Fixed-Charge Coverage Ratio means the company is more likely to pay back the loan without issues.

This helps lenders feel confident about lending money.

3. Helps Investors

Investors look at the Fixed-Charge Coverage Ratio to see if a company is worth investing in. A higher ratio means the company can manage its expenses and debts well, making it a safer investment.

This ratio gives a clear picture of the company's financial strength.

4. Guides Management Decisions

Company managers use this ratio to make smart financial decisions. It helps them understand if they can afford new expenses or need to cut costs.

This way, they can keep the company running smoothly and avoid financial problems.

5. Predicts Future Performance

The Fixed-Charge Coverage Ratio can give clues about a company's future. A consistent or improving ratio suggests the company will continue to do well.

This information is useful for anyone interested in the company's long-term success, including employees, investors, and partners.

Conclusion

Understanding the Fixed-Charge Coverage Ratio is essential for knowing how well a company can manage its regular costs and debts. This ratio helps lenders, investors, and managers make smart decisions. A high FCCR shows financial stability, making it easier to trust a company's ability to pay its bills. In short, this ratio paints a clear picture of a company's financial health.

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Calibration of Hull-White Two-Factor Interest Rate Model

The Hull-White one-factor (1F HW) interest rate model is a widely used model in finance for simulating the evolution of interest rates over time. It is based on a mean-reverting stochastic process where short-term interest rates revert to a long-term mean at a certain speed. The model incorporates two key parameters: the rate of mean reversion and the volatility of interest rate changes. One of the advantages of the Hull-White model is its flexibility, as it can fit the current term structure of interest rates, making it particularly useful for pricing interest rate derivatives like bonds, swaps, and options.

The Hull-White two-factor interest rate model (2F HW) is a generalization of the 1F HW model. In this model, the short rate incorporates two stochastic factors. Reference [1] presented methods for calibrating both the 1F and 2F HW models. Essentially, the calibration process for the 1F HW model proceeds as follows,

1. Interpolating the yield curve
2. Estimating the parameters using swaption pricing

As for the calibration of the 2F HW model, the author pointed out,

The 2F HW model aims at estimating short-term and long-term movements in interest rates. Similar to the 1F HW model, this second stage of the model, whereby it uses cap volatilities to price caps, is complex. Transforming these volatilities into accurate cap prices was difficult and was an important part of the model calibration. Furthermore, the calibrated parameters showed that not all parameters of the 2F HW model were statistically significant for this specific data; hence, the efficiency of the model depends on these parameters and the data used. The model might help researchers and practitioners gain higher accuracy by applying it to different datasets with the given calibration techniques. Nevertheless, the 2F HW model provides a dynamic picture of interest rates for different maturities, and thus it is useful.

In short, the calibration of the 2F HW model operates similarly to the 1F HW model, except that in the second step, cap prices obtained from the Black model are used instead of swaption prices.

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

References

[1] Vithanalage, W. C. Calibration of two factor Vasicek and Hull-White models with contemporary data, University of Calgary, 2024

Originally Published Here: Calibration of Hull-White Two-Factor Interest Rate Model

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External Audit: Definition, Responsibilities, Role, Purposes, Advantages, Disadvantages

An audit is a systematic and independent examination of financial statements, records, and operations of an organization to ensure accuracy, compliance, and reliability. While there are various types of audits, the one most commonly known is an external audit.

What is an External Audit?

An external audit is an independent review of a company's financial statements by an auditor not affiliated with the organization. The primary goal is to ensure that the financial records accurately reflect the company's financial position and are prepared by applicable accounting standards and regulations.

The external auditor's independence is crucial to ensure an unbiased examination of the company's financial health. After the audit, the auditor issues an opinion on whether the financial statements are free from significant errors or misstatements. This process validates the company's compliance with relevant laws and enhances the credibility of its financial disclosures.

How does an External Audit work?

An external audit starts with careful planning, where the auditor and company management agree on the audit's scope and objectives. The auditor reviews financial statements, internal controls, and past audit reports to tailor the audit approach to the company's risks. In the fieldwork phase, the auditor examines financial records, performs tests, and assesses internal controls to gather evidence on the accuracy and completeness of the financial statements.

Following the fieldwork, the auditor evaluates the collected evidence to determine if the financial statements are free from material misstatements and compliant with accounting standards. The audit concludes by issuing a report that includes the auditor's opinion on the financial statements. This report may highlight any discrepancies or issues found and, in some cases, offer recommendations for improving internal controls and accounting practices.

