In quantitative finance, the asset price is often modeled as the Geometric Brownian Motion (GBM). The GBM model is a stochastic process that describes the evolution of a price or other measurable quantity over time, assuming that it is subject to small random fluctuations (or "noise") at each point in time. The model is used to price options and other financial derivatives and is also a key ingredient in the Black-Scholes option pricing formula. The GBM model assumes that the autocorrelation of asset returns is zero. Lately, there is some effort devoted to developing asset and options pricing models where the autocorrelation of the underlying asset is non-zero, i.e. the asset is mean-reverting or trending. In this context, Reference [1] examined trading strategies developed based on the autocorrelation property of asset price and volatility, We have investigated strategies for trading stocks based on measures of roughness in their volatility. We have compared long-short strategies based on realized roughness (calculated from high-frequency stock returns) and implied roughness (calculated from option prices). Both measures support a strategy of buying stocks with rougher volatilities and selling stocks with smoother volatilities; but sorting on implied roughness yields higher returns and is more robust to controlling for other factors. In particular, it is robust to controlling for illiquidity and the level of the ATM skew. We have argued that implied roughness provides a measure of near-term idiosyncratic risk: a stock with greater implied roughness is one that the market perceives to have downside uncertainty that will be resolved quickly. On this interpretation, the profitability of our rough- minus-smooth strategy reflects compensation for bearing this risk. The performance of our strategy is enhanced near earnings announcements, when stocks face elevated idiosyncratic risk, and it is suppressed near FOMC announcements, when the dominant near-term risk is systematic. In short, the autocorrelation property, which is embedded in the roughness/smoothness of volatilities, can be exploited to develop profitable investment strategies. This article contributes to a small number of papers that study the trending/mean-reverting property of asset prices in trading and portfolio management. References [1] P. Glasserman and P. He, Buy Rough, Sell Smooth (2018). https://ssrn.com/abstract=3301669 Post Source Here: Trading Strategies Based on Roughness of Volatility
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When it comes to trading, there are a lot of options out there. You can trade stocks, options, futures, Forex, and more. So which one should you choose? In this blog post, we will discuss the pros and cons of options trading vs futures trading. By the end of this post, you will have a better understanding of each type of trade and be able to decide which is right for you. Option TradingPros -You can limit your risk. When you trade options, you can control how much money you lose on a trade. This is because you can buy or sell an option at any time before it expires. -You can make a lot of money in a short period of time. If you time your trades correctly, you can make a lot of money in a short period of time. -You can trade options on stocks, indexes, and commodities. You can trade options on almost any security out there. Cons -You can lose a lot of money in a short period of time. If you make the wrong decision, you can lose a lot of money very quickly. -You need to know what you are doing. Trading options is not as simple as buying and selling stocks. You need to have a good understanding of how they work in order to be successful. Futures TradingPros -You can make a lot of money in a short period of time. Just like options, if you time your trades correctly, you can make a lot of money in a short period of time. -You can trade futures on stocks, indexes, and commodities. You can trade futures on almost any security out there. Cons -You can lose a lot of money in a short period of time. Just like options, if you make the wrong decision, you can lose a lot of money very quickly. -You need to have a lot of money to start trading futures. In order to trade futures, you need to have a margin account. This means that you need to have a lot of money in your account to cover your trades. The difference between options trading and futures tradingOptions are contracts that give you the right, but not the obligation, to buy or sell a security at a specific price on or before a certain date. Futures, on the other hand, are contracts that obligate you to buy or sell a security at a specific price on or before a certain date. Also, with options trading, time decay is a factor you should consider. With futures trading, time decay is not as important of a factor. Similarities between options trading and futures tradingBoth options trading and futures trading involve leverage. This means that you can control a large position with a small amount of money. Another similarity is that both types of trading involve risk. You can make a lot of money, but you can also lose a lot of money. Finally, both options trading and futures trading can be used to hedge risk. For example, if you are long a stock, you can buy a put option to protect yourself from a sell-off. Or, if you are short a stock, you can buy a call option to