Below is the reference and Bibliography we are often using for our research and development work in the area of Financial Investment and Trading. We only list this reference & Bibliography for some curious traders and investors. For average traders and investors, there is absolutely no need to read any of these papers. More direct instructions and usage manuals on our products can be found on our Manual page.

Asset Pricing

Alderfer C.P., Bierman H., 1970, Choices with Risk: Beyond the Mean and Variance, The journal of Business, Vol. 43 (No. 3), 341-353

Andersson F., Mausser H., Rosen D., Uryasev S., 2001, Credit Risk optimization with conditional value at risk criterion, Mathematical Programming, Vol. 89 (No. 2), 273-291

Alexander G.J., Baptista A.M., 2006, Portfolio selection with drawdown constraints, Journal of Finance and Banking, Vol. 30 (Issue 11), 3171-3189

Altman, 1968, Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy, The Journal of Finacne, Vol. 23 (No. 4), 589-609

Altman E.I., Saunders A., 1998, Credit Risk Measurement: Developments over the last 20 years, Journal of Banking & Finance, Vol. 21, 1721-1742

Azmi R., Tamiz M., 2010, A Review of Goal Programming for Portfolio selection, Lecture Notes in Economics and Mathematical Systems, Vol. 638, 15-33

Bodie Z., Kane A., Marcus A.J., 2008, Investments, 8th ed., New York, McGraw Hill/Irwin

Branke J., Scheckenbach B., Stein M., Deb K., Schmeck H., 2009, Portfolio optimization with an envelope based multi objective evolutionary algorithm, European Journal of Operational Research, Vol. 199, 684-693

Chang, T.J., Meade N., Beasley J.E., Sharaiha Y.M., 2000, Heuristics for cardinality constrained portfolio optimization, Computers & Operations Research, Vol. 27, 1271-1302

Chapados N., 2011, Portfolio Choice Problems: An Introductory Survey of Single and Multiperiod models, New York: Springer

Chekhlov A., Uryasev S., Zabarankin M., 2005, Drawdown measure in portfolio optimization, International journal of Theoretical and applied Finance, Vol. 8, 13-58

Fishburn P.C., Mean-risk analysis with risk associated with below target returns, American Economic Review, Vol. 67 (No. 2), 116-126

Freedman R.S., DiGiorgio R., 1993, A Comparison of Stochastic Search Heuristics for Portfolio Optimization, Proceedings of the Second International Conference on Artificial Intelligence Applications on Wall Street: Software Engineering Press, 149-151

Gilli M., Kellezi E., 2002, A Global Optimization heuristic for Portfolio Choice with VaR and Expected Shortfall, Computational Methods in Decision making, Economics and Finance, Applied Optimization Series, Kluwer Academic Publishers, 167-183

Gregory J., 2010, Counterparty Credit Risk: The new challenge for global financial markets, Chichester: John Wiley & Sons Ltd.

Group of Thirty, 1994, Derivatives: Practices and principles, Group of Thirty, Washington D.C.

Guidolin M., Hyde S., 2008, Equity portfolio diversification under time varying predictability: Evidence from Ireland, the US, and the UK, Journal of Multinational Financial Management, Vol. 18, 2008

Gulpinar N., Rusten B., 2007, Worst case robust decisions for multi period mean-variance portfolio optimization, European Journal of Operational Research, Vol. 183, 981-1000

Huang C., Litzenberger R., 1988, Foundation for Financial Economics, 1st ed., New York: Prentice hall

Jarrow R.A., Turnbull S.M., 2000, The intersection of market and credit risk, Journal of Banking & Finance, Vol. 24, 271-299

Jackson M., Staunton M., 2001, Advanced modeling in finance using Excel and VBA, Chichester: John Willey Sons Ltd.

Konno H., Yamazaki H., 1991, Mean absolute deviation portfolio optimization model and its application to Tokyo Stock Market, Management Science, Vol. 37 (No. 5), 519-531

Markowitz H., 1952, Portfolio Selection, Journal of Finance, Vol. 7 (No. 1), 77-91

Ogryczak W., Ruszczynski A., 1999, From stochastic dominance and mean risk models: Semideviations as risk measures, European Journal of Operational Research, Vol. 116, 33-50

Osorio M.A., Gulpinar N., Rustem B., Settergren R., 2004, Tax impact on multi stage mean-variance portfolio allocation, International Transactions in Operational Research, Vol. 11, 535-554

Rockafeller R.T., Uryasev S., 2000, Optimization of conditional Value at Risk, Journal of Risk, Vol. 2, 21-42

Roy A.D., 1952, Safety first and the holding of assets, Econometrica, Vol. 20 (No. 3), 431-449

Whitemore G.A., Findlay M.C., 1986, Stochastic dominance: An approach to decision making under risk, Risk Analysis, Vol. 6 (Issue 1), 35-41


Grigoletto M., 1998, Bootstrap prediction intervals for autoregressions: some alternatives, International journal of Forecasting, 14, 447-456

Hossein A., Yousefi M. R., Araabi B.N., Lucas C., Barghinaia S.,2007, Combination of Singular Spectrum Analysis and Autoregressive Model for Short Term Load Forecasting, Power Tech 2007 IEEE Lausanne, 1090-1093

Time Series Forecasting

Chatfield C., 1993, Calculating interval forecast, Journals of Business and Economic statistics, 11, 121-144

De gooijer J.G., Hyndman R.J., 2006, 25 year of time series forecasting, International journal of forecasting, 22, 443-473

Dorffner G., 1996, Neural Networks for Time Series Processing, Neural Network World, 6(4), 447-468

Gardner E.S.Jr., 1988, A simple method for computing prediction intervals for time series forecasting, Management Science, Vol 34, 541-546

Makridakis S., Wheelwright S.C., Hyndman R.J., 1998, Forecasting Methods and Applications, 3rd ed, Danvers, United states of America: John Wiley & Sons, Inc.

Tay A., Wallis K.F., 2000, Density forecasting: A Survey, Journal of Forecasting, 19, 235-254

Taylor J.W., Bunn D.W., 1999, A Quantile regression approach to generating prediction intervals, Management Science, Vol. 45(No. 2), 225-237

Taylor J.W., 2010, Triple Seasonality Methods for Short-Term Electricity Demand Forecasting, European Journal of Operational Research, 204, 139-152

Statistics and Data Mining

Balkin S., 1997, Using recurrent neural networks for time series forecasting, International symposium on forecasting, 1997, Barbados

Burgess A.N., Refenes A-P. N., 1999, Modeling non-linear moving average process using neural networks with error feedback: An application to implied volatility forecasting, Signal Processing, Vol. 74 (Issue 1), 89-99

Pascual L.J., Romo J., Ruiz E., 2001, Effects of parameter estimation on prediction densities: A bootstrap approach, international Journal of Forecasting, 17, 83-103

Prudencio R.B.C., Ludermir T.B., 2003, Neural network hybrid learning: Genetic algorithms & Levenberg-Marquardt, Studies in Classification, Data analysis and knowledge organization, 2003, 464-472