Ex-Balyasny Trader Eyes El Niño for Energy Hedge Fund Trades

Zulfiqar Ali is positioning London-based ZAMS Asset Management, which manages about $350 million, to profit from market dislocations he expects as El Niño alters weather and energy markets. The fund returned 5.7% in August and is up roughly 13% year to date.

Ali founded ZAMS two years after leaving Balyasny Asset Management. He is a 34-year-old Cambridge mathematics graduate. The firm operates from London with a team of about six traders, quantitative specialists and weather strategists.

ZAMS combines energy futures analysis with weather-model data to identify discrepancies between market pricing and expected weather-driven supply and demand. The firm buys forecasts from providers including MetDesk and layers its own analysis on top. Power futures accounted for about 80% of the fund’s gains, according to Ali.

The fund typically runs 25 to 30 positions and holds trades for an average of eight days. Ali described El Niño as “a particularly important market driver” through this year and into early 2027, saying shifts in wind, precipitation and temperature will change generation and demand profiles across regions.

ZAMS anticipated some pressure on European power markets this summer, when high temperatures and low river levels compounded operational problems at French nuclear plants and tightened available supply.

The strategy carries risks. Earlier this year ZAMS held short positions in French and German electricity contracts expecting a later shift from La Niña to El Niño. Wind generation weakened, available supply fell and wholesale power prices rose sharply, producing the firm’s worst month of the year.

According to Ali, “Markets moved about 30% against the positions.” He acknowledged the transition began in May rather than later as the firm had assumed, which left ZAMS exposed.

ZAMS uses quantitative models, weather-model inputs and commodity-market experience to target short-term pricing dislocations. Other alternative managers are increasingly using weather data as climate patterns and extreme events affect commodities, inflation and economic activity.