protect yourself from a rally. Which one is right for you?The best way to decide which type of trading is right for you is to try them both out. See which one you are more successful at and which one you enjoy more. Trading is not a one size fits all activity, so find the type of trading that works best for you. ConclusionIn this blog post, we discussed the pros and cons of options trading vs futures trading. By the end of this post, you should have a better understanding of each type of trade and be able to decide which is right for you. Options trading is a great way to limit your risk, while futures trading can allow you to make a lot of money in a short period of time. However, both types of trading involve risk and should only be attempted by those who have a good understanding of how they work. Post Source Here: Options Trading vs Futures Trading: The Pros, Cons and Difference When you purchase a life insurance policy, you are essentially making an investment for the future. You hope that you will never have to use it, but knowing that it is there if something happens can provide peace of mind. But what happens if you need money now? Is it possible to cash out your life insurance policy? In this blog post, we will discuss 7 tips you need to know before cashing out your life insurance policy. Tip #01: Check the PolicyBefore you cash out your life insurance policy, it is important to check the terms and conditions of your policy. Some policies have a cash surrender value, which is the amount of money that you would receive if you decided to cancel the policy. Other policies may have a death benefit, which is the amount of money that will be paid to your beneficiary if you die. Make sure you understand what is involved in cashing out your policy and how it might affect you financially. Tip #02: Consider the Tax ImplicationsWhen you cash out your life insurance policy, there may be tax implications. For example, if you receive a cash surrender value, you may have to pay income tax on the money that you receive. Make sure you understand how cashing out your policy will impact your taxes and plan accordingly. Tip #03: Consider Your Financial SituationBefore you cash out your life insurance policy, it is important to consider your financial situation. If you are in debt or if you are struggling to make ends meet, cashing out your life insurance policy may not be the best option for you. Make sure you have a clear understanding of your current financial situation and how cashing out your policy might impact your future. Tip #04: Talk to a Financial AdvisorIf you are considering cashing out your life insurance policy, it is important to talk to a financial advisor. A financial advisor can help you evaluate your current financial situation and offer advice on whether cashing out your policy is the right decision for you. Tip #05: Weigh the Pros and ConsBefore making a decision, it is important to weigh the pros and cons of cashing out your life insurance policy. The pros might include the fact that you will receive a lump sum of money that can be used for any purpose. The cons might include the fact that you will have to pay taxes on the money you receive and that you may lose some or all of the money if you die soon after cashing out your policy. Make sure you consider all of the pros and cons before making a decision. Tip #06: Don't Rush into a DecisionWhen it comes to cashing out your life insurance policy, don't rush into a decision. Take the time to evaluate your financial situation and make sure you are making the best decision for yourself and your family. Tip #07: Consider Other OptionsIf cashing out your life insurance policy is not the right decision for you, there are other options available. You might want to consider borrowing money from a friend or family member, taking out a loan, or using a credit card. These options may not be as desirable as cashing out your life insurance policy, but they may be better than doing nothing. ConclusionWhen it comes to cashing out your life insurance policy, there are a number of things you need to consider. Make sure you understand the terms and conditions of your policy, the tax implications, and your current financial situation before making a decision. weigh the pros and cons carefully before making a final decision. If cashing out your life insurance policy is not the right decision for you, there are other options available. Talk to a financial advisor if you need help making a decision. Article Source Here: How to Cash Out Your Life Insurance: 7 Tips You Need to Know Data science is one of the most important and rapidly-growing fields today. But what does data science actually do? In this blog post, we will discuss what data science is and how it can benefit you. We will also cover the different types of jobs that are available in the field of data science. What is data science?Data science is the process of extracting knowledge and insights from large data sets. This process involves using various techniques, such as machine learning, to analyze data and find patterns. The goal of data science is to use these insights to improve decision-making. Data science can be used in a variety of different industries, including finance, healthcare, and retail. In the finance industry, for example, data science can be used to predict stock prices and identify