Programming language
It does not matter whichy technology and programming language you choose to write trading bot, you should focus on algorithms that will help your bots run better. A good bot should anticipate market behavior. Bring us the profit and guarantee a low risk of capital loss. Basic approach would be seting 'border value' and buying when red selling when the profit exceeds the assumed percentage. Such approach may works but probability of loss is high.
Markov chains
To understand the markov chains will present several situations in which they apply.
Student takes part in the class once a week. If in one week the student came prepared the probability that he will be prepared in the next week is 0.7 on the other hand, if in a given week the student is unprepared for classes, the next week the probability of being prepared is 0.2. Markov chains will help you answer the following questions, If a student is unprepared for a week(red), how long will it take for him to prepare(green)? Or If in a given week the student is prepared for the class, how long will we have to wait until he is imprepared?(how long will it be green?)
If it's so easy then why is it so hard?
The biggest problem is gathering the right amount of data to determine the probability of a particular event. In the beginning the bot should walk without turning real money. The later bot starts functioning on the real exchange, the better the results will be.
Additional resources
If you still do not understand how markov chains works, check http://setosa.io/ev/markov-chains/ for visual explenation or http://www.statslab.cam.ac.uk/~rrw1/markov/ for full course in this field.