#Machine Learning in Trading

[ganonfan1995]

Burnt out

[knifekris]

every day i struggle to make choices

[gibbearish]

a weird little thing abt me is i will definitely mock shitty ai art but it never feels right doing it about the hands simply by virtue of the fact that a lot of them look indistinguishable from the hands i was doing years ago when i first got a drawing tablet

[danieldavidreitberg]

From Amateur Hour to Organized Crime: The Growing Sophistication of Sandwich Bot Networks

Remember the early days of DeFi, when sandwich bots were clumsy scripts written by hobbyists, easily detectable and swatted away? Those days are gone. The landscape of MEV (Miner Extractable Value) exploitation has evolved into a sophisticated ecosystem, with well-organized networks employing cutting-edge tools and coordinated strategies to fleece unsuspecting users.

From Solo Players to Syndicates

Gone are the days of lone bots lurking in the mempool. Today, MEV teams operate like criminal enterprises, pooling resources, expertise, and infrastructure to maximize their gains. These teams leverage:

Advanced bots: Employing AI and machine learning, these bots can predict market movements, identify profitable opportunities, and execute complex arbitrage strategies in milliseconds.

Flash loan manipulation: Borrowing vast sums instantly, these teams manipulate markets, trigger liquidations, and extract hefty profits before disappearing.

Front-running bots: These bots predict user actions and place transactions ahead, denying them the intended price and reaping the difference.

Distributed networks: Operating across multiple nodes and blockchains, these networks are harder to detect and disrupt.

The Stakes are High

The impact of these organized attacks extends far beyond individual losses:

Market manipulation: By manipulating prices, these bots distort markets, creating unfair advantages and undermining trust in DeFi.

Exacerbated volatility: Their rapid arbitrage activity fuels market volatility, discouraging participation and hindering adoption.

Centralization concerns: Large, well-resourced teams gain an unfair edge, raising concerns about centralization within DeFi.

Fighting Back

The good news is, that the fight against organized MEV exploitation is not one-sided. Here are some promising developments:

MEV-resistant protocols: Projects like Flashbots and MEV Boost offer infrastructure to mitigate certain MEV exploits.

Layer 2 scaling: Solutions like Optimism and Arbitrum aim to reduce MEV by processing transactions off-chain.

Collaboration and research: Ongoing research and collaboration between developers, users, and researchers aim to develop fairer and more efficient mechanisms for distributing MEV rewards.

The Future of MEV

The battle against organized MEV networks is an ongoing one, requiring constant vigilance and adaptation. By staying informed, supporting responsible projects, and advocating for fair and transparent DeFi, we can ensure that this revolutionary technology benefits everyone, not just the digital robber barons of the mempool.

[princesspeach5]

[ID: a graphic of hands washing dishes with the caption "men and boys! Revolution begins in the sink! Only when men take full responsibility for their share of the cooking, the cleaning, and the washing up… only then can they join with the women, and together build a new world!!!" End ID.]

My least favorite things about anti- UBI discourse is always the techbros whining that "nobody is going to work anymore! People will just watch Netflix all day!" and I have 2 responses:

1) Who the fuck cares. Who the fuck cares what people do with their time! That's kind of the fucking point!

2) People aren't going to stop laboring. Housework (look, it's right there in the word!) will still need to be done. So will maintenance on our homes and personal spaces. Children will still need carers, as will the elderly and disabled. There are millions of examples of ~work~ that we do all the time, uncompensated, that won't suddenly stop because we aren't forced to sell our labor to provide corporation's profits.

I'm not surprised that what is traditionally women's work is invisible to these dipshits, but it never fails to anger me.

Anyway. Join the IWW.

[algos11]

In recent years, algo trading in India has become an essential part of the country’s financial landscape. With technology getting more advanced and markets becoming more complex, traders as well as institutions are switching to algorithmic trading to make their trading strategies better. Algorithmic trading, or algo trading, is a method that utilises automated programs to carry out trades based on certain rules such as price, volume, and timing. The soaring adoption of algo trading in the Indian stock markets has immensely strengthened liquidity, thus forming a more efficient and stable market atmosphere. Through this blog, we will find out the ways that algo trading is increasing liquidity in the financial markets, especially in India and also will see how it is a key component in the modern market operation.