potential financial risks. In the healthcare industry, data science can be used to improve patient care and find new treatments for diseases. And in the retail industry, data science can be used to improve customer service and increase sales. How can data science benefit you?Here are a few ways that data science can benefit you -Data science can help you make better decisions by providing insights into your data. -Data science can help you improve your products and services by identifying trends and patterns in your data. -Data science can help you find new customers and increase sales by predicting customer behavior. -Data science can help you improve your operations by identifying inefficiencies in your data. -Data science can help you protect your company from financial risks by predicting stock prices and identifying potential financial risks. Different types of jobs that are available in the field of data scienceThe field of data science is growing rapidly, and there are many different jobs available in the field. So, if you are interested in data science, now is a great time to get started. There are many different jobs available in the field of data science. Some of the most common jobs include data analyst, data scientist, machine learning engineer, and big data engineer. Data analysts are responsible for organizing and cleaning data sets. Data scientists are responsible for extracting knowledge and insights from data sets. Machine learning engineers are responsible for developing algorithms that can learn from data sets. And big data engineers are responsible for managing large data sets. What is the job prospect for data scientists?The job prospect for data scientists is very good. According to a recent study, the number of jobs for data scientists is expected to grow by 28% in the next few years. So, if you are interested in data science, now is a great time to get started. How to become a data scientist?If you are interested in becoming a data scientist, there are several things you can do to prepare yourself. First, you should learn how to use Python and R, two of the most popular programming languages for data science. You should also become familiar with machine learning algorithms and big data technologies. And Finally, you should develop your problem-solving skills and learn how to think critically. The field of data science is growing rapidly, and there are many different jobs available in the field. So, if you are interested in data science, now is a great time to get started. ConclusionIn this blog post, we have discussed what data science is and how it can benefit you. We have also covered the different types of jobs that are available in the field of data science. And finally, we have discussed the job prospect for data scientists. If you are interested in data science, now is a great time to get started. Article Source Here: What Data Science Does and How It Can Benefit You When it comes to investing your money, there are a lot of options to choose from. You can go the traditional route and talk to a human financial advisor, or you can automate the process with a robo advisor. But what's the difference between algorithmic trading and robo advising? In this blog post, we will explore the key differences between these two investment strategies and help you decide which is right for you. What is a robo advisor?A robo advisor is a computer program that uses algorithms to make investment decisions for you. Robo advisors are designed to be simple and easy to use, so they are a good option for people who don't have a lot of experience with investing. They also tend to be cheaper than human financial advisors, which makes them a popular choice for people who are looking to save money on their investments. What is algorithmic trading?Algorithmic trading is a more complex investment strategy that uses computer programs to make buy and sell decisions for you. Algorithmic traders use sophisticated mathematical models to predict market trends and make trades accordingly. This strategy is often used by professional traders who have a lot of experience with investing. The difference between algorithmic trading and robo advisingSo, what's the difference between algorithmic trading and robo advising? The main difference is that algorithmic trading is a more complex investment strategy that requires a lot of experience and knowledge, while robo advising is a simpler investment strategy that is designed for people who don't have a lot of experience with investing. Similarities between algorithmic trading and robo advisingDespite the differences between these two investment strategies, there are some similarities. Both algorithmic trading and robo advising are designed to be simple and easy to use, and they both tend to be cheaper than human financial advisors. Additionally, both algorithmic trading and robo advising can be used to automate the investment process and help you save money on your investments. Which one is more profitable?That's a difficult question to answer, as it depends on a variety of factors such as your investment goals and the state of the market. However, in general, robo advisors are more likely to be profitable than algorithmic traders, as they are designed to be simple and easy to use. Which one is riskier?Again, this depends on a variety of factors. However, in general, algorithmic