What is an Angel Investor?

Companies need capital to operate and carry out their business. For established companies, raising finance is not an issue. Usually, these companies have sufficient funds and reserves to continue their business. For startups, the same does not apply. These companies need capital to take off. However, most traditional investors do not trust these companies with their money.

Startups usually have limited options when it comes to raising capital. Even when they have investors, they can only get little funds. However, there are other investors that can provide these companies with sufficient funds to carry out their business. One of these investors includes angel investors.

What is an Angel Investor?

Angel investors are affluent individuals that provide capital to startups or small companies. Usually, these investors provide more finance than normal investors. In exchange for their investment, they receive part ownership of the company. However, owning the company's shares isn't the primary goal for angels. Instead, these investors invest in startups that have the potential to provide them with high returns in the future.

Angel investors can be significantly crucial for startups. At the stage these companies are at, most investors do not provide them with finance. However, angel investors do not have the same objectives as those investors. In contrast, angel investors have long-term goals in mind. For that reason, they provide startups with finance for a longer time.

Usually, angel investors include wealthy investors that are affluent enough to invest in startups. These investors carry out their due diligence before choosing a startup in which they can put capital. Most startups also compete to gain their attention. Therefore, acquiring funds through these investors may be challenging. The finance that angel investors provide may vary. However, it is sufficient enough to get most startups going.

How do Angel Investors work?

Angel investors may include full- or part-time investors. Usually, these individuals identify companies that have significant potential. Based on their assessment, they select a company and invest their funds in it. In exchange, they get an ownership stake in the company. In some cases, they may also receive debt instruments. Based on their position, angel investors can also play a role in a company's management or provide advice on critical matters.

Angel investors are not temporary or short-term investors. These investors may provide finance to companies for up to seven years or even more. During this period, they remain the owner of the company to which they provide finance. If the company has progressed during this time, the value of the investment angel investors provided can grow substantially. After this period, angel investors sell their investments or go public with the company to reap the rewards.

What is the difference between Angel Investors and Venture Capitalists?

People often confuse angel investors with venture capitalists. While both of them have similar characteristics, they are also different. Both of these include investors that provide companies with capital in exchange for ownership. However, angel investors are usually private investors that invest their own money in a startup. Venture capitalists are professional investors and put other people's money into startups.

Similarly, angel investors usually provide fewer funds compared to venture capitalists. However, they are also more lenient and patient with startups. Angel investors are also less intrusive when it comes to the company's management. They usually take a passive approach when it comes to involvement in the company's operations. Venture capitalists, however, are more hands-on.

Conclusion

Angel investors are investors who provide startups with capital. Usually, they are wealthy individuals that seek investments in high-potential startups. In exchange for their finance, they receive ownership of the company. After a long time, usually between five to seven years, angel investors sell their ownership to get the rewards for their investment.

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Why is Econometrics Important in Business?

Econometrics has been an area of high interest within the economics world. While the concept comes from the early- to mid-1900s, it has developed rapidly over the last few decades. Econometrics primarily applies to the world of economics. However, it has also contributed a lot to the business world. Before understanding why econometrics is important in business, it is crucial to know the concept itself.

What is Econometrics?

The term econometrics comes from the work of Ragnar Frisch. He was one of the founding fathers of the Econometrics Society, which aimed to unify the theoretical-quantitative and empirical-quantitative approaches to economic problems. There were three primary aspects of the quantitative approach that he sought to unify as econometrics. These include mathematics, statistics, and economic theory.

Through the above history, it is possible to define econometrics. Econometrics is the field of study within economics that applies mathematical and statistical models to economic data. Simply put, it relates to the quantification of economic theories. Since its invention, the field of econometrics has experienced many changes. One of these includes the various subdivisions within it. These primarily include econometric theory or applied econometrics.

There are several models within econometrics that analysts can use. These models may be linear, multi-variable, nonparametric, or nonlinear. The most commonly used ones include regression analysis, statistical inferences, probability, correlation analysis, etc. Econometrics provides analysts with the necessary information to use in these models and further process it for forecasting needs.

Why is Econometrics important in business?

Econometrics has traditionally only had application in economics. However, most businesses have realized its importance and started it using in their financial systems. Econometrics takes a different approach to other methods that firms have used, such as statistics. It allows businesses to develop models, which they can customize to their needs.

There are several reasons why econometrics can play an important role in businesses. Some of these are as follows.

Forecasting for the future

Econometrics allows businesses to analyze future events and make forecasts. This application can be helpful when they plan to make changes or build new strategies. Firms can use time series forecasting and econometrics modeling to gauge the effectiveness of their plans.

Analyzing customer behaviour

Customer behaviour can change from time to time. For most businesses, keeping track and predicting behavioural changes is highly crucial. Through econometrics, these businesses can model customer choices and preferences based on several variables. Using those models, they can make the right decisions and develop strategies accordingly.

Identifying risks and predicting economic outcomes

Econometrics can also help businesses model their risks and predict economic outcomes. In most cases, doing so is highly challenging. Firms can use various econometrics models to mitigate their risks and predict economic outcomes. By doing so, they can increase their profitability and reduce costs.

Help with resource allocation

An area that is highly critical within businesses is resources allocation. Econometrics can help firms forecast their activity for the future. Based on that forecast, those firms can then allocate their resources. Through this, econometrics can help businesses efficiently run their operations and minimize wastage.

Conclusion

Econometrics is the application of statistical and mathematical methods in economics. Through econometrics, analysts can test and develop economic theories. Similarly, it has an application for businesses in several ways. These may include forecasting for the future, analyzing customer behaviour, identifying risks and predicting economic outcomes, and helping with resource allocation.

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Is Private Equity an Alternative Investment?

Investors have many options when it comes to building a diversified portfolio. These options may include stocks, bonds, cash, etc. However, some investors may go beyond these options to maximize their returns or for diversification. These may include options such as private equity, private debt, real estate, etc. These constitute types of alternative investments.

What is an Alternative Investment?

The term alternative investment signifies an investment that does not fit in the same category as other conventional investments. Usually, when investors think of investing, they consider stocks, bonds, or cash. However, many other investment categories do not fall in the same group. As mentioned, these may include venture capitals, commodities, private equity, etc.

Alternative investments provide investors with an opportunity to diversify their portfolios beyond conventional investments. However, they come with some downsides, such as lower returns and liquidity. However, some categories of alternative investments may also provide high rewards while bearing higher risks. Investors must consider all these factors before choosing alternative investments.

One reason why investors may prefer investing in alternative investments is the low correlation with other investments. Most alternative investments do not behave similarly to conventional assets. Therefore, they provide better diversification for investors. Despite that, investors may have to bear some risks due to the lower demand for these investments.

What is Private Equity?

Private equity is a type of investment class that involves investing in unlisted companies. In other words, these include stocks from companies that do not trade on the stock market. Private equity usually includes companies in which investors can invest. However, finding such investments may be challenging due to the absence of a proper market for them.

Private equity may also involve investing in private equity funds. These funds, managed by private equity firms, allow investors to invest in private equity. In exchange, they charge investors with management and performance fees. There are further classifications of private equity, such as venture capital, leveraged buyouts, real estate private equity, etc. These provide investors with more options when seeking private equity investments.

Unlike other investments, casual investors may not have access to private equity. Usually, these investments are limited to institutional or accredited investors. Most private equity firms collect money from these investors and invest it in different private companies. Due to the higher risks involved, these investments are not available for most investors.

Is Private Equity an Alternative Investment?

As stated above, alternative investments include investments that do not fall in conventional investment categories. Private equity, meeting this definition, also constitutes an alternative investment for investors. Apart from these, several other characteristics emphasize why private equity is an alternative investment.

Private equity has a low correlation with conventional investments. Similarly, they usually have lower liquidity compared to other equity investments. Due to the absence of a primary market, determining the value of a private equity investment is challenging. Investors also have to bear high transaction costs on these investments. These are all characteristics that illustrate that private equity is an alternative investment.

Conclusion

Most investors prefer investing in conventional investment categories. However, some may also invest in alternative investments. These are investments that do not fall under the above categories. Private equity includes investing in companies that are not listed publicly. Private equity meets all the features of alternative investment.

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What is the Difference Between Statistics and Econometrics?

Econometrics and statistics have common overlapping areas that some people may find confusing. While both of these fields deal with statistics and the relationship between data, they are different. Before learning how these two differ from each other, it is crucial to understand what they are.

What is Econometrics?

The term econometrics is a combination of two words, "econ" and "metrics". "Econ" refers to economics, social science that studies the production, distribution, and consumption of goods and services. "Metrics" means a system or standard of measurement. Econometrics is a field within economics that involves the quantification of economic data.

