Questions related to Trading
Currently I am working in the internship program at Arihant capital which is based on the trading and brokering the stock market. my college have made me resarch on the my internship organization so please provide me the perfect tittle.
RSI vs MACD: Mastering Key Trading Indicators for Better Results | L-25
Welcome to our latest video where we dive deep into two of the most powerful technical indicators in trading: the Relative Strength Index (RSI) and the Moving Average Convergence Divergence (MACD). In this comprehensive guide, we explain what RSI and MACD are, how they are calculated, and how you can use them to enhance your trading strategies. Whether you're a beginner or an experienced trader, understanding these tools can help you make more informed trading decisions.
We'll cover:
The basics of RSI and MACD
Step-by-step calculations
Practical examples and real-world applications
Tips for combining RSI and MACD for better trading signals
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If so can we apply the approach for Market Regime Detection?
Market regime detection is an important problem in finance, as it involves identifying shifts in the behavior of financial markets over time. Understanding these shifts can help investors to manage risk and develop more effective trading strategies. The research paper "Causal deconvolution by algorithmic generative models" describes a method for inferring causal relationships between variables using algorithmic generative models. This study proposes to apply this method to the problem of market regime detection, with the aim of identifying causal relationships between different market variables and detecting changes in market regimes.
First of all, what is the most optimal way to represent market information in a cell configuration?
Then, how do we auto-discover and extract features from such space-time diagrams?
The History of Reserve Currencies
Lets begin with understanding money as liquid, which is how CHINESE describes MONEY as WATER.
MONEY as WATER & LIQUIDITY
The expression "money is like water" is often attributed to Chinese culture, and it reflects a particular mindset about wealth and its fluid nature. While not everyone in China may use this expression, it does capture a common attitude towards money. Here are some reasons why money is sometimes metaphorically equated with water in Chinese culture:
- Fluidity and Circulation: Water is fluid and can flow easily. Similarly, the idea is that money should not be stagnant but should circulate and flow smoothly through various channels of the economy. This concept emphasizes the importance of keeping money in motion to generate economic activity.
- Adaptability: Water can take the shape of its container and adapt to different forms. Money, too, is seen as something that should be adaptable and flexible. The ability to adapt to different financial situations is valued, and the metaphor highlights the importance of being nimble in financial matters.
- Renewal and Growth: Water is essential for the growth of plants and sustaining life. Money, in a similar sense, is considered crucial for economic growth and development. The metaphor emphasizes the idea that money, like water, is essential for sustaining and fostering prosperity.
- Symbol of Abundance: In Chinese culture, water is often associated with abundance and prosperity. The metaphor of money being like water might convey the idea that there is an abundance of financial opportunities and resources available, and one should tap into them wisely.
- Flowing Fortunes: The phrase could also imply that fortunes, like water, are ever-changing. What may be plentiful today might be scarce tomorrow, emphasizing the importance of being mindful of financial fluctuations and making sound financial decisions.
CO2 as LIQUIDITY
If we conceptualize CO2 as liquidity rather than a gas or vapor, we are essentially considering carbon dioxide as a form of tradable liquid asset that represents environmental impact. This approach adds an additional layer to the integration of CO2 into a financial system. Here's how this could be incorporated into the concept:
- CO2 Liquidity Units: Instead of carbon credits, introduce the concept of CO2 liquidity units. These units would represent a standardized measure of carbon emissions that can be bought, sold, or traded in the market.
- Liquid Carbon Market: Establish a liquid carbon market where entities, including businesses, governments, and individuals, can buy and sell CO2 liquidity units. This market would function similarly to financial markets where liquidity is traded.
- Carbon Liquidity Exchanges: Create specialized carbon liquidity exchanges where participants can engage in the buying and selling of CO2 liquidity units. These exchanges would operate alongside traditional financial exchanges.
- Liquidity Providers: Designate entities, such as environmental organizations or sustainable initiatives, as liquidity providers. These entities would contribute to the market by removing excess CO2 liquidity units from circulation through activities like carbon sequestration or environmental projects.
- Centralized Liquidity Authority: Establish a centralized authority responsible for regulating and overseeing the CO2 liquidity market. This authority would manage the overall liquidity supply, adjusting it based on environmental goals and targets.
- Carbon-backed Liquidity Reserves: Implement carbon-backed liquidity reserves to stabilize the value of CO2 liquidity units. These reserves would function similarly to central bank reserves in traditional financial systems.
- Carbon Liquidity-backed Financial Instruments: Develop financial instruments, such as bonds or loans, that are backed by CO2 liquidity units. This would provide a way for financial markets to support sustainable projects, similar to green bonds.
- Liquidity-based Incentives: Introduce incentives for entities to maintain or increase their liquidity levels. Those who reduce their carbon emissions and maintain a surplus of CO2 liquidity units could benefit financially, while those with deficits would face higher costs.
- Real-time Liquidity Monitoring: Implement advanced monitoring systems for real-time tracking of carbon liquidity levels. This transparency would enable better decision-making and responsiveness to changes in environmental conditions.
- Education and Adoption: Promote education and awareness about the CO2 liquidity system to ensure widespread understanding and adoption. Stakeholders, including businesses and individuals, need to grasp the concept of CO2 as a form of liquid asset.
This conceptualization aims to integrate the idea of liquidity into the carbon economy, treating CO2 as a tradable liquid asset with a value that can be influenced by market forces. It introduces the dynamics of supply, demand, and liquidity management into the broader context of environmental sustainability. As with any innovative financial system, careful planning, regulation, and adaptation are crucial for its successful implementation. Additionally, it's essential to consider potential unintended consequences and continually assess the system's effectiveness in achieving environmental goals.
