(a) (b) (c)
FIGURE 2.6. (a) Demand Relationship (b) Supply Relationship (c) Demand and
Supply Relationship
Therefore, it can be said that price is the reflection of demand and supply. It is believed that behind the allocation of various resources underlies the relationship between these two (demand and supply). For example, if there is a shortage of oranges in the market, their price would increase. This reason behind this is the reduced supply and increased demand for the fruit. It will create a competition amongst the buyers who will compete by offering higher pricesand will result in enabling the sellers to increase the price of the oranges. Also, the laws of demand and supply suggest that in order to overcome the …show more content…
It can also be said that these are the ’live’ orders,
i.e, the orders that are still not dropped by the traders that initiated them. In market language, offers can also be known as asks.
As shown in table 2.1 (below), the LOB has two parts: the ask book(part for sellers)and the bid book(part for buyers). The first book displays quantity and prices of recorded asks in increasing order in a way that the lowest or best ask price is at the top of that side of the book. Whereas the bid book shows the available quantity and the prices of outstanding bid(proposal) orders, in decreasing order, such that the highest or best bid is at the top of that side of the book.
For example, it may be seen from table 2.1 that the best bid is GBP1.62 with an available quantity for that bid is 8; whereas the offer-price (or the best ask) is GBP1.20,
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2.3. ECONOMICS INVOLVED
Table 2.1: Limit order book (LOB) for ABC. with available quantity as 25. There is further stock available apart from best bid and ask but at less good values. Currently, the bid-ask spread is 0.42GBP.
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C H A P T E R …show more content…
The principle objective of conducting these examples is to learn about how to train and test the neural network models using Keras so that better traders can be generated for the research. Moreover, this will ensure that the tensorflow and keras are properly installed on the system and also that the neural networks hence created are correctly modeled.
Consequently, the learnings from this chapter will serve as an elaborated explanation of all the Keras parameters that will be used in chapter 5.
The following examples include training the neural network and evaluate their accuracy for the famous handwritten digits dataset: MNIST(using MLP and CNN) and an International Airline Passengers prediction problem(using LSTM-RNN).
MNIST Dataset
MNIST is the dataset of handwritten digits, available from the Yann LeCun et al. webpage[40]. The database constitutes of 60,000 and 10,000 examples for the training set and test set respectively. The example constitutes of the black-white figures