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.
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.
Post Source Here: What is an Angel Investor?
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.
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.
Post Source Here: Why is Econometrics Important in Business?
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.
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.
Post Source Here: Is Private Equity an Alternative Investment?
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.
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.
Article Source Here: What is the Difference Between Statistics and Econometrics?
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.
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.
Article Source Here: What is an Infrastructure Fund
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  that demonstrated the usefulness of advanced volatility estimators in trading by reducing trading strategies’ turnover.
On the same topic, Reference  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 , 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?
 Baltas, Nick and Kosowski, Robert, Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations. "Market Momentum: Theory and Practice", Wiley, 2020
 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?
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.
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.
Originally Published Here: Performance-Based Fees of Investment Advisors
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:
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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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.
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.
Post Source Here: Econometrics vs Actuarial Science
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  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:
Finally, we also find the results regarding Bitcoin volatility interesting and relevant.
 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