Econometrics uses statistical and mathematical models to analyze economic theories. This process has a crucial application within economics. Similarly, through econometrics, analysts can test and develop economic theories. They can also use the information in predictive modeling. For example, analysts can create time series models using the application of econometrics.

Econometrics includes three primary areas. These include mathematics, statistics, and economic theory. However, econometrics is not the same as mathematical science, economic statistics, or general economic theory. Instead, it combines all of these to help analysts understand the quantitative relations in modern economic life.

What is Statistics?

Statistics is a much broader concept compared to econometrics. It is the branch of applied mathematics that involves collecting, reviewing, analyzing, and inferring conclusions from quantitative data. The application of statistics is prevalent in almost every field, particularly scientific. This field generally focuses on two areas, uncertainty and variation.

The primary objective of applying statistics is to draw a conclusion about a large number of events based on observable characteristics of small samples. There are two significant areas within statistics, known as descriptive and inferential statistics. Descriptive statistics involves describing the properties and sample and population data. Inferential statistics, on the other hand, deals with testing theories and reaching conclusions.

There are several tools within statistics that statisticians use. These may include variance, skewness, kurtosis, analysis of variance, null hypothesis testing, etc. Some of these tools may also have application in econometrics, such as regression analysis. Apart from other fields, economists also use statistics to collect, review and analyze data. Based on this information, they can draw conclusions, which is also a part of statistics.

What is the difference between Statistics and Econometrics?

The difference between statistics and econometrics comes from their fundamental areas of study. Statistics primarily relates to applied mathematics. Econometrics, on the other hand, is a part of economics. On top of that, statistics covers a significantly large area of study. While econometrics also includes statistics, it is not as broad.

Econometrics depends on statistics and statistical models to work. However, it doesn't only include these. It also consists of mathematics and economic theory, both of which are a fundamental part of it. The statistics used in econometrics only involves a particular area of the field. On top of that, econometrics includes other areas, such as causal inference and time series. These areas, while included in statistics, are not as prominent in the field.

Conclusion

Econometrics is a field within economics that depends on statistics and statistical models. However, it is different from statistics. Econometrics also includes other areas, such as mathematics and economic theory. Statistics is a field that consists of collecting, reviewing, analyzing, and inferring a conclusion from quantitative data.

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What is an Infrastructure Fund

The term infrastructure signifies basic physical systems that may be for a market, economy, or region. It may include water and sewer services, shipping, waste management, utilities, electric systems, etc. Due to the high cost involved in it, infrastructure systems are capital intensive. It also represents an asset class. For investors, infrastructure also provides a unique investment opportunity in the form of infrastructure funds.

What is an Infrastructure Fund?

An infrastructure fund is a type of fund that invests in public assets and services. In other words, these funds primarily include infrastructure investments. As mentioned, these may include systems such as water and sewage services, waste management, electric and utility services, oil and gas pipelines, etc. Usually, these infrastructures are part of a company. Therefore, infrastructure funds invest in companies that include these infrastructures.

As stated above, infrastructure represents an asset class. Therefore, it can be a viable option for investors looking to build a diversified portfolio. Through infrastructure funds, investors get the opportunity to do so. On top of that, these funds include a mix of infrastructure investments, which further helps investors with their goals.

In stock markets, infrastructure companies form a part of a different sector. Infrastructure funds seek to invest in this sector. Unlike other sectors, this sector presents a more stable investment opportunity to investors. The primary reason for it is that it involves investing in companies that provide products or services required for daily living.

What are the advantages of investing in an Infrastructure Fund?

Infrastructure funds provide investors with various advantages. One of the primary advantages includes the stability that the underlying investments offer. The demand for products or services provided by these companies usually remains constant throughout different economic periods. Therefore, they provide stable income compared to other sectors, such as banking, technology, automobile, etc.

Another advantage of infrastructure funds for investors is the diversification they provide. These funds allow investors to invest in a different asset class, which can be highly valuable. Infrastructure funds also offer more safety against market volatility. Therefore, investors have to suffer lower losses due to uncertainty.

The underlying companies in the funds generate constant cashflows throughout the year. It is due to the nature of infrastructures. Therefore, investors can get a stable income from these funds. On top of that, the capital-intensive nature of the sector also allows companies to dominate the market. Therefore, investors can get almost guaranteed income from these funds.

What are the disadvantages of investing in an Infrastructure Fund?

Infrastructure funds also come with some disadvantages. Due to their stable nature, infrastructure companies may not generate the best returns for investors. Usually, these companies perform well in the market. Compared to other sectors, however, the returns are lower. For investors, the decision to invest in these funds will linger on whether they want stability or higher returns.

Furthermore, infrastructure funds are not a viable option for investors looking for capital gains or growth investing. In contrast, these funds are more suited to dividend investors. However, that also implies that investors will get lower returns on these investments. Overall, these funds can provide lower returns to investors compared to other options.

Conclusion

Infrastructure funds involve investments in the infrastructure sector. These funds provide investors with the opportunity to diversify their portfolios while also getting stable income. Generally, investing in infrastructure funds involves lower risks. However, they can also hinder the returns that investors can expect from their investments.

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Are Econometric Models Useful in Trading?

We have previously presented time series analysis for identifying autocorrelation properties of stock indices and econometric techniques such as ARIMA and GARCH for estimating volatilities. We also highlighted an article [1] that demonstrated the usefulness of advanced volatility estimators in trading by reducing trading strategies’ turnover.

On the same topic, Reference [2] attempted to directly incorporate econometric models into existing trading systems. Specifically, it utilized three econometric models to forecast SPY prices: (i) Auto Regressive Integrated Moving Average (ARIMA), (ii) Generalized Auto Regressive Conditional Heteroskedasticity (GARCH), and (iii) Vector Autoregression (VAR). It then integrated these models into existing trading strategies that use two technical indicators, Bollinger Bands and Moving Average Convergence Divergence (MACD).

However, unlike Reference [1], the authors concluded that incorporating these econometric models did not improve the trading strategies’ performance.

In this paper, we consider linear process models using the VIX Index as a proxy for market sentiment, to predict the movement of the SPY ETF prices. The coefficients on the SPY lags of the ARIMA(2,1,1) model turn out to be statistically insignificant with the addition of the VIX Index, even though this particular model performs better out-of-sample than the ARIMA(2,1,1) model without the VIX Index. Furthermore, the one-step forward forecasts generated by a VAR(1) model performs better than an ARIMA(2,1,1) model. However, in the context of algorithmic trading strategy, it counters the many signals generated by Bollinger Bands and MACD. The one-step forward GARCH(1,1) volatilities do not help in the context of algorithmic trading strategies either, perhaps because of the limited predictive capability of the VAR(1) model.

In summary, the 2 articles’ results are contradictory.

So what do you think? Are econometric models useful in trading or not?

References

[1]  Baltas, Nick and Kosowski, Robert, Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations. "Market Momentum: Theory and Practice", Wiley, 2020

[2] YM Kobara, C Pehlivanoglu, OJ Okigbo, A Linear Process Approach to Short-term Trading Using the VIX Index as a Sentiment Indicator, Preprints 2021, 2021070673

Article Source Here: Are Econometric Models Useful in Trading?

Performance-Based Fees of Investment Advisors

Investing in the stock market has become highly accessible to all investors around the globe. However, the role of investment advisors remains crucial in the process. These individuals can provide significant value to investors when it comes to their portfolios. In exchange for their services, they require compensation. Before understanding their fees, it is crucial to understand who investment advisors are.

Who are Investment Advisors?

Investment advisors, also known as stockbrokers, are individuals or firms that provide guidance related to investing to their clients. They usually give recommendations related to where investors should invest their capital. Investment advisors conduct detailed analyses based on which they provide those recommendations. As mentioned, for these services, they charge their clients a fee.

Investment advisors may have many clients to whom they provide their services. They have a fiduciary duty toward their clients, meaning that they always act in the best interest of their clients. Some investment advisors may also be registered, which will increase their regulatory duties. Usually, these advisors charge their clients a management fee. In some cases, they may also require a performance-based fee.

What are the Performance-Based Fees of Investment Advisors?

As mentioned, investment advisors identify the best investments and recommend them to clients. Some advisors may charge their clients based on how their recommended investments perform. These charges usually come in the form of a percentage of the returns their clients get. Therefore, the more returns an investment recommended by these advisors generates, the more they earn.

Performance-based fees of investments advisors are not as prevalent. In some jurisdictions, these advisors may not be allowed to charge their clients a performance-based fee. More specifically, registered investment advisors cannot require these fees due to mandatory prohibitions. However, these requirements may differ from one jurisdiction to another.

