Encinitas, CA (PRWEB) July 12, 2017
The net return of the Trade Ideas’ simulated portfolio for 2017 for Q1 and Q2 ending June 30 was 22% after commissions in Risk-Off mode. These results were achieved by the company’s A.I. powered, Investment Discovery Engine, ‘Holly.’ The portfolio’s gross return before commissions and fees measured 39%. These results compare to the S&P 500, measured by the $SPY index, which earned an 8.2% return over the same period. Risk-Off performance reflects a strict adherence to Reward and Risk targets for each trade. Actions are not deviated from original trade plan rules regardless of initial positive performance; however, positions may be exited earlier if existing profits erode significantly. This mode is meant to conservatively portray HOLLY performance results.
“Again, this performance exceeds our expectations and confirms the enormous value our A.I. innovation brings to the investment decisions of our clients,” said David Aferiat, Co-Founder and Managing Partner of Trade Ideas. “On a quarterly and semi-annual basis, the A.I. outperforms market benchmarks since its inception January 4, 2016. This track record of performance bodes well as we position Trade Ideas into the Model Marketplace, where subscribers access the daily A.I. generated algorithms for actionable intelligence, but retain control and discretion to implement the trades according to their own decision process and leverage their own trading and rebalancing software. We’re unique in providing such results via an A.I. powered SaaS model.”
HOLLY’s performance in Risk-On mode, where a trade idea’s positive performance affects the decision to go beyond Reward targets (without, however, extending beyond the Market Close), stands at 26% after commission and fees. Taking the best possible scenario, a summation of all the correct decisions on whether to apply Risk-Off and Risk-On modes yielded a whopping 72% return after commissions and fees.
Performance of the Trade Ideas simulated long/short equity portfolio reflects historical daily paper trades in the U.S. and Canadian equity markets. It is not a backtest. Trades are initiated from the daily list of algorithms published by the A.I. system, named ‘HOLLY’, and the result of its overnight optimization analysis or ‘Quantitative Combine.’ The portfolio started with a $1M beginning balance on January 2, 2017 and used $80k (rounded) worth of shares per trade. Commissions are calculated at $0.0075 per share and reflected in the Net Performance (shown in chart). Slippage is not factored. Short trades assume that customer's Broker has access to short inventory for the trades identified by Trade Ideas. In order to showcase the effectiveness of the trades identified by HOLLY for the simulated portfolio, no positions are held overnight. This avoids any conclusion that the outsized return of the A.I. system is the result of one or a handful of successful positions held for weeks or months.
Detailed trade data is available from Trade Ideas and can be segmented by gross and net performance, market cap, and by time periods. The Trade Ideas Simulated Portfolio is transparent, consistent in data processing, and free from selection or survivorship bias. Its inception date is January 4, 2016.
“The innovation of HOLLY as a Virtual Analyst who can separate the signal from the noise this well shakes up the FinTech community. We keep adding innovation atop of more innovation in both the Machine Learning capabilities of HOLLY as well as the experience in receiving the actionable intelligence. See it for yourself,” observed Dan Mirkin, CEO and Co-Founder of Trade Ideas. “You’ll either be using this innovation to capture alpha or others will be using it against you to get theirs. Advisors and Professionals have an entirely new way of not just talking to their clients about leveraging technology, but in generating alpha for their portfolio.”
About Trade Ideas LLC
Trade Ideas creates actionable market intelligence for institutions, advisors, and self-directed investors to make consistently informed decisions mitigating risk and capturing alpha. As a SaaS Fintech innovator for over 13 years, Trade Ideas leverages algorithms derived from recursive, Machine Learning, Artificial Intelligence to develop trade plans and ideas and produce statistically tested, optimized performance results. Trade Ideas' inputs include Big Data sets from U.S. and Canadian market feeds, technical, fundamental, and non-structured data sets such as news and social media. Trade Ideas' client base is from around the world totaling more than 8,000 with operations in the U.S., Canada, China, and Europe.
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