MONEY & CURRENCIES PEGGED to CO2 as LIQUID SUPPLY & DEMAND
Here's a conceptual approach to a real-world system where money is pegged to CO2 supply and demand:
- Carbon Credits as Tradable Assets: Implement a system where carbon credits become tradable assets, similar to stocks or bonds in financial markets. These carbon credits would represent the right to emit a certain amount of CO2.
- Carbon Pricing Mechanism: Introduce a carbon pricing mechanism, such as a carbon tax or cap-and-trade system. This places a cost on carbon emissions, creating a direct economic incentive for businesses and individuals to reduce their carbon footprint.
- Centralized Carbon Authority: Establish a centralized carbon authority responsible for issuing and regulating carbon credits. This authority would control the overall supply of carbon credits in circulation, adjusting it based on environmental goals and targets.
- Currency Pegged to Carbon Credits: Create a new form of currency that is directly pegged to the supply of carbon credits. The value of this currency would be tied to the overall carbon emissions allowed within a specified period.
- Carbon Reserve System: Implement a carbon reserve system, similar to a central bank's reserve system, to manage fluctuations in carbon credit supply and demand. The reserve would be used to stabilize the value of the carbon-backed currency.
- Incentives for Carbon Reduction: Offer financial incentives for businesses and individuals to reduce their carbon emissions. Those who emit less than their allocated carbon credits could sell their excess credits, while those exceeding their limit would need to buy additional credits.
- International Carbon Exchange: Facilitate an international carbon exchange where countries can trade carbon credits, fostering global cooperation in addressing climate change. This exchange would allow nations to balance their emissions by buying and selling credits on the international market.
- Carbon-backed Financial Instruments: Develop financial instruments such as bonds or loans that are backed by carbon credits. This could encourage investments in sustainable projects and provide a way for financial markets to support environmentally friendly initiatives.
- Carbon Auditing and Verification: Implement rigorous carbon auditing and verification processes to ensure the accuracy and legitimacy of carbon credit transactions. This would prevent fraud and maintain the integrity of the carbon-backed currency.
- Transition Period and Education: Recognize that transitioning to a carbon-backed currency would require careful planning and education. Governments, businesses, and the public would need to understand the new system and its implications.
It's important to note that while this concept provides a real-world approach, it is highly complex and would face numerous challenges, including international cooperation, regulatory frameworks, and the need for a robust infrastructure to manage the carbon credit system.
The CARBON COIN/ DOLLAR
Pegging an international currency to a conception of CO2 reduction involves linking the value of the currency to the success and progress of global efforts in reducing carbon emissions. Here's a conceptual framework for how this might be achieved:
- Creation of a Carbon-Backed International Currency: Develop a new international currency, let's call it "CarbonCoin" for illustration purposes, directly pegged to the global reduction of carbon emissions. The value of CarbonCoin would be tied to the success in achieving predetermined global CO2 reduction targets.
- Global Carbon Reduction Targets: Establish ambitious and scientifically informed global carbon reduction targets. These targets would serve as the benchmark against which the value of CarbonCoin is pegged. The more successful the world is in meeting these targets, the stronger the value of CarbonCoin.
- Carbon Reduction Verification Mechanism: Implement a robust and transparent global mechanism for verifying carbon reduction efforts. This could involve international organizations, technological solutions, and agreements that ensure accurate reporting and accountability for CO2 reductions.
- CarbonCoin Reserve System: Create a global CarbonCoin reserve system that stores CarbonCoins in proportion to the cumulative global CO2 reductions achieved. This reserve would act as a backing for the international currency, similar to gold backing traditional currencies in the past.
- International CarbonCoin Authority: Establish an international authority responsible for managing the CarbonCoin system. This authority would oversee the pegging process, verify carbon reductions, and adjust the supply of CarbonCoins in circulation based on global progress toward emission reduction goals.
- CarbonCoin Exchange Mechanism: Develop a global exchange mechanism for CarbonCoins, where countries and entities can buy, sell, and trade CarbonCoins based on their individual and collective contributions to CO2 reduction. This exchange would influence the value of CarbonCoin in the international market.
- CarbonCoin as a Reserve Currency: Promote the use of CarbonCoin as a reserve currency alongside traditional fiat currencies like the U.S. dollar or the euro. Countries could hold CarbonCoins in their reserves as a way to demonstrate and support their commitment to environmental sustainability.
- Incentives for Carbon Reduction: Offer financial incentives for countries and entities that contribute significantly to global CO2 reductions. This could involve rewarding nations with additional CarbonCoins based on their achievements in emission reduction.
- CarbonCoin-Backed Bonds and Financial Instruments: Introduce financial instruments, such as bonds, loans, or investment products, that are backed by CarbonCoins. This would create a market for sustainable investments and encourage the allocation of funds to projects contributing to CO2 reduction.
- International Cooperation and Agreements: Encourage international cooperation through agreements and treaties that support the CarbonCoin system. Cooperation would be vital to the success of this currency peg, requiring commitments from nations to pursue and maintain effective carbon reduction policies.
Implementing such a system would require significant coordination, cooperation, and commitment from the international community. It would also involve addressing challenges such as varying levels of economic development, differing national priorities, and potential resistance to adopting a new international currency system. Additionally, technological advancements in monitoring and verification of carbon reduction efforts would play a crucial role in the success of this conceptual framework.
How Pegging CO2 as LIQUIDITIES to CURRENCY EXCHANGES can OVERCOME EXISTING INERTIA to CO2 REDUCTION
Pegging CO2 as liquidities to currency exchanges could potentially introduce innovative financial mechanisms to overcome hurdles in CO2 reduction efforts. Here are ways in which this approach might help address challenges:
Market-Driven Incentives:
How it Helps: By pegging CO2 as liquidities to currency exchanges, you create a market for trading carbon assets. This introduces market-driven incentives for businesses and nations to reduce emissions, as they can profit from selling excess carbon liquidities or face costs for exceeding their allocated limits.
