Should i buy palladium 2011

At expiration, the contracts are physically settled by delivery of palladium. Investing in futures requires a high level of sophistication since factors such as storage costs and interest rates affect pricing.

As with futures, options have an expiration date. However, options also have a strike price, which is the price above which the option finishes in the money. An options bet succeeds only if the price of palladium futures rises above the strike price by an amount greater than the premium paid for the contract.

To learn more about how options work, see our Options Trading Guide. While investing in companies can be a leveraged way to gain exposure to palladium prices, many of these companies have significant exposure to other precious metals.

In addition, factors such as company management and the overall stock market can also affect these investments:. Another way to trade in palladium is through the use of a contract for difference CFD derivative instrument. CFDs allow traders to speculate on the price of palladium without owning the asset.

Some regulated brokers worldwide offer CFDs on palladium. Customers deposit funds with the broker, which serve as margin. Traders who want to invest in palladium may consider purchasing it along with a basket of commodities that includes other precious metals , base metals i.

Purchasing a basket of commodities helps protect investors from the volatility of any individual commodity. It also adds overall diversification to a stock and bond portfolio.

China is the top consumer of palladium and could increase its consumption in the years ahead. The Chinese economy has experienced a recent slowdown, although there are signs this may be coming to an end. Investing in palladium is one way to bet on a resurging Chinese economy. The proliferation of ETFs has exposed more investors to precious metals. As the gold and silver trade becomes crowded, investors could seek new ways to gain exposure to precious metals. Higher energy costs make mining an increasingly challenging business.

As fuel and electricity costs rise, more mining operations could close or consolidate. Most analysts who follow the palladium market pay attention to its price relationship with platinum.

Palladium is powering on with the demand for more vehicles. But palladium and platinum are two other precious metals not often discussed — yet still extremely valuable. The metal is very tarnish-resistant, is soft and malleable, and can bond easily with other elements due to its location in the middle of the periodic table.

Platinum often tends to fetch a higher per-ounce price than gold since it is several degrees rarer. Like platinum, palladium is extensively used in the electronics industry and in critical newer technologies like fuel cells. Palladium is 30 times rarer than gold — often giving the metal new record highs as its market further develops. While palladium looks similar to platinum, it is much lighter in weight. As a result, palladium is enjoying greater use in wedding bands for people interested in maximizing comfort with as little extra weight on the finger as possible.

If palladium and platinum look so much alike and share many of the same uses, which metal is the better option to invest in? Is it smarter to buy palladium in ? Or opt to invest in platinum for the next year.

Keep reading to understand the benefits of investment in each metal and how they can fit into your investment portfolio. Platinum and palladium have been around for millennia but have just broken into the market over the past several years. Both metals are similar but have a few notable distinctions that investors should understand. Demand is also more likely to rise because of the forecasted increased demand in the automobile industry especially in the emerging markets of China and India because platinum is used primarily for catalytic converters.

Also, palladium is slowly replacing platinum as a lower-cost material from the past two decades, since it can basically perform the same function as platinum in catalytic converters.

However, researchers argue that, in the longer term, platinum might be a better performer than palladium based on Johnson Matthey Plc Executive Summary Report of The research firm forecasts that gross platinum demand will rise by around 4. The performance of these two precious metals as investments in the long run is tested in this study.

Understanding return and volatility characteristics of platinum and palladium spot prices is important because persistent changes in their time-series structures can expose investors and hedgers alike to risk especially when weak industry demand and instability of supply occur.

Accurate modeling of their time-series return and volatility characteristics can become a major concern if supply deficit continues to increase for platinum and decrease for palladium. The possible spillover to the globalized commodity precious metals markets made scholars and practitioners more interested in knowing the predictability and asymmetric volatility properties of platinum and palladium.

The predictability of precious metals under study can be determined by the positive dependence or the so-called long-memory process, which models the presence of a persistent temporal dependence among distant time-series data in returns and volatility. On the other hand, the asymmetric volatility property of the platinum and palladium data series describes the negative correlation between their returns and innovations in volatility.

