I am trying to figure out the best way to setup custom price calculations. Basically my product will have 5 options for example:
Width (mm):
Bends (Qty):
Length: Qty:
Straps: Yes/No
I can do these as custom options however its quite a complex calculation and needs to be carried out in a specific order. An example would be
The width needs to be rounded up to the next 50
Discount to be applied
Add cost per bends (Bends worked out by £0.06/m * length)
Multiple by Qty
Add 10% for straps
I know how to do the calculation but just not sure the best way if integrating this with Magento.
Any ideas would be much appreciated.
Related
I'm considering various grid trading strategies and I'm wondering what's the optimal action (if any) to take when the price goes out of grid bounds.
In the image below, the price is within a size 4 grid, with 2 buys below and 2 sells above.
Say the price goes above the highest buy or below the lowest sell. If that happens, one can:
Do nothing, and hope that the price goes back into grid bounds.
Set a stop loss or take profit and cancel the grid when they trigger.
Lowering or raising the grid. Price can thus be closer to the grid or inside it.
I can't think of any other ways right now. Any suggestions are welcome.
I designed a new trading strategy called bollmaker in order to overcome the drawbacks of grid trading -- price range issue.
check this out, it's an open source strategy:
https://medium.com/bbgo/bbgo-bollmaker-trading-strategy-3a4e80b482e3
I am in the process of designing an algorithm that will calculate regions in a candlestick chart where strong areas of support exist. An "area of support" in this case is defined as an area in the chart where the price of a stock rises by a large amount in a short period of time. (Please see the diagram below, the blue dots represent these strong areas of support)
The data I am working with is a list of over 6000 TOHLC (timestamp, open price, high price, low price, close price) values. For example, the first entry in this list of data is:
[1555286400, 83.7, 84.63, 83.7, 84.27]
The way I have structured the algorithm to work is as follows:
1.) The list of 6000+ TOHLC values are split into sub-lists of 30 TOHLC values (30 is a number that I arbitrarily chose). The lowest low price (LLP) is then obtained from each of these sub-lists. The purpose behind using this method is to find areas in the chart where prices dip.
2.) The next step is to determine how high the price rose from each of these lows. For this, I take the next 30 candlestick values from the low and determine what the highest high price (HHP) is. Then, if HHP / LLP >= 1.03, the low price is accepted, otherwise it is discarded. Again, 1.03 is a value that I arbitrarily chose, by analysing the stock chart manually and determining how much the price rose on average from these lows.
The blue dots in the chart above represent the accepted areas of support by the algorithm. It appears to be working well, in terms of that I am trying to achieve.
So the question I have is: does anyone have any improvements they can suggest for this algorithm, or point out any faults in it?
Thanks!
I may have understood wrong, however, from your explanation it seems like you are doing your calculation in separate 30-ish sub lists and then combining them together.
So, what if the LLP is the 30th element of sublist N and HHP is 1st element of sublist N+1 ? If you have taken that into account, then it's fine.
If you haven't taken that into account, I would suggest doing a moving-window type of approach in reading those data. So, you would start from 0th element of 6000+ TOHLC and start with a window size of 30 and slide it 1 by 1. This way, you won't miss any values.
Some of the selected blue dots have higher dip than others. Why is that? I would separate them into another classifier. If you will store them into an object, store the dip rate as well.
Floating point numbers are not suggested in finance. If possible, I'd use a different approach and perhaps classifier, solely using integers. It may not bother you or your project as of now, but surely, it will begin to create false results when the numbers add up in the future.
I'm making a shop with clothing. But there is a minimal order amount per order. Now i want to have a choice that the customer can make with different sizes.
So the minimal count is 10 pieces, and if a customer wants 4 size M, 5 size L and 1 size XL. what is the easiest way in code that i can accomplish this?
I'm using simple products associated with configurable products.
Maybe this could help :)
How to get the Total Quantity Of All the Items In your Shopping Cart
Today I was studying how Magento tax calculation works to understand the difference between the behaviors for "Tax Calculation Method Based On".
I traced deep into Mage_Tax_Model_Sales_Total_Quote_Tax which implements all methods in the _unitBaseCalculation, _rowBaseCalculation, _totalBaseCalculation.
I discovered that they produce exactly the same results. So why did they go through the trouble of implementing them ?
For example, unit-price calculation goes to the trouble of calculating the tax for the single unit and then dividing the discount amount by the qty (if tax applied after discount), then subtracting both, and then multiplying again by the quantity... which just introduces rounding errors.
Whereas Row Total calculation is the most intuitive one (which takes the price from the row "subtotal") minus discount amount (if tax applied after discount).
While the third one is just an aggregation of the second, calculated at once.
This just introduces confusion and obfuscation to the tax calculation logic. Can anyone shed a light onto why this was done ?
(Rounding errors ? Backward compatibility ? Candidate for TheDailyWTF prize ?)
EDIT: For the record this is true as of Magento 1.6 and 1.7, don't know about older versions.
I found this from: https://gist.github.com/2572772 (by Alan Storm it seems)
This feature was probably motivated by individual local rules (or client requests) as to how taxes should be calculated, as fractional amounts could add up differently depending on when adding and rounding occurs. THat said, I haven't run through the code to see if my guesses are right so YMMV. Other areas to consider for future research.
How does each mode play with shopping cart price rules and store wide discounts
For shopping cart price rules, it goes through painstaking trouble to divide the discount amount (which may not be divisible by the quote item quantity thus introducing a rounding error) so that the end result is the actually the same process, but only with different "when"s and "where"s as to rounding.
Here is the scenario. I have a configurable product which has two attributes. However, the price increment for the second attribute is dependent on the first. The price increments are a combination of fixed and percentage. So, lets assume the two attributes in question are size and colour - the amount added on for larger sizes is fixed, but the amount added on for different colours is a percentage.
The issue is that magento is adding the percentage increment for colour to the base price, not to the price plus the fixed increment for size.
As an example, let assume my product is available in three sizes, small medium and large; and in three colours, red, green and blue. The increment for medium and large are £5 and £10 respectively, and the increment for colour is 5% for green and 10% for blue (to be applied dependent on the size selected). My product has a base price of £100.
A customer purchasing a medium red product would pay £105, however magento applies the same price to a customer purchasing a medium blue product (because the percentage increase is calculated BEFORE the size is selected).
Is there any way to handle this so that the correct percentage increase is calculated AFTER the size is selected?
Cheers
Simon
Generally I do not like to recommend this extension as it makes pricing in Magneto way more complicated and time consuming (I just got out of it myself and it was not the fault of the module), but I think this might be the solution for you:
http://www.magentocommerce.com/magento-connect/simple-configurable-products.html
Basically this modifies the way Configurable products are priced so that it uses the price of the simple product and not the values contained in the super attributes.
The upside is that the price of the simple product is the price that it will be sold for on the configurable page.
The downside is that it is very easy to have the website do some funky things with pricing if you are not careful. For example we had a lot of scenarios where the configurable product price was $10.00, but all the simple products price was $8. Each item in the dropdown had a "negative upcharge" in there.
This was not the modules fault, rather carelessness of people managing the products.