What are the advantages of an External Audit?

External audits provide significant benefits by enhancing the credibility of a company's financial statements. The independent verification by an external auditor increases trust among investors, creditors, and other stakeholders, ensuring that the financial reports accurately reflect the company's financial health. Its added credibility can facilitate better relationships with financial partners and investors.

Moreover, external audits help improve financial accuracy and compliance. The audit process identifies any weaknesses in internal controls or discrepancies in accounting practices, allowing the company to address these issues proactively. It ensures adherence to regulatory requirements and strengthens overall financial management, leading to more efficient operations and reduced risk of fraud or errors.

What are the disadvantages of an External Audit?

External audits, while beneficial, also come with certain disadvantages. One of the primary drawbacks is the cost involved. Audits can be expensive, particularly for smaller companies, due to the fees charged by auditors and the time required to complete the audit process. This financial burden can be significant, especially for businesses with tight budgets.

Additionally, external audits can be time-consuming and disruptive. The process requires substantial documentation and cooperation from company staff, which can interfere with regular business operations. Moreover, the audit might uncover issues requiring additional corrective actions, leading to further disruptions and potentially impacting the company's operations and financial stability.

Conclusion

External audit is when independent auditors examine a company's financial statements to determine whether they are true and fair. These auditors use auditing standards to structure the audit process. External audits can provide credibility to a company's financial statements, among other advantages. However, they might also have some disadvantages, as discussed above.

Article Source Here: External Audit: Definition, Responsibilities, Role, Purposes, Advantages, Disadvantages

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Beta Arbitrage Around Macroeconomic Announcements

The macroeconomic announcement premium refers to the phenomenon where financial markets, particularly stock and bond markets, experience higher-than-usual returns on days when significant macroeconomic announcements are made. The premium represents the additional returns investors may receive due to increased trading activity, market reactions, or adjustments to expectations following these announcements. Markets tend to experience greater volatility or price changes on these days as new information about the economy is revealed, influencing investor sentiment and asset prices.

Reference [1] studied the dynamics of high-beta stock returns around macroeconomic announcements. The authors pointed out,

Stocks in the top beta-decile earn an average excess return of −0.075% on days before announcements, 0.164% on announcement days, and −0.093% on days after announcements. More importantly, driven by high-beta stock returns, beta premium experiences a significant swing around the announcement.

The authors also designed a trading strategy based on these observations and investigated the reasons behind the abnormal return.

Since macroeconomic announcements are pre-scheduled, the above finding implies that a feasible long-short strategy of betting against beta (BAB) on days before and after announcements and betting on beta (BOB) on announcement days yields an annualized 25.28% return…

We examine alternative hypotheses for the variation of high-beta stock returns around macroeconomic announcements. Specifically, we find that the liquidity effect is only consistent with pre-announcement high-beta stock returns, whereas risk exhibits a consistent but rather weak pattern around the announcement. In comparison, trading volume exhibits consistent patterns as stock returns across beta portfolios around the announcements. Moreover, shifts in investor risk aversion have a significant explanatory power for the variation of beta return spread around the announcement. Nevertheless, our results show that changes in liquidity, risk, and investor risk appetite around the announcements at best partially account for variations in high-beta stock returns. The finding of our study highlights the dynamic effect of macroeconomic announcements on asset prices and adds further to the puzzle of the effect of macroeconomic announcements.

In short, a profitable trading strategy was developed to take advantage of the macroeconomic announcement premium. A partial explanation for the excess return is attributed to changes in liquidity, risk, and investor risk appetite around the announcements.

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

References

[1] Jingjing Chen, George J. Jiang, High-beta stock valuation around macroeconomic announcements, Financial Review. 2024;1–26.

Article Source Here: Beta Arbitrage Around Macroeconomic Announcements

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EBIT/EV Multiple: Definition, Calculation, Formula, Examples, Usage

When it comes to finance, understanding the right metrics can make all the difference. The EBIT/EV Multiple is one such crucial tool that helps to measure a company's performance.

For anyone curious about making smart investment choices or just wanting to understand a company's true value, this metric is super important.

Knowing about it can really open up new ways of looking at business success.

What is EBIT/EV Multiple?

The EBIT/EV multiple is a handy tool that investors and analysts use to figure out a company's value based on its earnings.

