Quantitative & Derivatives Strategy
Flows & Liquidity : Investors start the year with low cash allocations
January 3, 2024
Flows & Liquidity : Investors start the year with low cash allocations
Flows & Liquidity : Investors start the year with low cash allocations
This document is being provided for the exclusive use of blake@sandboxfp.com.
03 January 2024

This material is neither intended to be distributed to Mainland China investors nor to provide securities investment consultancy services within the territory of Mainland China. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan.

Flows & Liquidity

Investors start the year with low cash allocations

J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision.

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  • The implied cash allocation of non-bank investors globally has declined towards the lows of the end of 2021, suggesting that there is currently a very low liquidity cushion to propagate financial assets further, thus posing downside risk to both equities and bonds going forward.
  • Our indicators currently point to elevated equity and bond positioning and low commodity positioning ex gold. Instead, investors appear to have been flocking into gold and bitcoin.
  • The picture looks mixed in credit with a lower short base in HY vs. HG or vs. EM sovereign credit. Investors appear to be still underweight EM equities.
  • IMF’s COFER data point to marked outflows from USD in 3Q23 on a combination of rebalancing flows after dollar appreciation, central banks supporting their own currencies and diversification demand for gold.
  • A persistent financing surplus portrays a picture of a still cautious US corporate sector.
  • As a new year begins the question that arises is about how investors are positioned at the start of the year.
  • In equities, a flurry of indicators point to overbought conditions. This is seen in our futures position proxy for S&P500 futures in Figure 1, the spec positions on US equity futures as reported by CFTC in Figure 2, the low short interest on SPY and QQQ ETFs in Figure 3 and the momentum signals for major equity indicates in Figure 4.  In addition, our proxies of the retail impulse shown in Figure 5 to Figure 7  are all suggesting that the strong retail impulse into equities seen at the end of last year has already peaked.

Figure 1: Our position proxy based on cumulative daily changes of S&P500 mini futures multiplied by the sign of the price change

’000s of contracts. Last obs. 2nd Jan 2024.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 2: Positions in US equity futures by Asset managers and Leveraged funds

CFTC positions in US equity futures by Leveraged funds and Asset managers (as a % of open interest). It is an aggregate of the S&P500, DowJones, NASDAQ and their Mini futures contracts.

Source : CFTC, Bloomberg Finance L.P., and J.P. Morgan.

Figure 3: Short interest on the SPY and QQQ US equity ETFs

Short Interest as a % share of share outstanding. Last obs is for 1st Jan 2024.

Source : S3, J.P. Morgan.

Figure 4: Momentum signals across major equity indices

Average z-score of Short and Long term momentum signal in our Trend Following Strategy framework shown in Tables A3 and A4 below in the Appendix.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 5: AAII US Investor Sentiment Bullish over Bearish readings ratio

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 6: Exchange-traded Call Option Buys at Open minus Sells at Open for Costumers with less than 10 contracts for options on individual equities

In mn contracts. Last obs is for the week ending 29th Dec 2023.

Source : OCC, J.P. Morgan.

Figure 7: Retail Investor' Favorites US equity basket vs. S&P500 index

Ratio of two return indices

Source : GS, Bloomberg Finance L.P., J.P. Morgan.

  • Similarly in bonds, our futures position proxy for 10y UST futures has risen sharply over the previous two months to the highs of Q3 2020  as shown in Figure 8. Our momentum signals on core bond futures are also pointing to an overhang of long duration positions (Figure 9), though the signals have already started declining from the high levels reached at the end of last year.

Figure 8: Our position proxy based on cumulative daily changes of 10y UST futures multiplied by the sign of the price change

’000s of contracts. Last obs. 2nd Jan 2024.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 9: Momentum signals for 10Y UST, 10Y Bund & 10Y Gilt

Average z-score of Short and Long term momentum signal in our Trend Following Strategy framework shown in Tables A3 and A4 below in the Appendix.

Source : Bloomberg Finance L.P., J.P. Morgan.

  • In credit, the low short interest on major credit ETFs such as HYG for US HY credit, LQD for US HG credit and EMB for EM sovereign credit are pointing to lower short base in HY vs. HG or vs. EM sovereign credit (Figure 10 and Figure 11). The still elevated short interest on the EEM ETF suggests that investors are still underweight EM equities (Figure 11).