For investment advisors prohibited from charging such fees, a management fee may be prevalent. In those cases, they may charge a management fee based on the overall size of the portfolio they manage for a client. Some investment advisors also charge a management fee, which differs from the above two forms of compensation. Lastly, some advisors may also have a flat fee system, which is the least common type of fee charged.

What are the advantages and disadvantages of Performance-Based Fees of Investment Advisors?

There are several advantages that charging performance-based fees provides to investment advisors. The most crucial of these is that performance-based fees encourage advisors to offer the best value to their clients. As their income depends on their recommendations to clients, investments advisors must identify the best investments to earn more.

However, it may also come with some limitations. For clients, the primary disadvantage is that investment advisors may take more risks to earn more. In some cases, the clients may not agree with high-risk investments. While it may provide high returns for clients, it can also result in significant losses, which the clients may not be willing to bear.

Conclusion

Investment advisors provide clients with advice regarding their investments. They charge a fee in exchange for these services, which may be performance-based. Performance-based fees relate to how much returns any investments recommended by advisors generated. In some jurisdictions, charging clients such fees may be prohibited. In those cases, investments advisors may charge a management fee or flat fee.

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The Fundamental Law of Active Portfolio Management

The Fundamental Law of Active Portfolio Management is a postulate that states that the return from any investment strategy can be improved by adding an active management component to it. The law was first proposed in 1989 by Richard Grinold and Ronald Kahn and has been proven by decades of data. It was basically designed for assessing the value of active management, as expressed by the information ratio (IR), using only two variables. One variable is the "Skill" of the portfolio manager and another variable is the "Breadth", or the number of independent investment opportunities.

So now let's dig more into The Fundamental Law of Active Portfolio Management.

What is the Fundamental Law of Active Portfolio Management

Let's start with the definition:

The Fundamental Law Of Active Portfolio Management states that an investment approach can produce higher returns through a combination of two things. One component is active management and another component is the “breadth” or the number of independent bets placed on different opportunities.

The law basically shows that by adding more investments to a portfolio containing only a single investment, we can increase returns.

In a nutshell, the Fundamental Law of Active Portfolio Management states that by adding more bets to your portfolio you can get better performance.

The law also implies that higher performance is achievable with active portfolio management as opposed to passive investing. The question then arises if it's possible to find investments that exhibit higher investment returns and demonstrate positive performance. The answer to this question is most certainly yes, but it's a question of time and effort.

Picking the best investment portfolio requires hard work and research, but as with everything in life the rewards are proportional to your efforts.

How does The Fundamental Law of Active Portfolio Management work

Once you have identified the source of these opportunities then you can successfully implement the Fundamental Law of Active Portfolio Management.

The first step in implementing active management is the identification of the investment opportunities within one's reach. The law offers some guidance for single manager investing, but it also works with a portfolio of several managers or a group effort.

Once you have identified these investment opportunities then you need to actively manage your portfolio by narrowing down your options to the best investment opportunities available.

In order to apply The Fundamental Law of Active Portfolio Management effectively then you need an accurate and realistic assessment of each portfolio manager's skill or alpha:

Different styles have been developed that measure various elements of a manager's performance. These include tracking error, risk-adjusted performance, absolute performance, and excess return.

The Fundamental Law of Active Portfolio Management states that the potential for achieving good portfolio performance is in direct proportion to the size or breadth of investment opportunities available as such an approach allows you to diversify your portfolio of investments, which results in eliminating negative investment returns from individual securities.

Benefits of The Fundamental Law of Active Portfolio Management

The Fundamental Law of Active Portfolio Management states that an investment approach can produce higher returns through a combination of two things. One component is active management and another component is the breadth or number of independent bets placed on different opportunities.

Let's take a look at the Fundamental Law of Active Portfolio Management benefits:

1. The potential for achieving good portfolio performance is in direct proportion to the size or breadth of investment opportunities available
2. By adding more bets to your portfolio you can get better performance
3. The Fundamental Law of Active Portfolio Management implies that higher performance is achievable with active portfolio management as opposed to passive investing
4. The Fundamental Law of Active Portfolio Management states that it's possible to find investments that exhibit higher investment returns and demonstrate positive performance
5. Identifying the investment opportunities within one's reach is the first step in implementing active management

Conclusion

The Fundamental Law of Active Portfolio Management can aid in the development and implementation of an investment portfolio that delivers higher investment returns than passive or simply diversified portfolios. It offers a useful guideline for all investors looking to achieve better investment performance through active investing.

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Econometrics vs Actuarial Science

Both econometrics and actuarial science involve similar areas of study. These include statistics, mathematics, economics, and finance. However, they usually have different applications and are prevalent in particular industries. Despite their similarities, however, both of these fields also differ from each other in various aspects. Before understanding those differences, it is crucial to look at these fields individually.

What is Econometrics?

Econometrics is a term used to describe the application of mathematical and statistical models in economics. It involves using these models to analyze and test economic data. It also has applications in the world of finance. Similarly, econometrics deals with the quantification of economic theories and hypotheses. The field has progressed significantly over the few years.

Econometrics is highly crucial for economists and analysts. Economists use it to test various economic policies and evaluate their impact. Analysts, in contrast, use it to test economic theories and make forecasts or predict trends. There are several tools within econometrics that these parties have at their disposal. These include regression analysis, probability, statistical inference, correlation analysis, etc.

Econometrics helps analysts analyze data using statistical methods. Using the processed data, they can then test or develop economic theories. The primary objective behind this process is to convert economic concepts into quantitative information. There are several fields within econometrics that deal with different aspects of this process.

What is Actuarial Science?

Actuarial science is a field of study that involves the use of mathematical and statistical methods. However, it relates to using probability and statistics to assess the impact of future uncertain events. The field deals with how these events will impact an entity financially. It may apply to specific organizations, regions, or nations.

Actuarial science is usually prevalent in the business field. In particular, its application is crucial in industries where complex calculations are necessary. For example, actuarial science has a critical application in the insurance, pension, and banking industry. Since it involves quantifying risks related to specific events, it can be crucial in those areas.

Actuarial science requires actuaries, who are professionals, to assess the risks associated with uncertain events. Once they do so, they must quantify those risks to provide how these will impact an entity. In the past, actuaries used deterministic models for this process. Since the 1980s, however, they have switched to a combination of stochastic actuarial models with modern financial theory.

What is the difference: Econometrics vs Actuarial Science?

Both econometrics and actuarial science involve similar study areas, as mentioned above. However, they are both fundamentally different from each other. The primary difference between both fields is the use of statistics in both. In actuarial science, the use of statistical methods is more prevalent compared to econometrics. However, it does not imply that statistics does not play a critical role in econometrics.

Both fields also focus on modeling based on processed data. However, the models for each differs based on the assumption and application. Furthermore, while econometrics is usually prevalent in economics-related industries, it has an application elsewhere as well. Actuarial science primarily relates to the insurance, reinsurance, pension, and banking industries.

Conclusion

Econometrics is a field of study within economics involving the application of statistical and mathematical models. Analysts use these models to test economic theories and hypotheses. On top of that, they may also apply them for forecasting or trend analysis. Actuarial science also involves using statistics and mathematics. However, it primarily studies the financial impact of uncertain events.

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Trading Strategies Based on Autocorrelation Properties of Bitcoin

Bitcoin was born as a niche investment vehicle, but over time it has become a mainstream asset. Many research papers have been devoted to developing trading strategies for Bitcoin, but we just recently came across one [1] that examined the PnL/risk driver in terms of autocorrelations and developed trading systems accordingly.

Specifically, the paper investigated the autocorrelation properties of Bitcoin in different timeframes. It pointed out that, like stock indices, Bitcoin is mean-reverting. But unlike stock indices, Bitcoin is mean-reverting across a broader spectrum of timeframes.

We analyzed the intraday behavior of Bitcoin, comparing the features of its market with the stylized facts that characterize the series of traditional financial assets such as stocks and foreign exchange pairs. The comparison was based on data recorded between March 2015 and June 2018, and highlighted several similarities as well as some important differences. Among those differences, the primary finding was the presence of significant negative first-order autocorrelation in the series of Bitcoin returns, not only limited to extremely high-frequency returns, but extended to medium-frequency ones, such as those computed at intervals of one, two and four hours.

The author subsequently provided main reasons for the mean-reverting nature of Bitcoin, namely (i) investor and trader overreaction, (ii) excess volatility, and (iii) cascading liquidations due to excessive use of leverage by market participants.

Significant negative autocorrelation of returns indicates that price tends to systematically mean-revert in the period immediately subsequent to a move. We attribute this finding to a combination of factors. Among them, we believe the most important ones to be investor and trader overreaction, high volatility, and excessive use of leverage leading to liquidation cascades.