Think of it like a score that shows how much profit a company is making compared to its overall worth.

A higher EBIT/EV multiple is good news for investors, as it often means the company has less debt and more cash.

This metric is great for comparing different companies, even if they have different amounts of debt or pay different taxes. It's a quick way to see which companies might be better investments.

How EBIT/EV Multiple Works

The EBIT/EV multiple helps investors see how profitable a company is compared to its overall value.

Here's how it works - EBIT stands for Earnings Before Interest and Taxes, which is basically the profit a company makes from its operations before paying interest and taxes.

EV stands for Enterprise Value, which is the total value of the company including its debt and cash. By dividing EBIT by EV, investors get a ratio that shows how much profit a company makes for every dollar of its total value.

A higher ratio is usually better because it means the company is making good profits while having less debt.

This makes it easier for investors to compare different companies and figure out which ones might be better bets for their money.

Calculating EBIT/EV Multiple

Here is how to calculate EBIT/EV Multiple

EBIT/EV

To find EV here is the equation

Enterprise Value = Market Capitalization + Market Value of Debt – Cash and Cash Equivalent

Where,

Market Capitalization: Market Capitalization is the total value of a company’s shares of stock. It's like adding up the price of all the company’s shares to see what it’s worth.

Market Value of Debt: The Market Value of Debt is the total value of a company’s borrowed money. Think of it as the price tag on all the loans and debts the company owes.

Cash and Cash Equivalent: Cash and Cash Equivalent are the funds a company has on hand. It's basically the cash in your wallet plus any money that can quickly be turned into cash.

Benefits of EBIT/EV

Here are some of the key benefits of EBIT/EV

1. Helps Compare Companies: EBIT/EV makes it easy to compare companies, even if they have different debt levels. This way, investors can figure out which one is performing better.
2. Highlights Debt Levels: This metric shows how well a company is doing, even if it has debt. A higher EBIT/EV means the company is managing its debt well while making good profits.
3. Simplifies Investment Decisions: By providing a clear profitability ratio, EBIT/EV helps investors decide where to put their money. It offers a quick snapshot of which companies might be better investments.
4. Assesses Financial Health: EBIT/EV gives insight into a company’s financial health by comparing its profits to its total value. This helps investors understand if the company is in good shape.

Conclusion

Understanding the EBIT/EV multiple can make a big difference when evaluating companies. This simple metric helps investors see which companies are performing well and managing their debt effectively. It’s a quick way to compare companies and make smarter investment choices.

Originally Published Here: EBIT/EV Multiple: Definition, Calculation, Formula, Examples, Usage

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Pricing Convertible Bonds Using Monte Carlo Simulations

A convertible bond is a type of hybrid security that acts like a traditional bond but includes an option to convert the bond into a predetermined number of shares of the issuing company's stock. This feature offers investors the potential to benefit from rising stock prices while providing downside protection through regular interest payments and the return of principal upon maturity. Convertible bonds are attractive to companies as they typically pay lower interest rates than traditional bonds, making them a cost-effective way to raise capital.

Reference [1] examined the Chinese convertible bond market. The Chinese convertible bonds (CCB) have a special feature, which is a downward adjustment clause. Essentially, this clause states that when the underlying stock price remains below a pre-set level for a pre-defined number of days over the past consecutive trading days, issuers can lower the conversion price to make the conversion value higher and more attractive to investors. The authors utilized a Monte Carlo simulation approach to account for this feature and to price the convertible bond. They pointed out,

The downward adjustment provision poses a significant challenge in the pricing of CCBs. We treat the triggering of downward adjustment as a probabilistic event associated with the activation of the put option, ensuring compatibility within our pricing framework. Furthermore, we demonstrate that a unique solution exists when employing the Least Squares method to regress the continuation value at each exercise time…

In CCB research, the downward adjustment clause is often the most difficult to consider. Taking practical situations into account, in order to avoid financial distress upon put provision, bond issuers can use the downward adjustment clause to lower the conversion price. Therefore, we treat the downward adjustment clause as a probabilistic event triggering the put provision. In this way, we combine the downward adjustment clause with put provision in a simple manner.

Essentially, in this approach, the stock price is simulated, and the condition for the put provision is determined. When this condition is met, the downward adjustment works as follows,

• A probability of 0.8 is assumed for the adjustment to occur, and
• The conversion price is adjusted to the maximum of the average of the underlying stock prices over the previous 20 trading days and the last trading day.