[saiyan34blog]

Synvestable - Financial Artificial Intelligence & Portfolio Management

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https://learn.synvestable.com

[webideasolutionca]

Discover the power of AI and machine learning for traders. Explore advanced analytics, predictive insights, and automated strategies reshaping investment decisions. From algorithmic trading to market sentiment analysis, uncover how AI and ML revolutionize trading efficiency and unlock new opportunities. Learn more at Web Idea Solution!

[captainjonnitkessler]

I think I can trace my intense hatred for the whole "regulations are just corporate bullshit, building codes are just The Man's way of keeping you down, we should return to pre-industrial barter and trade systems" nonsense back to when I first started doing electrical work at one of the largest hospitals in the country.

I have had to learn so much about all the special conditions in the National Electric Code for healthcare systems. All the systems that keep hospitals running, all the redundancies and backups that make sure one disaster or outage won't take out the hospital's life support, all the rules about different spaces within the hospital and the different standards that apply to each of them. And a lot of it is ridiculously over-engineered and overly redundant, but all of it is in the service of saving even one life from being lost to some wacky series of coincidences that could have been prevented with that redundancy.

I've done significantly less work in food production plants and the like, but I know they have similar standards to make sure the plants aren't going to explode or to make sure a careless maintenance tech isn't accidentally dropping screws into jars of baby food or whatever. And research labs have them to make sure some idiot doesn't leave a wrench inside a transformer and wreck a multi-million dollar machine when they try to switch it on.

Living in the self-sufficient commune is all fun and games until someone needs a kidney transplant and suddenly wants a clean, reliable hospital with doctors that are subject to some kind of overseeing body, is my point.

[signode-blog]

Mistakes Traders Make While Using Moving Averages

Moving averages have a long history in the field of statistics and technical analysis. Their origins can be traced back to the early 20th century, and they have since evolved to become a fundamental tool for traders and analysts in various financial markets. Here’s a brief history of moving averages: Early Development (Early 20th Century): The concept of moving averages can be traced back to…

[abiodun-360degree]

Information Technology

Information Technology What is Information Technology? Information Technology (IT) is a term that arouse during the 1970’s to describe the combination of two previously existing discipline, computing and telecommunication. Very many definitions of the term exist ranging from the narrow, that would encompass those traditional aspects of office data processing to the broad, that would involve the…

[ummakcem]

RSI Para Kazandırır mı?

RSI Para Kazandırır mı?

RSI Para Kazandırır mı sorusuna cevap arıyoruz, elle test yapmak yerine MQL5 yazılım dilini kullanarak tek tuşla binlerce işlem açtırıp doğru cevabı bulmaya çalışacağız. Tüm bu işlemlere başlamadan önce RSI nedir konusuna bir göz atalım. Makaleyi okumak yerine izlemek isterseniz Youtube videomu aşağıda bulabilirsiniz.

RSI Nedir ve Nasıl Hesaplanır?

Göreli Güç Endeksi (GGF veya İngilizce adıyla RSI), finans piyasalarının analizinde yaygın olarak kullanılan bir teknik göstergedir. J. Welles Wilder tarafından 1978’de geliştirimiştir. Bu gösterge, momentum osilatörleri sınıfına girer ve genellikle aşırı alım veya aşırı satım sinyalleri üretmek için kullanılır.

RSI’ın Hesaplanma Formülü

RSI’nın hesaplanması için kullanılan formül oldukça önemlidir. Öncelikle, pozitif kapanış değeri ve negatif kapanış değeri belirlenir. Pozitif kapanış, son mumun kapanış fiyatı ile bir önceki mumun kapanış fiyatı arasındaki farktır. Eğer bu fark sıfırdan büyükse, bu değer pozitif kapanış olarak kaydedilir, eğer fark sıfırdan küçükse, bu değer negatif kapanış olarak kaydedilir.

Kapanış değerleri, istenilen periyot içinde hesaplanır. Örneğin, 14 periyotluk bir RSI hesaplanırken, bu işlem şu anki mumdan geriye doğru 14 bar için tek tek yapılır.