Flexibility and Adaptability:
How it Helps: Liquid markets are often more flexible. This flexibility can be harnessed to adapt to varying circumstances, allowing entities to buy or sell carbon liquidities based on changing economic conditions or technological advancements. It provides a dynamic system that can adjust to evolving emission reduction challenges.
Global Collaboration through Trading:
How it Helps: A liquid carbon market could facilitate global collaboration. Countries with a surplus of carbon liquidities can trade with those facing challenges, promoting a more efficient allocation of resources for emissions reduction. This approach encourages a collaborative, international effort to achieve overall reduction targets.
Liquidity-Backed Investments:
How it Helps: The concept of CO2 liquidities as a tradable asset could attract investments in sustainable and low-carbon projects. Financial instruments backed by carbon liquidities, such as bonds or green funds, may become attractive to investors, funneling capital into initiatives that contribute to emission reduction.
Transparent Market Mechanism:
How it Helps: Liquid markets often operate with a high degree of transparency. This transparency could help overcome challenges related to verification and trust. It ensures that the buying and selling of carbon liquidities are conducted with integrity, minimizing the risk of fraudulent activities.
Carbon Liquidity Reserves:
How it Helps: Establishing reserves of carbon liquidities can act as a stabilizing mechanism. During economic downturns or unexpected challenges, entities can tap into these reserves to meet emission reduction targets without facing excessive financial burdens, promoting long-term stability in carbon markets.
Economic Growth with Emission Reduction:How it Helps: Liquid carbon markets could provide a mechanism for balancing economic growth with emission reduction. As economies grow, they may need additional carbon liquidities, which can be acquired through the market. This allows for economic development while ensuring adherence to overall carbon reduction goals.
Private Sector Participation:
How it Helps: Liquid carbon markets could attract greater participation from the private sector. Businesses can actively engage in emissions reduction efforts by buying and selling carbon liquidities, aligning their financial interests with environmental goals and contributing to a more sustainable economy.
Carbon-Backed Financial Instruments:
How it Helps: The creation of financial instruments backed by carbon liquidities, such as carbon futures or options, could provide businesses and investors with tools to manage and mitigate risks associated with emissions. This can enhance financial planning and encourage long-term sustainability.
Public Awareness and Engagement:
How it Helps: A liquid carbon market could be designed to include public participation, allowing individuals to buy and sell carbon liquidities. This engagement can increase public awareness and encourage environmentally conscious behavior, as individuals see a direct link between their actions and the carbon market.
While pegging CO2 as liquidities to currency exchanges introduces potential benefits, it's crucial to recognize that implementing such a system would still require careful design, international cooperation, and ongoing monitoring to ensure its effectiveness in promoting meaningful CO2 reduction. Additionally, considerations for potential market manipulation, regulatory frameworks, and social equity issues should be addressed in the development and implementation of this approach.
The POLITICAL ECONOMY of CARBONCOIN
A political economist would likely analyze the concept of pegging CO2 to currency exchanges from a multidimensional perspective, considering the economic, political, and social implications of such an approach. Here are some aspects a political economist might consider:
Economic Efficiency:
Analysis: A political economist would assess whether pegging CO2 to currency exchanges promotes economic efficiency by creating market-driven incentives for emissions reduction. They might evaluate the efficiency of the proposed carbon market in allocating resources and encouraging innovation in low-carbon technologies.
Distributional Effects:
Analysis: Political economists would scrutinize the distributional effects of the proposed system. They might investigate how the costs and benefits are distributed among different socioeconomic groups, regions, and nations. Consideration would be given to whether the approach exacerbates or mitigates existing inequalities.
International Cooperation:
Analysis: Political economists would study the feasibility of achieving international cooperation through a liquid carbon market. They might analyze the political dynamics and power structures among nations, assessing whether the proposed system provides sufficient incentives for countries to collaborate on emission reduction efforts.
Policy Instruments and Instruments Choice:
Analysis: Political economists would examine the choice of policy instruments within the proposed framework. They might consider the use of market-based mechanisms, regulatory approaches, and the role of government intervention. The analysis would explore how different policy instruments align with political and economic ideologies.
Political Will and Implementation Challenges:
Analysis: Political economists would assess the political will required to implement and sustain such a system. They might analyze potential political resistance, lobbying efforts, and the ability of governments to commit to long-term emission reduction targets, considering the political economy of climate change policies.
Environmental Justice:
Analysis: Political economists would scrutinize the environmental justice implications of the proposed approach. They might assess whether the system disproportionately affects vulnerable communities or if it addresses historical disparities in environmental burdens.
Role of Private Sector and Corporate Influence:
Analysis: Political economists would consider the role of the private sector within the proposed framework. They might analyze how corporations influence policy decisions, whether the approach aligns with corporate interests, and how the involvement of the private sector may impact the effectiveness of emission reduction efforts.
Policy Stability and Long-Term Commitments:
Analysis: Political economists would evaluate the stability of the proposed system over the long term. They might consider the potential for policy reversals with changes in government or economic conditions, assessing the resilience of the system to political volatility.
Global Governance and Institutions:
Analysis: Political economists would examine the global governance structures and institutions needed to support the proposed system. They might explore the role of international organizations, the effectiveness of existing institutions, and the need for new forms of global governance in managing a liquid carbon market.
Public Perception and Democratic Legitimacy:
Analysis: Political economists would consider how the public perceives the proposed approach and whether it aligns with democratic principles. They might assess the level of public engagement, participation, and the legitimacy of decision-making processes in shaping climate policies.
