In currency trading, forward points are the number of basis points added to or subtracted from the current spot rate of a currency pair to determine the forward rate for delivery on a specific value date. When points are added to the spot rate this is called a forward premium; when points are subtracted from the spot rate it is a forward discount. The forward rate is based on the difference between the interest rates of the two currencies [currency deals always involve two currencies] and the time until the maturity of the deal.
Forward points are also known as the forward spread.
Basis points can be either added or taken away from the spot rate. If they are added, they are forward points. If subtracted, they are discount points.
Key Takeaways
- In currency trading, forward points are the number of basis points added to or subtracted from the current spot rate of a currency pair to determine the forward rate for delivery on a specific value date.
- A discount spread is the currency forward points that are subtracted from the spot rate, to obtain a forward rate for a currency.
- When points are added to the spot rate this is called a forward premium; when points are subtracted from the spot rate it is a forward discount.
The Basics of Forward Points
Forward points are used to calculate the price for both an outright forward contract and a foreign currency swap. Points can be calculated and transactions executed for any date that is a valid business day in both currencies. The most commonly traded forward currencies are the U.S. dollar, the euro, the Japanese yen, the British pound, and the Swiss franc.
Forwards are most commonly done for periods of up to one year. Prices for further out dates are available, but liquidity is generally lower. In an outright forward foreign exchange contract, one currency is bought against another for delivery on any date beyond the spot. The price is the spot rate plus or minus the forward points to the value date. No money changes hands until the value date.
In a foreign exchange swap, a currency is bought for the near date [usually spot] against another currency, and the same amount is sold back for the forward date. The rate for the forward leg of the swap is the near-date rate plus or minus the forward points to the far date. Money changes hands on both value dates.
Discount Spreads
In contrast to the forward spread, a discount spread is the currency forward points that are subtracted from the spot rate, to obtain a forward rate for a currency. In the currency markets, forward spreads, or points, are presented as two-way quotes; that is, they have a bid price and an offer price. In a discount spread, the bid price will be higher than the offer price, while in a premium spread, the bid price will be lower than the offer price.
Examples of Forward Points
Forward points are often quoted in numbers, such as +13.2 or minus -270.68. These represent 1/10,000, so +13.2 means 0.00132 when added to a currency spot price.
For example, if the euro can be bought versus the dollar at the rate of 1.1350 for spot, and the forward points are +13.2, the forward rate is 1.13632 [or 1.1350 + 0.00132].
Just based on this information we can determine that the interest rate in the US is higher than in the Eurozone. The positive forward points when buying the EUR/USD tell us that the rate goes up the further out into the future we go. This is because the forward points compensate for the difference in interest rates between the two currencies.
Thinking of it a different way if the euro interest rate is 1% and the U.S. interest rate is 2%, you could make the 1% difference by holding U.S. dollars instead of euros. So when exchanging or locking in currency exchange rates for the future [forward rate] this needs to be factored in.
Adjusted beta tends to estimate a security’s future beta. It is a historical beta adjusted to reflect the tendency of beta to be mean-reverting – the CAPM’s beta value will move towards the market average, of 1, over time.
The beta estimate based purely on historical data – known as the unadjusted beta – is not a good indicator of the future. As a consequence of different choices in the time period used, intervalling effect, and market index, different services adjust their regression betas towards one and use the adjusted beta to calculate the expected return.
Summary
- Adjusted beta estimates a security’s future beta. It is a historical beta adjusted to reflect the tendency of beta to be mean-reverting.
- Beta measures a security’s volatility, or systematic risk, relative to the movements in the overall market.
- Because most companies tend to grow in size, become more diversified, and own more assets, over time, their beta values fluctuate less, resulting in beta mean reversion.
What is Beta?
Beta measures a security’s volatility, or systematic risk, relative to the movements in the overall market. It is estimated by regressing the returns on any asset against returns on an index representing the market portfolio, over a reasonable period.