trading is riskier than robo advising, as there is more room for error when you are making investment decisions yourself. Which one is right for you?So, which is right for you? If you are a beginner investor and you are looking for a simple and easy-to-use investment strategy, then robo advising is the right choice for you. If you are an experienced investor who is looking for a more complex investment strategy, then algorithmic trading is the right choice for you. Closing thoughtIn this blog post, we have explored the key differences between algorithmic trading and robo advising. We have also discussed the similarities and differences between these two investment strategies. Finally, we have provided our opinion on which one is right for you. We hope this information has been helpful. Originally Published Here: Algorithmic Trading vs Robo Advisor Expenses are a necessary evil, we all have them. You may not think about them every day but they’re always there lurking in the background of your life. They can be overwhelming and stressful if you don’t keep up with them or know what to do when unexpected expenses come up. When it comes to business, expenses are even more important to track and manage. Not doing so can lead to big problems down the road. That's why we've created this guide for you. In it, we'll cover the definition of business expenses, different types of expenses, and some examples to help you get a better understanding. What are ExpensesAn expense is any cost incurred by a company in the course of running its operations. It can be anything from the cost of raw materials to the salaries of employees. These costs can be divided into two broad categories: operating expenses and capital expenses.
Types of ExpensesThere are dozens of different types of expenses, but they can all be classified into one of four categories:
So the first category is the cost of goods sold, or COGS for short. This includes the direct costs associated with making or selling a product, such as the cost of raw materials and labor. It is a crucial number for businesses because it directly impacts their bottom line.
The second category is selling, general, and administrative expenses, or SG&A. This includes all the costs associated with running a business that is not directly related to making or selling a product. These can be things like marketing and advertising expenses, office rent, and employee salaries.
The third category is depreciation and amortization. This includes the costs of wear and tear on assets, such as equipment or vehicles. It's important to note that these costs are not actually cash expenses, but they still need to be tracked and accounted for.
The fourth and final category is taxes. This includes all the various taxes a business has to pay, such as income tax, payroll tax, and sales tax. Now you can't do much to reduce these expenses, but it's still important to be aware of them and account for them in your financial planning. Examples of ExpensesNow that we've covered the basics, let's take a look at some specific examples of expenses.
ConclusionSo there you have it. Now you know what expenses are and some of the different types that businesses have to deal with. Keep in mind that this is just a brief overview and there are many other types of expenses not covered here. But if you're just starting out in business, this should give you a good foundation to work from. Post Source Here: Expenses: Definition, Types, Examples Inflation is a hot topic in the world of economics. But what is it, exactly? Inflation is defined as a sustained increase in the general level of prices for goods and services. It occurs when the demand for goods and services exceeds the available supply. This can be caused by many different factors, such as an increase in population or a rise in the cost of production. In this blog post, we will explore how often inflation occurs and what causes it. How often does inflation occurInflation can occur in any country, at any time. It is a global phenomenon that affects all economies. Inflation rates vary from country to country and from year to year. They also depend on the type of economy. For example, developing countries typically have higher inflation rates than developed countries. Specifically, the average inflation rate in the United States is about three percent. Strong inflation rates can cause serious problems for an economy, such as higher prices for goods and services, unemployment, and a decrease in the value of money. It happened in the 1970s in the United States and it is happening in Venezuela right now. What causes inflationThere are many factors that can cause inflation. Some of the most common causes are: - An increase in the money supply - An increase in population - A rise in the cost of production - A decrease in the value of money - A war - Natural disasters Each of these factors can cause inflation in different ways. For example, an increase in the money supply can lead to an increase in prices, while a rise in the cost of production can lead to a decrease in the availability of goods. It is important to understand the factors that can cause inflation so that you can protect yourself from its harmful effects. How will the governments fight inflation?Governments around the world are always trying to find ways to fight inflation. They do this by