In essence, a political economist would analyze the proposed approach within the broader context of political and economic systems, considering its implications for power dynamics, social equity, and the overall political economy of climate change mitigation. This multidimensional analysis would provide insights into the feasibility, effectiveness, and potential challenges associated with pegging CO2 to currency exchanges.
Image Source: https://www.investopedia.com/terms/c/currency-peg.asp
Hello!
I am currently researching labor investment costs in Fremont stone bead production, and I am planning on setting up an experiment where I test stone bead production techniques in order to understand labor costs in the production of beads in Fremont society. I have run into a bit of a barrier in my literature review where I cannot find very many resources that cover the topic of stone bead production in the Great Basin, let alone stone bead production within the Fremont material record. There are plenty of papers about shell bead production and trading, but not as many for stone beads. I am primarily looking for any previous studies that may have already covered the topic of stone bead production or any previous experiments testing labor investment in bead production. I am also looking for any ethnographic data on stone bead production techniques, similar to what has been observed in the Fremont material record. Any help is greatly appreciated, thank you!
Hi, which peer to peer energy trading simulation software do you recommend? I will have to carry out a thesis activity.
Thanks everyone for the replies!
For each type of RL-based algorithms, it is necessary to define an appropriate environment till agents can interact in it and learn based on their states and actions. In python programming, how is this environment defined for energy market (P2P trading)?
I am conducting an event study on the volume-inducing effects of technical analysis signals generated by the RSI, MACD, and SMA indicators in the Baltic stock market. With this regard, technical analysis signals are considered as an event in my model while abnormal volume is the expected effect.
Since technical trading signals happen on almost a daily basis, my data set is likely to contain overlapping event dates. How should I deal with this?
Igbo apprenticeship scheme is a master- apprentice economic model that operates largely in southeast Nigeria and which contributes to self reliance and economic development of the predominantly trading indigenous people of the area.
I have got weekly auction data of 91-day t bill along with date of issue and cut-off implicit yield. I have read one paper they converted this data into daily by dividing the yield by number of trading days following the issue. I can't understand this line. I am attaching the excel file of data I have got and the paper. Someone please helo me asap.
I'm implementing a pairs trading strategy.
I am working on peer to peer energy trading and I want to simulate a P2PETS for that I need a benchmark or real data, Anyone can help?
Hi All,
Is it possible to use GARCH with Fama French 3 or 5 factor models? Is there any article that uses this technique and I can refer to it?
I want to study the impact of option trading on volatility and underlying stock price.
I’m looking for a data source for country specific cryptocurrency trading volume
I want to know about the current status of carbon trading in agriculture for C sequestration or mitigation.
Thanks.
I have just started research for my dissertation as an Electronic Engineer and want to look into the use of an automated market maker for Peer to Peer electricity trading.
An automated market maker is a method of settling trades whereby a buyer and seller make trades out of a centralised liquidity pool. This method allows for traders to make trades whenever they want to and also without having to be matched to a corresponding buyer. You can read more here https://medium.com/balancer-protocol/what-is-an-automated-market-maker-amm-588954fc5ff7.
One of the drawbacks of such a system is that buyers and sellers are not matched and therefore it is harder to ensure that the electricity sold and electricity bought are exactly equal (as is required in a power system)? Do you think that this drawback will render an automated market maker impractical?
Is it possible to use the Synthetic Control Method in the firm-level study?
Currently, I am trying to measure the impact of environmental regulation (state-level emission trading scheme) on a firm's green innovation. I have used DID and PSM-DID but want to use SCM with firm-level data, is it applicable? I found most of the paper used state-level data. Expecting your kind opinion in this regard.
I am an EMBA student, and I plan to do my thesis on the Forex market In the Kurdistan region of Iraq to find out about the impacts it will have on the economy and comprehend the financial situations of those traders that trade on Forex platforms. This information then is used to determine whether Forex trading affects the employment rate or not.
My initial intention is to analyze stock prices after firms have successfully emerged from bankruptcy (post-emergence date), as relevant literature report abnormal high returns after emergence. The complication is that there is a period of time where stocks are often suspended from trading during the chapter 11 process.
The average time between the bankruptcy filing and the official emergence date is around 300 days, meaning there is a gap in stock returns for firms under Chapter 11 process. Furthermore, firms may cancel the old stock and issue new stock on the emergence day.
Given this, I would like to know if this is a correct way of performing an event study: to use pre-bankruptcy stock prices as estimation window and post-emergence stock prices as event window?
Hi everyone,
I am doing my research related to IPOs long term performance. For the BHAR formula, I just want to confirm the formula is that always compared with the first trading day price, or is compared with last month trading price?
Simply, I calculated 1+Rit (a) and (b), which one is the correct one used in BHAR formula?
Exactly from which date gold options are introduced on gold futures in India and on which derivatives exchange.
is the historical data on gold options( option price,strike price, open interest, no. of contracts etc.,) available. if so, from which data?
please let me know
thanks in advance
When the value of our Trading Account is PI and our cash is equal PI-qS.
q is number of shares of stock (S).Where q is between one and minus one.(why?)
we know:
- dPI=r(PI-qs)ds+qds
- ds=s(mu)dt+s(sigma)dX
hello,
currently i am doing an analysis on a research with the topic "role of stock exchange markets," and i have these two variables which i can't find its measures. one is domestic turnover ratio and the other is liquidity (stocks), and the only available data that i have are turnover, trading volume, closing prices and shared issues of the companies. my Main question is how can i measure those variables using these datum that i have acquired?
emission certificates (EUA), which are determined by the EU emission trading system (ETS) as the carbon price
I am interested to pursue my PhD Finance in the following topic:
"High Frequency Trading or HFT and Robo-advisors in Investing - FinTech in investment management, Investech".
