Discrete-choice life cycle models of labor supply can be used to estimate how social security reforms influence employment rate. In a life cycle model, optimal employment choices during the life course of an individual must be solved. Mostly, life cycle models have been solved with dynamic programming, which is not feasible when the state space is large, as often is the case in a realistic life cycle model. Solving a complex life cycle model requires the use of approximate methods, such as reinforced learning algorithms. We compare how well a deep reinforced learning algorithm ACKTR and dynamic programming solve a relatively simple life cycle model. To analyze results, we use a selection of statistics and also compare the resulting optimal employment choices at various states. The statistics demonstrate that ACKTR yields almost as good results as dynamic programming. Qualitatively, dynamic programming yields more spiked aggregate employment profiles than ACKTR. The results obtained with ACKTR provide a good, yet not perfect, approximation to the results of dynamic programming. In addition to the baseline case, we analyze two social security reforms: (1) an increase of retirement age, and (2) universal basic income. Our results suggest that reinforced learning algorithms can be of significant value in developing social security reforms.

We present FinAI Data Assistant, a practical approach for natural-language querying over financial databases that combines large language models (LLMs) with the OpenAI Function Calling API. Rather than synthesizing complete SQL via text-to-SQL, our system routes user requests to a small library of vetted, parameterized queries, trading generative flexibility for reliability, low latency, and cost efficiency. We empirically study three questions: (RQ1) whether LLMs alone can reliably recall or extrapolate time-dependent financial data without external retrieval; (RQ2) how well LLMs map company names to stock ticker symbols; and (RQ3) whether function calling outperforms text-to-SQL for end-to-end database query processing. Across controlled experiments on prices and fundamentals, LLM-only predictions exhibit non-negligible error and show look-ahead bias primarily for stock prices relative to model knowledge cutoffs. Ticker-mapping accuracy is near-perfect for NASDAQ-100 constituents and high for S\&P~500 firms. Finally, FinAI Data Assistant achieves lower latency and cost and higher reliability than a text-to-SQL baseline on our task suite. We discuss design trade-offs, limitations, and avenues for deployment.

Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text, containing textual and tabular data, remains underexplored. In this research, we specialize in harnessing the potential of LLMs to comprehend critical information from financial reports, which are hybrid long-documents. We propose an Automated Financial Information Extraction (AFIE) framework that enhances LLMs' ability to comprehend and extract information from financial reports. To evaluate AFIE, we develop a Financial Reports Numerical Extraction (FINE) dataset and conduct an extensive experimental analysis. Our framework is effectively validated on GPT-3.5 and GPT-4, yielding average accuracy increases of 53.94% and 33.77%, respectively, compared to a naive method. These results suggest that the AFIE framework offers accuracy for automated numerical extraction from complex, hybrid documents.

Nvidia stock rose over 8% in extended trading on Wednesday after the company reported slightly higher revenue and net income than Wall Street expected, despite a year-over-year decrease in both categories. Here's how the chipmaker did versus Refinitiv consensus expectations for the quarter ending January: Nvidia reported $0.57 in GAAP net income per share. Nvidia forecast $6.5 billion in sales in its first quarter, higher than the $6.33 billion expected by Wall Street. Although both revenue and earnings were down from last year's $1.32 per share and $7.64 billion in sales, Nvidia has increasingly been seen by investors as one of the chip stocks best positioned to endure an economic slowdown that hurts PC and semiconductor sales. Nvidia's data center business, which includes chips for AI, continued to grow, suggested that it could continue to benefit heavily from artificial intelligence software like ChatGPT and Microsoft Bing's AI chatbot.

"All of the automation that we're looking at enhances the capabilities and makes the jobs easier for our best and brightest people, and it eliminates a lot of the otherwise mundane projects or activities," Mr. Wren said on the company's earnings call Tuesday. CMO Today delivers the most important news of the day for media and marketing professionals. His comments were in response to an analyst's question about how technology from Microsoft Corp. -backed OpenAI could affect Omnicom's business and the advertising market overall. Microsoft is integrating the ChatGPT tech into its Bing search engine. The company reported organic revenue growth of 7.2% in the fourth quarter, beating the average analyst estimate of 3.7% organic revenue growth, according to FactSet.

Artificial intelligence (AI) is one of the buzziest terms in technology at the moment. Given how complex AI is, it is hard to separate the pretenders from the real innovators. The industry is expected to grow at 20% annually through 2029 and hit over $1 trillion in annual spending worldwide. Companies that are the leaders in AI and machine learning can capture a lot of this spending, helping their businesses grow and leading their stocks to put up great returns for shareholders. Here are two AI stocks that look ready to make a bull run over the next decade.

Significant increase in Q3 net income of over $961K, up 464% compared to the previous year. During the nine months ended September 30, 2022, the Company repurchased 17,807,500 common shares of the Company for $2,040,350. Toronto, Canada, November 22, 2022 – Datametrex AI Limited (the "Company" or "Datametrex'') (TSXV: DM) (FSE: D4G) (OTCQB: DTMXF) is pleased to report its financial results for the third quarter. The Company has filed its financial statements ("FS") on SEDAR and related management discussion and analysis ("MD&A") for the quarterly results ending September 30, 2022 ("Q3 2022"). For the three months ended September 30, 2022 (Q3-2022), the Company reported revenue of $9,202,894, net income of $961,922 and EBITDA of $2,699,239. For the nine months ended September 30, 2022 (Q3-YTD), revenue was $27,544,338, net income of $2,791,511, and EBITDA of $5,965,145. The Company continues to hold a strong cash and marketable securities position of approximately $13 million after ...

Microsoft likely recorded slower earnings and sales growth last quarter as a sharp decline in personal computer sales eroded demand for its Windows software, counteracting some of the demand for its cloud and other businesses serving companies. The Redmond, Wash., corporation's revenue growth is expected to slow to about 10% in the three months through September compared with a year earlier, while its net income is expected to edge up 1%, according to analysts surveyed by FactSet. They predicted the company would report sales of $49.66 billion and net income of $17.36 billion for the period. That would mean last quarter had the slowest revenue growth in more than five years and the lowest income growth in more than two years. The company is scheduled to announce results after the market closes on Tuesday. A weekly digest of tech reviews, headlines, columns and your questions answered by WSJ's Personal Tech gurus.

Energy giant Saudi Aramco says its 2021 net profit soared by more than 120 percent due to higher crude oil prices, as global economic growth recovered from a pandemic induced downturn. The announcement came on Sunday hours after Yemen's Houthi rebels – against whom Saudi Arabia leads a military coalition – targeted several locations, including Aramco facilities, in cross-border armed drone attacks. Aramco, Saudi Arabia's cash cow, did not say if the attacks caused any damage. "Aramco's net income increased by 124 percent to $110bn in 2021, compared to $49bn in 2020," the company said in a statement. Aramco achieved a net income of $88.2bn in 2019 before the coronavirus pandemic hit global markets, resulting in huge losses for the oil and aviation sectors, among others.

We've reached a point where 1980s-90s sci-fi buzzwords are turning into reality. A few examples are nanotechnology, the metaverse and quantum computing. In the past few years, all three of these concepts have turned into full-fledged industries. In particular, quantum computing could be incredibly valuable over the coming decade. Quantum computing essentially makes computing-intensive processes easier.