Time Series Terminal

24-month review of prediction performance * Using 2-day forecast period * and input data of?daily?granularity, * assuming?zero?trading cost,? * using the net prediction as the on-paper trading position (i.e. "23% of models predict up in net” would translate to “long 0.23 shares”), **under this setting**,?we surveyed US stock indices, US single stocks, currencies, commodities, cryptocurrencies, and meme stocks. We will see over the past 24 months of live running record, * Passive buy-and-hold of US stock indices Nasdaq 100, S&P 500 ETFs QQQ, SPY was unbeaten by the active trading strategy * Passive buy-and-hold of Gold ETF GLD was unbeaten by the active trading strategy * Passive buy-and-hold of cryptocurrency Bitcoin BTCUSDT, Ethereum ETHUSDT was unbeaten by the active trading strategy * otherwise tsterm.com may help realise a better return vs max drop trade-off

https://lnkd.in/evgsTeqk 2024-11: Bitcoin driving global (US and ex-US) assets; 1933, 1934 US gold/silver nationalisation

https://lnkd.in/eTXH3ccq Title: Neuronal network reconstruction through causality measures Abstract: Understanding the causal connectivity within a network is crucial for unraveling its functional dynamics. However，the inferred causal connections are fundamentally influenced by the choice of causality measure employed, which may not always align with the actual structural connectivity of the network. The relationship between causal and structural connectivity, especially how different causality measures affect the inferred causal links, requires further exploration. In this talk, we examine nonlinear networks characterized by pulse signal outputs, such as spiking neural networks, using four prevalent causality measures: time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We provide a theoretical analysis of the interconnections among these measures when applied to pulse signals. Utilizing both a simulated Hodgkin–Huxley network and an empirical mouse brain network as case studies, we validate the quantitative relationships between these causality measures. Our results show a strong correspondence between the causal connectivity derived from any of these measures and the actual structural connectivity, thereby establishing a direct linkage between them. We highlight that structural connectivity in networks with output pulse signals can be reconstructed on a pairwise basis, without needing global information from all network nodes, effectively avoiding the curse of dimensionality. Our approach offers a robust and practical methodology for reconstructing networks based on pulse outputs.

CommonCrawl ( internet-wide corpus for AI training)'s presentation for the Natural Language Processing Interest Group of the Turing Institute Thu 31 Oct: - Slides: https://lnkd.in/eJzwMMFW - More information about Common Crawl can be found on their website:?https://commoncrawl.org - Participate in discussion by joining their?Google Group?(https://lnkd.in/ezCFE5hG) and?Discord channel (https://lnkd.in/eryseEYY)

https://lnkd.in/esPFDP_a Royal Statisitcal Society data visualisation guide, republished in a series of articles under the title “Presenting data the Significance way”, Part 1-4.

In terms of what is driving the value (on the single day 6 months away from Tue 29 Oct) of the Nasdaq 100 index, the No 2 computed causal predictor is the US TIPS bond ETF **TIP** that protects against inflation. The ETF's price is going down as the 10-Year real interest rate is back to the normal level around "2%" before the 2007-2008 Financial Crash at the moment. (https://lnkd.in/dcf2sDF7) The ETF TIP mainly holds 5-10 Year inflation-protected US TIPS bonds. (https://www.etf.com/TIP, choose "Holdings" from menu) So the Nasdaq 100 index of innovative technology is predicted more confident when the US fixed income is delivering solid value. The computed daily position has been trending up since October. (https://tsterm.com/?q=qqq)

https://lnkd.in/ehUxVsfZ Hannaneh Hajishirzi - OLMo: Accelerating the Science of Language Modeling (COLM)

2024-10: AI deployment drives the Dow Jones Industrial Average index, which in turn drives the US Dollar's value vs other western currencies https://lnkd.in/eAKfcNBT

Accenture ACN computed to be driving (causally predictive of the values of) the three US stock indices on the day in 6 months, which may mean the deployment of AI into enterprises is beginning and expanding. Accenture is a global consulting company. https://lnkd.in/eTdzdaPc

https://lnkd.in/ebyAcTpb Precision information visualisation, demo video available