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.

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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.

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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

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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

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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

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