It measures the risk added on to a diversified portfolio and is centered around one. A stock that moves more than the market shows a beta more than 1.0, and a stock that moves less than the market demonstrates a beta less than 1.0. Low-beta stocks are less risky and fetch lower returns than high-beta stocks.
Beta = Covariance / Variance
Capital Asset Pricing Model [CAPM]
The Capital Asset Pricing Model [CAPM] outlines the relationship between the expected return for assets and systematic risk – measured by the covariance of an investment’s return with the returns of the market. A positive covariance indicates that the returns move in the same direction, while a negative covariance indicates that they move inversely.
The model describes individual stock returns as a function of the overall market returns and assumes zero transaction costs. It concludes that the optimally diversified portfolio includes every traded asset in the market, and the risk of an investment is the risk added on to a diversified portfolio. The expected return is calculated as:
Expected Return = Risk-free Rate + [Beta * Market Risk Premium]
Important Observations:
- If the beta of an individual portfolio is 1, then:
Return of the Asset = Average Market Return
- Beta represents the slope of the line of best fit.
- The asset is expected to generate at least the risk-free rate of return.
Issues with the Beta Estimate
1. Choice of market index
In actual practice, there are no indices that come close to the market portfolio. Instead, the equity market indices and fixed income market indices include only a subset of the securities in each market and are not comprehensive.
The S&P 500 – the most widely used index for beta estimation for US companies – includes only 500 of the thousands of equities that are traded in the US market. The indices used in emerging markets include very few companies and tend to be even narrower.
2. Impact of return interval
The choice of return interval also affects beta estimates. The theory does not state whether returns should be measured daily, weekly, monthly, quarterly, or annually. The beta coefficient of the security varies across return frequencies. The phenomenon is referred to as the intervalling effect bias in beta.
Assets are not traded on a continuous basis, and as a result of such a non-trading problem, the beta estimate can be affected – non-trading during a return period can reduce the measured correlation with the market index.
Betas calculated during shorter intervals are likely to show a significant bias due to the non-trading problem. Illiquid companies report lower beta than they ideally should assume, and liquid companies report higher beta than is justified.
3. Choice of time horizon
Risk-return models are silent on the time period one needs to use to estimate betas. While selecting a time period for beta estimation, one must be careful of the trade-off involved. By going back further in time, although there’s an advantage of including more observations in the regression, it can be offset by the fact that the company itself might’ve changed in terms of its business mix, characteristics, and leverage, over time.
Blume’s Beta Adjustment
The Blume Technique was proposed by Marshall E. Blume, who was the Howard Butcher Professor of Finance at the University of Pennsylvania, in 1975 in his paper “Betas and Their Regression Tendencies.” According to Blume, there is a tendency of betas to converge towards the mean of all betas. He describes the tendency by correcting historical betas to adjust the beta to revert to 1, assuming that adjustment in one period is a good estimate in the next period.
Consider betas for all stocks j in period 1, βj1, and betas for the same stocks j in the successive period 2, βj2. Further, the betas in period 2 are regressed against the betas for period 1 to obtain the following equation:
βj2 = b0 + b1βj1
Vasicek’s Technique
Vasicek [1973] adjusted past betas towards the average beta by modifying each beta depending on the sampling error about the beta. If β1 is the average beta, across the sample of stocks, in the historical period, then the Vasicek technique involves taking a weighted average of β1, and the historic beta for security j.
Bloomberg Estimate
Adjusted Beta = Regression Beta [0.67] + 1.00 [0.33]
Why Adjust Betas Towards One?
Research suggests that, over time, there is a general tendency for betas of all companies to converge towards one. Intuitively, it should not be surprising. Because most companies tend to grow in size, become more diversified, and own more assets, over time, their beta values fluctuate less, resulting in beta mean reversion.
Related Readings
Thank you for reading CFI’s guide to Adjusted Beta. To keep learning and developing your knowledge of financial analysis, we highly recommend the additional resources below: