Learn About EUR, GBP and JPY In Detail

6.1 EUR-INR Futures

Varun: Isha I keep seeing EUR-INR and GBP-INR pop up. Is it Worth exploring?

Isha: Definitely. If you understand USD-INR, the others are just variations on the same theme. Think of it like knowing how Nifty works ,  then Bank Nifty isn’t a mystery.

Varun: So the contract specs are similar?

Isha: Almost identical. Same expiry cycle, same trading hours. The only real difference is the underlying currency and how its global movements affect the pair.

Varun: Hmm. I guess I’ll need to brush up on Eurozone and UK macro trends too.

Isha: Exactly. And don’t forget JPY-INR — it behaves differently because of Japan’s interest rate policies. But once you get the hang of it, technical analysis works across all pairs.

Varun: Alright, let’s dive into the specs first. Then maybe we can chart out some setups together?

Isha: You read my mind. Let’s get started.

The EUR-USD pair continues to dominate global forex markets, thanks to the Euro’s role as a major reserve currency and the US Dollar’s central position in international trade. Although this pair isn’t yet available for trading on Indian exchanges, regulatory approval has already been granted — so we can expect EUR-USD, GBP-USD, and JPY-USD contracts to be listed in India soon.

For now, Indian traders can access the EUR-INR futures contract, which allows them to speculate on or hedge the Euro against the Indian Rupee. What sets the Euro apart is its backing by the collective economies of the European Union, rather than a single nation — making it a unique macro asset.

Structurally, the EUR-INR contract mirrors the USD-INR format. It shares the same trading hours (9:00 AM to 5:00 PM), expiry cycle (two working days before month-end), and settlement method (cash-settled in INR). The key difference lies in the lot size, which is €1,000 per contract.

Let’s calculate the contract value using the latest traded price:

• Last traded price: ₹102.6300
• Lot size: €1,000
• Contract Value= 1,000 × 102.6300 = ₹102,630

Assuming a margin requirement of 2.5%, the estimated margin to initiate one lot would be:

• Margin≈ ₹102,630 × 2.5% = ₹2,566

This margin is slightly higher than that of USD-INR due to the Euro’s stronger exchange rate, but still significantly lower than what’s required for equity derivatives — making EUR-INR a cost-effective and globally relevant instrument for Indian currency traders.

GBP-INR Futures

The GBP-INR futures contract continues to be the second most traded currency derivative in India, right after USD-INR. Structurally, it follows the same framework — identical trading hours (9:00 AM to 5:00 PM), expiry cycle (two working days before month-end), tick size (₹0.0025), and cash settlement in INR.

The key differences lie in the underlying currency and the lot size. The underlying is the exchange rate of 1 British Pound against the Indian Rupee, and each contract represents £1,000.

Using the latest traded price:

• Last traded price: ₹117.8400
• Lot size: £1,000
• Contract Value= 1,000 × 117.8400 = ₹117,840

Assuming a margin requirement of 2.5%, the estimated margin to initiate one lot would be:

• Margin≈ ₹117,840 × 2.5% = ₹2,946

This margin is slightly higher than that of USD-INR and EUR-INR, reflecting the Pound’s higher notional value. Still, it remains accessible for retail traders seeking exposure to UK macroeconomic trends.

Forex Trivia: In international markets, the GBP-USD pair is famously known as “Cable.” This nickname dates back to the 19th century when exchange rates between London and New York were transmitted via the first transatlantic telegraph cable laid under the ocean in 1858. So when a trader says they’re “short Cable,” they’re betting against the Pound in the GBP-USD cross

JPY-INR Futures

Among all INR-based currency futures, the JPY-INR contract stands out for its unique structure. Unlike the USD-INR, EUR-INR, or GBP-INR contracts — which use a lot size of 1,000 units — the JPY-INR contract uses a lot size of 100,000 Japanese Yen. However, the price is quoted per 100 Yen in Indian Rupees, which can be a bit tricky for first-time traders.

Let’s break it down using the latest traded price:

• Last traded price: ₹66.4800 (per 100 JPY)
• Lot size: ¥100,000
• Contract Value= (100,000 × 66.4800) ÷ 100 = ₹66,480

Now, assuming a margin requirement of 4.2%, the estimated margin to initiate one lot would be:

• Margin≈ ₹66,480 × 4.2% = ₹2,791

This margin is noticeably higher than what’s required for USD-INR or EUR-INR contracts. One reason could be the relatively lower liquidity and higher volatility of the JPY-INR pair — often influenced by Japan’s interest rate policies, safe-haven flows, and global risk sentiment.

That said, this is a general observation. If you’re analyzing volatility or margin dynamics, it’s best to use actual price data and calculate standard deviation or ATR in Excel for a clearer picture.