İkinci adım ise pozitif ve negatif kapanışların toplanarak ortalamasının alınmasıdır. Bu, RSI hesaplamasında kullanılan RS değerini verir. RS değeri, aşağıdaki formülle hesaplanır:

RS=Ortalama Pozitif Kapanışlar / Ortalama Negatif Kapanışlar​​

Elde edilen RS değeri aslında yeterlidir fakat okumayı kolaylaştırmak ve göstergenin daha net ve geniş bir aralıkta yorumlanabilmesi için 0 ile 100 arasındaki değerlere dönüştürülür:

RSI=100−(100/(1+RS))RSI=100−(100/(1+RS)) formülü kullanılır.

RSI’nın birden fazla kullanım yöntemi bulunmaktadır. Temel kullanımlardan biri, 14 periyotluk bir RSI’ın 70 değerinden yüksek olması durumunda satış yapmayı, 30 değerinden düşük olması durumunda ise alış yapmayı içerir. Bu kullanım stratejisinin temel mantığı, alım veya satım trendinin aşırı seviyelerde olduğunu ve yakın zamanda düzelme eğilimi gösterebileceğini işaret etmesidir.

Hemen Hızlıca Bu Stratejiyi Robotlaştıralım ve RSI para kazandırır mı görelim.

Görsel modda ilk denemeleri yapıp robotun doğru çalıştığına emin olduktan sonra hemen backtest ve optmiasyon aşamasına geçtim. Test için EUS/USD paritesini ve M15 zaman dilimini tercih ettim. Gelen ilk sonuçlar oldukça tatmin edici görünüyordu. Sadece 5 ay backtest yapıldı fakat bir stratejinin gerçekten iyi çalıştığını düşünmeye başlamam için önce 1 yıllık bactesti tamamlamalı daha sonra 3 yıllık testten geçmeli daha sonra ise 5 yıl backtest yapıldığında düzgün sonuç vermeli. Gerçek hesapta çalıştırmadan önce 2-4 hafta arasında demo hesapta işlem açtırır daha sonra 2-4 hafta backtest yaparak gerçek işlemler ile backtest arasında bir fark var mı diye kontrol ederim 🙂 Para kolay kazanılmıyor her zaman temkinli olmakta fayda var. Para kazanmanın ilk adımı cebinizdeki parayı kaybetmemektir.

En karlı robotun sonucuna baktığımızda 51 Dolar kar ettiğini ama bazı haftaların sürekli zarar ettiğini görüyoruz. Bunun önüne geçmek için risk yönetimi yapmalıyız. Bu yüzden bende risk yönetimi algoritmasını devreye alarak yeni bir optimizasyon yaptım.

RSI Para Kazandırır mı sorusunun cevabını ararken risk yönetimi algoritmasını devreye aldığımızda karımızın yaklaşık %45 arttığını ve zararlı haftaların artık olmadığını görebiliyoruz. Risk yönetim algoritmalarını BURAYA TIKLAYARAK inceleyebilirsiniz.

RSI Para Kazandırır mı sorusunun cevabı kesinlikle evet fakat risk yönetimi ile birleştiğinde 🙂

RSI gerçekten güçlü bir indikatör başka indikatörler ile birleştiğinde harikalar yaratabilir hepsini zamanla test ediyor olacağız. Sizde eğer bu robotu kendiniz test etmek ve hatta kullanmak isterseniz sitemize abone olabilirsiniz. ANASAYFA‘mızı ziyaret etmeyi unutmayın 🙂

Daha detaylı anlatım için Youtube videomu izleyebilirsiniz.

[danieldavidreitberg]

Explore the AI-driven edge in high-frequency trading! 🚀 Daniel Reitberg dives into the fast-paced world of AI Arbitrage. Check it out! #AITrading #Arbitrage #HighFrequencyTrading #FinanceInnovation

[that-edgy-gal]

Sees "ai image" tag

Unfollowed. Blocked. Perish.

[algos11]

Backtesting is a simulation process where a trading strategy is applied to historical market data to assess how it would have performed in the past. The primary objective is to determine whether a trading strategy is viable and to identify any potential issues or weaknesses. By analysing historical data, traders can gain insights into how their algorithmic trading software might behave in different market conditions.