Trading strategies were developed based on research results, and they’re profitable across a broad range of timeframes and triggers,

…a strategy that checks price every five minutes, then goes long if the return in the last five minutes was negative and greater in absolute value than two standard deviations, or goes short if the return in the last five minutes was positive and greater than two standard deviations. Each trade is then closed after a single period, regardless of the outcome. In our example, this means that each trade only lasts five minutes. The results are significantly positive across the board, meaning that even with a basic strategy like the one used, the negative autocorrelation of returns would likely be exploitable, assuming market microstructure to be similar to that of legacy markets.

We find the research results interesting and promising. However, there are a couple of points worth  mentioning:

• The trading strategies were developed with a benefit of hindsight, i.e. the backtest results suffer from the lookback bias.
• Since the negative autocorrelation is the main PnL driver of the trading strategies, going forward it would be crucial to develop an indicator to monitor and signal a regime change, from negatively autocorrelated to random walk or positively autocorrelated.

Finally, we also find the results regarding Bitcoin volatility interesting and relevant.

References

[1] GD Nicola, On the Intraday Behavior of Bitcoin, Ledger, Vol 6 (2021) 58-80

Article Source Here: Trading Strategies Based on Autocorrelation Properties of Bitcoin

Style Drift in Hedge Funds

When it comes to style drift in hedge funds, there is a lot of confusion as to what the term actually means. Investors and traders need to understand how this can affect their investments. In order to help you better protect yourself, we will be providing some useful information on this topic

We'll go over some key points about style drift that should give you a good grasp on this subject matter and get you ready for the rest of the blog post!

What is Style Drift

When discussing style drift in hedge funds a good place to start is by defining the term itself. Style drift occurs when an investment portfolio's allocation is modified over time. Style drift may result in a portfolio's assets becoming more or less aggressive than it was designed to be, violating the expectations of investors.

Style drift can occur naturally in a portfolio due to gains from certain assets and losses on others. A fund can also change if the investment manager changes or abandons the portfolio’s strategy.

Usually, a portfolio manager's commitment to managing a fund's assets according to its stated investment style over several years is a key point of differentiation between funds. Historically, even the most actively managed hedge funds and other investment strategies have been able to withstand some style drift without affecting long-term performance.

However, research has shown that extreme cases of style drift do affect fund returns and risk measures, especially over several years, as well as investor withdrawals from the fund.

What are Hedge Funds

Hedge funds typically make more money with less risk, thanks to a portfolio of investments that uses different types of investment methods and assets.

Hedge funds are not regulated by the SEC, so they are usually only available for accredited investors who qualify. Hedge funds are also offshore to some extent since they don't have to comply with SEC regulations. One aspect of hedge funds that has set them apart is the fact that they face less regulation than other investment tools like mutual funds.

What is Style Drift in Hedge Funds

Style drift is a phenomenon in which hedge fund strategies change over time due to changes in the economy, asset prices, and market trends. The effects of style drift can have a significant impact on performance and risk measures for an investment portfolio.

Style drift is one of the major issues for Hedge managers. Style drift typically begins small and evolves into more complex changes. Some managers may be able to avoid style drift by investing broadly and observing position limits. They can change their strategies and investment instrument to tune into the trends of changes in the market.

Does Style Drift Affect Performance

YES! Style drift can negatively affect performance if the manager loses control over their investment strategy due to any of the factors mentioned above. Hedge fund investors need to understand the strategies of their managers and the purpose their funds serve to maintain a healthy relationship.

Does Style Drift Affect Risks

YES! Style drift affects risks due to several factors that are listed below:

Inappropriate asset allocation: If a portfolio's assets don't match its stated allocation; this would affect the risk profile of the portfolio.

The passing of time: Over a period of time as a result of a change in market conditions, assets become riskier. The performance and allocation are no longer at par with what is expected from the strategy.

Over Concentration: If an investor holds too much in one asset; it can create unnecessary risk.

Under Concentration: If an investor holds too little in one asset it can create a significant loss due to lack of diversification.

Conclusion

As you can tell by now, style drift can have an impact on a portfolio's risk, returns, and volatility. Therefore, it is vital to understand the investment style of your portfolio manager throughout the period of time you're invested in the fund. The effects of style drift are amplified by severe and drastic changes over a long period. However, changes that are gradual and less drastic can have a more limited effect on the portfolio's returns. The bottom line is that style drift affects risk by creating problems with asset allocation, the timing of trades, concentration levels in a fund.

Originally Published Here: Style Drift in Hedge Funds

Econometrics vs Mathematical Economics

Economics is a field of study that relates to analyzing various factors that affect a country's economy. These factors include production, distribution, and consumption of goods and services, collectively termed as value. However, the field of economics usually involves theoretical analysis. When it comes to quantifying these theories, there are several options. These include econometrics and mathematical economics.

What is Econometrics?

Econometrics is a field within economics that deals with applying statistical and mathematical models to analyze economic theories. This field relates to how analysts can test or prove various economic hypotheses through quantification. Analysts that use econometrics to do so are known as econometricians. The primary objective of econometrics is to use statistical and mathematical methods to develop theories or test existing ones.

Econometrics is substantially helpful for analysts that use economic theories for trend analysis or forecasting. During the process, they use tools, such as regression analysis, time series analysis, probability, correlation analysis, etc. Depending on their needs, analysts can use these tools to make predictions and forecast future trends.

Although econometrics involves using mathematical and statistical methods, it still relies on theory. The field exists since the 1970s. However, it has grown over the last 30 years. Most nations depend on econometrics to develop their economic policies and test those policies to assess their impact.

What is Mathematical Economics?

Mathematical economics is a field within economics the involves the use of mathematical principles to develop economic theories. Unlike econometrics, it does not include statistical analysis. Therefore, mathematical economics is more limited when it comes to its application. However, it does not imply that one field is more superior to the other.

Through the use of mathematics, economists can develop accurately defined models using mathematical logic. Based on those models, they can reach conclusions, which they can use statistical models to test. Therefore, mathematical economics can contribute to the data required for analysts to apply in econometrics. Based on these models, analysts can also use statistical tools to make quantifiable predictions about economic activity.

Mathematic economics plays a critical role in allowing economists to develop economic models. It can be significantly helpful when weighing various economic policies against each other and assessing their impact. Overall, mathematical economics helps economists describe an observable phenomenon. By doing so, it allows economists to develop a theoretical interpretation.

What is the difference: Econometrics vs Mathematical Economics?

Econometrics and mathematical economics involve similar areas. Econometrics usually deals with the application of both statistical and mathematical methods to the field of economics. It relates to how economists use these methods to develop or test economic models. It also involves using any interpreted data to make predictions or analyze trends.

Mathematical economics, on the other hand, has limited application. However, it provides the basis for the use of econometrics. Mathematical economics deals with analyzing data using mathematical methods or models. By doing so, it provides the information necessary for economists to use in statistical models and econometrics.

Conclusion

Econometrics and mathematical economics are fields within economics that involve the quantification of economic theories. However, they are both different. Econometrics deals with the use of statistical and mathematical tools to analyze trends and predict future outcomes. Mathematical economics involves the application of mathematical models in the analysis of economic concepts.

Post Source Here: Econometrics vs Mathematical Economics

Holding-based Style Analysis

Holding-based style analysis is a type of investment strategy that can help you make better decisions about stocks. It takes into account the holding period and market capitalization to analyze a stock's risk, return, and volatility. The idea is to see if a particular company has an edge over its competitors because it possesses some unique quality or characteristic that cannot be easily duplicated by other companies in the same industry.

Definition of Holding-based Style Analysis

Holding-based style analysis is a type of investment strategy used to describe the structure of a company's investment portfolio. It combines two different approaches to investing: valuation analysis (looking at a company's stock price in relation to its earnings and book value) and style analysis.

Holding-based style analysis is used by investors, analysts, and traders to analyze the unique investment approach that an individual company has. Using this strategy allows you to determine whether or not a company's strategy is successful. It also helps you decide if the company is run by a good management team that has the ability to invest in and manage industry trends effectively.

How does Holding-based Style Analysis work

Holding-based style analysis is based on the premise that a company's performance can be analyzed through an examination of its investment portfolio. The portfolio gives you insight into how management manages the company's particular business trends.

For example, if you are looking at a technology firm and you notice that it has increased its holdings in other technology stocks, such as software, you can assume that the company is reacting to technological trends in its business.

A holding-based approach looks at a company's holdings and compares them to similar companies within the same industry. It then assesses the risk, returns, and volatility of each company in order to make an overall judgment about the way that management is investing the company's assets.