Figure 10: Short interest on the LQD and HYG US ETF

Short Interest as a % share of share outstanding.

Source : S3, J.P. Morgan

Figure 11: Short interest on the EEM and EMB US ETF

Short Interest as a % share of share outstanding.

Source : S3, J.P. Morgan

  • In commodities (ex gold), whether one looks at CFTC reported spec positions on oil futures in Figure 12 or the momentum signals in Figure 13, the picture that arises is of low investor positioning. Instead, investors appear to have been flocking into gold (Figure 14) and bitcoin (Figure 15).

Figure 12: Oil spec positions

Net spec positions divided by open interest. CFTC futures positions for WTI and Brent are net long minus short for the Managed Money category.

Source : CFTC, Bloomberg Finance L.P., J.P. Morgan.

Figure 13: Momentum signals for WTI and Brent futures

Average z-score of Short and Long term momentum signal in our Trend Following Strategy framework shown in Tables A3 and A4 below in the Appendix.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 14: Gold spec positions

$bn. CFTC net long minus short position in futures for the Managed Money category.

Source : CFTC, Bloomberg Finance L.P., J.P. Morgan.

Figure 15: Our Bitcoin position proxy based on open interest in CME Bitcoin futures contracts

In number of contracts. Last obs. for 2nd Jan 2023.

Source : J.P. Morgan.

  • The above picture is overall consistent with the most holistic of our position indicators, i.e.  the equity, bond, cash and commodity allocations of non-bank investors shown regularly in Charts A51 -A54 in the Appendix, also shown in  Figure 16-Figure 19 below.  The implied equity allocation currently stands close to the highs of the end of 2021. The implied bond allocation looks low relative to the post-Lehman crisis history, but above average relative to the higher interest rate period before the Lehman crisis, which is likely more relevant in the current juncture.  The implied commodity allocation (ex gold) has declined to the previous lows of 2014/2015 period.  The implied cash allocation has declined towards the lows of the end of 2021, suggesting that there is currently a very low liquidity cushion to propagate financial assets further, thus posing downside risk to both equities and bonds going forward.

Figure 16: Implied equity allocation by non-bank investors globally

Global equities as % total holdings of equities/bonds/M2 by non-bank investors. Dotted lines are averages.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 17: Implied bond allocation by non-bank investors globally

Global bonds as % total holdings of equities/bonds/M2 by non-bank investors. Dotted lines are averages.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 18: Implied cash allocation by non-bank investors globally

Global cash held by non-bank investors as % total holdings of equities/bonds/M2 by non-bank investors. Dotted lines are averages.

Source : Bloomberg Finance L.P., J.P. Morgan.

Figure 19: Implied commodity allocation ex-gold by non-bank investors globally

Proxied by the open interest of commodity futures ex gold as % of the stock of equities, bonds and cash held by non-bank investors globally.

Source : Bloomberg Finance L.P., J.P. Morgan.

  • In all, investors appear to be starting the year with low cash allocations, close to the lows of the end of 2021. Our indicators currently point to elevated equity and bond positioning and low commodity positioning ex gold. Instead, investors appear to have been flocking into gold and bitcoin. The picture looks mixed in credit with a lower short base in HY vs. HG or vs. EM sovereign credit. Investors appear to be still underweight EM equities.

IMF’s COFER data point to marked outflows from USD in 3Q23 on a combination of rebalancing flows after dollar appreciation, central banks supporting their own currencies and diversification demand for gold

  • With the release of the IMF’s COFER data covering 3Q23, we update on our estimates of reserve manager bond demand supplemented with our more timely proxy for 4Q23. In order to estimate the net flow, we adjust changes in reserve balances by currency for both currency and bond returns, using our 1-5 year GBI country indices to proxy for the latter. Adjusted for these returns, we estimate that reserve managers saw a net decline in FX reserves of around $75bn in 3Q23.
  • The outflows from FX reserves were largely concentrated in the dollar, which saw net outflows of around $150bn after adjusting for bond returns (Figure 20). Around half of this outflow was offset by inflows into yen, euro and the Australian dollar as the largest beneficiaries. Given that the trade-weighted US dollar appreciated by around 2% in 3Q23, a significant share of the outflows from the dollar are likely to be driven by rebalancing flows. That said, given around half of the outflow was not offset by inflows into other currencies, there are two further factors that have likely played a role. The first is that some of the reduction in reserves in the IMF’s COFER data could be related to central banks supporting their currencies. A second factor could be related to diversification demand for gold. Indeed, 3Q23 saw a rebound in central bank gold demand (Figure 21), after a normalisation in 2Q23 largely driven by sales by the CBRT amid turmoil in the local gold market (F&L, Sep 6th and Metals Weekly, Aug 24th) that appears to have proved temporary. The net purchases of close to 340 tonnes in 3Q23 amount to around $22bn, or just below a third of the net outflow from FX reserves based on adjusted IMF COFER data that do not include gold.

