CloudQuant and Industry Tweets

#TraderTerminology: ►Long/Short◄ A model which takes long and short positions often aiming for an equal share of capital on each side. https://t.co/84zakO2Uhh

#TraderTerminology: ►Long-Only◄ A model which only takes long trades - Risky if the market suddenly takes a downturn. Hence it is suggested that this kind of model is hedged or turned into a long/short model. https://t.co/PH66mymVrT

Goldman is seeking to hire engineers to help traders automate. Those wanting to move over really should have some experience like building algos on CloudQuant! https://t.co/qqhBys0a0E

#altData news for 8/21: The use of AltData from Quantitative Finance to actionable intelligence is growing. ● Are these lists of “In Demand” jobs their own alternative data? ● #AI and AltData continue to overlap. ● The number of Datasets continues to… https://t.co/BLXSnhgL6m

#TraderTerminology: ►Long◄ Buying shares on the assumption that the price will rise putting you in profit. https://t.co/6FF5vL87R9

ML/AI News covering Towards Data Science's Weekly Selection, US and China Jockey for AI Lead, Bloomberg Uses Predictive Intelligence in Corporate Credit, Ideas on pricing alternative data and Neueda & Levyx bring Python into big data era. https://t.co/Qn7p4nsRvT

#TraderTerminology: ►Large, Medium and Small Cap◄ Based on Market Capitalization : Small cap = $250 million-$2 billion, Mid cap = $2-$10 billion, Large cap = $10 to -$100 billion. Used to represent Large Established vs Small companies. https://t.co/jzyftFnGRM

#TraderTerminology: ►HFT or High Frequency Traders◄ are traders running algorithms which can see other peoples trades entering the market and race ahead of the trade buying and selling, in order to make a penny or two in the process. https://t.co/8thBu4o3S6

#TraderTerminology: ►Emerging Markets◄ Countries which are developed but still have a great deal of positive potential. Whilst a number of their top companies are US listed the easiest way to trade these countries is via an ETF like EEM. https://t.co/2Ant3vdalz

CloudQuant Thoughts: Technology skews towards the wealthy white male and so it is obvious that AI data will skew too. It is imperative that all people involved in creating AI/ML give regular thought to whether or not their systems may be displaying a bias. #DataScience

#TraderTerminology: ►BRIC◄ Brazil, Russia, India, China - Considered to be the top of the Emerging markets and thus a ripe opportunity for investment and profit. https://t.co/cw00aHL2yu

The expansion of #AlternativeData into investing and trading has been growing. We are aware of the challenges that portfolio managers, data scientists, and quantitative traders have in assimilating the huge number of data sets.

What are your #altData roadblocks?

#TraderTerminology: ►Earnings◄ When traders say "it's Earnings" they mean we are in the middle of the earnings period, when most companies issue their Earnings Reports. This is a time of increased Volume and increased Volatility. GREAT! https://t.co/nhTPo6WTds

Every step forward in improving #AI identification of images is helpful. Improving image recognition has benefits for #AlternativeData investing. Better classifications of data in image-derived data = Better quality data = Better Quant Investing. https://t.co/omJM1mhF3g

#TraderTerminology: ►Average Dollar Risk - Trading◄ In trading this means the average $ capital in play per day. So if you traded $10m on day 1, $30m on day 2 and $60m on day 3 your Average Dollar Risk would be $33.3m. https://t.co/VhZPRYwxV4