摘要: Algorithmic trading has proliferated across global FX markets over the past decade. Today, roughly 20% of the institutional foreign exchange trading volume is now executed through algos. FX algo usage is following that of the equities market - where algos currently account for more than half of all equity trading volume. So what’s behind all this algo growth?

摘要: Executing trades in the financial market has been made extremely accessible. With a few hundred $ and an internet connection you have the whole world under your thumb. This makes it seem that trading is a simple way of making big bucks. Being profitable in the market however demands a lot more than just entering trades, even if you happen to obtain accurate signals.

摘要: 有位香港大亨是Samathur Li(李建勤),他的父親是Shaftesbury Plc(一家英國房地產投資信託基金)的主要投資者,Shaftesbury Plc擁有倫敦唐人街、柯芬園和卡納比街的大部分物業。他最近控告銷售人員是Raffaele Costa,他主要為投資管理公司英仕曼集團(Man Group Plc)和旗下全資子公司GLG Partners Inc銷售投資基金工作。控告的理由是Raffaele Costa宣稱利用AI操盤的機器人投資可以賺大錢,結果害他賠錢。

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.

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