This property is commonly connected to the leverage effects phenomenon, because negative changes are often followed by future higher volatility than positive innovations. These data characteristics have been seen in stock returns e.

However, the literature has yet to characterize the predictability and asymmetric volatility of platinum and palladium spot prices. The study is motivated by the recent surge in the application of fractionally integrated FI long-memory and asymmetric volatility models in financial time-series. This research is also inspired by the possible upward momentum in the prices of platinum and palladium because of the steadying supply beginning the second quarter of The paper wants to add to the dearth in literature of platinum and palladium prices returns and volatility, particularly statistically establishing their predictable and safe harbor properties as investments.

The closest paper that can be identified in the literature is the work of Arouri et al. In another related study, Batten et al. In relation with the motivation and contributions, this paper differs from the previous studies through these four main objectives: a Identifying which type of models is better to characterize future values using lagged returns in the time-series of platinum and palladium prices.

The research is written as follows. Section 2 explains the data and the four fractional integration models applied; Section 3 presents the empirical results; and Section 4 gives the conclusion. This research analyzes daily London closing prices of platinum and palladium from the Johnson Matthey Base Price database downloaded in Quandl. The platinum data has a total of 5, data points, and palladium has a total of 5, observations. The returns series of both precious metal prices were computed as , where represents the price at time.

The model was introduced by Granger and Joyeux [ 13 ] and Hosking [ 14 ], which offered the initial testing of the long-memory process. The model complies with both stationary and invariability conditions and can be represented as where denotes a fractional integration real number parameter, corresponds to the conditional mean, represents the lag operator, and denotes a white noise residual.

The function corresponds to the fractional differencing lag operator. The AR and the MA processes have all roots outside the unit circle and can be shown as and , respectively. The model becomes nonstationary when and stationary but a noninvertible process when , which means that the data time-series is impossible to model by any AR process. With regard to the modeling of data dependencies, the ARFIMA model represents a short memory if , where the effect of shocks decays geometrically; and a unit root process is shown when.

Furthermore, the model has a positive dependence among distant observations or the so-called long-memory process if ; and it also has an antipersistent property or has an intermediate memory if. The model assumes that the returns process is expressed as an AR process of order :. The GARCH model is consistent with a short-memory model having its autocorrelation function decaying slowly with a hyperbolic rate [ 15 ]. The APARCH model integrates a power term in its structure that emphasizes periods of relative tranquility and volatility by magnifying the outliers in the time-series.

The APARCH model offers the flexibility of a varying exponent with the asymmetry coefficient to account for the leverage effect. The model was introduced by Baillie et al. The FIGARCH model can be expressed as where represents a fractional integration parameter, denotes the lag operator, and corresponds to a white noise residual process; represents the fractional differencing operator; and denotes an infinite summation, which has to be truncated.

The model has a long-memory process when , which allows more flexibility in modeling the conditional variance rather than the mean. The model was introduced by Tse [ 19 ] and is considered superior to the FIGARCH process through the improvement in volatility with the function , which can be written as follows: where corresponds to the fractional integration parameter and gamma represents the asymmetry model parameter.

The model assumes a long-memory process when and determines if negative shocks have more impact on volatility than positive shocks when. Table 1 shows that both precious metals prices have positive returns with palladium having slightly higher returns with 0. Palladium returns are also more significantly volatile with 0. The research concludes that the Modern Portfolio Theory of Markowitz [ 20 ], stating that a higher risk is compensated with higher returns, is consistent with the two precious metals under study.

Moreover, platinum returns are negatively skewed, while palladium returns are positively skewed, but both have leptokurtic distributions. Table 2 illustrates the use of Augmented Dickey-Fuller test to examine the stationarity of the platinum and palladium returns and the minimum value of the Akaike Information Criterion to identify the orders of the models.

Tables 3 a and 3 b compare the findings of lagged returns and volatilities from the four combinations of models for platinum and palladium spot prices. Majority of the estimated values illustrate that significant lagged conditional variances of and are relatively stronger than those of significant lagged mean returns of and.