I am wondering:
If it is a feasible topic for PhD?
Which methododology would I need to use to research the topic?
Will I be able to get the required data?
Which data sources are accessible to get data for this topic?
Can someone in the field of finance and investing guide me please in this regard?
Thank you in advance for those commenting on my post.
I am learning ml, data science for data crunching of financial market data for my trading in financial market . I want to make a terminal which takes live data from NSE and do certain task(some calculation , graph representations ,ml model to run on data )but don't know is it possible with ml and python or have to go through whole software development road . so pls help me to figure out what i need to learn for this and how to do this .
Respectfully
Hello,
I try to predict daily stock market movements of German DAX using the SVM. As input features in want to take the daily changes of several stock markets. The problem is that different stock markets have different holidays which results in missing data (on trading days of the DAX). I get the data from Yahoo Finance. For example the S&P500 has similar trading days as the DAX with just a few days missing (1-2 days in a row).
The trading days of SSE composite vary more significantly from the ones of the European markets, sometimes 5 days in a row are missing.
Studies use different approaches on that topic. Some take the linear interpolated data between two trading days. This seems problematic because in reality, investors do not have these informations of market trends when the SSE is closed. Other studies remove the missing data with the changes of the previous day. Here a sequence of days would have the same values which could cause difficulties.
What would you recommend to deal with this issue? Should I remove all data, where at least one stock market is missing, from the training and test set (~8% of data set) and use the changes to the previous trading day of every individual stock markets?
Thank you in advance!
Hello, I am working on an educational/academic project on stock trading bots (both utilizing DL, RL or DL+RL). Found lots of resources over GitHub, Blogs, GScholar etc. Wish to have some responses on this topic from experts over here on how to proceed or how/which (SOTA) one to follow. Thanks.
Hi,
I have submitted a paper on Journal of Stock and Forex Trading of Longdom publication. I have already paid the APC. Now their staffs have stopped communicating with me. What should I do now?
Thanking you in advance.
It is said tha derivatives trading operation are very risky. Can anybody suggest reading material addressing the historical issues and challenges faced in derivatives trading and managing their risk. I have to compile a report regarding previous historical issues and challenges faced , and what we have learnt from such challenges?
I am conducting research on a stock trading app. I need technical guidance from someone who deals with stock trading. Need to make the questionnaires for the survey.
For my research work I have identified the following variables; Supply chain management practices, organisation performance and level of information sharing with trading partners.
Am using agro dealers and my variables are based on
Am using agro dealers and my variables are based on Supply chain management practices, organisation performance and level of information sharing with trading partners.
Is it better to have a Lot of bitcoins compared to rather having a lot of paper money or savings at the bank ? Thoughts
#cryptocurrency #money #bank
Daily stock price data. Daily trading volume. Annual Dividends. Tax rates on capital gains and dividend. Ex dividend dates.
I'd like to investigate if we can observe some level of self-similarity in the distributions of intra-day versus daily returns of stocks and stock indexes.
If the intra-day returns are sampled at 5 minute intervals there would be 78 periods in a trading day, assuming a regular 6.5 hour day. In that case to compare intraday results to day results you'd multiply the 5 min geometric returns, essentially ln(Pn/Pn-1) by 78.
Where you run into issues is when you look at different short-term periods say 1min versus 5min which can have relatively similar returns at times but then vastly different implied daily returns. For instance, if your 5min return was say 0.001% and using the 78 periods it will generate about 0.078% daily and 21.7% annualized (252 days). But one could hypothesize that 5min returns won't look vastly different from say 1min returns and mapping 1min returns using the same approach will result in about 0.39% daily and about 167% annualized returns.
Also, if one was to look at say 24 hour forex or futures markets using the same approach would again result in many more 5min or 1min intervals with vastly different results.
Can you recommend any papers or share some theoretical work of scaling factors to map intra-day returns to daily returns? Thanks in advance!
Hello,
My area of research is to valuate Exchange option (Margrabe option). I am looking for Monte Carlo simulation technique that can be applied to some real trading data. I have evaluated them using Liu process and wish to compare my results with simulation. In excel I prepare basic model based on Margrabe formula, but results deviate. Thanks in advance.
Shorting or going long in the stock and Fx markets are popular trading strategies — I'm curious to know if a similar approach can be adopted for alternative asset classes such as Art.
Art exchanges are booming, allowing investors worldwide to trade art on a much more liquid and 'transparent' market. To what extent can we see significant profits by using the same trading strategies in the financial markets? Has anyone tried this yet?
* am conscious that the expected return on prices of Art can be a lag
Standard Deviation is the difference between the true closing price and the average price or average closing price.
I'm working on a proposal for my bachelor thesis and I am looking for areas to work on in the conjunction between Reinforcement Learning and Finance(I have some application domain knowledge in finance). I'm aware about the work being done in using RL for stock trading. I was considering using Advanced RL techniques like Rainbow etc for stock trading but don't know if it's a good enough proposal and whether it's been done before.
any Thoughts on this question will help me
Thanks
Looking to simulate energy trading between multiple residential units. It is not blockchain based however any recommendations would be highly appreciated !
Hi,
I am conducting research related to financial innovation. So, I decided to use broad-to-narrow money (M2/M1) as a proxy for financial innovation. Although the M2 money (broad money) data is available on the World Bank website, I was unable to come across any website that offers the M1 money (narrow money data) of all the countries for free. I have seen a website like Trading Economics that has the data related to M1 and M2 money supply, but they are on a pay per basis. As I am still an undergraduate student, I cannot afford to buy this data. It would be really helpful if anyone could suggest, where can I get Narrow Money (M1) or broad-to-narrow money (M2/M1) data of all the countries for free?