implementing policies that will increase the availability of goods and services, and by controlling the money supply. They also try to keep the cost of production down. However, these measures are not always successful. In some cases, inflation can get out of control, leading to serious economic problems. How does inflation affect my finances?Inflation can have a serious impact on your finances. It can cause the value of your money to decrease, making it harder to buy goods and services. It can also lead to higher prices and unemployment. For this reason, it is important to protect yourself from the harmful effects of inflation. One way to do this is to make sure that you have a diversified investment portfolio. This will help you to protect yourself from the fluctuations in the market. ConclusionIn conclusion, inflation is a global phenomenon that affects all economies. It occurs when the demand for goods and services exceeds the available supply. There are many factors that can cause inflation, such as an increase in the money supply or a rise in the cost of production. Governments around the world are always trying to find ways to fight inflation, but it can be difficult to control. In some cases, inflation can get out of control, causing serious economic problems. You can protect yourself from the harmful effects of inflation by making sure that you have a diversified investment portfolio. Originally Published Here: How Often Does Inflation Occur? You are certain to come across the P/E ratio in various areas as an investor. Although simple, it can be significantly useful when evaluating companies. We have covered the P/E ratio before. In this article, we will provide concrete examples of how to use it. An online calculator is presented at the end of this post. What is the P/E Ratio?The P/E ratio is a relative measure of a company’s stock price to its earnings per share (EPS). It has been one of the most reliable ratios for investors when valuing companies. Although you can use other financial ratios, the P/E ratio is straightforward to calculate. The P/E ratio tells you how much money you pay for every $1 earned from the investment. This information can be valuable when investing in companies based on their relative returns. However, it is crucial to know why, when, and how to use the P/E ratio. Why do we use the P/E Ratio?A company’s P/E ratio shows you the relative value of its shares. However, it is not helpful on its own. You must use the P/E ratio comparatively to reap maximum benefits. Nonetheless, it can help you decide between various stock investment options when used comparatively. The P/E ratio can help determine the growth to expect when investing in companies. On top of that, it can be an indicator of the market as a whole to compare companies from the same industry. However, we recommend using this ratio with other financial ratios for the best results. How to use the P/E Ratio?Using the P/E ratio is straightforward. First, you need to select some companies for analysis. For each, you must obtain their stock price and earnings per share. You can get this information from various sources. Once you have those items, you can put them in the following formula. P/E Ratio = Share Price / Earnings Per Share (EPS) You must also understand what the P/E ratio means. Usually, a high P/E ratio can help identify companies with growth stocks. On the other hand, a low P/E ratio shows a value stock. However, each of these can have an adverse side to them. Where to use the P/E ratio?We recommend you use the P/E ratio as a primary analysis tool. Similarly, it provides the best results when used comparatively between similar companies. Don't use the P/E ratio on its own or for advanced stock analysis. In these cases, you won't get the desired results. Furthermore, don't use the P/E ratio as the only tool when analyzing various companies. We recommend utilizing the ratio as a part of several other tools. You can also use other versions of P/E ratios to enhance your decision-making. ExampleYou can obtain a company's P/E ratio from various sources. We recommend using Yahoo Finance as it provides different versions of this ratio. First, you must find the company on the platform. For this example, let's consider Tesla Inc. (TSLA). When you find Tesla on Yahoo Finance, you can get its P/E ratio for the last 12 months under the "Summary" tab. You can also visit the “Statistics” tab for further information and analysis. Other types of the P/E ratio are available under the “Valuation Measures” section. ConclusionThe P/E ratio is an essential financial ratio to determine a company's value. However, you must use it comparatively. It is readily available on various platforms once you find your desired company. We recommend you add it as a part of your analysis tools. CalculatorUse the dropdown menu highlighted in yellow to choose the stock. Post Source Here: P/E Ratio: Calculator, Example When it comes to trading, there are two main types: option trading and equity trading. Both have their pros and cons, which we will discuss in this blog post. Equity trading is the more traditional type of trading, where you buy and sell shares of stock in publicly traded companies. Options trading is a bit more complex but can be more profitable if done correctly. Let's take a closer look at the pros and cons of each type of trading. The