Figure 20: Quarterly flows by FX Reserve Managers

In $bn per quarter. Based on COFER data adjusted for both bond and FX returns. Last obs. is for 3Q23.

Source : IMF COFER, J.P. Morgan.

Figure 21: Net purchases of gold by central banks

Tonnes per quarter, last obs is for 3Q23.

Source : Metals Focus, Refinitiv GFMS, World Gold Council, J.P. Morgan Commodities Research.

  • What about the picture for 4Q23? To estimate this, we use a more timely proxy of net reserve accumulation for EM based on monthly disclosures on FX reserves. Similar to the above, we adjust changes in FX reserves for bond and currency returns, assuming for simplicity that reserves are distributed roughly 60:40 in USD and non-USD currencies, broadly in line with the distribution in the COFER data on global FX reserves, and proxy non-USD currencies with DXY returns and DXY weights for bond returns. Figure 22 depicts this estimate, and suggests continued net outflows from FX reserves in October and November. Taken together, we estimate that FX reserve managers have likely on net sold around $120bn of bonds in 2023, or a deterioration in bond demand of around $90bn relative to 2022, compared to a $30bn deterioration we had previously pencilled in (F&L, Nov 23rd).

Figure 22: Changes in EM FX reserves, adjusted for FX valuation changes

$bn per month.

Source : Bloomberg Finance L.P., J.P. Morgan.

  • As a result, the 2023 demand picture was marginally weaker, but still suggested a modest improvement in the overall bond supply-demand balance for the year as a whole (Figure 23). This is consistent with a modest overall decline in the Global Agg yield in 2023 of 22bp.

Figure 23: Annual change in the balance between global bond supply and demand

Change in excess bond supply in $bn per annum in the left axis calculated as the difference between changes in global bond supply and changes in global bond demand as explained in the text. It includes our 2023 and 2024 estimates. Right axis shows the annual change of the yield on the Bloomberg Global Agg index in % (Jan-Oct in dotted lines for 2016 and 2018), and the blue diamond shows the change in 2023.

Source : J.P. Morgan.

A persistent financing surplus portrays a picture of a still cautious US corporate sector

  • The release of the US Flow of Funds for Q3 2023 last month revealed a still elevated financing surplus for the US non- financial corporate sector , i.e. a persistent gap between corporate cash flows and capex (Figure 24). An elevated corporate financing surplus is typically a reflection of a cautious corporate sector given it tends to be the result of capex lagging cash flows, ie the result of higher savings. Looking at the software and R&D components of capex, given the recent focus on AI-related spending, suggests a significant increase in spending in the aftermath of the pandemic, but over the past year or so this growth has slowed sharply (Figure 25).  

Figure 24: US Non-Financial Corporate Sector Cash Flows vs Capex

% of US GDP.

Source : Federal Reserve Flow of Funds, J.P. Morgan.

Figure 25: R&D and Software spending  by the US Non-Financial Corporate Sector

% growth y/y.

Source : Federal Reserve Flow of Funds, J.P. Morgan.

  • As shown in Figure 26 this financing surplus has been hovering at around 2% of US GDP since the pandemic. The financing surplus has been mostly positive since the financial crisis of 2008 reflecting a persistently cautious corporate sector. And according to Figure 26 there is little evidence of a change since the pandemic. In addition, Figure 26 shows that, before the financial crisis of 2008, the corporate financing surplus was mostly negative; ie the corporate sector was in deficit as it was dissaving, thus reflecting a less cautious or more expansionary corporate sector before 2008.

Figure 26: US Non-Financial Corporate Sector Financing Surplus as % of GDP

The financing surplus is proxied by the difference between corporate cash flows and capex as % of US GDP.

