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摘要: Given the commodification and decline of high frequency trading, I was a bit surprised to see that Michael Lewis wrote a book on the topic. Not only that, but based on the reviews (I haven't read the actual book), it sounds like a scary "tell-all" book revealing how HFT rips off "the little guy".

摘要: Right around the time you get your first basic regression or classification model going, it will at least cross your mind. The vast piles of time series data, coupled with the possibility of retiring young has the irresistible pull of finding an old treasure map in your grandfather’s attic. How can you NOT think about it? Can you use machine learning to predict the market?

摘要: While volatility and illiquidity in the U.S. equities markets have created obstacles to low-cost transacting, trading innovations being put in place in 2019 are now making liquidity more efficient and accessible to buy-side firms that continue to invest in technology, according to new research, IET 2019, Liquidity: Blocks, Algos, Analytics and Impact, the first of a six-part US equities trading interview-based benchmark study that has been published annually by TABB Group for 15 years.

摘要: When first introduced, algorithms were designed primarily for automation to mimic a trader executing orders in pursuit of specific benchmarks. In the second phase, brokers stressed qualitative analysis by leveraging real-time data from the order book to model their assertions, and tailor how model behavior would respond to changing market conditions. In the most recent phase, leading providers on the sell-side have begun to use quantitative measures into their execution strategies, most notably integrating machine learning principles.

摘要: Fundamentally, trading is about analyzing the supply and demand of a security (asset which can be traded), such as stocks, commodities, or Forex pairs. A trader then makes decisions to purchase or sell these securities, ideally for a profit. When entering a trade, there are numerous factors to take into consideration, such key price levels, liquidity, and momentum.

摘要: Artificial intelligence is upending the financial management industry in spectacular ways. The majority of machine learning and deep learning solutions have focused on fundamental analysis of securities. However, deep learning and other artificial intelligence technologies will also change the future of technical analysis as well.

摘要: AI 工程師薪水只有 9K 到 18K 台幣是怎麼回事?事實上他們不算是工程師,他們的工作是「標注」,教導 AI 做影像和聲音的辨識,這是個低技術門檻的工作,很像是工廠的作業員。雖然標注的技術低,但它卻是 AI 發展中重要的一環。通常 AI 新創的規模不大,沒有多餘的人力去做這類勞力密集的工作,因此會將此類工作外包,也讓中國誕生了這種新興的行業。

摘要: 人工智慧(AI)已經成為新一輪科技革命和產業變革的核心驅動力,2018年底以來,不少國內基金業者摩拳擦掌,推出AI概念基金,法人分析,AI已經是「現在進行式」,無論是在對世界經濟的樣貌、社會進步和人類生活,都有極其深刻的影響,在三大利基加持下,新年伊始,投資人不妨考慮把握未來趨勢,卡位人工智慧的投資契機。

摘要: 面對數位化的潮流,發展金融科技(Fin Tech)已成為兆豐金(2886)旗下兆豐銀行轉型並提升競爭力的重要策略之一。繼行動理專APP服務後,兆豐銀再推出財富管理「智能領航Follow蜜」線上智能投資試算服務,民眾只要透過手機或是PC打開網頁,依照個人的投資屬性點選,就能推算預期報酬的金額,或者也可以用預期報酬來推算出原始的投資金額,兼顧風險管理,讓理財變得簡單又聰明。

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