Benefits of Holding-based Style Analysis

Using this type of analysis to determine a company's investment strategy can help you make better buying decisions. You are able to more accurately assess the risks and returns associated with an investment in a particular stock.

The holding-based approach has become much more relevant as institutional investors have shifted their focus away from stocks and bonds, and towards other types of assets such as derivatives and commodities.

The holding-based style analysis strategy can also help you diversify your portfolio. If you are looking for a way to make your stock holdings more diverse, this investment approach may be right for you.

The benefits of the Returns-based Style Analysis include

• Better investments by seeing how management reacts to trends
• Determine risks and return in the company's portfolio
• Increases your overall diversification in your portfolio
• Allows you to see if a company is reacting and responding to industry trends
• Less Time-Consuming
• Improved Decision making

Conclusion

Holding-based style analysis helps you decide if a particular company is a good investment or not. You are also able to see what type of management team is running the business and whether they have the ability to effectively manage industry trends. This may be especially important for small businesses and start-ups that do not necessarily have the capital or resources to invest in industry research and development.

Post Source Here: Holding-based Style Analysis

Return-based Style Analysis

Return-based style analysis is a statistical technique that helps investors understand the risk and return characteristics of their portfolios. It does this by looking at how often different stocks in your portfolio go up or down, irrespective of what other stocks are doing. The idea behind return-based style analysis is to determine if you have any "overweight" positions in one sector with unusually high volatility, which could cause you to experience heavy losses when things don't go as planned for that particular industry.

What is Return-based Style Analysis

Return-based style analysis is a well-established and highly useful analytical tool. It attempts to determine an individual security's exposure to various market factors by examining how often the security has gone up or down over a specific period of time. The intent is to identify under-diversified holdings within your portfolio, so you can make adjustments if necessary.

How does Return-based Style Analysis work

The Return-based Style Analysis is mostly used for the analysis of individual securities. The process involves determining an individual security's exposure to various market factors by examining how often the security has gone up or down over a specific period of time. Then, this information is used to evaluate the risk/return characteristics of your portfolio as a whole – and in particular, your sector exposure.

The information generated by this procedure about the portfolio's sector exposure can then be compared to that of a benchmark index or some other theoretical market, such as a market of stocks that are weighted according to their projected earnings.

Benefits of Return-based Style Analysis

Return-based style analysis is a statistical technique that helps investors understand the risk and return characteristics of their portfolios. It does this by looking at how often different stocks in your portfolio go up or down, irrespective of what other stocks are doing.

The idea behind return-based style analysis is to determine if you have any overweight positions (i.e. overweight positions in one sector with unusually high volatility, which could cause you to experience heavy losses when things don't go as planned for that particular industry) in your portfolio.

The benefits of the Return-based Style Analysis include

• Determining if you have any overweight positions in your portfolio
• Evaluating risk/return characteristics of your portfolio as a whole
• Providing information on how often security has gone up or down over a specific period of time
• Helping you to pinpoint what's driving your portfolio's overall risk, and hence helping you manage the portfolio accordingly
• Return-based style analysis is used to gauge the exposure of your portfolio to various risk factors.

Conclusion

Return-based style analysis is a well-established and highly useful analytical tool. It attempts to determine an individual security's exposure to various market factors by examining how often the security has gone up or down over a specific period of time. The intent is to identify under-diversified holdings within your portfolio, so you can make adjustments if necessary.

The idea behind return-based style analysis is to determine if you have any overweight positions in one sector with unusually high volatility, which could cause you to experience heavy losses when things don't go as planned for that particular industry.

Originally Published Here: Return-based Style Analysis

Stop Losses in Options Trading

A financial option is a rather complex instrument. Unlike delta-one products, an option value depends not only on the underlying, but also on volatility, time to maturity, strike, interest rate, and dividends. Options have been used as hedging instruments, but they’re becoming a speculative vehicle these days thanks to a growing number of retail traders and the increasing popularity of financial media.

Even though options are derivatives, and thus trading  them would require a different thinking, retail traders often apply delta-one trading techniques to options trading. One such popular technique is stop loss. The trading rule usually goes like this: sell options to collect premium, and if the marked-to-market loss exceeds a certain multiplier of the premium received, then exit. On this topic, Reference [1] examined the role of stop losses in options trading. Specifically,

This paper is devoted to the research and development of profitable option sell-side trading strategies, and proposes an operating mechanism for stop-loss. In addition, statistical methods and random forest algorithms are used to estimate the win-rate of the strategy. The win-rate represents the proportion of all transactions that the premium has not doubled before settlement, and we can also express it with precision.

After performing numerical experiments, the authors concluded,

The experimental results can confirm that the trading strategy proposed by this paper can effectively achieve risk control through the development of a stop-loss mechanism with a fixed premium double multiple. And apply statistical methods and random forest algorithm to estimate the win-rate of the strategy, and screen out the trading range with higher profit and stable. The precision predicted by the model classification can prove that the strategy is practical and profitable.

The paper led us to ask ourselves the following questions:

• Why do we use a stop loss instead of employing a defined payoff position, e.g. a vertical? Recall that an option position is a bet on either the underlying’s terminal distribution or its dynamics. Using verticals would allow us to have a well-defined bet on the terminal distribution of the underlying. If we sell an option and then apply a stop loss, what the nature of the bet would be?
• The use of stop losses would prevent us from taking advantage of the mean reversion property of stock indices. Defined payoff positions will allow us to do this.
• Can we get realistic fills using stop losses in options trading? It’s well known that, even in a liquid, primary market, when volatility increases, stop losses will become less effective, i.e. traders will find it more difficult getting fills. Options are less liquid, derivative market with bigger Bid-Ask spreads. Can stop losses be applied effectively?

These are just some questions. Let us know what you think.

Last and not least, we also observed from the paper:

• Figure 1 is incorrect in the context of time decay in the real world.
• Predicting the win rate is meaningless if the strategy’s expectation value is negative.

References:

[1] C-F Chao, Y-C Wang, M-E Wu, A Quantitative Model for Option Sell-Side Trading with Stop-Loss Mechanism by Using Random Forest, 2021, https://www.researchsquare.com/article/rs-769898/v1

Originally Published Here: Stop Losses in Options Trading

Equal-Weighted Commodity Index

This is not to be confused with the equal-weighted ETF which has created a lot of buzz in recent months. Equal-weighting commodities can be risky because you are investing in assets that may have been undervalued or overvalued for extended periods of time, but this method does have its benefits and should not be ignored altogether. In general, it's good to diversify your portfolio with both low-risk and high-risk investments so as not to lose all your money when one investment tanks.

What is the Equal-Weighted Commodity Index

The equal-weighted commodity index is a portfolio of futures contracts on commodities that are equally weighted. It takes the price of multiple commodities and calculates an average, then buys all those assets in proportion to their value, which can be done because the prices are quoted in dollars per unit so it's as easy as dividing by the quantities purchased.

This is a way to diversify your assets across multiple sectors of the economy and give you access to an asset class that isn't readily available in typical portfolios.

How is the Equal-Weighted Commodity Index Calculated

The equal-weighted commodity index is calculated by taking the current price of each asset and dividing it by its average historical value, then multiplying that result by the quantity purchased. An example of how this is done can be seen below:

(Brent Crude Oil Price / Average Historical Price) * Quantity Purchased = Weighted Average Price

For example, if you have a current price of $100 and an average historical value of $80, then:

(100/80) * 5 = $125

This means that for every dollar invested, you would receive four dollars' worth of oil. There is some inherent risk in this strategy because the high-risk commodities will make up a greater portion of the portfolio. So if gold and silver prices skyrocket, your portfolio will be heavily weighted in those assets which could become dangerous if they were to suddenly crash.

However, this is not a bad strategy because you should have a diversified portfolio anyway. It gives you access to an asset class that would normally only be available to institutional investors, at least to a limited degree.

How does the Equal-Weighted Commodity Index compare with other indexes

It has been shown that commodities tend to rise when equities are falling, and vice versa. However you should be cautious about investing in commodities because they are much more volatile than stocks, so there is a greater chance that you'll lose a lot of money in them if the prices plummet.

In addition, investing in commodities is not as liquid or simple as trading stocks because most indexes are value-weighted and therefore only take into account the current price of each asset, not its average historical value.

Advantages and Disadvantages of Equal-Weighted Commodity Index

The Equal-weighted Commodity Index comes with both advantages and disadvantages.

Advantages

• All commodities in the index are equally weighted so you can diversify your portfolio in this asset class.
• Some indexes are value-weighted which means that they only take into account the current price of each commodity, but with equal weighting, you'll have greater exposure to historical performance and won't be able to form a judgment about whether the commodity is overvalued until you do a comprehensive analysis of its historical performance.