Source : Federal Reserve Flow of Funds, J.P. Morgan.

  • A persistent positive financing surplus after the pandemic implies that the background support that the corporate sector has been providing to financial assets, both equities and bonds, since the financial crisis of 2008 was not withdrawn post the pandemic. A positive financing surplus means that the corporate sector is saving and this saving can be deployed in either equities via share buybacks or acquisitions or in bonds via reduced debt issuance, thus supporting credit.

Appendix

Table A1:Weekly Flow Monitor

$bn per week. The first two rows include Mutual Fund and ETF flows globally, i.e. flows for funds domiciled both inside and outside the US(source: EPFR). The last four rows only include funds domiciled in the US.International Equity funds are equity funds domiciled in the US that invest outside the US (source: ICI and Bloomberg Finance L.P.)

Source : EPFR, Bloomberg Finance L.P., ICI, J.P. Morgan.

Chart A1: Fund flow indicator

Difference between flows into Equity and Bond funds: $bn per week. Difference between flows into Equity vs. Bond funds in $bn per week. Flows include Mutual Fund and ETF flows globally, i.e. funds domiciled both inside and outside the US (source: EPFR) The thin blue line shows the 4-week average of difference between Equity and Bond fund flows. Dotted lines depict ±1 StDev of the blue line. The thick black line shows a smoothed version of the same series. The smoothing is done using a Hodrick-Prescott filter with a Lambda parameter of 100.

Source : EPFR, J.P. Morgan.

Chart A2: Global equity & bond fund flows

$bn per year of Net Sales, i.e. includes net new sales + reinvested dividends for Mutual Funds and ETFs globally, i.e. for funds domiciled both inside and outside the US. Flows come from ICI (worldwide data up to Q2’23). Data since then are a combination of monthly and weekly data from Lipper, EPFR and ETF flows from Bloomberg Finance L.P.

Source : ICI, EPFR, Lipper, Bloomberg Finance L.P., and J.P. Morgan.

Table A2: Trading turnover monitor

Volumes are monthly and Turnover ratio is annualised (monthly trading volume annualised divided by the amount outstanding). UST Cash is primary dealer transactions in all US government securities. UST futures are from Bloomberg Finance L.P. JGBs are OTC volumes in all Japanese government securities. Bunds, Gold, Oil and Copper are futures. Gold includes Gold ETFs. Min-Max chart is based on Turnover ratio. For Bunds and Commodities, futures trading volumes are used while the outstanding amount is proxied by open interest. The diamond reflects the latest turnover observation. The thin blue line marks the distance between the min and max for the complete time series since Jan-2005 onwards. Y/Y change is change in YTD notional volumes over the same period last year.

Source : Bloomberg Finance L.P., Federal Reserve, Trace, Japan Securities Dealer Association, WFE, J.P. Morgan.

ETF Flow Monitor (as of 3rd Jan)

Chart A3: Global Cross Asset ETF Flows

Cumulative flow into ETFs as a % of AUM

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A4: Bond ETF Flows

Cumulative flow into bond ETFs as a % of AUM

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A5: Global Equity ETF Flows

Cumulative flow into global equity ETFs as a % of AUM

Source : Bloomberg Finance L.P., J.P. Morgan. Note: We include ETFs with AUM > $200mn in all the flow monitor charts. Chart A5 exclude China On-shore (A-share) ETFs from EM and in Japan. We subtract the BoJ buying of ETFs.

Chart A6: Equity Sectoral and Regional ETF Flows

Rolling 3-month and 12-month change in cumulative flows as a % of AUM. Both sorted by 12-month change

Source : Bloomberg Finance L.P., J.P. Morgan.

Short Interest Monitor

Chart A7: Short interest on the EEM and EMB US ETF

Short Interest as a % share of share outstanding.

Source : S3, J.P. Morgan

Chart A9: Short interest on the SPY and QQQ US ETF

Short Interest as a % share of share outstanding. Last obs is for 1st Jan 2024.

Source : S3, J.P. Morgan

Chart A8: Short interest on the LQD and HYG US ETF

Short Interest as a % share of share outstanding.

