quantpylib.hft.lob
LOB
__init__(timestamp=-1, bids=None, asks=None, depth=100, buffer_size=100)
A class representing a Limit Order Book (LOB) for financial trading.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
timestamp
|
float
|
The initial timestamp in milliseconds. Defaults to current time. |
-1
|
bids
|
ndarray
|
Initial bid array. Defaults to None. |
None
|
asks
|
ndarray
|
Initial ask array. Defaults to None. |
None
|
depth
|
int
|
The maximum depth of the order book. Defaults to 100. |
100
|
buffer_size
|
int
|
The size of the buffers for storing historical data. Defaults to 100. |
100
|
as_dict()
Represent the current state of the order book as a dictionary.
Returns:
| Name | Type | Description |
|---|---|---|
dict |
The current timestamp, bids, and asks. |
as_tuple()
Represent the current state of the order book as a tuple.
Returns:
| Name | Type | Description |
|---|---|---|
tuple |
The current timestamp, bids, and asks. |
buffer_len()
Get the length of the buffers.
Returns:
| Name | Type | Description |
|---|---|---|
int |
The length of the buffers. |
clear_buffer()
Clear all historical data buffers.
cumulative_size(dir, price)
Returns the size and volume that can be executed given a limit price instantaneously.
get_asks_buffer()
Get the buffer of three-dimensional (time,price,size) ask arrays.
Returns:
| Type | Description |
|---|---|
|
np.ndarray: The array of ask arrays in the buffer. |
get_bids_buffer()
Get the buffer of three-dimensional (time,price,size) bid arrays.
Returns:
| Type | Description |
|---|---|
|
np.ndarray: The array of bid arrays in the buffer. |
get_mid()
Get the mid price of the current order book.
Returns:
| Name | Type | Description |
|---|---|---|
float |
The mid price. |
get_mids_buffer()
Get the buffer of one-dimensional mid prices.
Returns:
| Type | Description |
|---|---|
|
np.ndarray: The array of mid prices in the buffer. |
get_spread()
Get the spread of the current top of book.
Returns:
| Name | Type | Description |
|---|---|---|
float |
The spread. |
get_ts_buffer()
Get the buffer of one-dimensional timestamps.
Returns:
| Type | Description |
|---|---|
|
np.ndarray: The array of timestamps in the buffer. |
get_vamp(notional)
Calculate the volume-adjusted mid price.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
notional
|
float
|
The notional amount for the calculation. |
required |
Returns:
| Name | Type | Description |
|---|---|---|
float |
The volume-adjusted mid price. |
get_vol(n=None, absolute=True, exp=False)
Calculate the volatility of the mid prices over the last n updates.
Excludes zero differences.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
n
|
int
|
The number of updates to consider. Defaults to the length of the mids buffer. |
None
|
absolute
|
bool
|
Whether to return absolute volatility. Defaults to True. |
True
|
exp
|
bool
|
Whether to use exponential weighting. Defaults to False. |
False
|
Returns:
| Name | Type | Description |
|---|---|---|
float |
The calculated volatility. |
load_buffer(timestamps_buffer, bids_buffer, asks_buffer, mids_buffer)
staticmethod
Load a Limit Order Book (LOB) from existing buffers.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
timestamps_buffer
|
RingBuffer
|
Buffer containing timestamps. |
required |
bids_buffer
|
RingBuffer
|
Buffer containing bid arrays. |
required |
asks_buffer
|
RingBuffer
|
Buffer containing ask arrays. |
required |
mids_buffer
|
RingBuffer
|
Buffer containing mid prices. |
required |
Returns:
| Name | Type | Description |
|---|---|---|
LOB |
The loaded Limit Order Book. |
load_numpy_arr(timestamps_array, bids_array, asks_array, mids_array)
staticmethod
Load a Limit Order Book (LOB) from existing numpy arrays. Buffer attributes are instantiated exactly equal to the length of arrays passed in.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
timestamps_array
|
ndarray
|
Array containing timestamps. |
required |
bids_array
|
ndarray
|
Array containing bid arrays. |
required |
asks_array
|
ndarray
|
Array containing ask arrays. |
required |
mids_array
|
ndarray
|
Array containing mid prices. |
required |
Returns:
| Name | Type | Description |
|---|---|---|
LOB |
The loaded Limit Order Book. |
taker_impact(dir, size)
Returns the price of size being executed on the orderbook instantaenously.
update(timestamp, bids, asks, is_snapshot, sort_levels=False)
Update the order book with new bid and ask data.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
timestamp
|
float
|
The current timestamp in milliseconds. |
required |
bids
|
ndarray
|
The new bid array. |
required |
asks
|
ndarray
|
The new ask array. |
required |
is_snapshot
|
bool
|
Whether the update is a snapshot (true) or an incremental update (false). |
required |
a_in_b(a, b)
Check if elements of array a are in array b.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
a
|
ndarray
|
The array of elements to check. |
required |
b
|
ndarray
|
The array to check against. |
required |
Returns:
| Type | Description |
|---|---|
|
np.ndarray: A boolean array indicating if elements of |