Yeswici (YesWeSee) is a quantitative modeling and computing platform for innovative investment research. The platform transfers investment research into Internet/mobile apps and services. The audience of the platform includes (1) portfolio managers, traders, financial advisors and investment analysts with quant background; (2) corporations and institutions that care about their ticker performance and market volatility; (3) high-net-worth investors who appreciate real-time stock recommendations, financial news and stock insights from the crowd.

Comparing to MorningStar's charting with historical data, the premium app of the platform, SentimentAssetPricingEngine (SAPE), visualizes real-time future asset prices. The engine aggregates a large amount of traders' real-time sentiments on the future prices of stocks or ETF funds. The financial value of the SAPE may be assessed by the stock picking (advisory) fees of mutual funds. For example, Fidelity Magellan (FMAGX) took in $3.7 billion fees during the 1999-2008 period.

SAPE entails a unique set of computer algos that aggregate traders’ real-time sentiment to estimate an individual asset’s future prices. It fills the gap of the Black-Scholes model and other Nobel models that did not consider behavioral factors in asset pricing. Comparing to the Nobel models that provide theories and formulas, SAPE provides an end-to-end solution to portfolio management, including a new theory on behavioral investing, a new formula on estimating future prices of individual assets, and a new computer system for real-time future asset pricing, asset allocation, and market timing.

 

Desktop: visualFunds download

 

More on SAPE algos appear in Dr. Gewei Ye’s new book: "High-Frequency Trading Models," released in January 2011 by John Wiley & Sons, Hoboken. The book, at Wiley, includes teaching notes for training Hopkins graduate students to be top portfolio managers and investment experts with humanity in mind. See a sample chapter entitled "Loss Aversion in Option Pricing: Integrating Two Nobel Models."

(This site is for academic use; SAPE funds are effective with sophisticated arbitrage and hedging strategies; consult an investment expert or contact info@yeswici.com before exercising on SAPE charts)

 

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Labs to transfer research to Internet applications

1. AlgoTrading feeds: platform as service with SOA*; use REST/XML: sample

2. SOA Value Calculator: Calculate the Financial (business) value of SOA; Calculate the Net Present Value of SOA.

3. Fund Box Chart Widget: Get box charts on your site or blog for 11012 funds with the widget. See Demo 1; Demo 2

4. Stock Box Chart Widget: Get stock chart on your site or blog. See Demo 1

5. visualConfidence(vc): forecast equity performance with realtime investor confidence

6. Customer equity calculator; Elliott Wave detector; Behavioral finance approach.

7. NewspaperStocks. Widget Demo

8. Yes ratio: extending Sharpe ratio with a debiasing algorithm. Which states are better for business? SharpeRatioMap; YesRatioMap

9. Air2tv: a sleek and secure desktop video search engine; Windows version download

10. CRM_ECS system: customer equity, churning, and SOA services.

11. myMapSearch: find anything locally.

12. priceOption with the Black-Scholes model, UI built in Flex; priceBondOption with the Black model; portfolioManager design

13. Some thoughts: Arbitrage algorithm for foreign exchange; real time efficient frontier; riskChart; strategy simulations: fixed income arbitrage vs. quantitative vs. event driven; VaR and GARCH with R-Rmetrics; term structure of interest rates and the Black-Derman-Toy (BDT) model; SP500StrategyChart

14. NewsPortal on twitter; yesTwitter: send data and share as Tweets;

15. What is the best context to use the custom-built APIs for calculating VaR with Garch sigma (ready for REST or RIA)? Realtime option pricing with BSModel and Garch volatility.

16. StockInsights: realtime insights from traders' tweets; plan on making tickers searchable

17. microVIX: a ticker-based investor sentiment indicator that aggregates option positions and community sentiment with text mining technique (YALE) catering for hedge funds and ticker companies; YALE to appear in cloud (Google appEngine)

18. SentimentAssetPricing: calculate asset prices on future dates based on sentiments from very large samples

19. SapeFund: the topTickEngine with SAPE algos determines the portfolio components; compare real-time SAPE fund performance to DJI; compare fund prediction strategy (forward testing)

20. memberServices: need to login; future asset pricing; asset allocation; fund portfolio construction; fund of ETF funds

21. LAOP: real-time empirical data and significance tests on Loss Aversion in Option Pricing

22. Mobile SAPE on Android - sample image; Android twitterSearch; twitterHeadlines on Android

23. About the Wiley book: modeling interest rate swaps; multinomial models and computer algos for bond pricing; SDT algos; VIX forecasting; SDT algos for comparing funds; personalized VaR app with risk propensity of SDT for portfolio managers.

*SOA: Yeswici Web services enable interoperable and repeatable automated access to YesWici scores. Given a fund ticker, the Web services will respond to your client with data in XML format.

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The platform may provide on-demand APIs for carefully evaluated requests. Here is an example for an on-demand API that is based on REST:

http://www.yeswici.com/wici/ws.php?ticker=BFOCX

 

One may request a REST-based API using the following form. If the request is consistent with the thoughts of the platform, the API will appear on this page. If possible, please define the response of the request in XML format. One may also use the form for querying premium apps or services.

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Yeswici is a modeling and computing platform for investment research. The research platform overlaps financial engineering, quantitative and behavioral finance, choice modeling, and Internet computing.

The flagship solution of the platform is the SAP system (see sentimentAssetPricing). For investor relations, please contact investor@yeswici.com.

At present the platform focuses research on investor confidence algorithms that derive riskPropensity (also termed as the investor decision criterion, IDC, or the micro investor confidence) with Signal Detection Theory (a respectable decision model) from the Black-Scholes model. Aggregated in a nonlinear manner, the riskPropensity is transformed to VIX (Volatility Index, CBOE) as the macro investor confidence. The VIX is then translated into meaningful and real time sentiment in a Google gadget (see the left). visualFunds will implement the IDC algorithm for comparing present and future (Monte Carlo Simulation) performances of ETF and mutual funds. visualConfidence attempts to forecast equity performance with live investor confidence data (so far with about 90% accuracy to fit recent 3 month trends).

The principal mission of the platform is to use investor confidence research to establish successful quantitative strategies and algorithms for forecasting market trends and creating or auditing financial instruments. The mission may be achieved by creating novel real-time investing utilities based on investor confidence.