This is another example of the versatility of the Monte Carlo approach.

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

References

[1] Yu Liu, Gongqiu Zhang, Valuation Model of Chinese Convertible Bonds Based on Monte Carlo Simulation, arXiv:2409.06496

Post Source Here: Pricing Convertible Bonds Using Monte Carlo Simulations

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Top-down Estimating: Definition, Techniques, Approaches, Advantages and Disadvantages, vs. Bottom-up Estimating

Companies may use various estimation methods for specific projects. One of the most prevalent ones is top-down estimating.

What is Top-down Estimating?

Top-down estimating is a project management technique that involves creating high-level estimates for a project's cost, duration, or effort. Instead of breaking down the project into individual tasks, estimates are based on an overall view of the project, often using historical data, analogies, or expert judgment. This method is faster but typically less accurate than detailed, task-specific estimating.

This approach is useful in the early stages of project planning when detailed information is not yet available or when quick estimates are needed. While it provides a broad overview, top-down estimating is often supplemented with more detailed methods as the project progresses to improve accuracy.

How does Top-down Estimating work?

Top-down estimating works by starting with a broad project overview and applying general estimates based on similar past projects, expert judgment, or industry standards. Instead of breaking the project into individual tasks or components, the estimator considers the entire project and makes a high-level prediction of the required resources, time, and costs.

The process typically begins by reviewing the project's scope and comparing it to previous projects with similar characteristics. Experienced project managers or subject matter experts may then use their knowledge to provide rough estimates. These estimates can be adjusted based on project complexity, known risks, and specific project goals.

What is the difference between Top-down and Bottom-up Estimating?

Top-down and bottom-up estimating are two project management estimation techniques that work inversely. The difference between the two comes from the following points.

Level of detail

Top-down estimating provides a high-level overview of the estimation. On the other hand, bottom-up estimating requires a detailed task-by-task analysis.

Accuracy

Top-down estimating can be accurate but is more general compared to the detailed approach taken by the bottom-up method. Therefore, the former might be less accurate comparatively.

Stage of use

Top-down estimating is more suitable during the early stages of the project management cycle. On the other hand, bottom-up estimating is best for detailed planning stages.

Estimation base

Top-down estimating uses historical information based on past projects or expert judgment. However, bottom-up estimating is based on a detailed analysis of individual tasks.

Complexity

Based on all the above differences, top-down estimating can be relatively straightforward. In contrast, bottom-up estimating is more detailed, which makes it more complex and thorough.

What are the advantages and disadvantages of Top-down Estimating?

Top-down estimating is advantageous for its speed and simplicity, making it ideal for the early stages of project planning when only a rough estimate is needed. It allows project managers to gauge the feasibility of a project and set initial budgets or timelines without needing detailed information. This method is also helpful when historical data or expert judgment is available, enabling quick comparisons with similar projects.

The primary disadvantage of top-down estimating is its lack of accuracy, as the estimates are based on broad assumptions and may overlook unique factors. It can lead to under- or overestimation of costs, time, or resources, potentially resulting in budget overruns, missed deadlines, or inadequate resource allocation. Moreover, because it doesn't involve a detailed analysis, it may miss critical tasks or risks, leading to unforeseen challenges as the project progresses.

Conclusion

Top-down estimating helps companies create estimates for specific projects with a high-level overview. Usually, companies utilize this approach during the early stages of a project. It can use various bases such as experience from past projects, industry standards, and expert judgment. Top-down estimating differs from bottom-up estimating based on the analysis provided above.

Originally Published Here: Top-down Estimating: Definition, Techniques, Approaches, Advantages and Disadvantages, vs. Bottom-up Estimating

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Trading VIX Futures Using Machine Learning Techniques

VIX futures are financial contracts that allow investors to trade on the expected future volatility of the S&P 500 Index, as measured by the VIX (Volatility Index). These contracts provide a way to hedge against or speculate on changes in market volatility. VIX futures are popular in times of uncertainty, as they tend to increase in value when market volatility spikes, making them useful for managing risk or profiting from volatile market conditions.