Margin, Liquidity & Contract Selection in Currency Futures

• Among all INR-based currency futures, the JPY-INR contract typically demands the highest margin. This is largely due to its unique structure and relatively lower liquidity, which can lead to sharper price movements. While this is a general observation, it’s worth validating with actual data — try calculating historical volatility or ATR in Excel to get a clearer picture of how JPY-INR behaves compared to other pairs.
• On the infrastructure side, spread contracts are available across all major currency pairs and expiry combinations. These allow traders to take positions on the price difference between two expiry months — useful for hedging or calendar spread strategies. You can view live spread contract data on the NSE Currency Derivatives Market Watch, which includes bid-ask prices, volumes, and open interest.

• However, in practice, liquidity in spread contracts is concentrated mostly in USD-INR. The other pairs — GBP-INR, EUR-INR, and JPY-INR ,  tend to have lower participation in spreads, making execution and slippage more challenging.

If you’re selecting contracts based on liquidity and ease of execution, here’s a practical order of preference:

1. USD-INR Futures– Most liquid and widely traded
2. USD-INR ATM Options– Good depth and active participation
3. GBP-INR Futures– Decent liquidity, especially around UK macro events
4. EUR-INR Futures– Moderate volumes, suitable for directional trades
5. JPY-INR Futures– Least liquid, best used with caution and clear setups

With this, you should now have a solid grasp of the logistics and structure of currency trading in India. Next, we’ll shift focus to developing basic trading strategies — starting with technical setups and risk management principles tailored for currency derivatives.

6.2 Testing for Seasonality in Currency Markets

Varun: Isha, some traders say USD-INR always goes up before expiry or drops in December. Is that really true?

Isha: People say that a lot, but unless we check the data, it’s just guesswork.

Varun: So how do we find out if those patterns are real?

Isha: We use a method that looks at past price data to see if there are regular patterns. Let me show you what the numbers say.

Overview

Seasonality refers to recurring price patterns tied to specific time intervals, such as months, weeks, or days. In currency markets, traders often speculate on seasonal behavior, making claims like “USD-INR tends to fall in December” or “USD-INR rises before expiry.” Such assertions, if unverified, can lead to trading decisions based on anecdotal beliefs rather than statistical evidence.

This module examines the presence of seasonality in the USD-INR spot market using a structured statistical approach. The analysis is based on eight years of spot price data sourced from the Reserve Bank of India (RBI).

The Holt-Winters Framework

Seasonality in time series data can be evaluated using the Holt-Winters method, which decomposes a series into three components:

• Level: The baseline value or average change over time
• Trend: The directional movement across periods (e.g., month-on-month)
• Seasonality: Repeating patterns tied to specific time intervals (e.g., consistent January rallies)

Each component can be modeled in either additive or multiplicative form, depending on the nature of the data. For the purpose of this analysis, two models are constructed:

• Model 1: Includes only level and trend components
• Model 2: Includes level, trend, and seasonality components

The accuracy of each model is evaluated using a Chi-Square test to determine whether the inclusion of seasonality improves forecast performance.

Weekly Seasonality Analysis

• Model 1 (No Seasonality)Configuration: (M, N, N) Coefficient: Level = 0.9999 Interpretation: Weekly price movement resembles a random walk, with next week’s price nearly equal to the current week’s price.
• Model 2 (With Seasonality)Configuration: (M, N, M) Coefficients: Level = 0.7, Seasonality = 0.0786 Interpretation: Attempts to attribute part of the weekly movement to seasonal effects.

Chi-Square Result: The test indicates a 100% probability that Model 2 does not outperform Model 1. Conclusion: No statistically significant weekly seasonality exists in USD-INR spot prices.

Monthly Seasonality Analysis

• Model 1 (No Seasonality)Configuration: (A, N, N) Coefficient: Level = 0.9999 Interpretation: Monthly price movement also resembles a random walk.
• Model 2 (With Seasonality)Configuration: (A, N, A) Coefficients: Level = 0.9999, Seasonality = 0.0001 Interpretation: Seasonality has negligible influence on monthly price changes.

Chi-Square Result: The test shows only a 20% chance that Model 2 performs better than Model 1. In statistical terms, a minimum confidence level of 95% is required to confirm seasonality. Conclusion: No statistically significant monthly seasonality is present.

6.3 Fundamental vs Technical Analysis: A Contextual Comparison

Varun: Isha, I know how to do fundamental analysis for stocks—like checking company profits and future plans. But how does that work for currencies?

Isha: It’s much harder for currencies, Varun. You have to look at the economy of both countries, not just one company.

Varun: So things like interest rates, inflation, and global news?

Isha: Exactly. And because it’s so complex, most traders prefer using charts and patterns instead. That’s called technical analysis.

Varun: Makes sense. Charts are easier to follow than economic reports.

Isha: Right. Let me show you how technical analysis works for USD-INR and why it’s so useful.

In equity markets, fundamental analysis typically involves evaluating a company’s business model, financial statements, corporate governance practices, peer comparisons, and valuation models. For example, analyzing Hindustan Unilever Limited would require studying its revenue streams, cost structure, industry positioning, and future growth potential.

This process is relatively structured and accessible to most market participants.

