Best of Finance — 2024

1. 1
   Article

   Hacker News·1y

   my second year without a job

   The poster reflects on their second year without a traditional job, having initially quit due to personal reasons with $80K in savings. They describe their year’s journey, including financial challenges, collaborative entrepreneurial projects, maintaining mental health through co-living, and indulging in hobbies like music and sports. The individual acknowledges the setbacks but focuses on the positive experiences gained, aiming for personal growth and sustainable success in the upcoming year.

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2. 2
   Article

   Machine Learning News·2y

   OpenBB: An Open-Sourced Python-Based Finance ResearchPlatform

   OpenBB is an open-sourced and free financial platform offering extensive access to economic data including fixed income, macroeconomic indicators, equities, options, cryptocurrency, and forex. It features a customizable command-line interface and an AI financial analyst for data evaluation. Users can install it via PyPI or clone the repository, leveraging continual updates from developers.

   75

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3. 3
   Article

   gitconnected·2y

   Monte Carlo Simulation in Python: Advanced Investment Risk Analysis

   Monte Carlo Simulation is a computational algorithm that utilizes repeated random sampling to obtain numerical results. It is used in finance to model scenarios that involve uncertainty and predict the impact of risk. The simulation for stocks and cryptocurrencies involves historical data analysis, random sample generation, price simulation, and result analysis. The accuracy of the simulation depends on the assumptions made about return distributions and volatility.

   60
4. 4
   Article

   Community Picks·2y

   tcsenpai/goldigger

   goldigger is a Python-based tool for stock price prediction using machine learning models like LSTM, GRU, Random Forest, and XGBoost. It retrieves historical data from Yahoo Finance, incorporates technical indicators, and uses ensemble prediction to combine model results. It also features hyperparameter tuning, time series cross-validation, risk metrics calculation, and performance visualization. Designed for educational use, it provides customization through command-line arguments.

   40

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5. 5
   Article

   Community Picks·2y

   Managing High Performers

   With the end of the zero interest rate environment, numerous products that previously claimed to be unlimited have faced new limits, restrictions, or pricing changes. The notion of unlimited products is often unsustainable and likened to a Ponzi scheme.

   35

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6. 6
   Article

   Planet Haskell·1y

   Normal People Shouldn't Invest

   Inflation erodes the value of fiat money over time, leading to limited options for preserving wealth. Traditional saving options offer minimal protection against inflation, and investing in stocks or cryptocurrencies can be risky and stressful. The author argues that Bitcoin presents a better alternative by rewarding low time preference and saving, without the stress and risk associated with traditional investments.

   29

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   Article

   Hacker News·2y

   jpmorganchase/python-training: Python training for business analysts and traders

   JPMorgan Chase offers a Python training course for business analysts, traders, and select clients, focusing on numerical computing and data visualization. The training, conducted in-person by JPMorgan technologists and traders, aims to make complex topics accessible to those without formal programming backgrounds. It leverages resources like Binder, IEX Cloud, and OpenFlights data.

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   Article

   Medium·2y

   I Built an Algorithmic Trading System in Rust. Here’s What I Regret.

   The author built an algorithmic trading system in Rust to improve performance but faced challenges due to the language's complexity. Despite the difficulties, Rust provided significant performance enhancements and support for computationally expensive algorithms.

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9. 9
   Article

   Medium·2y

   Employing AI in Finance Analytics

   AI is revolutionizing predictive financial analytics by utilizing machine learning algorithms to handle vast datasets and complex, non-linear relationships. These advanced models, such as neural networks and decision trees, improve the precision of economic forecasts by continuously learning from diverse data sources, including transactional data and social media trends. Case studies highlight AI's effectiveness in predicting stock market trends and assessing credit risks, underscoring its impact on financial stability and profitability. Strategic integration into financial systems and a robust data foundation are vital for leveraging AI's benefits.

   22
10. 10
    Article

    Ayende @ Rahien·1y

    Isn't it ironic: Money isn't transactional

    The author, who works on transactional databases, finds it ironic that there are no real-world transactions for money transfers, highlighting inefficiencies in the banking system. They share an example where a payment remained pending despite the recipient confirming receipt, providing insights into historical banking methods and distributed system design.

    20

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11. 11
    Article

    AWS·2y

    Few-shot prompt engineering and fine-tuning for LLMs in Amazon Bedrock

    Company earnings calls are crucial for transparency and can significantly impact stock prices. This post explains how generative AI, specifically large language models (LLMs), can streamline the creation of earnings call scripts. It introduces two methods: few-shot prompt engineering and fine-tuning, both utilizing Amazon Bedrock's capabilities. Through examples and evaluations, it demonstrates the potential of these AI technologies to improve financial communications while considering trade-offs in comprehensiveness, hallucinations, ease of use, and cost.

    20
12. 12
    Article

    Machine Learning News·2y

    Collaborative Small Language Models for Finance: Meet The Mixture of Agents MoA Framework from Vanguard IMFS

    Language model research has advanced rapidly, particularly in specialized fields like finance. Large Language Models (LLMs) face challenges such as high computational costs and the risk of producing inaccurate information. Vanguard IMFS introduced the Mixture of Agents (MoA) framework, featuring a network of small, specialized models designed for Retrieval-Augmented Generation tasks. The MoA system has shown significant improvements in response quality and efficiency, proving to be cost-effective and scalable for large-scale financial applications.

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    Article

    Medium·2y

    How to Manage Your Budget with a Simple Python Script

    A simple Python script that helps manage your budget by tracking income and expenses, and visualizing the data.

    19

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14. 14
    Article

    UX Planet·2y

    10 Psychology Laws to Design Digital Banking App UX

    Understanding the psychology behind user behavior is crucial for designing products that are not only functional but also engaging and stress-free. This article explores the key psychological principles that can transform financial UX design from a source of frustration to one of satisfaction and loyalty.

    18

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15. 15
    Article

    finout·2y

    K3s vs. K8s: Breaking Down the Differences and Deciding When to Use Each

    Comparison between K3s and K8s, highlighting their key differences and use cases.

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16. 16
    Article

    olegwin's public Squad·2y

    How I Built an AI Tool to Understand Crypto Spikes for Any Coin

    A tool built using AI helps to understand sudden price spikes or drops in cryptocurrencies by analyzing news articles. This tool collects news from various sources, uses AI to identify the main reasons behind price movements, and provides quick insights on whether it's a good day to buy. The app was developed in just 45 minutes and is designed to save users time by offering speedy news analysis.

    14

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17. 17
    Article

    Medium·2y

    I am Aurora, the Most Powerful AI Financial Assistant That The World Has Ever Seen

    Aurora is a powerful AI financial assistant developed by Austin Starks. Aurora specializes in trading automation and financial research, aiming to make investing and trading more accessible. Aurora can generate tailored indicators, design trading strategies, and analyze company financial information. Austin believes that Aurora's ability to find novel investing opportunities using natural language makes it more powerful than any other platform. Aurora is a neural network powered by OpenAI's GPT APIs and plans to improve its functionality in 2024.

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    Article

    Medium·2y

    How to Find the Best Stocks in the Stock Market Using AI

    Learn how to use AI to find the best stocks in the stock market using the NexusTrade Platform. Discover the features of intelligent stock screening and the implementation process. Also, explore the MongoDB Aggregation Framework for executing complex queries.

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    Article

    C/C++ Community·2y

    How to start making money as a C++ programmer?

    11

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20. 20
    Article

    Coins Bench·2y

    Blockchain-Based ROSCA: Implementing On-Chain Verification for Secure Fund Claims

    By implementing a Rotating Savings and Credit Association (ROSCA) on the blockchain, traditional cooperative savings and lending methods are enhanced with decentralization, transparency, and automation. Using smart contracts, participant registration, contribution collection, recipient selection, and on-chain verification are efficiently managed. This approach reduces reliance on mutual trust and provides increased security and reliability.

    11

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    Article

    Medium·2y

    Exploring Career Paths in Finance? Here’s the complete roadmap by Finance and Economics Club, IIT Kharagpur.

    Explore different career paths in finance, learn about well-known careers and certifications in the field, and discover how to develop qualitative and quantitative finance skills.

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