August – Research & performance reporting

1. Macro and Market Perspectives – Thinking qualitatively

The risk aversion of investors towards US stocks has been rising of late, with positive earnings surprises triggering negative reactions on average, something that happened for the last time in 2011.

SP500_EPS_BG

In a counterbalancing manner, the USD has significantly depreciated (-9%) against its trade basket. This is a situation that seems to be likely to last for some time. The winners in this scenario are the global US large cap firms, which report earnings in USD, though their markets are global. The big losers are the smaller domestic firms and in particular the retailers, which see the cost of their imports libelled in USD increase sharply, while their margins are being eroded by the newly emerged digital distribution champions. By the way, this latter point helps to contain inflation.

Despite a situation of low noise but ongoing political instability in the US, growth related to consumption is strong and the expected reflation promised by president Trump is not necessarily required, as it might lead to overheating.

Overall, while the increased political uncertainty in the US has led to a risk based repricing of stocks (hence the poor market reaction to the Q2 earnings annoucements) , the macroeconomic situation looks sound with a current GDP growth level of 3%.

US_GDP_BG

However, leaving aside share-buybacks and related financial engineering, in the US, the trend towards rising profits seems to have clearly stopped for some time now. This means that not everybody is benefitting equally from such growth. Looking ahead, the possibility of interest rates rising further also makes long-only investing more risky than low beta & long-short strategies.

US_PROFITS_BG

Overall our view is that the US economy is benefiting from a growth level above escape velocity. US large caps are taking advantage from a weak USD, while the new digital retail distribution model limits considerably the risk of overheating and inflation. In this context, stock selectivity and active management should be kings.

Bramham_Gardens_Event

2. Artificial Intelligence US Investment Strategies – Results from the Research Lab

During this month of August, we globally got the trend right. The only issue is that we have been surprised by the fact that Q2 earnings results clearly above analyst expectations have led to substantial, sometimes even close to double digit, drops in price (NVIDIA, ULTA,…).
Despite these surprises that indicate some changes in mood in the US market, we have succeeded in capturing a positive performance above 1% on the Long-Short strategy, thanks to the noted contribution of the Short leg.

The Long leg is in positive territory, performing better than the SP500 this month. As a result, the Long-only strategy is 7.80% ahead of the SP500 year-to-date.

Obviously, these theoretical strategies are presented for research purposes in order to outline the power of Artificial Intelligence. They are measured gross of any cost & fees and assuming stock loan availability as well as no slippage. Returns are log-returns.

The Long-Short A. I. strategy

Long-Short Price based
Year to end of August 6.21%
August 1.21%

The Long-only A. I. strategy

Price based – ex dividends SP500 Long
Year to end of August 9.89% 17.70%
August 0.05% 1.11%

We are available to discuss with you our work : contact@bramham-gardens.com

June – Research & performance reporting

During this month of June, we have experienced a relatively low volatility level, with limited new idiosyncratic information able to impact the overall investment journey of the US strategies. The main sectors generating a positive performance have been Healthcare, Energy and Consumer Staples, while Industrials, Info Tech and Materials had a rather negative contribution.

What we tend to see is that the earnings announcement periods currently have a noticeable impact on performance, while the periods in-between such events are flat or close to flat.

  • During this month of June, it is not the largest positions in the portfolio that impacted the performance results, but rather the bulk of the holdings.
  • Given some intraday movements, the monthly performance has been quite sensitive to when during the day, the performance has been measured. In this analysis, we work on the basis of prices on close.

Obviously, these theoretical strategies are presented gross of any cost & fees and assuming stock avalaibility as well as no slippage. Returns are logreturns.

The long strategy on a steady track

Price based – ex dividends SP500 Long
Year to end of June 7.92% 13.59%
June 0.48% 1.65%

The long strategy on a steady track

Long-Short Price based
Year to end of June 5.05%
June 0.37%

We are available to discuss with you our work : contact@bramham-gardens.com

May – Research & performance reporting

The US equity market is probably the most efficient market globally. With a contribution of about 60% in the MSCI world equity index, it is also by far the largest equity market. A diversified Asset Allocation cannot be thought of without a weighting dedicated to US equities. Two questions then arise: Has the large cap. US market become a pure ETF market as it is impossible to outperform the correponding indices? Given the fact that the trailing SP500 Price Earnings Ratio is at the very high level of 24, would it be possible to reduce some of the market exposure (the beta) to this universe, while still generating performance?

