1652187068
Open free Demat account in India.
One of the most popular dilemmas in the world of trading - what is the difference between Margin Trading and Futures Trading? Are they literally one and the same?
This is the question that stumps many an amateur trader when they begin their trading journey.
Futures Trading and Margins trading are two fundamentally different concepts, providing different benefits altogether.
While Futures Trading allows you to sell contracts that allow you to buy/sell an underlying asset at a specific time and price, margin trading allows you to trade using leverage. You'll be required to set aside money as collateral (as margin), to use the levered funds for trading. if you end up losing money on the trades, you'll be required to post up more collateral.
Margin trading can be done both in the spot and in the derivatives market. This means, you can effectively utilize margins to trade in futures contracts as well.
With that out of the way, let's go more in depth about what Futures trading and margins trading really means, and how you can use that to your advantage.
Margin Trading allows you to purchase stocks that you can't otherwise afford (or you're comfortable investing in). You are allowed to purchase shares by paying only a marginal amount of the full value of the share. This margin is either paid as cash, or other shares as a collateral, allowing you to purchase these shares.
They are considered as levered positions - your stock broker funds your margin trading transactions. This additional margin is settled later, once the position is squared off. You can profit off this transaction only if the gains from this trade is much higher than the margin.
You are required to open a margin account with your preferred broker to avail this facility. The margin varies from broker to broker. You are required to maintain a minimum balance in your margin account at all time, else you run the risk of your position being squared off prematurely. At the end of each trading session, the square off is mandatory.
One of the best brokers that allow you to open free trading account online with margin facilities is Goodwill Wealth Management - one of the best trading brokers in India. Goodwill allows you to trade across multiple segments, all with a single margin.
Futures contract are a type of derivatives, that represents an agreement to sell/buy a specific quantity of the underlying asset (stocks, commodities, currencies or even cryptocurrencies), at a specified price, on a specific date in the future (hence the name).
These contracts are traded multiple times in the open market, up until the fulfillment date, making futures a popular investment for trading.
These contracts are either settled by physical delivery, or by cash.
Futures trading is particularly common with commodities. If someone purchases a march futures contract for crude palm oil, they're agreeing to purchase a 1000 barrels of crude palm oil at the specified price, upon expiration. The original writer/purchaser trades their contract to other people, and the ultimate holders will honor this contract, either by physical delivery, or settled using cash.
Some futures instruments might be cash settled only, where physical delivery is not common. For instance, all Foreign Exchange trades are currently cash settled in India.
While you don't necessarily need a Demat account to begin your futures trading journey in India, it is highly recommended that you open one. If you intend to take delivery of the futures contract, you're required to open free Demat account in India. Head on over to your preferred brokerage site, establish a futures trading system, and begin your trading journey now!
If you're looking to open a free Demat and Trading account, head on over to gwcindia.in, or click this link to begin the process.
#trending #finance #trading #account #india #management #exchange
1650686940
prose
prose
is a natural language processing library (English only, at the moment) in pure Go. It supports tokenization, segmentation, part-of-speech tagging, and named-entity extraction.
You can find a more detailed summary on the library's performance here: Introducing prose
v2.0.0: Bringing NLP to Go.
$ go get github.com/jdkato/prose/v2
package main
import (
"fmt"
"log"
"github.com/jdkato/prose/v2"
)
func main() {
// Create a new document with the default configuration:
doc, err := prose.NewDocument("Go is an open-source programming language created at Google.")
if err != nil {
log.Fatal(err)
}
// Iterate over the doc's tokens:
for _, tok := range doc.Tokens() {
fmt.Println(tok.Text, tok.Tag, tok.Label)
// Go NNP B-GPE
// is VBZ O
// an DT O
// ...
}
// Iterate over the doc's named-entities:
for _, ent := range doc.Entities() {
fmt.Println(ent.Text, ent.Label)
// Go GPE
// Google GPE
}
// Iterate over the doc's sentences:
for _, sent := range doc.Sentences() {
fmt.Println(sent.Text)
// Go is an open-source programming language created at Google.
}
}
The document-creation process adheres to the following sequence of steps:
tokenization -> POS tagging -> NE extraction
\
segmentation
Each step may be disabled (assuming later steps aren't required) by passing the appropriate functional option. To disable named-entity extraction, for example, you'd do the following:
doc, err := prose.NewDocument(
"Go is an open-source programming language created at Google.",
prose.WithExtraction(false))
prose
includes a tokenizer capable of processing modern text, including the non-word character spans shown below.
Type | Example |
---|---|
Email addresses | Jane.Doe@example.com |
Hashtags | #trending |
Mentions | @jdkato |
URLs | https://github.com/jdkato/prose |
Emoticons | :-) , >:( , o_0 , etc. |
package main
import (
"fmt"
"log"
"github.com/jdkato/prose/v2"
)
func main() {
// Create a new document with the default configuration:
doc, err := prose.NewDocument("@jdkato, go to http://example.com thanks :).")
if err != nil {
log.Fatal(err)
}
// Iterate over the doc's tokens:
for _, tok := range doc.Tokens() {
fmt.Println(tok.Text, tok.Tag)
// @jdkato NN
// , ,
// go VB
// to TO
// http://example.com NN
// thanks NNS
// :) SYM
// . .