It is worth mentioning that the OECD database has narrow money data for all the OECD countries, but they do not have broad money data. One can ask why am I not using broad money data from the World Bank’s website (WB). Well, that is because OECD’s narrow money (M1) data and the WB’s broad money data is using two different types of variable. I cannot figure out how they will work together. So, if you can also provide any suggestions related to this, it will help too.
Thank you.
CURRENCIE'S value differences in global trading causes costly purchase for low value currency and cheap purchase for high value currency.
Is insider trading by female executives is subject to higher behavioural bias than trades made by male executives? Current literature has just begun to reflect the question with the result being that female insider trades are significanrtly significantly more likely to be affected by prospect theory then trades by males.
Hi
Can anyone here help me understanding the marginal cost calculation in this article?
what is the index in summation notation in MC formula?
for example what is the form of MC for a given removal rate without summation notation?
thanks,
A large portion of stock market volume derives from automatic trading on the basis of algorithms. I am interested to know if they introduce completely new trends in stock price evolutions or if they integrate human behavioral factors thus accentuating the current trends.
The Problem Statement that may solve issues like land disputes, poor sanitary and water services (in general, utility services), and low tax collection by local councils in the small Trading Centers
The project that I am working on requires the quantification of lipids and of very small quantities of protein in complex solutions, which was performed on a Thermo Vantage Triple Quad with nano flow, but this instrument is no longer available to us. Buying a new LC/MS system is currently prohibitively expensive for the lab I work in, and we are considering other options (including paying another institution to process our samples for us). We may be able to purchase a used instrument from a company such as GenTech, International Equipment Trading Ltd, or Conquer Scientific. Can anyone speak to their experiences in buying equipment like this from such companies? Is the loss of support from the manufacturer worth the lower price tag, or is it likely to cost us more in repairs in the long run?
I am really confused now which simulation i can use to analyze.
Help me to recommend simulation software? which I can use to analysis my project
Why is there such a difference in goods and labour?
Hi
I am trying to build a trading market in a river syatem which multiple dishargers can trade multiple emission permits like BOD and total P and N. My question is how to calculate trading ratios between dischargers while we have multiple pollutants that could have influence each other and in different checkpoints in the river.
Thanks in advance.
Hi everyone,
I am working on emission trading for my thesis and I found the new article published in Journal of Environmental Management useful to my research. But It seems that I don't have access to this articles supplementary data. So I was wondered if anyone here could download and send it to me.
Thanks in advance,
Traders use many combinations of Moving averages(5-15-30,15-30-45, 3-5-15, 30-50-100) to forecast trends, Is there any work done where the optimized value of duration is found that can give better results. Please cite the work as well.
Dear Research Community,
I am currently conducting a research on whether corporate acquirers pay more than private equity firms for their targets. To examine this question the most prominent methodologies include the calculation of cumulative abnormal returns (CAR) from 42 trading days before the announcement to the day of deal completion.
Does this mean that I have to find data one by one for all of the different firms in my sample 42 days before the announcement or is there any time saving process to achieve this?
Thanks in advance,
In connection with the use of computerized, automated transaction systems, does the scale of the issue of the psychology of securities markets decrease?
Please reply
Best wishes
Dear Colleagues and Friends from RG,
The above discussion inspired me to formulate the following question:
What are the main determinants of research on behavioral reactions of investors on capital markets and consumer behavior on consumer goods markets?
On the basis of the above considerations and conclusions from the discussion on interesting issues discussed, I formulated the following thesis that in recent years the importance and applications of economics and behavioral finance have been growing. Therefore, it is crucial to define the dominant research determinants regarding behavioral reactions of investors on capital markets and consumer behavior on consumer goods markets.
Below I have described the key determinants confirming the formulated research thesis. To the above discussion I would like to add the following conclusion formulated as a summary of my previous considerations on this topic: Determinants of research on behavioral reactions of investors on capital markets and consumer behavior on consumer goods markets.
Economics due to the social issues of many subjects and problems in this field of knowledge, which it deals with is classified in many science centers in the field of social sciences. Social issues related to the economic conditions of people's lives, social determinants of economic development of economic entities and states, social policies led by states, behavioral factors of changes in economic situations in individual markets, etc. constitute a significant part of issues that are studied and described in the field of economics. Therefore, economics, even if not all of the issues it deals with, however, in most of the studied economic and financial issues falls within the scope of social sciences. In recent years, the importance of research in the field of behavioral economics, behavioral finance, etc. has grown.
In recent years, there has been an increase in the importance of behavioral economics and finance, including an analysis of the determinants of media shaping consumer opinions regarding company brand recognition, product and service offerings, etc. by increasing the importance of online information services, including social media portals. The growing importance of financial market psychology, the growing significance of behavioral factors influencing investment decisions of individual investors operating on capital markets and consumers making purchasing decisions on markets of popular products and services.
Therefore, the key questions that need to be answered are: Are investors active in the securities markets more cautious in making investment decisions after the global financial crisis, or are they more thoroughly analyzing the investment risk of investing in capital markets? Did any of you conduct research aimed at determining possible changes in the significance of financial market psychology and behavioral economics in capital markets, including securities markets, after the global financial crisis of 2008? If research shows that the importance of financial market psychology and behavioral economics in capital markets is decreasing, what is this mainly determined by? Is it the result of post-crisis greater awareness of investment risk among investors, or also a change in the structure of the dominant segments of investors operating on capital markets, or is it also the result of an increase in the number of transactions carried out by computerized transaction systems?
