For each (topic, subtopic) pair, we generate and solve 80 problems using GPT4.

Recent advancements in large language models (LLMs) and agentic systems have shown exceptional decision-making capabilities, revealing significant potential for autonomic finance. Current financial trading agents predominantly simulate anthropomorphic roles that inadvertently introduce emotional biases and rely on peripheral information, while being constrained by the necessity for continuous inference during deployment. In this paper, we pioneer the harmonization of strategic depth in agents with the mechanical rationality essential for quantitative trading. Consequently, we present TiMi (Trade in Minutes), a rationality-driven multi-agent system that architecturally decouples strategy development from minute-level deployment. TiMi leverages specialized LLM capabilities of semantic analysis, code programming, and mathematical reasoning within a comprehensive policy-optimization-deployment chain. Specifically, we propose a two-tier analytical paradigm from macro patterns to micro customization, layered programming design for trading bot implementation, and closed-loop optimization driven by mathematical reflection. Extensive evaluations across 200+ trading pairs in stock and cryptocurrency markets empirically validate the efficacy of TiMi in stable profitability, action efficiency, and risk control under volatile market dynamics.

Predicting the stock market is a big challenge for the machine learning world. It is known how difficult it is to have accurate and consistent predictions with ML models. Some architectures are able to capture the movement of stocks but almost never are able to be launched to the production world. We present Achilles, with a classical architecture of LSTM(Long Short Term Memory) neural network this model is able to predict the Gold vs USD commodity. With the predictions minute-per-minute of this model we implemented a trading bot to run during 23 days of testing excluding weekends. At the end of the testing period we generated $1623.52 in profit with the methodology used. The results of our method demonstrate Machine Learning can successfully be implemented to predict the Gold vs USD commodity.

At White Wind Research, we are looking for an AI/ML expert with trading knowledge to work on our AI-assisted cryptocurrency trading project. This includes both fully-automated trading (i.e., a trading bot) and AI-based assistance for further research and analysis to be made by humans. This project is our first at our company, and this position will be our first hire. Please note that this position requires a self-motivated individual. All of the above is a requirement.

Cryptocurrency markets have very distinct architectures from more conventional financial markets. The cryptocurrency market presents a unique set of opportunities for investment and trade. All of these factors--from market volatility to trading activity to inventory management to business hours--are included. The modern wave of digitization has given birth to the growth of AI-based trading bots. A growing number of businesses have adopted the use of chatbots to streamline their customer care processes in recent years.

While there are some concerns about how generative AI chatbots such as ChatGPT can be used maliciously -- to craft phishing campaigns or write malware -- several companies are harnessing the power of conversational AI technology to enhance their product capabilities, including for security. ChatGPT, a large language model (LLM) developed by OpenAI, uses GPT 3 LLM and relies on large test data sets culled from multiple sources. ChatGPT, which can understand human language, provides detailed answers to simple questions and can handle complex tasks such as creating documents and writing code in response to user queries. It's an example of how conversational AI can be used to organize large volumes of information and enhance user experience and communications. For instance, a conversational AI tool -- whether that's ChatGPT or something else -- could serve as the back end of an information concierge that automates the use of threat intelligence in enterprise support, according to IT research and advisory firm Into-Tech Research.

The crypto community appears to be having a ball with ChatGPT, a recently launched Artificial Intelligence (AI) chatbot created by research company OpenAI -- using it for a multitude of applications including a trading bot, a crypto blog and even an original song. The bot is a language interface tool that OpenAI says can interact "in a conversational way" and can be used to answer questions or assist in making almost anything it's prompted to create, with some limitations. A user on Twitter posted their interaction with ChatGPT showing that from a simple prompt the tool created a basic trading bot using Pine Script, a programming language used for the financial software TradingView. Should I try running this chatGPT generated crypto trading algorithm? Another user gave the bot instructions to create a trading terminal, with ChatGPT writing code that could display the current orders for the Bitcoin (BTC) and Tether (USDT) trading pair on Binance utilizing the crypto exchange's application programming interface (API).

We often see posts on Social Media by individuals who claim to have invented a Bot that can trade. Almost always the poster declines to mention specifics of the algorithm they have implemented, resorting to using vague and emotive terms such as "Artificial Intelligence" or "Machine Learning". Frequently they'll also post claims of profits, but these are what we call "unaudited financial results" . In other words, we have to take the poster's word of their trading Bot's skill. But how seriously should we consider this threat?

A Florida man is facing up to five years in prison after he pleaded guilty to committing financial fraud using a crypto Ponzi scheme and making away with approximately $100 million in investment funds. In a statement released on Sept. 8, the U.S. Department of Justice (DOJ) identified Joshua David Nicholas as the "head trader" for EmpiresX, a firm founded in 2020 and was publicized to investors as a legitimate cryptocurrency trading and investment platform. Nicholas admitted that he "fraudulently promoted EmpiresX by making numerous misrepresentations regarding, among other things, a purported proprietary trading bot and fraudulent'guaranteed' returns to investors and prospective investors in the company," according to the statement. Nicholas reportedly disclosed that he and his co-conspirators told investors that they had a trading bot, an algorithm based on AI technology that places trades and whose goal was to maximize profitability for investors. "EmpiresX operated a Ponzi scheme by paying earlier investors with money obtained from later EmpiresX investors," the DOJ noted in the statement.