Disadvantages

• The equal-weighted index is much more volatile than the value-weight indexes because it has more exposure to commodities that have been extremely volatile in the past. So if you invest heavily in this option, there's a good chance you'll lose a lot of money.
• It's difficult to create an index that is diversified because most commodities tend to move in the same direction, so if you invest heavily in them, there's a good chance they will all perform poorly and your portfolio will decline as a result.

Conclusion

Investing in the Equal-weighted Commodity Index is a great way to gain exposure to an asset class that does not represent the market as a whole. However, because commodities tend to move together and have been extremely volatile in the past, this option will likely result in your portfolio declining if you invest too heavily into it.

Article Source Here: Equal-Weighted Commodity Index

Market Capitalization Weighted Index

A market capitalization-weighted index is an equity index that measures the performance of a selection of stocks from a particular region or market. The cap-weighted indexes are some of the most commonly used indices because they measure the relative size (or weight) of each company in the portfolio, and can be used to help assess both volatility and liquidity levels.

In this blog post, we are going to look at what a market capitalization-weighted index is and how it actually works.

What is a Market Capitalization-Weighted Index

A market capitalization-weighted index is an equity index that measures the performance of the equities in a particular region or market. Cap-weighted indexes are some of the most commonly used indices, as they measure size accurately and can be used to assess volatility and liquidity levels.

The cap-weighted indexes are constructed so that an equal amount of money is invested in each stock. Each company's capitalization or 'market cap' is determined by multiplying the current market price of one share (usually expressed in USD) by the total number of shares outstanding for that company, with a minimum of $1 million and a maximum of $5 billion.

For example, if there are two companies in a portfolio and both have market capitalizations of $2 billion each, then the weighting for company A will be 50% and company B will hold the remaining 50%. The weightings cannot add up to more than 100%, unlike with an equal-weighted index.

How Does Market Capitalization-Weighted Index Work

With an index, a portfolio is chosen and is weighted to reflect the market or regional economy. For example, in Australia, the top 50 companies listed on the stock exchange have been selected to make up the All Ordinaries Index - which has a weighting of 16% for each company that represents a fair reflection of the Australian economy.

This method of calculating a portfolio's weight is known as capitalization-weighted.

The calculation for the market cap is straightforward – it involves multiplying the price of a stock by the number of shares issued while setting a minimum value on total assets and adjusting for foreign exchange fluctuations to arrive at a figure. In the case of an index fund, all stocks are divided by the total market cap of all stocks in the index to arrive at a percentage.

Why is Market Capitalization-Weighted Index Important

The market capitalization-weighted index has long been the most widely used method for constructing an index fund or a portfolio of securities. Market cap is calculated using each company's share price multiplied by the number of shares outstanding, with some exceptions including financial service companies (banks).

Another reason why the market cap is important in constructing an index is that trading securities using this method will ensure that a portfolio represents the companies with the highest value and most liquid stocks. Liquidity refers to the ability of an investor to enter or exit a stock without moving its price substantially, which makes it easier for investors looking for a short-term buy-and-hold strategy.

Conclusion

The market capitalization-weighted index is one of the most used indexes in finance. It's a weighted average where each share price has an equal weighting and represents the value of that company on the stock exchange. So you can get a better view of the market in general.

Article Source Here: Market Capitalization Weighted Index

How to Hedge Inflation?

For many of us, inflation has been a constant worry in recent years. One way to protect ourselves from the effects of inflation is by hedging our investments. So let's take a look at how can we hedge against inflation.

What is Inflation?

Inflation is a type of rising in prices across the board. If you have ever been on a shopping spree at the grocery store, you will probably agree that inflation has caused some of our groceries to become more expensive over time.

The easiest way to think about it is as follows: Suppose you need 100 dollars today to buy certain goods and services. Inflation means that the next time you buy those same goods and services, you will need more than 100 dollars to do so.

In simple words, inflation is a rise in prices over time, while deflation is a fall in prices. This also means that there is only one form of currency inflation and two forms of currency deflation.

What Causes Inflation?

Inflation happens when there's an increase in what's called "monetary supply". This includes everything from printing up money to issuing more debt. For example, when the U.S. government wants to boost economic growth they'll typically print a lot of money to pay their expenses. This increases the supply and reduces the purchasing power of everyone else's dollars.

How Does Inflation Impact Your Portfolio?

The two main ways that inflation impacts your portfolio are: on an absolute basis (i.e. it erodes the value of your portfolio) and on a relative basis (i.e. it increases your cost for trading). Let's take a look at both of these effects in detail below.

Impact Of Inflation On An Absolute Basis

Monetary inflation means that the purchasing power of our money will decline over time. If you think about it, it does actually make sense. If the Fed takes $100 and prints 10 more $10 bills, then we need to spend 100 dollars today in order to get what used to cost 80 dollars yesterday.

Impact Of Inflation On A Relative Basis

When inflation goes up, expenses go up as well. And when expenses go up, so do our trading costs. As the price of a stock goes up with inflation, the number of dollars we need to spend on that stock also increases with inflation.

How to Hedge Against Inflation?

There are many ways to hedge against inflation. Most of the time, people will use interest-bearing investments such as Treasury Inflation-Protected Securities (TIPS), CDs, and bonds. These pay you a guaranteed return on your investment above the rate of inflation that we see in our economy today.

Typically, they have lower yields than regular money market instruments. However, when you consider that they partially insulate your portfolio from the effects of inflation, their yield is worth far more than its face value.

For example: Let's suppose we invest $10,000 in a CD paying 3% per year over 5 years with an inflation rate of 2%. At first glance, it may seem like we're not doing too well because we're earning only 3% per year.

However, when you take into account the fact that inflation over this period is expected to be about 2%, we're actually doing better than if we were invested in a regular savings account paying 1%. This is because while $10,000 could have bought us $11,000 worth of goods 5 years ago, it will cost us around $12,500 today (due to inflation).

So while CDs and TIPs typically have lower yields, they're still valuable tools for insulating our portfolio from the effects of inflation.

Conclusion

If you're looking for hedging against inflation, consider investing in treasury bonds. The easiest way to do this is by purchasing an index fund that invests in a basket of Treasury securities (like the Vanguard Total Bond Market Fund ETF) and holds them until maturity.

Article Source Here: How to Hedge Inflation?

What is a Covered Bond?

Covered bonds are a type of debt instrument that is issued by a bank. These types of securities have two main features, which are: the issuer has pledged its assets to back up payments on the bond, and investors can buy these bonds at lower yields than other comparable instruments because they get paid if there's an issue with the borrower.

In this article, we are going to take a look at what covered bonds are and how they actually work.

Definition of Covered Bonds

Covered bonds are generally characterized as being long-term debt securities that are issued by banks. They can be either secured or unsecured, and they pay out interest over time with the goal of helping to provide liquidity for issuing banks.

Overall, covered bonds are perfect for spreading risk between investors and issuers, because the former will receive their income as long as the issuer hasn't defaulted or failed to pay. This helps reduce the risk for both parties.

Benefits of Covered Bonds

There are a number of benefits that covered bonds offer to both investors and issuers. For example, these types of securities are considered relatively safe when compared to other types of debt instruments like mortgages or loans. This is because they can't be traded on the secondary market. And in case there's an issue with the borrower, then investors will get their payments.

The risk management goals of covered bonds are also a good thing for investors. And these can even help to lower the cost of funds and raise capital for a bank or other financing institution that issues them. In short, covered bonds provide borrowers with cheaper funding sources that can be used to make new loans or otherwise improve liquidity in the market.

As said above, covered bonds are considered a safe investment because they have more collateral backing them up than other types of debt instruments. In this respect, the European Investment Bank (EIB) has mostly financed covered bond banking projects throughout Eurozone countries.

How do Covered Bonds Work?

Covered bonds work in a very similar way to how normal corporate bonds work. However, unlike standard bonds that can be freely traded on the secondary market, covered are only eligible for redemption from the issuing bank at the maturity date of these instruments. This is only possible if investors have actually been paid their interest and received principal payments (if due).

The main difference between covered and normal bonds is that the former have assets under them as collateral. This provides investors with a greater level of security in case there's a payment issue. And this also helps to bring down the cost of funds for issuing banks.

So as you can tell, there are a lot of advantages to both investors and lending institutions. But this doesn't mean that covered bonds aren't without their drawbacks. For example, they have a relatively low liquidity level (compared to normal corporate bonds). This is because they can only be sold back to the issuer at the end of their term period.

Conclusion

Overall, covered bonds are great for spreading risk between issuers and investors because the former gives up assets that can be used to back these instruments up in case there's a payment issue. And this provides investors with a greater safety net than they would normally have with other types of debt instruments.