}
}
prose
includes one of the most accurate sentence segmenters available, according to the Golden Rules created by the developers of the pragmatic_segmenter
.
Name | Language | License | GRS (English) | GRS (Other) | Speed† |
---|---|---|---|---|---|
Pragmatic Segmenter | Ruby | MIT | 98.08% (51/52) | 100.00% | 3.84 s |
prose | Go | MIT | 75.00% (39/52) | N/A | 0.96 s |
TactfulTokenizer | Ruby | GNU GPLv3 | 65.38% (34/52) | 48.57% | 46.32 s |
OpenNLP | Java | APLv2 | 59.62% (31/52) | 45.71% | 1.27 s |
Standford CoreNLP | Java | GNU GPLv3 | 59.62% (31/52) | 31.43% | 0.92 s |
Splitta | Python | APLv2 | 55.77% (29/52) | 37.14% | N/A |
Punkt | Python | APLv2 | 46.15% (24/52) | 48.57% | 1.79 s |
SRX English | Ruby | GNU GPLv3 | 30.77% (16/52) | 28.57% | 6.19 s |
Scapel | Ruby | GNU GPLv3 | 28.85% (15/52) | 20.00% | 0.13 s |
† The original tests were performed using a MacBook Pro 3.7 GHz Quad-Core Intel Xeon E5 running 10.9.5, while
prose
was timed using a MacBook Pro 2.9 GHz Intel Core i7 running 10.13.3.
package main
import (
"fmt"
"strings"
"github.com/jdkato/prose/v2"
)
func main() {
// Create a new document with the default configuration:
doc, _ := prose.NewDocument(strings.Join([]string{
"I can see Mt. Fuji from here.",
"St. Michael's Church is on 5th st. near the light."}, " "))
// Iterate over the doc's sentences:
sents := doc.Sentences()
fmt.Println(len(sents)) // 2
for _, sent := range sents {
fmt.Println(sent.Text)
// I can see Mt. Fuji from here.
// St. Michael's Church is on 5th st. near the light.
}
}
prose
includes a tagger based on Textblob's "fast and accurate" POS tagger. Below is a comparison of its performance against NLTK's implementation of the same tagger on the Treebank corpus:
Library | Accuracy | 5-Run Average (sec) |
---|---|---|
NLTK | 0.893 | 7.224 |
prose | 0.961 | 2.538 |
(See scripts/test_model.py
for more information.)
The full list of supported POS tags is given below.
TAG | DESCRIPTION |
---|---|
( | left round bracket |
) | right round bracket |
, | comma |
: | colon |
. | period |
'' | closing quotation mark |
`` | opening quotation mark |
# | number sign |
$ | currency |
CC | conjunction, coordinating |
CD | cardinal number |
DT | determiner |
EX | existential there |
FW | foreign word |
IN | conjunction, subordinating or preposition |
JJ | adjective |
JJR | adjective, comparative |
JJS | adjective, superlative |
LS | list item marker |
MD | verb, modal auxiliary |
NN | noun, singular or mass |
NNP | noun, proper singular |
NNPS | noun, proper plural |
NNS | noun, plural |
PDT | predeterminer |
POS | possessive ending |
PRP | pronoun, personal |
PRP$ | pronoun, possessive |
RB | adverb |
RBR | adverb, comparative |
RBS | adverb, superlative |
RP | adverb, particle |
SYM | symbol |
TO | infinitival to |
UH | interjection |
VB | verb, base form |
VBD | verb, past tense |
VBG | verb, gerund or present participle |
VBN | verb, past participle |
VBP | verb, non-3rd person singular present |
VBZ | verb, 3rd person singular present |
WDT | wh-determiner |
WP | wh-pronoun, personal |
WP$ | wh-pronoun, possessive |
WRB | wh-adverb |
prose
v2.0.0 includes a much improved version of v1.0.0's chunk package, which can identify people (PERSON
) and geographical/political Entities (GPE
) by default.
package main
import (
"github.com/jdkato/prose/v2"
)
func main() {
doc, _ := prose.NewDocument("Lebron James plays basketball in Los Angeles.")
for _, ent := range doc.Entities() {
fmt.Println(ent.Text, ent.Label)
// Lebron James PERSON
// Los Angeles GPE
}
}
However, in an attempt to make this feature more useful, we've made it straightforward to train your own models for specific use cases. See Prodigy + prose
: Radically efficient machine teaching in Go for a tutorial.
Author: jdkato
Source Code: https://github.com/jdkato/prose
License: MIT License
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