Reference [1] proposed using Constant Maturity Futures (CMF) to generate trading signals for VIX futures. It applied seven machine learning models to create these signals. The authors pointed out,

The experiment results indicate that VIX CMFs term structure features, specifically, μt and ∆roll, are highly effective in predicting the next-day returns of VIX CMFs and could potentially yield significant economic benefits. However, statistically derived features possess comparatively less predictive ability. Additionally, the C-MVO strategy shows overall superior backtesting performance across most machine learning models compared to the benchmark rank-based long-short strategy, providing valuable insights and practical implications for the formulation of trading strategies involving VIX CMFs and proving that numerically predicted returns can better guide trading strategies. Finally, evaluations of the machine learning models revealed that within the neural-network-based models, ALSTM exhibited the best performance in both predictive and backtesting assessments. No single tree-based model demonstrated clear superiority. More importantly, the linear regression model, which considers only linear relationships, outperforms all other models, thereby affirming the substantial ability of term structure features in predicting the next-day returns of VIX CMFs.

In short, the authors successfully developed timing strategies by leveraging CMF data and machine learning techniques, with promising results.

We note that this research integrates data science techniques with domain-specific knowledge, and we believe that this combination offers a higher chance of success than using data science methods alone.

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

References

[1] Wang S, Li K, Liu Y, Chen Y, Tang X (2024), VIX constant maturity futures trading strategy: A walk-forward machine learning study, PLoS ONE 19(4): e0302289.

Article Source Here: Trading VIX Futures Using Machine Learning Techniques

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Negotiable Certificate of Deposit: Definition, Example, Meaning, Characteristics, Advantages, Disadvantages

Understanding financial tools can be a game-changer, and one such tool is the Negotiable Certificate of Deposit (NCD).

It's important because it plays a key role in managing money and investments, which can impact the financial future.

NCDs can be a smart way to grow savings over time, making them a valuable option for anyone looking to boost their financial health.

What is a Negotiable Certificate of Deposit (NCD)?

Negotiable Certificates of Deposit (NCDs) are a type of certificate of deposit (CDs) that starts at a minimum of $100,000. Banks guarantee these CDs, but they can't be cashed out until they reach their maturity date.

However, they can often be sold in secondary markets, which are usually quite liquid. Similar to the U.S.

Treasury bills and NCDs are seen as low-risk investments with lower interest rates. They offer a secure way to save and earn a bit of interest, making them a safe choice for investors.

How Negotiable Certificate of Deposit Works

Let's understand how NCDs work - an investor buys an NCD from a bank, starting at $100,000.

The bank then holds onto the money for a set period, called the maturity date, which could be a few months or several years.

During this time, the bank pays interest on the deposit. If the investor needs their money before the maturity date, they can't just take it out.

Instead, they can sell the NCD in a secondary market, where other investors might buy it.

This makes NCDs quite handy because they offer both security and the option to sell if needed. Overall, NCDs provide a safe way to earn interest while also having the flexibility to sell if circumstances change.

Advantages of Negotiable Certificate of Deposit

Here are some of the key advantages of NCDs

1. Low Risk: NCDs are backed by banks, making them much safer compared to many other investment options. Investors can feel more secure knowing their money is in a low-risk vehicle.
2. Interest Earnings: Even though the interest rates might be lower, NCDs still provide a way to earn some returns on the invested money. This is better than letting money sit idle without any growth.
3. Liquidity: One of the coolest things about NCDs is that they can be sold in secondary markets. This means investors have the flexibility to get their money back before the maturity date if needed.
4. Fixed Terms: NCDs come with set terms, so investors know exactly how long their money will be tied up. This makes financial planning easier, as there's no guessing involved about when the funds will be available.
5. Diverse Maturity Dates: NCDs offer a range of maturity dates, from a few months to several years. This variety allows investors to choose a term that best fits their financial goals and needs.
6. Predictable Returns: With NCDs, the interest rate is fixed, meaning investors know exactly how much they'll earn by the end of the term. This predictability makes managing finances more straightforward.

Disadvantages of Negotiable Certificate of Deposit

Here are some of the key disadvantages of NCDs that everyone should be aware of

1. High Minimum Investment: NCDs require a minimum investment of $100,000, which can be a big issue for many people who don't have that much money available to invest.
2. Lower Interest Rates: Compared to other investment options, NCDs often offer lower interest rates. This means the returns might not be as high as those from more aggressive investments.
3. Early Redemption Limitation: Investors cannot cash out their NCDs before the maturity date. This lack of flexibility can be a drawback for those who might need access to their funds unexpectedly.
4. Market Risk: Although NCDs can be sold in secondary markets, their value can fluctuate. This means there is always a risk that they might sell for less than the initial investment.