Originally Published Here: What is a Covered Bond?

Is Cointegration the Best Method for Pairs Trading?

Pairs trading is a classic “market-neutral” trading strategy. Previously, we highlighted an article that claims that cointegration is a superior method for selecting pairs [1].

Reference [2] examined more pair selection methods. Specifically, it investigated the following approaches,

• Distance: Pairs are identified by using distance metrics. This is perhaps the simplest approach.
• Cointegration: Cointegration tests are applied to identify pairs and generate signals.
• Copula: Trading signals are generated by relative value drawn from estimating the joint probability distribution of returns.
• Time series: Focuses on generating trading signals by time series analysis. Often ignores formation period.
• Stochastic: Uses stochastic control theory in determining value and policy functions for this portfolio problem. Ignores formation period.
• Other: Experimental frameworks with less supporting literature. These approaches include machine learning and principal component analysis.

It concluded, contrary to Reference [1], that the best method for selecting pairs is the distance method. Cointegration is the second-best one only. Note that the results are applicable to the Finnish stock market.

This thesis confirms the assumptions made in previous literature about what types of pairs are suitable for pairs trading. When pair formation is limited to allow only pairs consisting of companies from the same industry, distance-based and cointegration-based selection favors pairs formed of different share classes of one company. An example of this is Orion Class A- Orion Class B. Such pairs provide more trading opportunities than other types of pairs (e.g. Stora Enso - UPM).

Although 2 articles are contradictory, we believe that:

• Simple methods work best. There is no need for more complex ones. Instead of using complex, advanced pair selection methods, one should focus on the strategy robustness, especially on minimizing divergence risks.
• Ideally the pairs should consist of different share classes on the same underlying. If different share classes don’t exist, then the pairs should consist of stocks in the same industries. If we generalize this to futures markets, then trading futures on the same commodities would make sense.

References

[1] N. Huck and K. Afawubo, Pairs trading and selection methods: is cointegration superior?, Applied Economics, 47:6, 599-613, 2015

[2] S. Kohvakka, Pairs trading revisited - the case of OMX Helsinki, Lappeenranta-Lahti University of Technology LUT, 2020

Post Source Here: Is Cointegration the Best Method for Pairs Trading?

What is a Collateralized Loan Obligation?

A collateralized loan obligation is a financial instrument that offers investors the chance to invest in the underlying assets of loans. CLOs are attractive because they offer higher yields than other types of investments like stocks or bonds.

You may be wondering what exactly a collateralized loan obligation or CLO is, and how it might help you with your investment portfolio? So keep reading to know more about Collateralized Loan Obligations

Collateralized Loan Obligation Definition

A collateralized loan obligation, or CLO, is a type of security that allows investors to pool their cash together and invest in the underlying assets of loans. To make this investment option possible, a corporation will purchase hundreds or thousands of individual loans from banks and financial institutions so that it can wrap them up into one package (the obligations). These obligations are then issued to investors who can collect interest payments and, if all goes well, eventually get their original investments back.

Conceptually, a CLO is similar to a real estate investment trust in that it offers the promise of collecting regular payments from individual loans. The key difference is that with the CLOs you can invest in a wide variety of loans, not REITs.

How Does Collateralized Loan Obligation Work

Like all other types of loans, collateralized loan obligations are made to those with good credit scores. Investors may also look for borrowers who have little or no debt and many years left before they need to pay off their loans so that they can get the best returns on their investment soon.

Loans range from anywhere between $50,000 and $20 million and have terms of anywhere between 4-10 years. After the loan has been issued, investment firms will then pool them together and make a new package that contains all the loans within it. With this new financial instrument for sale, they'll go to potential investors like hedge funds or mutual funds to get capital.

CLOs do not offer any of the underlying loan itself, just an interest rate on top of the original.

As a general rule, investment firms will keep at least 10% of loans in reserve to handle those who defaulted on their debts. This means that if you plan to invest in this type of security, you've to make sure they screen for quality borrowers and rely on a backup reserve so you can get your money back if you want to.

As with any other type of investment, be sure to fully understand all the rules before taking part in this market. This will help you to avoid making any costly mistakes later on down the road.

Conclusion

A collateralized loan obligation is a type of investment that pools together different types of loans, such as mortgages and corporate bonds. Because it has different types of assets in the pool, it can offer investors more diversification than just buying one kind of asset like stocks or real estate. We hope this article gave you a better idea of what a Collateralized Loan Obligation is, and how it might fit into your investing portfolio.

Article Source Here: What is a Collateralized Loan Obligation?

How Does Tail Risk Hedging Work?

Investors can manage their overall portfolio risk by allocating their funds across a diversified range of asset classes. Usually, investors can mitigate most of these risks through planning. Sometimes, however, some risks may occur which are beyond prediction. These risks may cause severe implications for investors and adversely affect their portfolios.

What is Tail Risk?

The term tail refers to the end portions of distribution curves. Tail risk represents an investment’s worst downside performance periods. It occurs when the possibility that the investment will move more than three standard deviations from the mean outweighs what the normal distribution shows. The events that cause these risks are usually unpredictable.

Tail risks can cause investors’ wealth to deplete severely. Therefore, investors need to develop a realistic assessment of the true tail risk probabilities for an investment. The tail risk for investment also relates to the normal distribution. Under normal circumstances, an investment's returns will move towards the middle of the curve. However, it is also possible for these returns to gravitate towards the ends of the curve. Nonetheless, there is a low probability of that happening.

What is Tail Risk Hedging?

The probability of tail risk events occurring and affecting investors' portfolio adversely are low. However, if these risks realize, they can have severe impacts on investors' portfolios and wealth. Therefore, investors may need to use strategies to hedge against these tail events. Tail risk hedging is the process of developing strategies to mitigate tail risks.

Tail risk hedging is crucial in protecting investors against any unpredictable risks. Since these risks can have severe implications on investors' portfolios, they can be highly detrimental. Therefore, investors need tail risk hedging to enhance their returns in the long run. In some cases, it may be necessary to do so. Diversification can help investors in tail risk hedging. However, they also have other options.

How does Tail Risk Hedging work?

There are several options that investors have when hedging against tail risk. One of these options includes portfolio protection. This process, also known as risk management, can be beneficial for investors seeking worthwhile returns while also protecting their portfolios against tail risk. There are several methods within this approach that investors can use for tail risk hedging.

One of these methods involves using put options. Investors can buy put potions for major stock indices for their tail risk hedging process. It allows them to enter into an option agreement for the right to sell their investments at a specific price and time in the future. However, buying put options to hedge against tail risk can be complicated, time-consuming, and expensive.

Apart from portfolio protection, investors also have the option to recoup losses. This process involves waiting for some time and recoups their losses. However, this process may require a significant time investment, usually lasting over several years. Recouping losses may be a viable option for investors with a long-term investment plan. However, investors may not be willing to put in the effort for this approach for tail risk hedging.

Conclusion

Tail risk constitutes the risk of an event that has a low probability. Therefore, it may rarely realize. However, investors may still need to employ tail risk hedging strategies to protect their wealth. There are several approaches to this process that they may use. These include risk management or recouping losses.

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What is the Option Adjusted Spread

The term embedded option refers to an option included in financial instruments that provides the issuer or holder with a right to perform some actions at a future time. However, this right does not obligate the issuer or holder to do so.  Embedded options can be a part of financial securities, including stocks and bonds.

Investors can use the nominal spread to measure the difference between the yield of the bond and the yield to maturity of similar treasury bonds. However, the same does not apply when embedded options are a part of the bond. Instead of using the nominal spread, investors can use the option-adjusted spread.

What is the Option Adjusted Spread?

The option-adjusted spread measures the spread of a fixed-income instrument and the risk-free rate of return. Subsequently, it adjusts this spread to account for the embedded option. Simply put, it converts the difference between a fixed-income security's market and fair price into yield. After that, it calculates a spread to make both of these prices equal.

Option-adjusted spread is common in mortgage-backed securities as they usually carry an embedded option. This option exists to hedge the prepayment risk associated with the mortgage. Analysts can adjust the risk-free rate to the embedded option. By doing so, they can calculate the expected cash flows and the present value of the mortgage-backed securities and how they may fluctuate.

How does the Option Adjusted Spread work?

The option-adjusted spread is crucial in helping investors evaluate embedded options against general market volatility. As mentioned, these apply to all bonds that carry an embedded option. This spread represents the spread after adjusting for the embedded option. That is how it gets its name. With option-adjusted spreads, investors can evaluate how the embedded option affects the bond and its value.

Embedded options may exist in various bonds. However, they create additional risks. For investors, looking at the option-adjusted spread for a bond can indicate whether they should invest in it. It also helps them evaluate whether the bond is worth the given price after accounting for the risks. Therefore, option-adjusted spreads can play a substantial role in determining the value of bonds with embedded options.