Source : S3, J.P. Morgan

Chart A10: S&P500 sector short interest

Short interest as a % of shares outstanding based on z-scores. A strategy which overweights the S&P500 sectors with the highest short interest z-score (as % of shares o/s) vs. those with the lowest, produced an information ratio of 0.7 with a success rate of 56% (see F&L, Jun 28,2013 for more details).

Source : NYSE, Bloomberg Finance L.P., J.P. Morgan

Chart A11a: Cross Asset Volatility Monitor 3m ATM Implied Volatility (1y history) as of 2nd Jan-2024

This table shows the richness/cheapness of current three-month implied volatility levels (red dot) against their one-year historical range (thin blue bar) and the ratio to current realised volatility. Assets with implied volatility outside their 25th/75th percentile range (thick blue bar) are highlighted. The implied-to-realised volatility ratio uses 3-month implied volatilities and 1-month (around 21 trading days) realised volatilities for each asset.

Chart A11b: Option skew monitor

Skew is the difference between the implied volatility of out-of-the-money (OTM) call options and put options. A positive skew implies more demand for calls than puts and a negative skew, higher demand for puts than calls. It can therefore be seen as an indicator of risk perception in that a highly negative skew inequities is indicative of a bearish view. The chart shows z-score of the skew, i.e. the skew minus a rolling 2-year avg skew divided by a rolling two-year standard deviation of the skew. A negative skew on iTraxx Main means investors favour buying protection, i.e. a short risk position. A positive skew for the Bund reflects a long duration view, also a short risk position.

Source : J.P. Morgan

Chart A11c: Equity-Bond metric map

Explanation of Equity - Bond metric map: Each of the five axes corresponds to a key indicator for markets. The position of the blue line on each axis shows how far the current observation is from the extremes at either end of the scale. For example, a reading at the centre for value would mean that risky assets are the most expensive they have ever been while a reading at the other end of the axis would mean they are the cheapest they have ever been. Overall, the larger the blue area within the pentagon, the better for the risky markets. All variables are expressed as the percentile of the distribution that the observation falls into. I.e. a reading in the middle of the axis means that the observation falls exactly at the median of all historical observations. Value: The slope of the risk-return tradeoff line calculated across USTs, US HG and HY corporate bonds and US equities(see GMOS p. 6, Loeys et al, Jul 6 2011 for more details). Positions: Difference between net spec positions on US equities and intermediate sector UST. See Chart A13. Flow momentum: The difference between flows into equity funds (incl. ETFs) and flows into bond funds. Chart A1. We then smooth this using a Hodrick-Prescott filter with a lambda parameter of 100. We then take the weekly change in this smoothed series as shown in Chart A1. Economic momentum:The 2-month change in the global manufacturing PMI. (See REVISITING: Using the Global PMI as trading signal, Nikolaos Panigirtzoglou, Jan 2012). Equity price momentum: The 6-month change in the S&P500 equity index. As of 29th Dec 23.

Source : Bloomberg Finance L.P., J.P. Morgan.

Spec position monitor

Chart A12: Weekly Spec Position Monitor

Net spec positions are proxied by the number of long contracts minus the number of short contracts using the speculative category of the Commitments of Traders reports (as reported by CFTC). To proxy for speculative investors for equity and US Treasury bond futures positions we use Asset managers and leveraged funds (see Chart A13), whereas for other assets we use the legacy Non-Commercial category. This net position is then converted to a dollar amount by multiplying by the contract size and then the corresponding futures price. We then scale the net positions by open interest. The chart shows the z-score of these net positions. US rates is a duration-weighted composite of the individual UST futures contracts excluding the Eurodollar contract.

Source : Bloomberg Finance L.P., CFTC, J.P. Morgan

Chart A14: Spec position indicator on Risky vs. Safe currencies

Difference between net spec positions on risky & safe currencies. Net spec position is calculated in USD across 5 “risky” and 3 “safe”currencies (safe currencies also include Gold). These positions are then scaled by open interest and we take an average of “risky” and “safe” assets to create two series. The chart is then simply the difference between the“risky” and “safe” series. The final series shown in the chart below is demeaned using data since 2006. The risky currencies are: AUD, NZD,CAD, RUB, MXN and BRL. The safe currencies are: JPY, CHF and Gold.

Source : Bloomberg Finance L.P., CFTC, J.P. Morgan.