As a Research Lab, Bramham Gardens rises to the technical challenge. Using adaptive techniques derived from Artificial Intelligence, we wish to prove that it is possible to create value in this very dynamic asset class. We have noticed that earnings announcement periods are important because related market events trigger price movements.

  • The month of May has been an interesting month for our long only strategy. By selecting stocks without resorting to sector rotation, our approach has added value over the benchmark.
  • In the wake of Q1 earnings announcements, the non leveraged long-short strategy has been able to capture the outperformance of stocks like Nvidia, Equinix, Domino’s Pizza or Broadcom limited, while limiting the beta to the overall market.

Obviously, these theoretical strategies are presented gross of any cost and assuming stock avalaibility and no slippage.

The long strategy is quite up this month

Price based – ex dividends SP500 Long
Year to end of May 7.44% 12.20%
March 1.15% 8.20%

A long-short delivery matching expectations

Long-Short Price based
Year to end of May 4.86%
May 3.03%

We are available to discuss with you our work : contact@bramham-gardens.com

March – Research & performance reporting

As a Research Lab, Bramham Gardens concentrates on building investment strategies based on Artificial Intelligence. Our effort concentrates on US large stocks.

This month of March is typical of what we would expect from these strategies, i.e. a positive performance while the market (SP500 index) is negative or flat.

Looking at the long strategy
The month of March has been a strong month with respect to the SP500. Out of the 10 top holdings, 5 have been showing a positive return, with a magnitude that largely supersedes the negative occurrences. The year-to-date cumulative return is still slightly below the SP500, as the January ramp-up of the strategy had been gradual in order to mirror real-world conditions, but the gap has considerably reduced.

Price based – ex dividends SP500 Long
Year to end of March 5.39% 4.66%
March -0.04% 1.80%

A decorrelated long-short
The long-short strategy has, since the start of the year, exhibited clear market decorrelation on the monthly frequency.

Long-Short Price based
Year to end of March 2.33%
March 1.51%

General news
97mUSD are now invested according to the long-short strategy. Obviously the results reported here would differ from the performance of a fund, due to a series of operational constraints and costs.

We are available to discuss with you our work : contact@bramham-gardens.com

February – Research & performance reporting

As a Research Lab, Bramham Gardens concentrates on building investment strategies based on Artificial Intelligence. Our effort concentrates on US large stocks.

What is very significant at the moment is the low level of volatility in the market. This does not help particularly to distinguish among companies, but it also shows that during such periods of time, our long-short approach behaves steadily.

Looking at the long strategy
The month of February has been a month of relative under-performance versus the SP500. Some firms in particular in the tech or in the healthcare sectors like NVIDIA or Edwards Lifesciences Corp. experimented some price mean-reversion after recent periods of growth. We see this as the indication that though the market is overall rising, there are some signs of forward-looking investor uncertainties related to valuations, as these firms experienced solid Q4 earnings above consensus.

Price based – ex dividends SP500 Long
Year to end of February 5.42% 2.86%
February 3.65% 1.69%

A steady long-short
The long-short strategy smoothed nicely the investment journey in February. [note that the January performance has slightly been revised upwards]

Long-Short Price based
Year to end of February 0.82%
February -0.03%

Partnership news
Boussard & Gavaudan, the well-recognized asset management firm, has now launched a UCITS Sicav fund, which follows our long-short US strategy.

We are available to discuss with you our work : contact@bramham-gardens.com

January – Research & performance reporting

As a Research Lab, Bramham Gardens concentrates on building investment strategies based on Artificial Intelligence.

Looking at the long strategies
The year started on a positive note. As the ramp up of the long strategies took place gradually over the first 10 trading days of the year, the long strategies undershot the SP500 this month for technical reasons: the SP500 made two thirds of its performance during this ramp-up period.