difference between equity trading and option tradingThe difference is that with equity trading, you are buying and selling shares of stock in publicly traded companies. This means that the price of the stock is determined by the market, and you can sell your shares at any time. With options trading, you are buying the right to buy or sell a certain amount of stock at a certain price within a certain time period. This means that the price of the option is determined by the market, and you can sell your option at any time. The pros and cons of equity tradingThe pros of equity trading are that it is a very liquid market, meaning that you can buy and sell shares quickly and easily. The cons of equity trading are that the stock prices can be volatile, meaning they can go up and down quickly, and you can lose money if you sell your shares at the wrong time. The pros and cons of option tradingThe pros of options trading are that options allow us to construct limited-loss positions. For example, we can buy a put option to protect ourselves against a market decline. The cons of options trading are that options can be expensive, and they can expire worthless if the stock price doesn't move in the right direction. Also, analyzing option positions is a complex process. Which type of trading requires less capital?This is a difficult question to answer, as it depends on the individual trader and the type of trading they are doing. With equity trading, you typically need to have a lot of capital, as you are buying and selling shares of stock. With options trading, you only need to have enough capital to purchase the option. However, if you are wrong about the direction of the stock price, you can lose a lot of money. Which type of trading requires less experience?Again, this is a difficult question to answer, as it depends on the individual trader and the type of trading they are doing. With equity trading, you typically need to have a lot of experience, as you are buying and selling shares of stock. With options trading, you can start trading with a small amount of capital, and you don't need to be as experienced. However, if you are wrong about the direction of the stock price, you can lose a lot of money. Which type of trading is riskier?Equity trading is riskier than options trading, as the stock prices can be volatile and you can lose money if you sell your shares at the wrong time. Options trading is less risky than equity trading, as the options allow us to construct limited-loss positions. However, if you are wrong about the direction of the stock price, you can lose a lot of money. Which type of trading is more complicated?Option trading is more complicated than equity trading, as you need to understand the concept of options in order to trade them correctly. Equity trading is less complicated than options trading, as you only need to understand the basics of the stock market in order to trade. ConclusionIn conclusion, both equity trading and options trading have their pros and cons. It ultimately comes down to what type of trader you are and what you are comfortable with. Originally Published Here: Options Trading vs Equity Trading Data science and machine learning are advancing at a rapid pace. They're now being applied in areas as diverse as healthcare, retail, marketing, and finance. However, a key question that still needs to be answered is: how much data do you need to train these models? The answer, it turns out, is not always more data. In some cases, using too much data can actually hurt the performance of your machine learning models. In this context, Reference [1] argued that more data is not always better, Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of keeping around an infinite supply of older (less relevant) data. In addition, we argue that increasing the stock of data by including older datasets may, in fact, damage the model’s accuracy. Expectedly, the model’s accuracy improves by increasing the flow of data (defined as data collection rate); however, it requires other tradeoffs in terms of refreshing or retraining machine learning models more frequently. The paper also pointed out that the value of a firm does not scale with its stock of data, This result, coupled with the fact that older datasets may deteriorate models’ accuracy, suggests that created business value doesn’t scale with the stock of available data unless the firm offloads less relevant data from its data repository. Consequently, a firm’s growth policy should incorporate a balance between the stock of historical data and the flow of new data. What implication does this paper have for trading and portfolio management? Should we use more data? The short answer is probably no. In fact, using more data can actually lead to sub-optimal results. The reason is that, in the financial world, data is often noisy and contains a lot of irrelevant information. If you use too much data, your machine learning models will end up picking up on this noise, which can lead to sub-optimal results. So how do we use data for trading? Let us know in the comments below. References [1] Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. Time and the Value of Data. Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.) Article Source Here: Machine Learning: Is More Data Always Better? |
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