Chart A13: Positions in US equity futures by Asset managers and Leveraged funds

CFTC positions in US equity futures by Leveraged funds and Asset managers (as a % of open interest). It is an aggregate of the S&P500, DowJones, NASDAQ and their Mini futures contracts.

Source : CFTC, Bloomberg Finance L.P. and J.P. Morgan

Chart A15: Spec position indicator on US equity futures vs. intermediate sector UST futures

Difference between net spec positions on US equity futures vs.intermediate sector UST futures. This indicator is derived by the difference between total CFTC positions in US equity futures by Asset managers + Leveraged Funds scaled by open interest minus the Asset managers + Leveraged Funds spec position on intermediate sector UST futures (i.e. all UST futures duration weighted ex ED and ex 2Y UST futures) also scaled by open interest.

Source : CFTC, Bloomberg Finance L.P. and J.P. Morgan

Mutual fund and hedge fund betas

Chart A16: 21-day rolling beta of 20 biggest active US bond mutual fund managers with respect to the US Agg Bond Index

The dotted line shows the average beta since 2013.

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A17: 21-day rolling beta of 20 biggest active Euro bond mutual fund managers with respect to the Euro Agg Bond Index

The dotted line shows the average beta since 2013.

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A18: Performance of various type of investors

The table depicts the performance of various types of investors in % as of 29th December 2023.

Source : Bloomberg Finance L.P., HFR, SG CTA Index, J.P. Morgan.

Chart A19: Momentum signals for 10Y UST and 10Y Bunds

Average z-score of Short and Long term momentum signal in our Trend Following Strategy framework shown in Tables A3 and A4 below in the Appendix.

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A20: Momentum signals for S&P500

Average z-score of Short and Long term momentum signal in our Trend Following Strategy framework shown in Tables A3 and A4 below in the Appendix.

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A21: Equity beta of US Balanced Mutual funds and Risk Parity funds

Rolling 21-day equity beta based on a bivariate regression of the daily returns of our Balanced Mutual fund and Risk Parity fund return indices to the daily returns of the S&P 500 and BarCap US Agg indices. Given that these funds invest in both equities and bonds we believe that the bivariate regression will be more suitable for these funds. Our risk parity index consists of 25 daily reporting Risk Parity funds. Our Balanced Mutual fund index includes the top 20 US-based active funds by assets and that have existed since 2006. Our Balanced Mutual fund index has a total AUM of$700bn which is around half of the total AUM of $1.5tr of US based Balanced funds which we believe to be a good proxy of the overall industry It excludes tracker funds and funds with a low tracking error. Dotted lines are average since 2015.

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A22: Equity beta of monthly reporting equally weighted Equity Long/Short hedge funds

Proxied by the ratio of the monthly performance of HFRI Equally-Weighted Equity Hedge fund index divided by the monthly performance of MSCI ACWorld Index

Source : Bloomberg Finance L.P., HFR, J.P. Morgan

Chart A23: USD exposure of currency hedge funds

The net spec position in the USD as reported by the CFTC. Spec is the non-commercial category from the CFTC.

Source : CFTC, Barclay, Datastream, Bloomberg Finance L.P., J.P. Morgan.

CTAs – Trend following investors’ momentum indicators

Table A3: Simple return momentum trading rules across various commodities

Optimal lookback period of each momentum strategy combined with a mean reversion indicator that turns signal neutral when momentum z-score more than 1.5 standard deviations above or below mean, and a filter that turns neutral when the z-score is low (below 0.05 and above -0.05) to avoid excessive trading. Lookbacks, current signals and z-scores are shown for shorter-term and longer-term momentum separately, along with performance of a combined signal. Annualized return, volatility and

information ratio of the signal; current signal; and z-score of the current return over the relevant lookback period; data from 1999 onward.

Source : Bloomberg Finance L.P., J.P. Morgan calculations.

Table A4: Simple return momentum trading rules across international equity indices, bond futures and FX

Optimal lookback period of each momentum strategy combined with a mean reversion indicator that turns signal neutral when momentum z-score more than 1.5 standard deviations above or below mean, and a filter that turns neutral when the z-score is low (below 0.05 and above -0.05) to avoid excessive trading. Lookbacks, current signals and z-scores are shown for shorter-term and longer-term momentum separately, along with performance of a combined signal. Annualized return, volatility and

information ratio of the signal; current signal; and z-score of the current return over the relevant lookback period; data from 1999 onward.