Conclusion

Negotiable Certificates of Deposit (NCDs) offer a secure way to invest large sums of money with the backing of banks. They provide low-risk and predictable returns - however, they come with high minimum investments and lower interest rates. Overall, NCDs are a solid option for those looking to grow their savings safely while having the option to liquidate if needed.

Originally Published Here: Negotiable Certificate of Deposit: Definition, Example, Meaning, Characteristics, Advantages, Disadvantages

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Enhancing Volatility Portfolio Returns with VRP Timing

The volatility risk premium (VRP) refers to the compensation investors receive for bearing the risk of higher-than-expected market volatility, often manifesting as the difference between implied and realized volatility in options markets. The VRP is not constant; it changes according to the market regime.

Reference [1] proposed a timing scheme based on the idea that an increase in market volatility is typically associated with a statistically significant decrease in the conditional one-month VRP. It utilizes the inverse of realized volatility, the VIX, and GARCH(1,1) volatility to determine position sizes for volatility portfolios. These portfolios include variance swaps, VIX futures, and S&P 500 straddles. The authors pointed out,

We develop timing strategies for the VRP that are analogous to equity premium timing strategies based on realized volatility, as in Moreira and Muir (2017). These strategies involve trading two assets: a variance asset and a risk-free asset. To begin, we examine a benchmark portfolio with a fixed weight on the variance asset each month. While this simple strategy already delivers remarkable long-term returns, we show that the portfolio’s performance can be significantly enhanced by incorporating various timing factors, including several volatility measures and an ex-ante VRP measure. We find the simple volatility-managed strategies are particularly effective and robust. Our findings remain robust in both older and recent times and across three variance assets: variance swaps, VIX futures, and S&P 500 straddles. Our findings are unlikely affected by bid-ask spreads and hold after accounting for margin requirements.

Our portfolios improve performance by reducing negative exposure to the variance assets once observing an increase in volatility. Essentially, we exploit the puzzle of the negative volatility-VRP relationship, which has been highlighted in several previous studies such as Cheng (2019). Notably, we find that, ex-post, various timing portfolios generate positive alpha and help reduce beta/exposure to constant-weight variance asset portfolio returns almost only during high-volatility regimes, not in low-volatility regimes…

In short, using realized volatility, the VIX, and GARCH(1,1) improves the risk-adjusted returns of volatility portfolios.

A counterintuitive argument used in this research is that when volatility is high, the VRP decreases. One would assume that when volatility increases, investors would increase the size of a short volatility position.

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

References

[1] Aoxiang Yang, Volatility-Managed Volatility Trading, 2024, papers.ssrn.com/sol3/papers.cfm?abstract_id=4761614

Originally Published Here: Enhancing Volatility Portfolio Returns with VRP Timing

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Step Allocation (Step-Down) Method: Definition, Meaning, Examples, Advantages, Disadvantages

Some departments within a company only exist to serve other departments. When allocating the costs incurred at these departments, companies must consider various factors. A technique that can help achieve that is the step allocation method.

What is the Step Allocation Method?

The step allocation method, or the step-down method, is a cost allocation technique that distributes service department sequentially costs to production departments. This method ranks service departments based on service provided to other departments and allocates their costs accordingly.

Unlike the direct method, which only allocates service department costs to production departments, the step method allows for partial allocation to other service departments. This process continues until all service department costs have been distributed to the production departments, reflecting a more accurate picture of interdepartmental services.

How does the Step Allocation Method work?

The step allocation method allocates service department costs to production departments in a hierarchical and sequential order. First, service departments are ranked based on the amount of service they provide to others. The highest-ranked service department's costs are then allocated to all other departments, including both service and production departments, using an appropriate allocation base.

Next, the method moves to the next ranked service department, allocating its total costs, which include costs received from the previously allocated department. This sequence continues until all service department costs are fully allocated to the production departments. By considering interdepartmental services, the step allocation method provides a more accurate distribution of costs, leading to better cost control and informed decision-making within the organization.

What are the advantages of the Step Allocation Method?