However, applying fundamental analysis to currency pairs—such as USD-INR—is significantly more complex. It requires a deep understanding of macroeconomic conditions in both countries involved:

• United States: Influenced by domestic indicators (e.g., interest rates, inflation, employment) and global dynamics (e.g., trade balances, geopolitical events).
• India: Similarly shaped by internal fiscal and monetary policies, external trade flows, and global capital movements.

To build a meaningful fundamental view on a currency pair, one must weigh these diverse factors against each other in a relative framework. This demands both economic expertise and market intuition—a combination not commonly found among retail traders.

Why Technical Analysis Dominates in Currency and Commodity Trading

Due to the complexity of currency fundamentals, many traders prefer Technical Analysis (TA) as a practical alternative. TA operates on a foundational assumption:  including macroeconomic developments, policy changes, and investor sentiment.

Rather than dissecting economic reports, TA focuses on price behavior itself. Chart patterns, trend lines, support/resistance levels, and momentum indicators become the primary tools for decision-making.

This approach is especially effective in markets like currencies and commodities, where:

• Price movements are continuous and globally influenced
• Fundamental data is vast, dynamic, and often difficult to interpret in real time
• Liquidity and volatility make technical setups more actionable

Application of TA Across Asset Classes

Technical Analysis principles apply uniformly across equities, currencies, and commodities. Once the core concepts are understood, they can be adapted to any asset class with minimal modification.

For those unfamiliar with TA, it is recommended to study foundational modules covering:

• Chart types and time-frames
• Trend identification and reversal signals
• Volume analysis and momentum indicators
• Risk management through stop-loss and position sizing

Technical Analysis (TA) applied to currencies and commodities follows the same principles as those used in equity markets. For individuals unfamiliar with TA methods, it is recommended to study the foundational module on Technical Analysis before proceeding with chart-based strategies in these asset classes. The highlighted candlesticks illustrate a well-known formation known as the Piercing Pattern. This bullish reversal pattern typically signals a potential upward move, prompting a long position in the USD-INR pair. In this instance, the trade progressed favorably, maintaining its trajectory without breaching the stop-loss level.

Transitioning from Currency to Commodity Trading

• A bearish Marubozu pattern has been identified on the GBP-INR chart. This candlestick formation typically signals strong selling pressure and suggests a short position may be appropriate, with the expectation of continued downward movement in the asset.
• Such setups are common across financial instruments, and the variety of technical patterns available makes trade planning both flexible and dynamic. It is a common misconception that currencies and commodities require a distinct set of technical tools. In reality, Technical Analysis (TA) principles apply uniformly across all time series data—whether analyzing equities, commodities, currencies, or fixed-income instruments.
• With this understanding, the currency segment of the module concludes. The next section will focus on commodity trading, exploring its unique characteristics, market structure, and technical applications.

6.4 Key Takeaways

• EUR-INR, GBP-INR, and JPY-INR contracts follow the same structure as USD-INR, with differences mainly in lot size and underlying currency.
• EUR-INR contracts are backed by the collective economies of the European Union, making them unique among currency pairs.
• GBP-INR is the second most traded currency future in India, offering good liquidity especially around UK macro events.
• JPY-INR contracts use a larger lot size of ¥100,000 and are quoted per 100 Yen, requiring careful attention to pricing.
• Margin requirements vary across pairs, with JPY-INR typically demanding the highest due to lower liquidity and higher volatility.
• Spread contracts are available across all major currency pairs, but USD-INR has the most active participation.
• Liquidity plays a key role in contract selection, with USD-INR being the most efficient for execution and strategy deployment.
• Technical analysis tools like candlestick patterns work consistently across all currency pairs.
• Traders should understand global macro trends—Eurozone, UK, and Japan—to trade these pairs effectively.

6.5 Fun Activity

You’re a trader comparing three INR-based currency futures: EUR-INR, GBP-INR, and JPY-INR. Use the data below to answer the questions and decide which contract suits your strategy best.

Market Snapshot:

• EUR-INR Last Price: ₹102.6300
• GBP-INR Last Price: ₹117.8400
• JPY-INR Last Price: ₹66.4800 (per 100 JPY)
• Lot Sizes:

• EUR-INR: €1,000
• GBP-INR: £1,000
• JPY-INR: ¥100,000
  • Margin Requirements:
• EUR-INR: 2.5%
• GBP-INR: 2.5%
• JPY-INR: 4.2%

Questions:

1. What is the contract value for each pair?
2. What is the margin required for one lot of each?
3. Which contract has the highest notional value?
4. Which contract demands the highest margin?
5. If you want to trade with minimal capital, which pair is most cost-effective?

Answer Key:

• EUR-INR: ₹102,630
• GBP-INR: ₹117,840
• JPY-INR: ₹66,480

      2. 

• EUR-INR: ₹2,566
• GBP-INR: ₹2,946
• JPY-INR: ₹2,791

      3. GBP-INR has the highest notional value.

      4. GBP-INRdemands the highest margin.

       5. EUR-INRis most cost-effective due to lower margin and moderate contract value.