Source : Bloomberg Finance L.P., J.P. Morgan calculations.

Corporate Activity

Chart A24: G4 non-financial corporate capex and cash flow as % of GDP

% of GDP, G4 includes the US, the UK, the Euro area and Japan. Last observation as of Q2 2023.

Source : ECB, BOJ, BOE, Federal Reserve flow of funds, J.P. Morgan.

Chart A25: G4 non-financial corporate sector net debt and equity issuance

$tr per quarter, G4 includes the US, the UK, the Euro area and Japan. Last observation as of Q2 2023.

Source : ECB, BOJ, BOE, Federal Reserve flow of funds, J.P. Morgan.

Chart A26: Global M&A and LBO

$tr. YTD 2023 as of 30th Dec 23. M&A and LBOs are announced.

Source : Dealogic, J.P. Morgan.

Chart A27: US and non-US share buyback

$bn, are as of Dec’23. Buybacks are announced.

Source : Bloomberg Finance L.P., Thomson Reuters, J.P. Morgan

Pension fund and insurance company flows

Chart A28: G4 pension funds and insurance companies equity and bond flows

Equity and bond buying in $bn per quarter. G4 includes the US, the UK,Euro area and Japan. Last observation is Q2 2023.

Source : ECB, BOJ, BOE, Federal Reserve flow of funds, J.P. Morgan.

Chart A29: G4 pension funds and insurance companies equity and bond levels

Equity and bond as % of total assets per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q2 2023.

Source : ECB, BOJ, BOE, Federal Reserve flow of funds., J.P. Morgan

Chart A30: Pension fund deficits

US$bn. For US, funded status of the 100 largest corporate defined benefit pension plans, from Milliman. For UK, funded status of the defined benefit schemes eligible for entry to the Pension Protection Fund, converted to US$at today’s exchange rates.

Last obs. is Nov’23 for US and UK.

Source : Milliman, UK Pension Protection Fund, J.P. Morgan.

Chart A31: G4 pension funds and insurance companies cash and alternatives levels

Cash and alternative investments as % of total assets per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q2 2023.

Source : ECB, BOJ, BOE, Federal Reserve flow of funds, J.P. Morgan.

Credit Creation

Chart A32: Credit creation in the US,Japan and Euro area

Rolling sum of 4-quarter credit creation as % of GDP. Credit creation includes both bank loans as well as net debt issuance by non-financial corporations and households. Last obs. is Q3’23 for US, & Q2’23 for Japan, and Euro Area.

Source : Fed, ECB, BoJ, Bloomberg Finance L.P., and J.P. Morgan calculations.

Chart A33: Credit creation in EM

Rolling sum of 4-quarter credit creation as % of GDP. Credit creation includes both bank loans as well as net debt issuance by non-financial corporations and households. Last obs. is for Q1’23.

Source : G4 Central banks FoF, BIS, ICI, Barcap, Bloomberg Finance L.P., IMF, and J.P.Morgan calculation

Chart A34: Monthly net issuance of US HG bonds

$bn. December 2023 up to 21st.

Source : Dealogic, J.P. Morgan

Table A5: Equity and Bond issuance

$bn, Equity supply and corporate announcements are based on announced deals, not completed. M&A is announced deal value and buybacks are announced transactions. Y/Y change is change in YTD announcements over the same period last year.

Source : Bloomberg Finance L.P., Dealogic, Thomson Reuters, J.P. Morgan.

Bitcoin monitor

Chart A35: Our Bitcoin position proxy based on open interest in CME Bitcoin futures contracts

In number of contracts. Last obs. for 2nd Jan 2023.

Source : J.P. Morgan

Chart A36: Cumulative Flows in all Bitcoin funds and Gold ETF holdings

Both the y-axis in $bn

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A37: Ratio of Bitcoin market price to production cost

Based on the cost of production approach following Hayes (2018).

Source : J.P. Morgan

Chart A38: Flow pace into publicly-listed Bitcoin funds including Bitcoin ETFs

$mm per week, 4-week rolling average flow

Source : Bloomberg Finance L.P., J.P. Morgan.

Japanese flows and positions

Chart A39: Tokyo Stock Exchange margin trading: total buys minus total sells

In bn of shares. Topix on right axis.