The step allocation method offers enhanced accuracy in cost allocation by recognizing the interdepartmental services provided among service departments. This sequential approach, starting with the department that provides the most services, ensures costs are allocated more precisely based on actual usage. This method's attention to detail allows organizations to reflect the true costs incurred by each department better, leading to more accurate financial reporting and insights.

Additionally, the step allocation method supports better decision-making and cost control. By providing a clearer understanding of cost structures, managers can identify inefficiencies and areas for potential savings. The fair and equitable distribution of costs also ensures that each department bears a realistic share of expenses, fostering a more accurate reflection of organizational dynamics and supporting more informed budgeting and performance evaluations.

What are the disadvantages of the Step Allocation Method?

The step allocation method's complexity and detailed data requirements make it a time-consuming process. Gathering and maintaining extensive data on interdepartmental services is labour-intensive, and the sequential allocation process can be challenging to implement compared to other methods. Additionally, the method introduces potential biases, as ranking service departments and selecting allocation bases can involve subjective decisions.

Moreover, the method has limitations in handling reciprocal services, as once a service department's costs are allocated, it does not receive further allocations from other departments. This one-way allocation can reduce the accuracy in situations with significant interdepartmental services. Implementing the step allocation method also requires specialized knowledge and advanced accounting systems, which can be a barrier for organizations lacking the necessary expertise and resources.

Conclusion

The step allocation method allows companies to distribute costs for service departments to production departments. This method establishes rankings for each service and allocates its costs sequentially. Thereby, it helps companies include the expenses incurred in service departments as a part of their decision-making. However, it may have some disadvantages as well.

Post Source Here: Step Allocation (Step-Down) Method: Definition, Meaning, Examples, Advantages, Disadvantages

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Using Hurst Exponent to Time the Market

The Hurst exponent is a statistical measure used to evaluate the long-term memory or autocorrelation of a time series, indicating whether a system exhibits trending behavior, mean-reverting characteristics, or randomness. A Hurst exponent greater than 0.5 signifies the existence of long-range dependence, implying that previous trends are prone to persisting into subsequent periods. Conversely, a Hurst exponent below 0.5 indicates mean-reverting behavior, where trends are likely to reverse, and an exponent near 0.5 suggests a random walk with no discernible trend.

Reference [1] proposed using the Hurst exponent to time the market. Specifically, the authors calculated the moving Hurst exponent for rolling windows of 100 and 150 days. The timing signals are generated as follows,

• If (H₁₀₀ − H₁₅₀)n > 0 and (H₁₀₀ − H₁₅₀)n+1 < 0, then the signal is BUY.
• If (H₁₀₀ − H₁₅₀)n < 0 and (H₁₀₀ − H₁₅₀)n+1 > 0, then the signal is SELL.

The authors pointed out,

The results of our study suggest that the Moving Hurst (MH) indicator offers a valuable approach to forecasting and managing volatility in Indian equity markets. Our analysis shows that MH provides a more effective means of capturing profitable trading opportunities compared to traditional indicators like Moving Averages (MA). It also shows how MH is a less lagging indicator than MA. For not consecutive buy/sell signals, an argument is made that for a current buy/sell, there might be a sell/buy indicator in the past or the future which was not included in the moving window frame. By incorporating the principles of chaos theory and fractal analysis, this new indicator presents a unique perspective for market analysis. Our analysis shows that MH provides a more effective means of capturing profitable trading opportunities compared to traditional indicators like Moving Averages(MA). By incorporating the principles of chaos theory and fractal analysis, this new indicator presents a unique perspective for market analysis.

In short, using the Hurst exponent as a timing indicator proved to be effective. We note that the research was conducted in the Indian stock market. However, it can be readily applied to any stock market.

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

References

[1] Shah, Param, Ankush Raje, and Jigarkumar Shah, Patterns in the Chaos: The Moving Hurst Indicator and Its Role in Indian Market Volatility. Journal of Risk and Financial Management 17: 390, 2024

Originally Published Here: Using Hurst Exponent to Time the Market

source https://harbourfronts.com/using-hurst-exponent-time-market/

Marketable Securities: Definition, Examples, Meaning, Characteristics, Types

Marketable securities play a crucial role in the financial world by offering an easy way to manage and grow money.

They're very helpful for businesses and individuals looking to keep their funds flexible and accessible.

Plus, they can be a solid safety net during unexpected situations. Understanding their importance can help in making smarter financial decisions, whether it's for saving, investing, or managing cash flow.

What are Marketable Securities?