How to calculate the Option Adjusted Spread?

Investors looking to calculate the option-adjusted spread can do so by using the option-adjusted spread formula. This formula considers the difference between the Z-spread and the embedded option cost. Therefore, it will be as below.

Option adjusted spread = Z-spread - Option cost

What are the advantages and disadvantages of Option Adjusted Spread?

There are several advantages of the option-adjusted spread. Most importantly, it allows investors to separate bonds from their embedded option. It can help investors decide whether an investment is worthwhile. Similarly, it provides investors with an accurate picture of embedded option contracts. Overall, it can be substantial in helping investors calculate a security's price that includes an embedded option.

However, there are some disadvantages that come with the option-adjusted spread. This spread uses advanced modes like Monte Carlo analysis in simulation. However, it may make the calculations much more complex. Similarly, it is prone to model risk and can distort investors' perception of how bonds behave if calculated inaccurately.

Conclusion

Embedded options may exist in financial instruments. These options provide one party with a right to perform some specific actions at a specific time. However, these may carry some risks. Therefore, investors will need to calculate the option-adjusted spread. This spread measures the value of a bond by removing the cost of the embedded option from it.

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Smart Beta Vs Factor Investing

Smart beta and factor investing are two terms often used interchangeably. These are both investing strategies that investors may use. However, there are various factors that differentiate both these investing strategies. Before understanding how they differ, it is critical to look at what each of these is.

What is Smart Beta Investing?

Smart beta investing is an investment strategy that allows investors to benefit from active and passive investing strategies. It combines both of these aspects to allow investors to maximize their gains. Smart beta portfolios are theoretically efficient compared to other portfolios. They try to strike a balance between the efficient market hypothesis and value investing.

Smart beta investing seeks to achieve several objectives for investors. These may include low-risk investments, highly diversified portfolios with low cost, or alpha. This approach to investing applies to all well-known asset classes, including stocks, commodities, bonds, etc. The smart beta investing strategy stems from the work of Harry Markowitz through the modern portfolio theory.

What is Factor Investing?

Factor investing is another strategy used by investors. Unlike smart beta investing, factor investing involves investing in assets based on predetermined factors. Each investor will specify or decide on which attributes they want their investments to match. Once they do so, they can choose investments that relate to those factors. These factors will also decide whether the investments are successful in achieving investors' goals.

There are two categorizations of factors that investors may consider during factor investing. These include macroeconomic and style factors. Macroeconomic factors seek to describe the risks associated with several asset classes. Style factors, on the other hand, explain the risks and rewards related to individual asset classes. Factor investing originates from the work of Fama and French as an asset pricing model.

What are the differences between Smart Beta and Factor Investing?

There are several characteristics that define and differentiate smart beta and factor investing. Both strategies have some commonalities, which can make them similar. However, there are some features that can separate them from each other as well. For investors, it is crucial to understand the differences between both of these to achieve their objectives.

Smart beta investing is a strategy that works with all popular asset classes. This approach to investing may emphasize achieving alpha, high diversification, or low-risk investments. For investors, it can help in building a portfolio with lower risks compared to traditional investing strategies. As mentioned, smart beta investing includes the advantages of both passive and active investing.

Smart beta investing follows specific rules which are also transparent. However, it seeks to identify ways in which investors can capitalize on any inefficiencies in the market. There are several investment factors that smart beta investing follows. These include value, quality, small size, momentum, and minimum volatility.

Factor investing, on the other hand, involves targeting specific return drivers across asset classes. As mentioned, these drivers may include macroeconomic and style factors. Each of these factors consists of various other investment factors within them. Through these, investors can achieve several objectives. These may include reduced volatility, diversification, and better returns.

Conclusion

Smart beta and factor investing are two common investment strategies that may confuse investors. Smart beta investing follows value investing and efficient market hypothesis. It involves a combination of active and passive investing strategies. On the other hand, factor investing focuses on achieving objectives that may come in the form of style or macroeconomic factors.

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Do Arbitrage Opportunities Still Exist?

The arbitrage principle is one of the cornerstones of modern finance, and it’s being used widely, from derivative pricing to hedging, trading, and risk management. Theoretically, there is only one arbitrage principle. Practically, however, there are other types of arbitrage, some of which are relaxed forms of the strictest one.

Reference [1] examined two seemingly simple trading strategies: the first one is based on the put-call parity, and the second one is the put-write strategy. These strategies are simple, but they  can stimulate some interesting thoughts regarding practical aspects of the arbitrage principle,

Coming back to the scheme for deriving trading strategies described in the introduction, both strategies started with stating assumptions on the financial market. For the put-call-parity this meant postulating that the no-arbitrage principle holds, for the put-write strategy pricing of options under certain model assumptions was considered. In a further step theoretical results were inferred. The put-call-parity itself in the first case and implicit volatility or expected returns of options in the latter. Testing on real market data quickly showed deviations for both theories.

The author first investigated a trading strategy based on the put-call parity and concluded that it is not profitable.  The author then examined the put-write strategy and concluded that it works better and can yield an excess return,

…the outcome of the two methods differed vastly. Whilst the deviations for the put-call-parity were too low to gain any noteworthy economical success when considering market frictions like margins and transaction costs, the put-write strategy looked much more promising.

The article’s results lead us to the following thoughts,

• The put-call parity strategy is one of the simplest examples of trading using the risk-neutral non-arbitrage principle. According to the author, it does not work. This is consistent with our experience that from the buy-side, it’s impossible to exploit mispricings in the risk-neutral world. Generally, we believe that this conclusion is applicable to more complex trading strategies as well.
• Put -write is one of the simplest strategies that exploit the volatility risk premium, and it works well, though with high risks. This strategy can be viewed as arbitrage between the risk-neutral vs. physical measures, which is a relaxed form of the non-arbitrage principle.
• Arbitrage is still possible but must be done mostly in the physical world, e.g. using some forms of statistical arbitrage and/or exploiting the risk premium.

Let us know what you think.

References

[1] A. Brunhuemer, Computer-Supported Testing of Option Strategies, Johannes Kepler University, July 2020

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What is a Total Return Swap?

A swap is a financial derivative that allows two parties to exchange their financial instruments or cash flows. These are highly crucial for investors, particularly for hedging. There are various types of swaps that investors can acquire. One of these includes total return swaps. Before understanding what these are, it is crucial to look at what total return means.

What is Total Return?

When investors acquire financial instruments, they expect some returns in exchange. These returns usually come in the form of interest or dividend payments. However, investors may also make capital gains on their financial instruments. The total return is a metric that allows investors to measure all the returns they generate on their investments.

In other words, total return represents the actual rate of return for an investment. It factors in various income sources when measuring the returns from an investment. These include interest payments, dividends, distributions, and capital gains. Total return represents the total income from an investment over a specific period, usually one year.

What is a Total Return Swap?

A total return swap is a derivative instrument that allows two parties to exchange the returns from their financial instruments. These returns include both the regular payments that investors receive and any capital appreciation. One party in a total return swap agrees to make regular payments to the other based on a set rate. This rate may be variable or fixed. The other party makes payments that relate to an underlying asset's returns.

The underlying asset involved in a total return swap is called a reference asset and owned by the party receiving the set rate payments. This asset can either be a loan, bond, or equity interest. Total return swap agreements allow investors to get payments from a financial asset without having to own it. However, they also have to pay a set rate to the other party, as mentioned above.

What are the advantages and disadvantages of Total Return Swaps?

Total return swaps offer investors many advantages. It can be a decent tool for investors that want to participate in leveraged investing. These contracts do not involve the exchange or transfer of an asset between the two parties. Therefore, investors do not need to acquire assets to obtain the benefits or returns from them. This feature can be significantly beneficial for investors that can't afford to invest in financial assets.

On top of that, these agreements are also beneficial to the receivers. They do not have to bear the administrative burden related to transferring assets. They also do not have to give away their financial instruments. However, they can still benefit from the payments they get from the other party. Overall, total return swap agreements can be beneficial for both parties.

However, total return swaps also come with some risks. One of these includes the interest rate risk, which impacts both parties. Any changes in interest rates can be detrimental to both parties. Additionally, investors may also have to bear losses if the underlying asset's value or total returns fluctuate. They have to pay interest regardless of these losses, which can further harm them.

Conclusion

The total return is a term that represents the overall income that investors get on their financial assets. A total return swap is a contract that allows two parties to exchange these returns. One party makes regular payments to the other in exchange for the total returns from an underlying asset. There are several advantages and disadvantages of these swap agreements, as mentioned above.

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