Source : Tokyo Stock Exchange, J.P. Morgan.

Chart A40: Monthly net purchases of Japanese bonds and Japanese equities by foreign residents

$bn, Last weekly obs. is for 22nd Dec’23.

Source : Japan MoF, Bloomberg Finance L.P., and J.P. Morgan.

Chart A41: Monthly net purchases of foreign bonds and foreign equities by Japanese residents

$bn, Last weekly obs. is for 22nd Dec’23.

Source : Japan MoF, Bloomberg Finance L.P., and J.P. Morgan.

Chart A42: Overseas CFTC spec positions

CFTC spec positions are in $bn. For Nikkei we use CFTC positions in Nikkei futures (USD & JPY) by Leveraged funds and Asset managers.

Source : Bloomberg Finance L.P., CFTC, J.P. Morgan calculations.

Commodity flows and positions

Chart A43: Gold spec positions

$bn. CFTC net long minus short position in futures for the Managed Money category.

Source : CFTC, Bloomberg Finance L.P., J.P. Morgan.

Chart A44: Gold ETFs

Mn troy oz. Physical gold held by all gold ETFs globally.

Source : Bloomberg Finance L.P., J.P. Morgan.

Chart A45: Oil spec positions

Net spec positions divided by open interest. CFTC futures positions for WTI and Brent are net long minus short for the Managed Money category.

Source : CFTC, Bloomberg Finance L.P., J.P. Morgan.

Chart A46: Energy ETF flows

Cumulative energy ETFs flow as a % of AUM. MLP refers to the Alerian MLP ETF.

Source : CFTC, Bloomberg Finance L.P., J.P. Morgan.

Corporate FX hedging proxies

Chart A47: Average beta of Eurostoxx 50 companies and Eurostoxx Small-Cap to trade-weighted EUR

Rolling 26 weeks average betas based on a bivariate regression of the weekly returns of individual stocks in the Eurostoxx 50 index to the weekly returns of the MSCI AC World and JPM EUR Nominal broad effective exchange rate (NEER).

Source : Bloomberg Finance L.P., J.P. Morgan

Chart A48: Average beta of S&P500 companies to trade-weighted US dollar

Rolling 26 weeks average betas based on a bivariate regression of the weekly returns of stocks in the S&P500 index to the weekly returns of the MSCI AC World and JPM USD Nominal broad effective exchange rate(NEER).

Source : Bloomberg Finance L.P., J.P. Morgan

Chart A49: Average beta of FTSE 100 companies to trade-weighted GBP

Rolling 26 weeks average betas based on a bivariate regression of the weekly returns of individual stocks in the FTSE 100 index to the weekly returns of the MSCI AC World and JPM GBP Nominal broad effective exchange rate (NEER).

Source : Bloomberg Finance L.P., J.P. Morgan

Chart A50: Average beta of MSCI EM companies to trade-weighted EM Currency Index

Rolling 26 weeks average betas based on a bivariate regression of the weekly returns of individual stocks in the MSCI EM index to the weekly returns of the MSCI AC World and JPM EM Nominal broad effective exchange rate (NEER).

Source : Bloomberg Finance L.P., J.P. Morgan

Non-Bank investors’ implied allocations

Chart A51: Implied equity allocation by non-bank investors globally

Global equities as % total holdings of equities/bonds/M2 by non-bank investors. Dotted lines are averages.

Source : Bloomberg Finance L.P., J.P. Morgan

Chart A52: Implied bond allocation by non-bank investors globally

Global bonds as % total holdings of equities/bonds/M2 by non-bank investors. Dotted lines are averages.

Source : Bloomberg Finance L.P., J.P. Morgan

Chart A53: Implied cash allocation by non-bank investors globally

Global cash held by non-bank investors as % total holdings of equities/bonds/M2 by non-bank investors. Dotted lines are averages.

Source : Bloomberg Finance L.P., J.P. Morgan

Chart A54: Implied commodity allocation by non-bank investors globally

Proxied by the open interest of commodity futures ex gold as % of the stock of equities, bonds and cash held by non-bank investors globally.

Source : Bloomberg Finance L.P., J.P. Morgan

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Completed 03 Jan 2024 05:59 PM GMTDisseminated 03 Jan 2024 05:59 PM GMT