August Summary: In August, 51 tons of gold ETFs (approximately US$2.9 billion, -1.4%) were outflowed, consistent with the performance of gold prices [1]. This is the fourth consecutive month of gold ETF outflow.

2025/04/1004:35:38 hotcomm 1979
August Summary: In August, 51 tons of gold ETFs (approximately US$2.9 billion, -1.4%) were outflowed, consistent with the performance of gold prices [1]. This is the fourth consecutive month of gold ETF outflow. - DayDayNews

8 Summary

html In August, global gold ETFs were outflowing 51 tons (approximately US$2.9 billion, -1.4%), consistent with the performance of gold prices [1]. This is the fourth consecutive month of gold ETF outflow. At present, two-thirds of the cumulative inflow of gold ETFs between January and April this year have been offset by recent outflows; so far this year, the inflow of global gold ETFs is 102 tons (about US$7.5 billion), and the total holdings are 3,651 tons (about US$202 billion), an increase of 3.6% year-on-year. The US dollar hit a new high in 20 years, and coupled with rising interest rates, the two have once again become the main resistance to rising gold prices. Gold failed to break through the $1,800/ounce mark, and then the Federal Reserve's hawkish stance continued to pressure gold, closing at $1,716/ounce at the end of the month, down 2%, and a cumulative decline of 5% year-to-date.

html In August, global gold ETFs flowed out on a large scale, and only "other" regions had inflows. Affected by the largest and most liquid U.S. funds, North American funds reduced their holdings by 40 tons (approximately US$2.2 billion, -2.1%), dominating the outflow of gold ETFs this month. The Fed's continued hawkish remarks have caused the U.S. 2-year interest rate to exceed its June high, even at the same level as during the 2008 global financial crisis. This month, almost all funds in North America experienced gold ETF outflows, including low-cost funds [2].

This month, European funds blew up 4.7 tons (approximately US$266 million, -0.3%), led by UK and Swiss funds. Europe has experienced severe stock market weakness, with the euro breaking parity against the dollar for the first time since 2002. On the other hand, Asian gold ETF traffic continued to fluctuate, reducing its holdings by 7.5 tons this month after rebounding last month (approximately US$433 million, -6.0%). Among them, Chinese funds dominated the outflow momentum this month, and China remains the country with the largest outflow of gold ETFs in the region this year. India’s gold ETF has seen a slight net outflow (0.1 tonne) because investors have turned to other asset classes such as stocks (BSE Sensex index, +3.6%) and bonds (India’s 10-year government bonds, +1.2%).

htmlGold trading volume in 28 shrinks, and gold futures demand declines

htmlIn 18, the average daily trading volume of gold fell sharply (this situation often occurs in the summer) to US$109 billion, lower than the average of US$131 billion in 2021. Gold futures trading volume fell 57% this month compared with the previous month, which is the main reason for the decline in gold trading volume. The latest trader position report (COT) shows that COMEX gold futures net long positions remain low, but the net long positions of managed funds increased from net short positions in July to 94 tons.

regional flow changes [3]

All regions except "other" regions have gold ETFs outflows, among which, Asian fund traffic continues to fluctuate:

North America: 39.9 tons (about US$2.2 billion, -2.1%);

Europe: 4.7 tons (about US$266 million, -0.3%);

Asia: 7.5 tons (about US$433 million, -5.6%);

Other regions: 1.2 tons (about US$71 million, 2.1%) [4].

Specific fund traffic changes

SPDR® Gold Shares and iShares Gold Trust led the outflow of gold ETFs in August:

North America: SPDR® Gold Shares dominated the outflow, and the asset management scale decreased by 32.5 tons (about US$1.8 billion, -3%), while iShares Gold Trust reduced its holdings by 5.1 tons (about US$288 million, -1%);

Europe: WisdomTree Core Physical Gold leaked 1.9 tons (about US$111 million, -17%), Invesco Physical Gold outflowed 0.8 tons (approximately US$48 million, -0.3%); Xtrackers Physical Gold EUR increased its holdings by 6 tons (approximately US$36 million, 1.7%);

Asia: Chinese gold ETFs dominated the outflow of Asian funds, among which Huaan Yifu Gold ETF (approximately US$219 million, -13%) and Bose Gold ETF (approximately US$112 million, -10%) both suffered double-digit percentage losses.

Long-term trend

Two-thirds of the global gold ETF inflows in the first four months of this year have been offset by recent outflows. As of the beginning of the year, its asset management scale has only increased by 3.6%:

Large-scale and strong liquidity funds continue to change with the gold price; low-cost funds continue to grow steadily;

In 2022, the inflow of gold ETFs in Europe is more than twice that of North America;

In 2022, the number of global gold ETF funds has increased by 10%.

Note:

[1]We calculate gold ETF flow in ounces/ton and USD at the same time, because both indicators are closely related to the accurate understanding of the performance of gold ETFs. Changes in tonnage can directly reflect fluctuations in position levels, while the US dollar value of flow is the financial industry standard, which can demonstrate the scale of funds invested in gold ETFs. Starting from July 1, 2021, we have made some adjustments and improvements to the calculation method, and will have a certain impact on historical and future data. We have specifically revised the method of estimating changes in gold positions, as described below:

Before, the tonnage change was calculated by converting the fund AUM (USD) into gold positions (tons) and estimating the difference between each time period. However, currency changes and large daily/weekly gold price changes may cause a deviation in the difference between tonnage changes and US dollar fund flows in the short term. Therefore, we adjust the tonnage change into a function of fund flow and AUM, and replace the tonnage change data with fund flow (tons).

[2] The US low-cost gold ETF is defined by the World Gold Council as an open-end fund for gold ETF established and traded in the United States and Europe, with annual administrative rates and other expenses (such as fixed costs) not exceeding 20 basis points, supported by physical gold.

[3] We calculate gold ETF flows in both ounces/ton and USD, because both indicators are closely related to an accurate understanding of gold ETF performance. Changes in tonnage can directly reflect fluctuations in position levels, while the US dollar value of flow is the financial industry standard, which can demonstrate the scale of funds invested in gold ETFs. Starting from July 1, 2021, we have made some adjustments and improvements to the calculation method, and will have a certain impact on historical and future data. We have specifically revised the method of estimating changes in gold positions, as described below:

Before, the tonnage change was calculated by converting the fund AUM (USD) into gold positions (tons) and estimating the difference between each time period. However, currency changes and large daily/weekly gold price changes may cause a deviation in the difference between tonnage changes and US dollar fund flows in the short term. Therefore, we adjust the tonnage change into a function of fund flow and AUM, and replace the tonnage change data with fund flow (tons).

Now for most funds, we estimate US dollar fund traffic (as described in Section 2.3.2 below) and then convert these traffic into fund traffic (tons).

Now, fund traffic (tons) and US dollar fund traffic will serve as a unified explanation of the investment demand for gold ETFs, and the fund's real gold holdings (in US dollars and tons) will still be approximately estimated, affected by the above-mentioned currency and price fluctuations.

According to our preliminary analysis, these changes are unlikely to have a significant long-term impact on historical information (especially the global or regional aggregate basis), but will adjust for short-term fluctuations sometimes caused by data input and time changes.

[4] "Other" regions include Australia, South Africa, Türkiye, Saudi Arabia and the United Arab Emirates.

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