Business and economics are connected or determined to a significant degree with psychology. Examples of the most often cited, described and researched are emotionally determined behavioral behaviors of both consumers in consumer product and service markets as well as stock market investors in capital markets, including securities markets, in addition also currency markets, etc. Issues of the influence of psychological factors on economics can be found also within the scope of marketing activity directed at potential consumers of certain products or services. Supported by intensively conducted advertising campaigns, the sale of certain types of products and services is particularly determined by psychological issues used in advertising campaigns, which increase the scale of appearance and fashion activities for specific types of products or services. Sometimes the effectiveness of advertising campaigns depends to a large extent on whether the information message contained in advertising spots acts on human emotions and thus generates smaller or larger revenues from the sale of specific products or services. In financial markets, on the other hand, the impact of psychology on investment decisions of individual investors can be significant. Periodically, in situations of increased speculation in capital markets, imbalances in securities markets, there is a period of investment euphoria, sheep's momentum, investing fashion and, as a consequence, a strong revaluation of securities valuation (bull market) and periods of strong stock market recession, during which there is fear of investing, panic, getting rid of already undervalued shares, bonds, derivatives, etc. (bear market). Bull market and bear market phases appear periodically, sometimes cyclically in succession. If in capital markets, including securities, the importance of emotions can be an important factor influencing the decisions of individual investors, then the issue of financial market psychology may be an important topic of scientific research. Another interesting research issue is the determination of the importance of increasing the automation of the process of placing stock exchange orders in connection with the use of automated transaction systems by investment banks. Therefore, in the context of the above issues, it may be important to verify the research thesis that the growing importance of automated IT transaction systems used for computer orders for the purchase and sale of securities may reduce the impact of financial market psychology. If it was possible to examine this correlation, then another research issue for which a research project could be launched would be to determine the impact of automated IT transaction systems used by investment banks on the issue of stabilizing the stock market situation, the period of recovery after the emergence of the stock market crash, etc.
What research methods are used to analyze the behavioral and pragmatic behavior of individual investors operating in financial markets, including capital and securities markets? In addition, in related issues it is also interesting to find the answer to the following question: What currently dominate research methods are used to analyze behavioral and pragmatic consumer behavior in specific markets? Are there methods for precisely measuring consumers' pragmatic attitudes? The key is to distinguish the determinants that shape consumer behavior in market conditions. In my opinion, a good method of collecting data for the needs of this type of analysis are survey research methods, which cover consumers of a specific, cross-sectional group, segment of citizens, with specific characteristics. Then statistical elaboration of the results of conducted research should provide analytical material for the formulation of specific assessments and characteristics of both behavioral and pragmatism of specific actions undertaken by a selected segment of participants in a specific market, e.g. consumers of specific types of products and services.
In addition, advertising of consumer products and services serves to increase the demand for the advertised offer, and thus significantly affects the increase in consumption and also indirectly to change the behavioral behavior of social behavior and also to increase consumerism. In developed and developing economies, advertising is largely responsible for the rise in consumerism, but it is not easy to investigate to determine precisely what quantitative dimension this impact is. In connection with the above, in recent years the importance of the issues of data sentiment analysis obtained from social media portals has been growing in Big Data systems. For many companies, social media portals such as Facebook, Tweeter and others are a source of data on shopping and behavioral preferences used by companies operating in various industries and sectors for the purposes of marketing activities.
In line with the above, in my opinion the importance and applications of economics and behavioral finance have been growing in recent years. The above considerations show that many determinants are currently operating that shape changes in behavioral responses of investors in capital markets and consumer behavior in consumer goods markets.
Do you agree with me on the above matter?
I conduct research in this area. The conclusions of the research I published in scientific publications that are available on the Research Gate portal.
In view of the above, I am asking you the following questions:
- What research methods are used to analyze behavioral and pragmatic consumer behavior in specific markets?
- What research methods are used to analyze the behavioral and pragmatic behavior of individual investors operating on financial markets, including capital and securities markets?
- What are currently theories of the development of emotional intelligence and logical intelligence in the context of research conducted in the field of behavioral finance?
- What are the main determinants of research on behavioral reactions of investors on capital markets and consumer behavior on consumer goods markets?
- Do advertisements of consumer products and services increase consumption and increase consumption?
- Is the importance of psychology of financial markets and behavioral economics in securities markets decreasing after the global financial crisis?
- Is capital market behavioral psychology still very important for capital markets?
- After the global financial crisis of 2008, is the capital behavioral psychology of the behavior of investors operating on these markets still important in capital markets?
- Are the determinants of investor behavioral factors still strong in recent years on the world's largest stock exchanges, including psychology of financial markets in interpreting changes in stock market trends on these markets?
- After the global financial crisis, are investors operating in the securities markets more cautious in making investment decisions, or do they more thoroughly analyze the investment risk of investing in capital markets?
- Were studies previously conducted to determine possible changes in the significance of financial market psychology and behavioral economics in capital markets, including securities markets, after the global financial crisis of 2008?
- If research shows that the importance of financial market psychology and behavioral economics on capital markets is decreasing, what is this mainly determined by?
- Is it the result of post-crisis greater awareness of investment risk among investors, or also a change in the structure of the dominant segments of investors operating on capital markets, or is it also the result of an increase in the number of transactions carried out by computerized transaction systems?
- How are behavioral finances related to behavioral behavior of investors operating on the securities markets changing due to the increasing use of ICT and Industry 4.0 in the scope of development and increasing the share in concluded automatic transactions, computerized transaction systems used by banks and investment funds performing short-term transactions , speculative, lasting even fractions of a second but with the use of large funds, so large that they are inaccessible to the average individual investor?
- What are the dominant, model behavioral reactions of investors operating on the securities markets?
