Parkinson’s disease is one of the dreaded diseases by the humankind and there is a lot of finance and resources going into Parkinson’s-related research. Once affected by the diseases, the patients will feel muscle rigidity coupled with a tremor in the body. The disease is also characterised by postural and gait abnormalities and sometimes the patients lose their ability to move. Various streams in the healthcare sector offer treatment to the disease, and the majority of the patients go for either parkinson's ayurvedic treatment or allopathic treatment.

Usually the patients will be demoralised and depressed once they come to know that they are affected by the disease; this in turn again affects their physical and mental health; hence the doctors ask the patients to put up a brave face and to face the consequences.

Let us look into the lives of those who bravely faced Parkinson’s disease. The great boxer Mohammed Ali will be a fine example as he continues his social obligations and makes public appearances, though the disease has robbed him of the control on his body movements to an extent. The chief of chipmaker Intel too had been affected by the disease and he started actively contributing to solve the riddles related to Parkinson’s. He used his influence and money to support and spur the research on the disease. The stories of these living models will be surely inspiring to other patients who continue their battle with the disease.

We have created some example models to demonstrate some of the abilities of Adaptive Modeler. The models can be downloaded from the download page. Most of them can be opened with any edition of Adaptive Modeler [1].

This page shows the performance of the example models and explains how they were created. We also explain how they can be used to view their historical evolution, verify
"out-of-sample"[2] evolution since their creation, and continue model evolution for ongoing performance evaluation. Finally we explain how these models can be used for trading.

The example models were created on the model creation date shown in the tables below (not to be confused with the historical model start date) and are still evolving and generating signals as of today.

The tables show the Trading Simulator performance of the models[3]. The historical results are the results from model start date until model creation date.

It should be noted that the historical model results may seem less impressive than those reported by many other trading software systems that use some form of optimization. However, as explained here, Adaptive Modeler's incremental walk-forward approach (not optimized) prevents overfitting and leads to more resilient models whose historical results are more reliable and more indicative of future results.

The results since creation are the results from model creation date until recently. Since the historical period generally spans several decades while the period since creation is much shorter, relatively less significance should be attributed to the results since creation. Models that have performed well historically, may also sometimes undergo periods of poor performance and may therefore (temporarily) show poor returns since creation date[4].

More extensive performance information is available inside the models.

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