Of course, because Bramham Gardens is a research firm, we do not account for transaction costs and slippage. With about 10 rotations per year in the portfolio and as we work on a liquid and cost effective market like the US large cap universe, costs would however remain around 0.5% per year. This would typically be compensated by the fact that results are reported as log-returns.

Price based – ex dividends SP500 Long – cash hedged Long – no hedge
January 1.77% 1.17% 1.17%

A steady long-short
The long-short went through a reasonably smooth ride over the month of January.

Long-Short Price based
January 0.64%

Partnership news
As was already mentioned in the November and December 2016 Bramham Gardens Research Reports, Boussard & Gavaudan, the well-recognized asset management firm, is currently launching a UCITS Sicav fund, which follows our long-short US strategy.

We are available to discuss with you our work : contact@bramham-gardens.com

Artificial Intelligence Research Reporting – YEAR 2016

1. FOCUSED ON PRODUCING GENUINE PERFORMANCE

Successful picking on the long leg
While the Financial Times dated 23/10/2016 reported that 99% of actively managed US equity mutual funds failed to outperform their benchmark, our long-only strategy has generated in 2016 a price return of 24.82% in excess over the SP500, without any leverage, and any small cap or style bias.

Of course, because Bramham Gardens is a research firm, we do not account for transaction costs and slippage. With about 10 rotations per year in the portfolio and as we work on a liquid and cost effective market like the US large cap universe, costs would however remain below 1 or 2% per year.

Price based – ex dividends SP500 Long only
Return in 2016 9.53% 34.36%

A robust long-short
Obviously, with a long-leg generating such outperformance, running an unleveraged long-short strategy with low directionality constitutes the natural next step. In 2016, we obtained a gross-of-fee-and-cost performance of 17.04%, with a positive skewness (meaning limited drawdowns).

Gross of fees & costs Long-Short
Return in 2016 17.04%


No trick

In order to evaluate how much directionality we carry, we compute on a yearly basis the 12-month correlation between the Deutsche Bank market-neutral investment style driven risk-premia and our long-short strategy. We can observe two things: first of all, a very limited dependency on the traditional style factors in 2016, but also a slight shift away from “low-beta” towards more “value” in the portfolio, which was the right move ex-post to have implemented.

2. MOVING FAST
As a Research Lab, Bramham Gardens concentrates on building investment strategies based on Artificial Intelligence.

People
The team is expanding, with Arnaud Apffel joining us as a partner. Arnaud brings us 25 years of experience in Investment Banking and Asset Management, and will provide immense value in terms of investment structuring, academic content delivery and business development.
Two young scientists are joining Bramham Gardens as well, helping us refining several Artificial Intelligence related technical aspects on which we wish to develop.

Partnership
As was already mentioned in the end of November 2016 Bramham Gardens Research Report, Boussard & Gavaudan, the well-recognized asset management firm, is working to open a UCITS Sicav fund, which follows our long-short US strategy. This fund is scheduled be launched at the start of February 2017, pending CSSF approval.

Assets
We are glad to announce that assets invested on our long-short US strategy are reaching $80 million in Q1-2017.

3. INSIGHT IN THE BRAMHAM GARDENS DNA: no magic, just work!

Let us articulate the core principles, which drive our asset allocation choices:

  • Comparing all stocks on the basis of an equal level of information: in our universe, there are around 400 stocks monitored live. Avoiding asymmetrical information among stocks is key for us, as emotional proximity to a given company can be a source of misallocation of capital.
  • Taking no industry rotation bet: a long experience in equities has shown us that sector rotation tends to generate a lower Sharpe ratio than single stock selection. This year has been particularly telling in this respect, requiring remarkable skill to get in the financial sector while moving away from healthcare. Our view is that proper sector diversification should be kept at all times.
  • Taking no specific “investment style” bet: there are many money managers who favor value or momentum as key drivers for their investment decisions. Again, getting the timing right for investment style rotation looks too difficult to be a dependable source of performance, from our perspective.
  • Focusing on relative bets within homogeneous industrial peer groups: we do not consider that we should be paid to predict the dynamics of the stock market indices overall. Our job is to identify resilient outperformers / underperformers and focus on them without being too concentrated on any of them.
  • Relying on Machine Learning to select stocks: adaptive learning is paramount to be able to distinguish between an expected future outcome, pure noise and an anomaly. Using altogether historical information and the multi-dimensional analysis of the peer group dynamics enables us to make complex judgment calls based on rules that evolve and adapt over time.
  • How does it compare with the typical investment process of active managers? In efficient markets like the US market is, it should not be the privileged access to information that drives performance. Defining a robust and sensible metric to capture company talent and applying it with a rigorous and agile methodology can be a game changer.
  • Avoiding accidents by averaging: qualitative analysis often leads to concentrated portfolios, as gaining superior information requires time, focus and capacity. On our side, we make every effort to spread bets looking at different entry points, different universes, various metrics for talent measurement. Averaging is thus an important element of risk management in our view.

We wish you a happy 2017 and are of course at your entire disposal to discuss about what we do : contact@bramham-gardens.com

November – Research & performance reporting

Madam, Sir,

This year 2016, we have looked to be as transparent as we could on the performance of our strategies based on Machine-Learning. Although no real money has been invested into these strategies yet, during the course of the year performance has been monitored by Thomson-Reuters, as a trusted third-party.

We are close to year-end, and we have the pleasure of announcing three significant pieces of news:

  • We are very proud to have signed an exclusive agreement with the highly respected firm Boussard & Gavaudan, by which these strategies will become investable under their umbrella, starting early next year.
  • The strategies have benefited from this month in the US, both on the long-short and on the long sides.
  • We will very soon be growing our team, increasing our research capacity to new domains in this greenfield territory of Artificial Intelligence applied to money management.

Overall, the month of November has been robust. When we look under the bonnet at the stocks that have been picked both on the long and short legs, we see few mistakes. As usual, there is no sector bet. Our goal is to identify the winners and the losers within each broad industrial sector.

Let us restate what we deliver, on a log-return basis (log-returns significantly undershoot returns, but transaction costs are not incorporated):

  • We focus on two long-only non-leveraged strategies: the “hedged” one which gradually turns away from the machine-learning algorithm to go into cash when the SP500 becomes too volatile and the “no hedge” one which switches to the SP500 when the SP500 volatility rises.
Price based – ex dividends SP500 Long – cash hedged Long – no hedge
Year-to-end-of-November 7.30% 23.65% 25.67%
November 3.36% 12.10% 12.07%
  • We run a Long-Short non directional, non leveraged strategy, consistent with the UCITs constraints.
Long-Short Price based
Year-to-end-of-November 13.06%
November 8.17%

Our approach is always to remain humble and down to earth, so let us not expect all months to look like November 2016!

We are available to discuss with you our work : contact@bramham-gardens.com

US Elections – Research & performance reporting

Madam, Sir,

We have the pleasure of informing you about what has happened to our Machine-Learning strategies during this month of October.

During this month of October, the uncertainties related to the US elections as well as the expected interest rate hike jolted the US equity markets. In addition the Q3 reporting brought some surprises.

Overall, the long strategies have been slightly impacted with respect to this last point, especially in the Healthcare sector, but this event driven volatility only has a minor effect on the year-to-date performance, which is well above the SP500 reference. The Long-Short strategy remains robust, well within the range of normal monthly volatility.

Let us restate what we deliver, on a log-return basis:

  • We focus on two long-only strategies: the “hedged” one which gradually turns away from the machine-learning algorithm to go into cash when the SP500 becomes too volatile and the “no hedge” one which switches to the SP500 when the SP500 volatility rises.
Price based ex-devidends SP500 Long-cash hedged Long-no hedge
Year-to-end of October 3.94% 11.56% 13.61%
October -1.96% -3.67% -4.06%
  • We run a Long-Short non directional, non leveraged strategy, consistent with the UCITs constraints.
Long-short Price based
Year-to-end of October 4.89%
October -1.09%

Thomson-Reuters operates as the independent calculator of the performance on the Long-Short side.

We are available to discuss with you our work : contact@bramham-gardens.com