- To what extent do changes in the behavior of individual investors in securities markets correlate with periodically occurring in these markets overvaluation (bull market) and undervaluation (bear market) valuation of securities?
- Do strong correlations of changes in behavioral responses of individual investors, i.e. periodically overvaluing (bull market) and undervaluing (bear market) valuation of certain assets also apply to other financial, capital and other markets? (e.g. derivative markets, currency markets, real estate markets, etc.)
What do you think about this topic?
What is your opinion on this topic?
Please reply
I invite you to discussion
thank you very much
Best wishes
Dariusz Prokopowicz
International Trade has become a necessity, not now a days, but long ago.In the modern era, marked by Globalisation, there has been a marvellous increase in the level of International Trade.My humble submission is that what is the rationale of having Trading Blocs, in case we are really living in the era of true globalisation.
Hello dear friends, Than every country is noisy and concerned about the exchange rate, every day at any time, should all countries in the world use only one single currency as a means of trading and transaction exchange? I personally cannot imagine if that could happen.
Please, How can I find the data of trading volume of foreign investors in the stock markets (G10 + BRICS)? I need monthly data.
For example, Energy Web Foundation’s (EWF) energy- sector promotes the use of blockchain in energy management. Like Bitcoin, the EWF blockchain is a distributed ledger, upon which users can code applications that run on top of it.
Trading Clocs like ASEAN,NAFTA,EU play an important role in international trade.What are the various factors affecting the mechanism of functioning of trading blocs.
I'm modelling the export of halal from Malaysia to its trading partners.
According to current literature, exporter-time-fixed effect, importer-time-fixed effect & pair-time fixed effect MUST be included in the model.
Since my model is only 1 country to its trading partners, should i still include the exporter-time-fixed effect & pair-time fixed effect? because i read in statalist, only destination-time-fixed effect should be included.
thanks
Under C. Advantages and Limitations it says:
More precisely, when taking the transaction fee into account, only the final return will be affected by our own trading volume. Hence, the input of the network is not dependent on the last output, and the training method is not limited with the stochastic learning.
If you don't pass the previous output as input, how do you prevent the agent from trading too much and paying a lot of fees?
here in their study they have not taken any AR ? They used this model
FVt = a+ b1 |RAt-1| + b2 HLRt-1 + b3 RVt-1+ e
FVt is the future volatility measure, |RAt-1|, HLRt-1 and RVt-1 are one-day lag absolute daily returns, daily high-low range and daily realized volatility respectively.
Can I used this model for my study?
Under what type of regression model it will come ? They mention multiple-factor model?
I am planning my Ph.D. and wanted to start writing a proposal for the same. But I am too much confused with topics. After doing a lot of brainstorms finally I decided below topics which are best in my Interest.
I am looking your expert guidance for finalizing topic from below segments.
- How demat accounts are helping to manage the stock market activities in different countries.
- Role of the financial manager in the company to sort out money matter.
- Insider Trading and Its Interaction with Compensation
- Financial Risk Management
All these topics are best for me and in my deep interest. Please help me to decide the final topic with your expert suggestions.
In developed countries, knowledge-based economies are characterized by the development of information services, and production processes are increasingly determined by the quality of such factors as information, technology, innovations, patents, etc. In addition, analogous standards of telecommunications, transaction, market, financial systems, etc. operate in different countries. Globalization is therefore still progressing.
In connection with the above, the communication, transactional and information aspects of globalization are characterized by a positive meaning. It is referred to as "the Earth as a" global village. "Through more and more modern communication, the global circulation of information is carried out in real time via Internet teleinformation systems.
But not all aspects of globalization have positive aspects.
In my opinion, globalization processes strengthen long-term business cycles. In this way, globalization may deepen economic crises, including the global financial and debt crisis. An example was the global financial crisis, which appeared in mid-September 2008. At that time bankruptcy was announced by one of the largest investment banks in the world. As a result of unreliable credit risk management procedures, billions of USD of financial losses have been generated. It turned out that the unwritten rule no longer works, that "big can not fall". However, it is the emergence of ever larger international corporations and financial institutions that is one of the main determinants of the processes of economic globalization that have been progressing in recent years. these processes continue. Every few years, as a result of the merger of some of the largest financial institutions through mergers and acquisitions, more and more banks are formed. On the other hand, international operating industrial corporations move their factories from country to country, looking for cheaper workforce, and international trading and service corporations set up subsidiaries and sales outlets in other countries. Capital links grow transnational and thus systemic risk grows, whose sources can be related to the progressing economic globalization.
In view of the above, I am asking you: What are the most important positive and negative aspects of globalization?
Please reply. I invite you to the discussion
Dear Friends and Colleagues of RG
The issues of globalization of financial and banking systems are described in the publications:
I invite you to discussion and cooperation.
Best wishes
I am looking for suggestions to develop a set of research analysis or surveys to individuate the economic impacts of EU emission trading scheme on companies in different sectors. The final aim would be that of detecting a relevant weight of carbon leakage in different sectors based on single companies data.
If I have two or more users and they can trade with smart grid (they can sell and buy energy), the constraint i want to apply is that users can't trade with eachother. The priority is given to Smart grid, If SG want energy then users will provide, if they have extra energy and vice versa. But the problem I am facing is that if I come up with summation for all users then it means users are also trading among themselves,so what kind of constraints I have to apply to stop users from trading between eachother and can only trade with SG.
Assume that you have an opportunity to visit a civilization in outer space. Its society is at roughly the same stage of development as our earth society is now. Its economic system is virtually identical to that of the earth, but derivative trading is illegal. Briefly introduce, explain, compare and contrast this economy with the earth economy, emphasizing the differences due to the presence of derivatives markets/instruments in the latter.
