Long time no post

Hi. I haven't written in this for a while. It's because I've finally settled into a good study routine with university courses as well as CFA curriculum study. I think it is a good routine and it involves doing the previous reading questions in the morning, then a new reading in the afternoon. At night I plan to do questions from analyst notes for a topic, but if I don't get around to it, it's no big deal since I can easily make it up later. Hopefully I can do 5 readings a week with this schedule but it means I wont finish the readings by the start of October :( Hopefully I will still be alright, I think I will still have enough time to do plenty of revision and exams before the exam.

Last week I finished reading 8 and so far this week I've completed readings 9 and 10. Reading 8 contained a lot of probability concepts (that's the title of the reading after all) and the most interesting was Bayes formula. It says you can update your calculated probabilities when you receive new information which will affect those probabilities:

Updated probability of event given the new information = (probablility of the new information, given the event/unconditional probability of the new information) * the prior probablity of the event

or: P(Event\Information) = P(Information\Event)/P(Information) * P(Event)

This reading was quite difficult because there were lots of different probability equations to remember. I will have to review these a few times in the future..

Reading 9 was concerned with probability distributions. By far, the most interesting concept introduced was Monte Carlo simulation which is a risk analysis technique in which probable future events are simulated on a computer. You use this to test scenarios before you actually perform it. This way you have a general idea of what may happen. The reading used an example of whether it could be profitable to trade based on the investor's ability to time the markets. The Monte Carlo simulation concluded you need to be able to predict at least 80% of the time whether the market in a given year will be a bull market or a bear one. Do you think you could do this?

Reading 10 is mainly dealing with sampling and constructing confidence intervals. There was nothing that interesting bought up in this reading but data-mining bias is something new I learnt about. This occurs when a dataset is searched through to find statistically significant patterns. When this bias exists, it's very unlikely the model will have any predictive power. So it's important to be able to spot situations where this exists.

I also did two basic question tests. I got 8/10 for responsibilities as a CFAI member or candidate, and an abysmal 5/17 (30%) for GIPS. I need to do a lot of revision on that.

137 days until the level 1 exam.