Marketable securities are like financial tools that individuals and businesses use to keep their money flexible and easy to access.

Common examples include stocks, bonds, preferred shares, and ETFs. There are also money market instruments, futures, options, and hedge fund investments that can be marketable securities.

The big thing about these securities is that they are super easy to buy or sell, making them very liquid. However, not all liquid assets are marketable securities, and not all marketable securities are liquid.

Regardless, every marketable security needs to meet the criteria of being a financial security. Understanding these can help in managing money better, whether it's for saving, investing, or handling cash flow.

How Marketable Securities Work

Marketable securities are essential because they offer a quick way to turn investments into cash. They work like a financial safety net, helping businesses and individuals manage their money easily.

These securities can be bought and sold quickly, making them super handy for covering unexpected expenses or taking advantage of new opportunities.

They also help in diversifying investments and spreading risk.

In simple words, marketable securities provide flexibility, accessibility, and liquidity to a financial portfolio. So, the more marketable securities there are in a portfolio, the easier it may be to manage and grow the money.

Different Types of Marketable Securities

As mentioned above, there are various types of marketable securities. Some of the common ones include:

1. Stocks

Stocks are basically owning a small piece of a company. When the company does well, the value of the stocks can go up, and sometimes they even pay out a bit of money called dividends.

They’re a popular choice for people wanting to grow their money.

2. Bonds

Bonds are like lending money to a company or the government. In return, they promise to pay back the money plus some extra, called interest. They’re usually less risky than stocks and can be a good way to earn steady returns.

3. Preferred Shares

Preferred shares are a mix between stocks and bonds. They pay regular dividends like bonds but can also increase in value like stocks.

They usually have priority over common stocks when it comes to dividend payments and asset distribution if the company goes bankrupt.

4. ETFs

ETFs, or Exchange-Traded Funds, are like a collection of stocks or bonds bundled together. They can be bought and sold on the stock market just like individual stocks.

They’re great for spreading out risk because they include a variety of investments in one package.

Conclusion

Marketable securities are an essential part of managing money smartly. They offer flexibility, easy access to cash, and investment opportunities. Whether it's for saving, investing, or handling unexpected expenses, marketable securities play a key role in financial planning. By learning how they work, it will be easier to make informed decisions.

Originally Published Here: Marketable Securities: Definition, Examples, Meaning, Characteristics, Types

source https://harbourfronts.com/marketable-securities/

Predicting Intraday and Daily Volumes Using ARIMA Model

Volume is an essential, integral market data. However, it receives much less attention in research literature compared to price data. Understanding and being able to model volume dynamics is important because buy-side firms must plan and time their trades to avoid significantly impacting the market, revealing their identities, and incurring excessive transaction costs. Sell-side institutions require knowledge of trading volume to make markets efficiently and need accurate forecasts to implement strategies related to volume, such as those that track some form of volume-weighted average price (VWAP).

Reference [1] studied the dynamics of intraday and daily volume data. The authors pointed out,

In this analysis, we focus on maximizing predictive power of time-series models in forecasting the intraday and daily trading volume of SPY according to the metrics MSE, MAPE, and VWAP error. Our intraday analysis indicates that using SARIMAX with the exogenous variables average directional index, exponential moving average, and momentum give us the optimal forecast, outperforming SARIMA and a spectral representation of the data using m = 3 Fourier frequencies. However, all three models significantly outperform our naïve baselines with respect to tracking VWAP. However, when performing our analysis of daily volume data, we see a lack of seasonality. This is confirmed by R choosing ARIMA and ARIMAX models over SARIMA and SARIMAX models during cross validation. Also, a higher m value of 40 for the FDPR model is optimal. But using exogenous variables with ARIMAX still gives the best predictions for daily data. Overall, we have shown that trading volume can be accurately predicted using ARIMA models with exogenous variables and adding seasonal components when necessary.

In short, the author demonstrated that volume can be predicted with reasonable accuracy using the ARIMA model.

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

References

[1] A Krishnan, M Pollack, A Cooper, Unraveling the Dynamics of SPY Trading Volumes: A Comprehensive Analysis of Daily and Intraday Liquidity Trends, arXiv preprint arXiv:2406.17198, 2024

Originally Published Here: Predicting Intraday and Daily Volumes Using ARIMA Model

source https://harbourfronts.com/predicting-intraday-daily-volumes-using-arima-model/